UMCSAWM Water Conference
on
Demonstrating the Strength of Water Engineering and Management Capability through Case Study Applications
This book is published as supplementary reading material demonstrating the strength of water engineering and management capability. The contents are designed and developed through case study applications. Reproduction of this book is permitted only for non-commercial purposes. Use of this book is encouraged for teaching and training activities with proper acknowledgements of Editor and Publisher.
ISBN: 978-955-9027-61-4
Published and Printed by UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) University of Moratuwa Moratuwa Sri Lanka
Website http://www.civil.mrt.ac.lk/UCM/index.htm
Email [email protected]
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM)
Vision
To be a premier centre of knowledge and outreach focused on sustainable water management in urban and rural environments
Mission
To promote techniques, technologies, management approaches, research and policy that support sustainable utilisation of water Preface
Though water resources engineering and management is vital for development activities of any country, water data collection is limited in most of the developing nations. Until recently, streamflow was gauged only in about 40 locations within the 103 river basins in Sri Lanka. The demand for data is on the rise with the increase in computational power of computers, the advances in mathematical modelling of hydrology, the demand for physics based distributed models and the demand for more water due to population rise. The biggest problem faced by civil engineers who deal with water resources is the lack of gauged data. Application of mathematical models to estimate, forecast and determine design parameters for ungauged watersheds require very clear up-to-date guidelines.
Solving of challenging field level problems in water engineering and management involves a thorough knowledge in the application of mathematical models, a clear understanding of hydrologic and hydraulic principles, a sufficient insight on the social and environmental parameters and an understanding on the methods to converge when ungauged situations are encountered.
It is a great relief that the Irrigation Department Guidelines developed 1984, under the guidance of Engineer A.J.P Ponrajah is currently serving as the only Sri Lankan guideline for drainage and water resources designs. Though this guideline contains immensely valuable information, most of the data, parameters, topics and methods require updating because world over research has advanced tremendously with the scientific advancements especially in the areas of computers and information technology. However, until the authorities’ initiate action to update these guidelines, the civil engineers in Sri Lanka in any sector dealing with irrigation, drainage and floods have to be content with the current Irrigation guideline of 1984.
The civil engineers must not only be conversant about water and its text book parameters which are mostly applicable to other parts of the world, but also must be aware of the strengths and weaknesses of available Sri Lankan guidelines and data. They should also be aware of solving practical problems without weeping over lack of updated guidelines and sufficient gauged data. The postgraduate degree programs of the UMSAWM and associated research are designed to cater to these needs.
This conference is to demonstrate the potential of our postgraduate students to systematically apply hydraulic and hydrologic principles, available guidelines, parameters and data to solve real life problems while verifying the solutions to ensure satisfactory implementation. In this conference proceedings, there are 19 selected papers on hydrology, water resources, Irrigation, GIS, water supply, solid waste planning, Integrated water resources management and mathematical modelling amidst situations of climate change. This conference will provide the opportunity for the decision makers from the industry to observe, question and discuss about the practical problems in the country and the solutions proposed by our students through their Problem Bbased Learning projects and research projects.
It is our fervent hope that the Sri Lankan industry and International institutions will identify the strength and potential of thorough teaching in the current postgraduate degree program conducted by UMCSAWM and the Department of Civil Engineering, which would then lead to a wider participation enhancing the critical mass of water engineers and managers.
i Contents Conference Programme and Messages ...... 1 Programme ...... 2 Message from the Vice Chancellor, University of Moratuwa ...... 4 Message from the Dean, Faculty of Engineering, University of Moratuwa ...... 5 Message from the Head, Department of Civil Engineering, University of Moratuwa ...... 6 Message from the Head, Hydraulic and Water Resources Engineering Division, Department of Civil Engineering, University of Moratuwa...... 7 Message from the Center Chairman, UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM), Department of Civil Engineering, University of Moratuwa ...... 8 Message from the Course Coordinator, MSc/PG Diploma in Water Resources Engineering and Management, UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM), Department of Civil Engineering, University of Moratuwa ...... 10 Message from the Director, Postgraduate Studies, Faculty of Engineering, University of Moratuwa…….12 TECHNICAL PAPERS SESSION 1 ...... 13 Climate scenario identification and evaluation of irrigation responses: case study application of Rambakan oya reservoir using irrigation department guidelines ...... 15 Potential of Water Balance Modelling with Surface Water Pollution Considerations to Manage Ungauged Watersheds with an Emphasis on Multi User Concepts – Demonstrating an Application at a Watershed in Dampe, Sri Lanka ...... 21 Raster GIS modelling when selecting a suitable solid waste dumping site ...... 29 Determination of a Design Rainfall Pattern by Comparing With Its Effect on Streamflow on Greater Colombo Watershed in Sri Lanka ...... 35 Evaluation of Irrigation Water Issue Practice for Better Water Management at Rajangana Reservoir, Sri Lanka………………………………………………………………………………………………………………………………………..………….41 Incorporation of Water Distribution Network Costs in Water Supply System Design Highlighting the Strength of Raster GIS Modelling ...... 53 Climate Change Impacts and Adaptation Measures for Pahala Divul Wewa, Anuradhapura, Sri Lanka .. 59 TECHNICAL PAPERS SESSION 2 ...... 63 Study of Urban Water Demand and Distribution System Reliability – A Case Study of Maharagama Water Supply Scheme, Sri Lanka ...... 65 A Quantitative Analysis of Surface water in the Uruboku Oya basin Demonstrating the Application Potential of IWRM Principles to Complex Irrigation Systems ...... 71 Increasing the Cropping Intensity by Changing the Cropping Pattern in a Minor Tank ...... 79 Computation and Optimization of Snyder’s Synthetic Unit Hydrograph Parameters…………………………… 83 Sustainable Solutions for the Drying Up of Groundwater Wells – A Case Study in a Selected Watershed in Dampe, Sri Lanka ...... 89 Investigating the impacts of climate change and adaptation options in Handegama tank for irrigation water management……………………………………………………………………………………………………………………………..99 TECHNICAL PAPERS SESSION 3 ...... 103 A Raster GIS Model for Water Supply Tower and Source Option Prioritisation in Community Based Water Supply Schemes at Attanagalla, Sri Lanka ...... 105 Hydrological Modelling Approach for Flood and Water Pollution Control in an Ungauged Catchment - A Case Study in Erewwala Catchment in Bolgoda River Basin, Sri Lanka ...... 111 Attempting to improve seasonal performance of Land and water productivity through systematic analysis: Case study of Dahanaka Minor Irrigation Tank in Anuradhapura District of Sri Lanka ...... 117 Climate Change Impacts and Adaptation Measures in Giritale Reservoir in Polonnaruwa Sri Lanka .....123 Possibility of Increasing the Land and Water Productivity of Command Area in Labunoruwa Irrigation Tank, Anuradapura, Sri Lanka ...... 129 Drainage Management in an Urban Watershed under Climate Change Scenario using IWRM Concepts ...... 137 THE UNESCO MADANJEET SINGH CENTRE FOR SOUTH ASIA WATER MANAGEMENT ...... 143 UNESCO Madanjeet Singh Centre for South Asia Water Management ...... 145 Irrigation and Hydraulic Urban Research Facility -1 ...... 146 Irrigation and Hydraulic Urban Research Facility -2 ...... 147 Hybrid Irrigation Research facility ...... 148 Meteorological Observation Station ...... 149 Acknowledgements ...... 150 CONFERENCE PROGRAMME AND MESSAGES
1 UMCSAWM Water Conference on Demonstrating the Strength of Water Engineering and Management Capability through Case Study Applications
Programme
Inaugural Session
8.00 am Arrival of Participants and Registration Arrival of Participants and Guests
8.15 am Arrival of Invited Guests and South Asian Foundation (SAF) Delegates
8.30 am Lighting of Traditional Oil Lamp
8.35 am National Anthem
8.40 am Welcome and Introduction to the Conference: Prof. Sohan Wijesekera, Centre Chairman/Overall Program Coordinator, UMCSAWM 8.50 am Address by Mr. Harsha Ratnasooriya Head, Hydraulic and Water Resources Engineering Division, Department of Civil Engineering, Faculty of Engineering 9.00 am Address by Prof. Saman Bandara Head, Department of Civil Engineering, Faculty of Engineering 9.10 am Address by Prof. Kapila Perera Dean, Faculty of Engineering 9.20 am Address by Prof. Ananda Jayawardane Vice Chancellor 9.30 am Vote of Thanks by Dr. Lalith Rajapakse Conference Chair, Course Coordinator-MSc/PG Diploma in Water Resources Engineering and Management Refreshments (First floor – lobby)
10.00 am Technical Session 1
Climate Change Impacts on Irrigation Schemes: Climate Scenario Identification and Evaluation of Irrigation Responses: Case Study Application of Rambakan Oya Reservoir using Irrigation Department Guidelines: W.V.K. Deshapriya and N.T.S. Wijesekera IWRM ungauged catchments: Potential of Water Balance Modelling with Surface Water Pollution Considerations to Manage Ungauged Watersheds with an Emphasis on Multi User Concepts – Demonstrating an Application at a Watershed in Dampe, Sri Lanka : A.C. Dahanayake and N.T.S. Wijesekera Raster GIS for Solid Waste: Raster GIS Modelling when Selecting a Suitable Solid Waste Dumping Site: R.M.L.U. Rathnayaka and N.T.S. Wijesekera Design Rainfall for Flood Management: Determination of a Design Rainfall Pattern by Comparing with its Effect on Streamflow on Greater Colombo Watershed in Sri Lanka: W.H.Keerthirathne and N.T.S. Wijesekera Evaluation of Irrigation Water Use Reality: Evaluation of Irrigation Water Issue Practice for Better Water Management at Rajangana Reservoir, Sri Lanka: H. Chemjong and N.T.S. Wijesekera
2 GIS and Water Supply Distribution Network Costs: Incorporation of Water Distribution Network Costs in Water Supply System Design Highlighting the Strength of Raster GIS Modelling: D.M.S.S. Dissanayake and N.T.S. Wijesekera Climate Change Impacts on Minor Irrigation Reservoirs: Climate Change Impacts and Adaptation Measures for Pahala Divul Wewa, Anuradhapura, Sri Lanka: P. S. Thakuri and N.T.S Wijesekera Luncheon
1.30 pm Technical Session 2
Urban Water Supply Distribution System Reliability: Study of Urban Water Demand and Distribution System Reliability – A Case Study of Maharagama Water Supply Scheme, Sri Lanka: D.M.S.S. Dissanayake and R.L.H.L. Rajapakse IWRM In Agricultural Areas: A Quantitative Analysis of Surface Water in The Uruboku Oya Basin Demonstrating the Application Potential of IWRM Principles to Complex Irrigation Systems: P.M. Jayadeera and N.T.S. Wijesekera Irrigation and Crop Yield Options: Increasing the Cropping Intensity by Changing the Cropping Pattern in a Minor Tank: R.M.M.R Alawatugoda and N.T.S. Wijesekera Hydraulic Modelling in Ungauged Catchments: Computation and Optimization of Snyder’s Synthetic Unit Hydrograph Parameters: G. Thapa and N.T.S. Wijesekera Groundwater Modelling with ABCD Model: Sustainable Solutions for the Drying Up of Groundwater Wells – A Case Study in a Selected Watershed in Dampe, Sri Lanka: A.C. Dahanayake and R. L. H. L. Rajapakse Climate Change Impacts on Minor Irrigation Reservoirs: Investigating the Impacts of Climate Change and Adaptation Options in Handegama Tank for Irrigation Water Management: K. Wangmo and N.T.S. Wijesekera Tea
3.30 pm Technical Session 3
GIS and Community Water Supply: A Raster GIS Model for Water Supply Tower and Source Option Prioritisation in Community Based Water Supply Schemes at Attanagalla, Sri Lanka: T.K.N.K. Kumari and N.T.S. Wijesekera Hydraulic Modelling for Flood and Pollution Control: Hydrological Modelling Approach for Flood and Water Pollution Control in an Ungauged Catchment: Case Study- Erewwala Catchment in Bolgoda River Basin, Sri Lanka: S. N. Jayasinghe and R. L. H. L. Rajapakse Land and Water Productivity in Minor Irrigation: Attempting to Improve Seasonal Performance of Land and Water Productivity Through Systematic Analysis: Case Study of Dahanaka Minor Irrigation Tank in Anuradhapura District of Sri Lanka: P.R. Gamage and N.T.S. Wijesekera Climate Change Impacts on Minor Irrigation Reservoirs: Climate Change Impacts and Adaptation Measures in Giritale Reservoir in Polonnaruwa Sri Lanka: M. Kamran And N.T.S. Wijesekera Water Productivity in Irrigation Reservoirs: Possibility of Increasing the Land and Water Productivity of Command Area in Labunoruwa Irrigation Tank, Anuradapura, Sri Lanka: M.B. Sharifi and N.T.S. Wijesekera IWRM in Urban Catchment : Drainage Management in an Urban Watershed Under Climate Change Scenario Using IWRM Concepts: J.P.G. Jayaratne and N.T.S. Wijesekera
3 Message from the Vice Chancellor, University of Moratuwa I am pleased to send this message to mark the UMCSAWM Water Conference organized by the UNESCO Madanjeet Singh Centre of South Asia Water Management (UMCSAWM) and Department of Civil Engineering, University of Moratuwa. The UNESCO Centre is an important entity of the University as it is our first ever UNESCO affiliation, first centre with a building facility of its own, and first centre with fulltime international students. Most importantly, it covers the globally important topic of management of water resources.
With our vision to be the most globally recognized Knowledge Enterprise in South Asia, the Hydraulic and Water Resources Engineering Division of the Department of Civil Engineering with its competent staff, has been providing quality education in water and irrigation to our nation and regional nations. The opening of the UNESCO Madanjeet Singh Centre and the commencement of the fulltime International Master’s Degree programme in Water Resources Engineering and Management in 2013 were remarkable achievements in this direction. I have no doubt that this UMCSAWM Water Conference is another huge stride by the University of Moratuwa towards this national and regional development mission. It demonstrates the quality of the Water Management and Engineering Education at our University aligning with our objective of carrying out nationally and regionally relevant, high- impact research to expand the boundaries of knowledge while enhancing the associated technological capabilities.
I note that the Centre and its programmes are progressing remarkably well with ongoing postgraduate research, projects undertaken, publishing and extending direct applications to the industry through knowledge sharing by leading the way through hosting important events in this nature. These efforts are substantially supported by the South Asia Foundation (SAF) which provides full scholarships to SAARC country students to join the programme as a result of visionary leadership of the UNESCO Goodwill Ambassador Late Shri Madanjeet Singh who also donated a new building for our regional centre.
While taking this opportunity to thank all those who have worked tirelessly to make this Conference a reality, I wish the programme, the Department and Centre, and its staff, alumni and students all the success and strength to do even better in the years to come.
Prof. A.K.W. Jayawardane
Vice Chancellor University of Moratuwa Moratuwa Sri Lanka
4 Message from the Dean, Faculty of Engineering, University of Moratuwa Engineering Faculty of University of Moratuwa is a well-established entity, leading the arena of technical education in the country. The Faculty at present comprises 12 academic departments, over 200 academic staff and around 3500 undergraduate and postgraduate students and offers Bachelor of the Science of Engineering degree in 9 disciplines and a a large number of post-graduate degrees. The UNESCO Madanjeet Singh Centre is affiliated with the Faculty of Engineering and is found to host the cross faculty and interdisciplinary water management course.
The existence of water is essential for life on earth. Although 70% of the earth surface is covered with water, less than 1% of this is available as drinking water and other needs of the 7 billion human population and all the other species. This limited capacity coupled with industrialization where water has also become much accepted renewable source of electricity generation, different political and institutional governance structures unique for each country etc., have made water resource management extremely complex. Prior to industrialization, water had been used predominantly for agriculture. Industrialization had resulted not only water pollution but also climate change which in turn had led to drought conditions. Ultimately there is a stiff completion for sharing of water between agriculture, industry and humans which has become difficult to manage.
Arising with the above described complexity, the Centre and its program have evolved addressing topics that include a broad range of application trends and are catering to the most pressing requirements such as water infrastructure, irrigation, water resources engineering and management, climate change, flood risk assessment and mitigation, trends in GIS and remote sensing, and industry applications and gap filling.
Furthering in this context, the Water Conference organized by the UNESCO Madanjeet Singh Centre for South Asia Water Management of the Department of Civil Engineering, University of Moratuwa, Sri Lanka will certainly demonstrate the strength of water engineering and management capability through case study applications. This forum where dissemination of the research projects and project based learning through case studies undertaken by the participants of the International Master’s program on Water Resources Engineering and Management is scheduled to take place, is timely to Sri Lanka and the South Asian countries because of the prevailing drought conditions.
There is a need for the industry to step up contributing towards research and training and I hope that this Conference will be successful platform not only for knowledge sharing and dissemination, but also in developing industry links and collaborations much needed in pursuing its future goals and aspirations.
Prof. K.K.C.K. Perera
Dean, Faculty of Engineering University of Moratuwa Sri Lanka
5 Message from the Head, Department of Civil Engineering, University of Moratuwa The Department of Civil Engineering is one of the strongest department in the Faculty of Engineering, and leadership in pioneering activities of University of Moratuwa has mostly been provided by the Department of Civil Engineering. The launching of the first ever fulltime postgraduate program in Water Resources Engineering and Management is one of them.
Over 35 years ago in 1982, Department of Civil Engineering commenced the first postgraduate programme in the university. Presently there are six (6) groups of research specializations for administrative purposes, namely; Building and Structural Engineering, Construction Engineering and Management, Environmental Engineering, Geotechnical Engineering, Hydraulic and Water Resources Engineering, and Transportation Engineering with highly qualified and talented staff cadre of 43, out of which 41 are with postgraduate qualification (33 with PhD’s), while 17 are professors. They are involved in undergraduate and postgraduate teaching, research and training while over and above contributing immensely to the development projects and activities of national interest.
The commencement of the UMCSAWM and its programme have been instrumental in further strengthening infrastructure facilities and capabilities of the Department. The cutting edge, state of the art research facilities under construction will be useful in enhancing postgraduate and undergraduate teaching and research. The recruiting of regional students from SAARC nations, undertaking of industry based projects and organizing of international workshops and conferences by UMCSAWM are helping to strengthen much needed industry and overseas research collaborations benefitting both undergraduate and postgraduate programs.
I would like to wish this UMCSAWM Water Conference which is based on students’ research projects an absolute success.
Prof. J.M.S.J. Bandara
Head, Department of Civil Engineering Faculty of Engineering University of Moratuwa Sri Lanka
6 Message from the Head, Hydraulic and Water Resources Engineering Division, Department of Civil Engineering, University of Moratuwa The Water Group of the Department of Civil Engineering is extremely proud of its achievements to date, including the introducing of the first postgraduate program in the University of Moratuwa. The establishment of the UNESCO Madanjeet Singh Centre of South Asia Water Management (UMCSAWM) is another milestone in the history line.
The biggest strength of the Water Group is its well-versed staff equally qualified with academic credentials and field expertise covering vast arena of water and related fields including surface and groundwater hydrology, hydraulics, irrigation, water resources management, coastal and engineering and estuarine modelling, water related GIS and remote sensing applications, and hydrodynamic modelling and applications, etc.
The staff is involved in teaching and pioneering research in water resources management, irrigation practices, coastal wave dynamics and various other themes of timely importance, and industry based research and applications while serving in various departmental, faculty and university committees and various other for a of national and international recognition.
The fully equipped hydraulic engineering laboratory has the apparatus and computer facilities required for studying hydraulic engineering problems of practical interest. These include, channel flow simulators and hydraulic flumes, pipe friction and hydraulic machinery, hydraulic benches for multiple test platforms, etc. Computer aided exercises are also carried out for the students to acquaint themselves with the use of computer packages used in the industry.
The newest additions to the group’s strengths are the UNESCO Water Centre and the international postgraduate program conducted by the Department of Civil Engineering in collaboration with the South Asia Foundation (SAF-India).
With all these facilities, strengths and expertise available, the Water Group is even more determined to serve the Department, University, nation and the region in the years to come.
Mr. A.H.R. Ratnasooriya
Head, Hydraulic and Water Resources Engineering Division Department of Civil Engineering Faculty of Engineering University of Moratuwa Sri Lanka
7 Message from the Center Chairman, UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM), University of Moratuwa
In 2003, UNESCO Madanjeet Singh Center for South Asia Water Management (UMCSAWM) project was initiated by then Honourable Foreign Minister Lakshman Kadiragarmar and it was finalized when South Asia Foundation (SAF) received the generous patronage of then UNESCO goodwill ambassador Shri Madanjeet Singh. Professor Malik Ranasinghe then Dean Engineering at University of Moratuwa and Professor Dayantha Wijeyasekera then Vice Chancellor extended their fullest support enabling the construction of buildings and commencing the fulltime international Master’s Degree program in Water Resources Engineering and Management. SAF supported the water management program by extending eight full time scholarships for member nations while Shri Madanjeet Singh provided personal contributions to fulfill fifty percent of requirements for UMCSAWM building. The UMCSAWM attached to the Faculty of Engineering, University of Moratuwa, Sri Lanka was established through a Cabinet Memorandum No. HE/UD/2010/31dated 29.09.2010.
The UMCSAWM building and the postgraduate degree program on water management was inaugurated in 2013. Since then, the center has stood up to its expectations. The collaborative Master’s Degree Programme with the Department of Civil Engineering from its inception reached the international standards. Presently the third intake is finishing their academic sessions. A salient feature of research and training spearheaded by the UMCSAWM is its strong emphasis on the practical applications and providing solutions for the gaps in the industry.
Other than the postgraduate programs, the UMCSAWM is proud about three new initiatives. One is the first irrigation and hydraulic research facility providing the capability to use full scale field canal level hydraulic structures for students to carryout research and for the industry personnel to obtain systematic field scale-training. This facility is the first of its kind not only in Sri Lankan universities but also in the industry filling a major gap in the determination of model parameters for water management. This facility located in front of the center is nearing completion. UMCSAWM is proud about this initiative which will no doubt encourage the industry to develop advanced field level experimental facilities further strengthening the hydraulic, irrigation and water management in the South Asian region.
Second initiative is the Urban Drainage Research facility that enables research on surface and subsurface drainage with the changes to the landcover, soil type, slope and rainfall. A major problem in our South Asian monsoon region is the poor drainage infrastructure designs associated with the roads, especially in Urban areas. With the slightest rain, most highways not only in Sri Lanka, but also in the region, become waterways thus negatively contributing to national economic growth. This research facility nearing completion at the UMCSAWM would provide opportunity to carryout infiltration and runoff research for the sustainable drainage infrastructure modelling and help to fill the lack of local parameters for road drainage structure designs.
The third initiative is research on the use of IoT (Internet of Things) breakthroughs for water management. This research facility is on “Precision Irrigation” which uses several soil moisture sensors to determine the moisture in the root zone of an agricultural crop and then provide water to fulfil the requirements of the plant growth without undue loading of the environment. This research facility uses the cloud based, wireless, low energy consuming technologies providing the plant-water status and control of solenoid water valves through a remote personnel computer linked via internet. This facility is a hybrid research facility intended to experiment between expensive research grade sensors and low cost freely available sensors for rain, soil moisture and water valve controls to compare the difference in water use and associated cost. This facility is also located in the vicinity of UMCSAWM and has achieved the establishment of equipment. This demonstrates the attempts made by UMCSAWM to combine
8 developments in the IT and Electronics engineering, with Water Management in the Civil engineering domain.
Last but not least, it is necessary to state that the UMCSAWM has established sufficient goodwill to secure the support of state institutions for research and training. The Mahaweli Authority enabled the establishment of a fully-fledged meteorological and water quality data collection station within the UMCSAWM compound linking the center to the national water data collection grid. The National Water Supply and Drainage Board and the Department of Irrigation have expressed their willingness to provide support for collaborative research.
Today, UMCSAWM has reached another milestone. It is this first water conference demonstrating the strength of our own postgraduate students to provide solutions for water resources engineering and management problems even in data scarce situations. This conference highlights the possibility of applying water management principles with state of the art modelling tools to ensure water and food security amidst climate change.
I wish that Late Shri Madanjeet Singh and Late Honourable Lakshman Kadirgamar were with us to share the joy and satisfaction felt by us. These two noblemen, the pioneers, persons with vision, commitment and faith entrusted University of Moratuwa to contribute towards the task of water management while achieving international standards and regional expectations. We gratefully acknowledge their contributions. The past and present vice chancellors of our university, the past and present board members of the UMCSAWM, past and present members of the SAF Sri Lankan Chapter and the SAF India, the university administrative and academic staff members, the Department of Civil Engineering heads and staff, the Water Division, Our past & present students and well-wishers are sincerely thanked for their tremendous contributions towards our impact on the regional water management.
Let me especially mention Ms. France Marquet, the Trustee, the other board members, and the governing council members for taking their time to visit the centre and to spend time with our past and present students. The initiative taken by Dr. Nishchal Pandey to hold the governing council meeting in Sri Lanka, the support given by Mr. Prabhakaran and other key personnel at SAF India, towards the UMCSAWM activities are gratefully acknowledged. We appreciate your kindness, consideration and look forward to your future visits and contributions.
The present conference is dedicated to selected projects and research conducted by our postgraduate students. Conference proceedings will demonstrate the comprehensiveness of the applications. I am confident that this event will project the quality of water resources management research and projects carried out by postgraduate candidates from the University of Moratuwa.
Prof. N.T.S. Wijesekera
Center Chairman, UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) Department of Civil Engineering Faculty of Engineering University of Moratuwa Sri Lanka
9 Message from the Course Coordinator, MSc/PG Diploma in Water Resources Engineering and Management, UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM), University of Moratuwa
In 1995, the Hydraulic Division of Department of Civil Engineering which is presently known as the Hydraulic and Water Resources Engineering Division conducted the first Master of Engineering / Postgraduate Diploma Course of University of Moratuwa. This program in Water Resources Engineering and Management was conducted once in two years until the year 2006. In 2013 with the Initiation of UNESCO Madanjeet Singh Center (UMCSAWM) and the support of the South Asia Foundation (SAF), the Hydraulic and Water Resources Engineering Division commenced the ongoing, Master of Engineering / Postgraduate Diploma in Water Resources Engineering and Management. This Master’s degree program which consists of two components as one-year full time and two-year part time offer eight fully paid Madanjeet Singh Scholarships funded by SAF to SAARC member countries and facilitate pioneer water management research in areas of relevance to South Asian countries. This postgraduate programme which is especially designed to teach Water Management in a regional context enables participants possessing a wide range of water management backgrounds to obtain a firm grounding in the principles, techniques, issues and practice of Water Resources Engineering and Management. This course is designed mainly for practicing civil engineers to update their knowledge and keep abreast with recent developments in hydraulic engineering and water resources management fields. The programme is run as a self-financed programme where the course fee paid by the students is used as the main financial resource for recurrent expenditure, development of the course and laboratory facilities.
This programme is designed to systematically cover all taught courses within the first 12 months. During this period, students follow a series of intensive lectures, attend seminars, complete subject specific assignments, experiments and field visits. Lectures and other academic activities for full time (international) students are conducted from Tuesday to Saturday while for part time (local) students, activities are usually conducted only on Fridays and Saturdays. The total of 60 credits required for the one-year fulltime program is comparable with any other international program usually conducted over a period of two years. This all-embracing program structure based on taught courses, research and especially with Problem Based Learning (PBL) approach common to all modules brings together the scientific study of water resources with practical planning and management skills, encouraging participants to study water management from a multi-disciplinary perspective and to seek integrated solutions.
The greatest strength of this postgraduate program is the individual “Problem Based Learning Project” that a student is required to complete to successfully complete each course module. Each of these individual PBL projects are based on real life data and experiences related to the water sector and to each specific subject module. These projects are the core of continuous assessment mechanism. World over almost all problem based projects are group activities. The problem based projects incorporated to the present program are hybrids because they are student driven, carefully guided, facilitated with time for group discussions and group working sessions, field data and literature backed, regularly supervised, closely monitored, and externally and internally evaluated.
This concept of problem based learning is new in the world, challenging in postgraduate programs, demanding at individual project basis and taxes additional time from academics. Over the last three programs, conducting and completing the PBL projects had been a great challenge. Determined efforts of Water Division Academics and commitment of UMCSAWM staff to achieve international dominance has made this effort a success.
10 Though most of the student reactions for PBL at the initial stage of each program indicated negative, the end of program feedbacks expressed a tremendous appreciation for the guidance and opportunity given to build confidence in practical applications. The consensus of student opinion had been that the water- maturity gained by attending the Master’s degree program was because of the individual projects for which the students had to find solutions on their own, produce a report, back the workings with field data and literature, and then carryout a final presentation as part of a viva.
In the recent three intakes the program has admitted 12 international and 7 fulltime students on scholarships, 40 part time local students. 06 have thus far graduated with a Master’s Degree while 04 have obtained the Postgraduate Diploma.
The present conference on Demonstrating the Strength of Water Engineering and Management Capability through Case Study Applications is an attempt to show the strength of the PBL and Research projects conducted by our present and past students. They demonstrate the case study applications and rigorous research undertaken as part of the program and exhibit the competence and maturity of our students when handling field level problems in water management.
As the course coordinator and the conference chair let me take this opportunity to thank all those involved in the program for their support and encouragement. During the past three years during my tenure as the course coordinator we have passed many milestones and conquered tough challenges. I am certain that the postgraduate program has served to its expectations and the SAF would be pleased with the outcomes. At this point of time it is my duty to first acknowledge the pioneering vision of Late Shri Madanjeet Singh and Late Honourable Lakshman Kadirgamar which has given us tremendous strength to shine among similar international postgraduate programs.
I would like to take this opportunity to thank the past and present vice chancellors of our university, the past and present board members of the UMCSAWM, the Director of the UMCSAWM, past and present members of the SAF Sri Lankan Chapter and the SAF India for all the support extended to us. Without such support and encouragement, this task would not have been fulfilled. We would not have been able to achieve these targets without the unstinted support given by the academic and non-academic staff of the Department of civil engineering. The support given by the Head civil engineering, Dean faculty of engineering, the Registrar, Bursar, Librarian and staff of their divisions are gratefully acknowledged. With the continued support of the university and the SAF, we are certain to achieve greater heights.
Dr. R.L.H.L. Rajapakse
Course Coordinator, MSc/PG Diploma in Water Resources Engineering and Management UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) Department of Civil Engineering Faculty of Engineering University of Moratuwa Sri Lanka
11
Message from the Director, Postgraduate Studies, Faculty of Engineering, University of Moratuwa
I feel very much honoured to add a message to the proceedings of the Water conference organized by the UNESCO Madanjeet Singh Centre for South Asia. First of all, I wish to congratulate the program Director, the Course Coordinator and the conference committee for organizing this event.
Water is an essential natural resource which is vital for the functioning of ecosystem and human wellbeing. At the same time, this precious resource is under considerable pressure with the global climate change, demographic and economic changes. Therefore, water resource management has been identified as a key theme in sustainable development all over the world. The ever increasing demand for drinking, sanitation, manufacturing, leisure and agriculture has exploited this limited resource. With that water resource management has evolved, aiming at optimizing the use of water and minimizing the environmental impacts. The functions involved in water resource management are complex and needs players at different levels. Significant management of any resource requires accurate knowledge of the resource availability, its uses, the competing demands, and policy decisions on the evaluating significance of competing demands. For water as a resource this is particularly difficult since the natural sources of water cross many national boundaries and hard to assign a financial value.
In this context, the Water Conference organized by the UNESCO Madanjeet Singh Centre is very timely and I am sure will demonstrate the strengths of Water Engineering and Management. Another prominent feature of the Masters course offered by the Madanjeet Singh Centre is its contribution towards international recognition of our university. At the Strategic planning workshop of University of Moratuwa, held on 6th and 7th of January 2017, one of the key themes identified as to position our university at a reputed international ranking system. Currently we are working on the QS ranking system with the hope of going for Times Higher Education ranking in the future. The international collaborations initiated and strengthened by the Masters course offered by the Madanjeet Singh Centre for South Asia is contributing to this exercise immensely. The course is in the right direction of internationalization and also run in a very systematic manner. As the Director, Postgraduate studies, Faculty of Engineering, I am happy to say that this is one of the best courses run by the Faculty with excellent coordination and also in terms of other administrative work. Our job at the Board of Studies has been made very easy with the commitment of the staff and the able course coordination.
The timely topics of this conference, on climate change impacts and adaptation options for water management, flood risk assessment and damage mitigation, GIS application for water resource planning and management will definitely pitch at the state of the art research and development.
I wish all the participants a very productive and a pleasant conference with knowledge sharing and dissemination.
Prof. Mrs. C. Jayasinghe
Director, Postgraduate Studies Division, Faculty of Engineering, University of Moratuwa Sri Lanka
12 UMCSAWM Water Conference – 2017
TECHNICAL PAPERS
SESSION 1
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 13 UMCSAWM Water Conference – 2017
14 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Climate Scenario Identification and Evaluation of Irrigation Responses: Case Study Application of Rambakan Oya Reservoir Using Irrigation Department Guidelines
W.V.K. Deshapriya and N.T.S. Wijesekera
ABSTRACT Present study was carried out to demonstrate the capability of Irrigation Department Guideline (IDG) model to assess climate change impacts under variety of scenarios by carrying out a case study of Rambakan oya irrigation scheme. The IDG model was optimized for the current irrigable area and verified by checking the irrigable area, spilling months, maximum and minimum storages with qualitative field assessments. Six climate change scenario were developed and three scenarios were identified as critical scenario after evaluating the possible impacts on cultivation extents. Critical scenario were incorporated in to the optimized model in order to evaluate the response and it was observed that a 30% decrease in north-east monsoon (December to February) and 30% increase in south-west monsoon (May to September) keeping the annual total constant would give rise to the highest impact. Annual irrigation demand of Ramabakan Oya reservoir increases by 3% and the cropping intensity reduces from 1.0 to 0.76 and 0.83 to 0.72 in maha and yala seasons respectively. Since cropping intensity of the Rambakan Oya could reduce up to 20% under future climate change scenario, it would be better to incorporate adaptation measures to execute water management plans in the future. Project efficiency enhancement of 7% will allow the present cropping intensity to be maintained under the worst-case scenario for Rambakan oya irrigation scheme
KEYWORDS: Climate change, Impacts, Irrigation schemes, Rambakan oya
many attempts have been made to predict future 1. Introduction scenario (Eriyagama and Smakthin 2010). However, there is a void in the establishment of Climate change is considered as the greatest critical climate scenario for Sri Lanka to evaluate the challenge for humanity to survive in a sustainable impacts on the irrigated agriculture. As the environment. The Intergovernmental Panel on evaluation of climate change on irrigation schemes Climate Change (IPCC) reports that the scientific in Sri Lanka does not appear sufficiently detailed evidence for warming of climate is unequivocal the present work carried out a study to evaluate the (IPCC 2014). As the earth’s temperature continues potential impacts on agriculture in Sri Lanka by to rise, significant impacts on water resources are carrying out a study of Rambakan oya irrigation expected. Water related effects of climate change scheme. This study is expected to contribute and mostly due to variations in air and water towards systematic planning of water resources temperature and rainfall, sea level rise and ocean proceed to develop suitable water management acidification. These impacts are expected to policy for situations under climate change. significantly affect many water use sectors such as agriculture and food production, water supply and 2. Literature Review human health, energy production, fisheries, infrastructure, ecosystems. The 5th Assessment Report (AR4) of IPCC (IPCC Agriculture and Food production sector is probably 2014) provides global temperature predictions facing the most critical situation mainly because of under four Representative Concentration Pathway the increased climate change effects experienced at (RCP) scenarios. Under all 4 scenarios global present combined with global population temperature is expected to increase by at least by explosion. Agriculture sector is the cornerstone of 2oC by year 2100. Highest increase of 4°C is Sri Lanka's economy with more than 70% of expected under the RCP 8.5 scenario. By 2100, the population in rural areas depending on agriculture temperature increase in Sri Lanka, during South- as their livelihoods. Currently agriculture sector West monsoon (SWM) season (May to September) contributes to about 18% of the Gross Domestic Product (GDP) and 30% of the employment. W.V.K. Deshapriya, B.Sc. Eng. (Hons), AMIE(SL), Literature review on climate changes in Sri Lanka Irrigation Engineer, Department of Irrigation, Sri Lanka. has shown that climate in Sri Lanka is changing in N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip the direction of IPCC forecasts. Though there is a (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., lack of perfect agreement between researchers, MICE(UK), FIE(SL), Senior Professor, Department of Civil Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 15 UMCSAWM Water Conference – 2017 is anticipated to be 2.5 °C, whilst the North-East guideline (ID 1984). Model computations were monsoon (NWM) season (December to February) based on the water balance of the reservoir system the expectation is 2.9 °C (Department of described in the guidelines of the Irrigation Meteorology, Sri Lanka). In this backdrop, it is fair Department. Water Balance model was optimized to expect at least a 2 degree rise in the temperature for the current irrigable area by changing the increase by the mid-21st century. Due to the storage at the beginning of October to match with increase in temperature there is the possibility of the end storage at the end of September using a trial rise in evaporation. Hence, determining and error process. Model was verified by checking evaporation rates is essential for efficient the irrigable area, spilling months in the model with management of reservoirs and water resources. actual cultivated land area. The calibrated model (Helfer, Lemckert & Zang, 2012) in a climate change was used to carry out an annual water balance impact study with a large reservoir in Australia incorporating the identified critical scenario. to find stated that between 2030 - 2050 annual evaporation out the impacts on cultivation extent. will be 8% higher than that estimated for the current temperature increase of 0.9 °C. 4. Data IPCC (2014) states that future increases in In the Rambakan Oya scheme a three-stagger precipitation extremes related to monsoon are very system is practiced. In water balance computations, likely in East, South, and Southeast Asia. Moreover, 75% probable rainfall was used as recommended by it states that all models and all scenario project an the ID (1984). 75% probable rainfall values in the increase in both the mean and extreme precipitation guideline were compared with those calculated in the Indian summer monsoon and Southern Asia. from monthly rainfall data of 25 years (1980/81 to In the case of Sri Lanka peer reviewed studies on 2004/05) considered in the feasibility study of the changes in precipitation are limited. (Eriyagama Rambakan Oya reservoir. Rainfall values used for and Smakhtin, 2010) states that it is evident that Sri the Feasibility Study were taken as inputs for the Lanka’s climate has already changed and although present work. Area capacity curve of Rambakan attempts have been made to project Sri Lanka’s Oya Reservoir, thiessen averaged rainfall, climate in the twenty-first century, these studies cultivation patterns, crops and crop factors etc., lack consensuses and their results and projections used to develop the water balance model was are contradictory. obtained either from those collected by the National level modeling, undertaken by the Sri Irrigation Department or from those in the ID Lankan Centre for Climate Change Studies, suggest (1984). Reference crop evapotranspiration (ET0), that the changes in Sri Lanka broadly - but not Crop coefficients and monthly evaporation data completely - follow the regional expectations. were also obtained from the ID (1984). Location of Rainfall in Sri Lanka is expected to be slightly the Rambakan oya reservoir is shown in figure 1. different from to the regional trend, with increases in rainfall levels anticipated in both SWM and NEM (Department of Meteorology, Sri Lanka). Eriyagama & Smakhtin, (2010) states that the two regional climate models (Kumar et al. 2006; and Islam and Rehman, 2004), and downscaled projections by Basnayake and Vithanage (2004) suggest increases in both SWM and NEM rainfall, with Basnayake and Vithanage (2004), suggesting higher increases in SWM than in NEM. Eriyagama & Smakhtin, (2010) in their work mentioned that Statistically downscaled projections from the HadCM3 model by De Silva (2006) predicts a 26-34 % decrease in the NEM rainfall in the dry zone and a 16-38 % increase in the SWM Figure 1 : Rambakan Oya Reservoir rainfall in the wet zone by 2050. Downscaled projections from CSIRO models Basnayake and 5. Analysis Vithanage, (2004) projected an increased rainfall in SWM and a decrease in NEM. 5.1. Climate Change Scenario Based on the literature survey and an order of magnitude evaluation of situations identified the 3. Methodology critical scenario described below. A reservoir water balance model was developed to Scenario - 01 model the feasible irrigable area in Maha and Yala A 15% evaporation increase for a 2 degree increase seasons for the current situations. Irrigation in temperature affecting the reservoir and Demand for Paddy cultivation in Maha and Yala cultivated crops. Seasons were calculated according to the Irrigation Scenario – 02
16 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
10% increase of rainfall in NEM and 10% increase in Dt 356 364 323 470 563 283 SWM Spt - - - 123 - - Scenario - 03 St 3731 4581 5486 5500 4967 4868 30% increase of rainfall in NEM and a 30% decrease in SWM Table 6.2: Yala Season Scenario - 04 Item Apr May June July Aug Sep 30% increase of rainfall SWM and a 30% decrease in St-1 NEM 4868 5119 4957 4291 3689 3184 Scenario - 05 It 343 308 68 148 182 537 10% decrease of rainfall in NEM and 10% decrease Et 68 77 90 86 78 66 in SWM Set 24 26 25 21 18 16 Scenario – 06 Dt 0 368 619 642 591 168 A one month backward shift of NEM and SWM Spt season commencement. ------St 5119 4957 4291 3689 3184 3471 5.2. System Water Balance Annual and seasonal irrigation demand, present irrigable area and cropping intensity for the existing The water balance of the reservoir system is as in situation in Rambakan oya scheme is shown in table equation 1. 6.3 It – (Et + Sei +Spt +Dt ) = St – St-1 ------(1) In this equation t is the time step which was Table 6.2: Seasonal Results considered as on month, I is the inflow, E is the Maha Yala Annual evaporation from the reservoir water surface, Se is Irrigation Demand 1626 1989 3615 the seepage from the reservoir bed, Sp is the spillage (Ha.m.) from the reservoir, D is the irrigation demand, S is Irrigable Area (Ha.) 1450 1200 2650 the storage of the reservoir. To model the irrigation Cropping Intensity 1.00 0.83 1.83 demand for each month Irrigation demand for 135 day and 105 day paddy cultivation in maha and 6.2. Identification of Critical Scenarios (CS) yala seasons respectively, was calculated according to the guideline of the Irrigation Department (1984). The changes in annual evaporation due to scenario Following equations were used for the computation 01 is less than 2% as a percentage of the inflow. of Irrigation Demand Hence this scenario was not considered as a critical (FWR)t = (LP)t + (Etc) + (FL)t ------(2) scenario. Under scenario 02, an even increase in the (FIR)t = (FWR)t – (ER)t ------(3) NEM and SWM both will lead to a better situation (ID)t = (FIR)t / η ------(4) than the present. Hence this scenario was not In these equations, t is the considered time step for considered as a critical situation. However, if an computations, Lp is the water requirement of land increase occurs then the irrigations planners may preparation, ETC is the water requirement for crop have to check the capacities to hold the water that evapotranspiration, and FL is the water would otherwise be spilled. If not, we will not be requirement to compensate for farm losses. FWR is able to take advantage of the climate change. the field water requirement, ER is the effective According to scenario 03, increase in rainfall in rainfall, FIR is the field irrigation requirement, D is NEM will not have much impact on the residual the irrigation demand and η is the project efficiency. storage at the end of maha season since even for the existing situation reservoir is at full capacity at the 6. Results end of January. Hence, decrease is SWM rainfall will have impact on the cultivation in yala season. 6.1. Present Situation in Rambakan Oya Therefore, scenario 03 was selected as critical Reservoir scenario 01 (CS – 01). Decrease in the NEM may Monthly storage at the beginning and end of each affect the Maha season and also the Yala season due month, inflow to the reservoir, evaporation, to the impact on the residual storage after the seepage, irrigation demand and spillage in hectare season. Since Yala rainfall is usually low, even if the meters (Ha.m) for the existing situation in SWM increases rainfall there is a high probability Rambakan oya scheme is shown in table 6.1 and for the Yala season to be affected. Hence the table 6.2 scenario 04 was studied as the critical scenario 02 (CS – 02). Table 6.1: Maha Season Under scenario 05 an even decrease in NEM and Item Oct Nov Dec Jan Feb Mar SWM rainfall will definitely have an impact on both St-1 3471 3731 4581 5486 5500 4967 seasons. Hence scenario 05 was categorized as critical scenario 03 (CS - 03). Cultivation activities It 688 1278 1297 691 116 277 such as land preparation, seeding, harvesting, etc., Et 55 45 46 58 58 69 in a scheme is planned according to the rainfall Set 17 19 23 27 28 25 pattern and expected monsoon onset dates.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 17 UMCSAWM Water Conference – 2017
Therefore, changes in rainfall pattern will have an Table 6.6: Cropping Intensity for scenarios impact on the cultivation activities. However, if the Cropping Intensity change in the pattern is straightforward then it can Case Maha Yala Total be recognized easily and then the farmers will adjust to the new rainfall pattern and plan their Scenario 1.00 0.83 1.83 cultivation activities accordingly. Therefore, CS 01 1.00 0.76 1.76 scenario 06 was not categorized as a critical CS 02 0.76 0.72 1.48 scenario. CS 03 0.83 0.78 1.60
6.3. Responses of Irrigation Schemes Under 7. Discussion Critical Climate Scenarios Future climate projections indicate that the climate Irrigation demand comparison of the three critical is changing and impacts on agriculture sector can be scenarios and the present situation is given table 6.4. expected. Worst climate change scenario for the It was observed that the irrigation demand Rambakan oya scheme is when the Northeast increases Maha season by 10% and 4% respectively monsoon decrease while increasing the southwest for CS 02 and CS 03. Irrigation demand reduces by monsoon. Worst climate scenario will reduce the 6% for the CS 01. In the Yala season irrigation cropping intensity of the scheme from 1.83 to 1.48, demand increase by 2% and 1% for CS 01 and CS 03. which is a decrease in 20%. Population growth in For CS 02 irrigation demand reduces by 3%. Total the future is also expected to increase and food irrigation demand increases by 3% and 2% for CS 02 scarcity is predicted in the future. So, it is important and CS 03 respectively, whereas total irrigation to at least maintain the existing irrigable in the demand reduces by 1% for CS 01. future. Therefore, implementing adaptation options Table 6.4: Irrigation Demand for Scenarios in the future is essential to the Rambakan Oya Irrigation Demand (mm) Scenario scheme. Maha Yala Total It is apparent that the due to the worst-case climate Present 1626 1989 3615 change scenario irrigation demand for paddy CS 01 1533 2032 3565 cultivation increases by 3%. In order to counter these impacts adaptation measures as to be planned CS 02 1790 1935 3726 for the scheme. Most common measure which the CS 03 1692 2005 3697 water managers are proposing is crop Comparison of possible cultivation extents are diversification. By cultivation crops which requires show in table 6.5. For all three scenarios, total less irrigation demand than paddy will enable cultivation extents during the year has reduced. farmers to cultivate the existing irrigable area. Highest reduction in cultivation extent is due to CS However, it is important to identify that the other 02. For CS 02 total cultivation reduction is 19% field crop cultivation will not generate sufficient which results due to reduction in maha and yala income compared to paddy. Therefore, increase in seasons by 24% and 13% respectively. For CS 03 poverty among the farmers could become a major reduction in total cultivation extent is 12%. For concern. In addition to that, if a proposed crop fails maha and yala seasons it is 17% and 6% farmers want be able to generate any income at all. respectively. Even though the total cultivation Hence, crop diversification may not be an extent reduces under CS 01, it was observed that acceptable adaptation measure moving forward. due to the increase in rainfall in north east monsoon One way to face the future scenario is to reduces the season cultivation extent can be increased than the losses by increasing the project efficiency. It was present situation. identified that project efficiency enhancement of 7% Table 6.5: Cultivation extents for scenarios would be sufficient to maintain the existing irrigable area under the worst-case climate change Irrigable Area (Ha) Scenario scenario. Hence, it is evident that most suitable Maha Yala Total adaptation measure is to increase the project Present 1450 1200 2650 efficiency. Adaptation measures such as CS 01 1525 1100 2625 development of resilient crops and early warning systems will be helpful to all irrigation schemes in CS 02 1100 1050 2150 the country. CS 03 1200 1125 2330 In this study, it was identified that for some Cropping intensities for each scenario is given in scenarios there could be greater rainfall in the maha table 6.6, cropping intensity reduces under all three season. Capturing this additional water by critical scenarios. Cropping intensity reduces from increasing the capacity is another point that the 1.83 to 1.48 water managers should look at. Furthermore, present study assumed that the climate change effects of rainfall will be predictable and uniform both spatially and temporally. Then only the
18 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 farmers can adapt to it provided that the change will become stationary. However, accuracy of these predictions is debatable. Therefore, it is important encourage more research work to predict the future climate scenarios more accurately.
8. Conclusions
Cropping intensity of the Rambakan Oya could reduce up to 20% under the expected worst-climate change scenario. Project efficiency enhancement of 7% will allow the present cropping intensity to be maintained under the worst-case scenario. Given the dependency of the agriculture in Sri Lanka it is important to study the possibility of development of resilient crops and early warning systems, and encourage more research work on climate change predictions since those would be helpful to all irrigation schemes in the country. Methodology used in this case study can be improved to develop a detailed approach to identify climate change impacts on irrigation schemes in Sri Lanka.
9. Acknowledgements
The authors are grateful to the UNESCO Madanjeet Singh Center for South Asia Water Management and the South Asia Foundation for conducting the international masters degree program in water resources engineering and management. The support given by the Irrigation Department of Sri Lanka by providing necessary data tis also acknowledged.
10. References
(Helfer, Lemckert & Zang, 2012). Impacts of climate change on temperature and evaporation from a large reservoir in Australia. Journal of Hydrology, 475, 365–378. IPCC. (2014). Summary for Policy Makers: In Climate Change 2014: Impacts, Adaptation, and Vulnerability. IPCC. Eriyagama, N., & Smakhtin, V. (2010). Observed and projected climatic changes, their impacts and adaptation options for Sri Lanka: a review. Proceedings of the National Conference on Water, Food Security, and Climate Change in Sri Lanka, 2, 99.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 19 UMCSAWM Water Conference – 2017
20 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Potential of Water Balance Modelling with Surface Water Pollution Considerations to Manage Ungauged Watersheds with an Emphasis on Multi User Concepts – Demonstrating an Application at a Watershed in Dampe, Sri Lanka
A.C. Dahanayake and N.T.S. Wijesekera
ABSTRACT Practicing integrated water resources management (IWRM) for sustainability is vital when there is multi user competition for the finite fresh water resources. In order to facilitate early decision making, it is necessary to evaluate ungauged small watersheds with simple, easy to apply but quantitative tools. This paper demonstrates the possibility of successfully applying the multiuser concept, the finite nature of water and system water balance, as a mean to overcome the surface water pollution in Dampe watershed (0.62km2), Sri Lanka. Since this watershed is ungauged, field visits, gauged data from the locality, estimates from available literature were used for a rational application of water balance to evaluate solutions for surface water pollution. The watershed runoff was calculated using a two parameter water balance model which enabled soil moisture accounting. The monthly water balance model for Dampe watershed which included multi sectoral water uses, the surface water quantity and quality at each key stream node for each sub catchment enabled the analysis of several scenarios. Remedial measures to overcome the problem and sustainable methods to preserve water for the future generation are proposed.
KEYWORDS: Integrated water resources management, Surface water pollution, two parameter water balance model, scenario analysis
application potential of IWRM principles especially 1. Introduction in data scarce or ungauged catchments. Hence a case study was undertaken to explore the potential In Sri Lanka over the past few decades the reliance of applying IWRM principles in a small ungauged on water for domestic, industrial, hydropower and watershed. The expectation was to carry out a agricultural uses has been on the rise and it is often systematic, logical step by step case study to arrive accused that discriminate and uncontrolled use is at the order of magnitude of water resources threatening the water resource availability of the situation at sub watershed levels paving the way to country. Water becomes a resource approaching convince the stake-holders to embark on data critical levels mainly because of the population collection programs to closely monitor the explosion and two factors behind it. One factor is watersheds and confirm the results. the increased demand for fresh water by the humans and their associated needs. Other is the 2. Methodology pollution created by the anthropogenic activities such as domestic and industrial waste disposal, 2.1. Study Area and Data urban and rural infrastructure development, agriculture and deforestation. Having recognized Dampe watershed (0.62 km2) located in the that water is a limited resource, it is critical that Kesbewa Divisional Secretariat Division of the sustainable methods of extracting, utilizing and Colombo district, Sri Lanka (Figure 1) was the study preparing future development plans must be area. It is composed of four Grama Niladari adopted without delay (IWMI, 2005). Divisions (GND s), namely, Delthara East, Since the World Summit in Rio de Janeiro in 1992, Madapatha, Batakettara South and Batakettara Integrated Water Resources Management (IWRM) North. This ungauged water-shed consists mainly has been accepted as a philosophy which considers different uses of water to manage with stakeholder participation while recognizing its economic value A.C. Dahanayake, B.Sc. Eng. Hons. (Moratuwa), AMIE and the role played by females (Anon., 2012). (Sri Lanka), Graduate Research Assistant, Department of The biggest drawback since this recognition has Civil Engineering,University of Moratuwa, Sri Lanka. been the lack of practice and many are now casting N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip doubts about this globally accepted philosophy (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., (Biswas, 2008). A literature survey sheds light in this MICE(UK), FIE(SL), Senior Professor, Department of Civil connection because of the void in case study Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 21 UMCSAWM Water Conference – 2017 of residential areas, a few in-dustries, open forest Site visits revealed that most internal drainage areas, paddy fields and a wet-land. paths in the residential areas were polluted due to Water for most residential and industrial areas is discharge of domestic wastewater. supplied by the National Water Supply and Drainage Board (NWSDB) and few use dug wells as 2.2. Problem Statement their main source of water. Water for cultivation of Field visit observations at the selected ungauged paddy is extracted from the stream and the excess is watershed revealed that the water at the outlet is released back to the same stream. Main water use polluted and that the stakeholders complain about sectors include water supply and sanitation, deteriorating status without any meaningful action agriculture, irrigation, industries and the either by themselves or by the administrative environment. Water related issues in the watershed authorities. Hence it is necessary to evaluate the were identified by conducting a reconnaissance status of water at each sub watershed and then survey including field interviews with community demonstrate the possibility of status identification stakeholders of the watershed. Sur-face water for better future planning. pollution by effluents was identified as the most severe problem affecting the social, aquatic and terrestrial environments.
2.3. Data for Water Usage
Figure 1: Location of Dampe Watershed and the Stream Schematic Monthly rainfall data of Ratmalana gauging station forest, built-up land, paddy, marsh, and from October 2011 to September 2012 was collected homesteads. In order to validate field observations, by Meteorological Department and average area averaged runoff coefficients for each monthly evaporation data from the Irrigation watershed were computed using land use related Department Guidelines (Ponrajah, 1984) were runoff coefficients from Chow, et al., (1988). available. Catchment was divided to eight sub Population, number of housing units, number of catchments in accordance with the terrain and well water users, number of NWSDB water users, in distribution of waterways. Vital monitoring each sub catchment were obtained from the GND locations to evaluate the status of water were based reports of the Department of Census and identified by considering sub catchment inflows to Statistics for year 2012. Off the shelf GIS software the main stream (Figure 1). In the absence of ArcGIS was used for spatial extent computations. detailed contours, lateral flows were assumed to Crop water requirements were taken from the contribute at the mid of each reach. Land use details Irrigation Department Guidelines. Threshold from 1:50,000 maps and available information from dilution factors and return flows after the multiple internet were used. Land cover consisted of; open uses were obtained from NWSDB guideline and the
22 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 practices of Irrigation Department, Sri Lanka. were assumed as representative for the sub Return flow factors of NWSDB supplied domestic watersheds. water, well water, industrial water and irrigation In case of each watershed water abstractions, water water were taken as, 0.8, 08, 0.3 and 0.3 respectively. inflow from outside, and return flow were The threshold values of pollution were calculated considered for water balance considering water considering 8 times dilution, according to the quality and quantity. The schematic showing the Central Environmental Authority (CEA) Guideline. sequence of water balance computations and the The spatial and temporal resolution of data is critical nodes are shown in Figure 1. shown in Table 1. The threshold dilution was considered for the Table1: Spatial and Temporal Resolution of Data separation of polluted water as beyond and within accepted levels. Environmental flow was taken to Temporal Spatial Data be 10% of the surface runoff. Data Type Data Resolution Resolution For the verification of the model, monthly rainfall Monthly da-ta and monthly evaporation data were checked rainfall data Rainfall data of against the estimated streamflow data of the from October Rainfall Ratmalana catchment. The observed flow hydrograph was 2011 to gauging station drawn in order to compare the values obtained September 2012 from the mathematical analysis of the water balance Average model with the real values. It is assumed that the Evaporation monthly soil moisture returns to the same state at the end of Evaporation data of evaporation Colombo station the water year. Hence a comparison of annual data evaporation can be used as a check for inflow and Field outflow. measurements Streamflow from the Monthly data catchment 2.5. Scenario Analysis from the Developed Water outlet Balance Model Land use 1:50,000 scale - The model was extended to analyse four scenarios, Population, namely, for the present condition (based on data for number of housing the year 2012), for the future condition in 2025, for units, number of Data for year GND level the evaluation of the situation in the past taking well water users, 2012 1987 as the reference, and then for present condition number of NWSDB water users with solutions. The following parameters were changed accordingly. Administrative 1:50,000 scale - divisions Mean value of annual population growth rate be- tween 1987 – 2012 had been 0.8% and 0.76% be- 2.4. Water Balance tween 2012 – 2014 (Anon., 2016). The decrease rates of open forest, marsh, paddy and the number of The present study focused the water balance of the wells were taken as 1%, 0.5%, 1% and 2% surface water only. All watersheds in Sri Lanka respectively. The increase rates of homestead, built- undergo an annual hydrological cycle during up area (industries), and number of NWSDB water which, two monsoons (southwest and northeast) using houses, were taken as 2%, 1% and 2% occur. Hence water balance computations were respectively. carried out for a typical water year starting from The effect of alternatives were analysed using the October and ending in September of the following ‘present condition with solutions’ scenario. year. Rainfall for the year was taken from the Evaluation of the present situation revealed a average monthly data of Ratmalana Station. pollution level in the surface water that can be either As the first step, the catchment water balance was abated by introducing more water or by reducing carried out by treating the entire watershed as a the pollutants reaching the surface water. Since single lumped unit with average observed rainfall pollution management with stakeholder consensus and evaporation data. The two parameter monthly is far better than diversion of water from adjacent water balance model (Xiong & Guo, 1998) was used basins, the present work assumed partial reduction for the accounting of soil moisture variation within of pollution from each source. the watershed during the water year for which the The results showed that high pollution levels were computations were carried out. The model was due to increase of domestic and industrial calibrated by using the pre-evaluated parameters wastewater discharge. As a remedial measure, it for similar basins, the starting and ending was considered that 50% of domestic wastewater watershed storage, the catchment runoff and 30% of industrial wastewater should be treated coefficients and the streamflow pattern estimated by using wastewater treatment units looked after by from the observations made during field visits. stakeholders. These percentages were determined After the calibration with the available data, the by using a trial and error process, such that at least watershed parameters of two parameter model the pollution level of the most critical sub catchment
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 23 UMCSAWM Water Conference – 2017 must be reduced by at least 10% with respect to the and its total values are shown in Table 1. present scenario. Unpolluted water quantity flowing in the stream was obtained by deducting the irrigation 3. Results requirement from the inflow from surface runoff. The values of unpolluted water quantity flowing in 3.1. Water Quality Balance the stream minus the fresh water requirement for The calibrated two parameter models have shown safe discharge were considered to determine the the Monthly Evaporation Coefficient (c) as 0.9659 critical months. The last column of Table 1 for all sub catchments. The variation of the represents the polluted water quantity flowing in catchment Field Capacity Coefficient (SC) for the the stream which is the same as the total wastewater eight sub catchments was between 300 mm and inflow column. 1600 mm. At present, the polluted water quantity discharged Water quality balance was analysed for all the sub to the stream is 180,448.27 m3 per year, while the catchments, and Table 1 and Figure 2 represents the contribution from rainfall after consumption results from the water quality balance analysis at requirements is 699,553.03 m3 per year. The fresh the catchment outlet I. In the Table 1, inflow from water requirement for safe discharge at 8 times sur-face runoff is the surface runoff obtained from dilution is 360,896.54 m3 per year. For the months the two parameter model. Environmental flow has of January, February, March, June and July, the total been taken to be 10% of the surface runoff. Return catchment is polluted beyond the threshold limit, flows from NWSDB supplied domestic water, well requiring on average an additional fresh water water, industrial water and irrigation water were amount of 9124.76 m3 monthly to get the catchment summed at each month to obtain the total back to the threshold level. wastewater inflow. Then the additional water The surface water pollution levels of the sub requirement for CEA acceptable level of catchments were classified into a five class system. concentration were calculated for all the Then the most critical sub catchment was identified. wastewater sources (NWSDB supplied domestic If the pollution level was below 15% it was taken as water, well water, industrial water and irrigation not critical, if it was between 15% – 20% it was water), by considering the dilution factors. After taken as less critical, if it was between 20% - 30% it that the fresh water requirement for safe discharge was taken as moderately critical, if it was between has been obtained by considering 8 times dilution, 30% - 40% it was taken as critical, and if it was above 40% it was taken as highly critical (Refer Figure 3).
Table 2: Water Quality Balance without Reservoir – Total Catchment at Key Point I
Unpolluted water quantity Unpolluted Polluted Fresh Water flowing in the Inflow from Total Water Water Environmental Requirement stream Minus Surface Wastewater Quantity Quantity Flow for Safe Fresh water Month Runoff In-flow Flowing in Flowing in (Thousands) Discharge requirement (Thousands) (Thou- the Stream the Stream (m3) (Thousands) for safe (m3) sands) (m3) (Thousands) (Thousands) (m3) discharge (m3) (m3) (Thousands) (m3) Oct 95 10 16 32 88 56 16 Nov 132 13 13 27 132 105 13 Dec 60 6 16 31 54 22 16 Jan 38 4 16 32 30 -2 16 Feb 24 2 14 28 21 -7 14 Mar 17 2 14 28 17 -10 14 Apr 109 11 13 27 109 82 13 May 45 4 17 34 34 0 17 Jun 43 4 17 33 32 -2 17 Jul 24 2 18 36 11 -25 18 Aug 80 8 14 28 80 52 14 Sep 93 9 13 27 93 66 13 361 700 180
24 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Sep Aug Jul Jun May Apr
Mar Month Feb Jan Dec Nov Oct
0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00 200.00 Water Quantity (m3) Thousands Unpolluted water quantity flowing in the stream Polluted water quantity flowing in the stream Fresh Water requirement for safe discharge
Figure 2: Water Quality Balance without Reservoir – Total Catchment at Key Point I
Figure 3: Five Class System Classification for the Pollution Levels the stream would be 706,771.45 m3 per year. The 3.2. Water Quantity Balance fresh water requirement for safe discharge of pollutants would be 1,731,515.57 m3 per year. All Water quantity balance was analysed for all the sub sub catchment pollution levels have increase in the catchments, and discharge at every key point was future condition. The pollution level of the most found. Then the inflow and outflow at each key critical sub catchment will be worsened by another point was obtained. It has also been checked that the 3.64% with respect to the present level. However, sum of total polluted water at the key point and the sub catchment with the highest increase rises by total unpolluted water at key point equals to the 6.14%, pushing its status from moderately critical discharge at that key point. Hence the water balance category to the critical category. In future, all law has been maintained. months have become critical, except for November. (Refer Table 2). 3.3. Future Condition The situation of the watershed in the future, with no 3.4. Past Condition remedial measures taken to overcome the surface In order to analyse the situation that would have water pollution, was studied using this scenario. been in existence 25-50 years ago, the past condition The year 2025 was considered and the multi sectoral scenario was used. The values relevant to the year water usage values were changed in the water 1987 were used in this scenario and the multi balance model accordingly. If no further remedial sectoral water usage values were changed in the action is taken, the entire catchment growing at water balance model accordingly. The watershed present rate would receive a polluted water was in a better condition in the past, when quantity equal to 216,439.45 m3 per year. Under the compared with the present situation. In the past the same conditions the total fresh water flowing into pollution levels were much lower. With time, the
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 25 UMCSAWM Water Conference – 2017 present pollution levels of all sub catchments have before releasing them into the stream. Furthermore, increased and the pollution level of the most critical some of the industries could incorporate sub catchment (SC7) has increased by an amount of wastewater treatment plants for their industrial 18.97% in these 25 years (from 1987 to 2012). (Refer wastewater discharge. The present level of Table 3). pollution values could be reduced to a considerable amount by the introduction of this alternative. With 3.5. Present Condition with Alternatives this solution, the pollution levels in all sub catchments have shown a decrease. The current Wastewater treatment plants should be established pollution level in the most critical sub catchment and the wastewater discharged from domestic (SC7) could be reduced by an amount of 12.3%. usage could be diverted to these treatment facilities (Refer Table 4).
Table 3: Comparison of Pollution Levels – Future Scenario with respect to Present Scenario
Percentage Present condition Future condition difference pollution levels pollution levels in pollution levels Pollution Level Change According to the Sub Catchment Percentage of Percentage of (Increase Five Class System (Polluted/Total) for (Polluted/Total) for with respect this catchment (%) this catchment (%) to present condition) SC7 47.97 51.61 3.64 still highly critical SC4 32.96 36.72 3.77 still critical SC6 30.70 31.59 0.88 still critical SC8 28.59 34.73 6.14 moderately critical has become critical SC5 21.71 24.30 2.59 still moderately critical SC1 16.28 17.25 0.97 still less critical SC3 15.26 18.25 2.99 still less critical SC2 10.33 11.38 1.05 still not critical
Table 4: Comparison of Pollution Levels – Present Scenario with respect to Past Scenario
Present condition Past condition pollution levels pollution levels Sub Catchment Percentage of Percentage of Percentage difference (with respect to past condition) (Polluted/Total) for (Polluted/Total) for this catchment (%) this catchment (%) SC7 47.97 29.00 18.97 increase with respect to past SC4 32.96 14.99 17.96 increase with respect to past SC6 30.70 9.55 21.15 increase with respect to past SC8 28.59 17.92 10.68 increase with respect to past SC5 21.71 7.97 13.74 increase with respect to past SC1 16.28 4.09 12.19 increase with respect to past SC3 15.26 4.00 11.25 increase with respect to past SC2 10.33 2.16 8.17 increase with respect to past
Table 5: Comparison of Pollution Levels – Present Condition with Alternatives Scenario with respect to Present Scenario Present with Present condition Alternatives pollution levels condition pollution Percentage difference of pollution (with respect to present Sub Catchment levels condition) Percentage of Percentage of (Polluted/Total) for (Polluted/Total) for this catchment (%) this catchment (%) SC7 47.97 35.66 12.30 decrease with respect to present SC4 32.96 22.24 10.72 decrease with respect to present SC6 30.70 18.14 12.57 decrease with respect to present SC8 28.59 21.50 7.09 decrease with respect to present SC5 21.71 13.31 8.40 decrease with respect to present SC1 16.28 8.86 7.42 decrease with respect to present SC3 15.26 8.74 6.52 decrease with respect to present SC2 10.33 5.45 4.89 decrease with respect to present
26 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
4. Discussion this method the sources of pollution could be identified easily. Then the problem could be There are difficulties in carrying out a water balance isolated and solutions could be implemented to that under data scare situations. If measured streamflow particular pollution source. Water quantity flowing data were available for a longer period, those data in the stream should also be measured and it could could have been used for the verification of the be checked for the availability of the minimum results. In this study, monthly rainfall data and amount of water that should be there in main canal monthly evaporation data were checked against the for the threshold dilution. Level gauges can be used streamflow data (estimated from the field to measure the discharges at key points. If the water measurements) of the catchment. Further, the quantity or quality is not up to the required level, average runoff coefficient obtained from the two remedial actions (such as wastewater treatment parameter model was compared with the area plants) for the source of that problem could be averaged runoff coefficient which was calculated implemented. In addition, the irrigation canal using the values given by Chow, et al., (1988). Since system and the drainage canal system, along with this watershed is ungauged, field visits, gauged the other related hydraulic structures, have to be data from the locality, estimates from available maintained in proper condition and should be literature were used for a rational application of checked for necessary repairs every three to four water balance to evaluate solutions for surface months. water pollution. This study reveals a simple method of estimating 5. Conclusion planning level water quantity and water quality, with the advantage of performing a study of this Surface water pollution by effluents was identified order of magnitude and then identifying troubled as the most severe problem affecting the social, areas. Then a detailed data collection program aquatic and terrestrial environments of Dampe could be initiated for those areas. watershed. Site visits revealed that most internal According to the results of this study, the most drainage paths in the residential areas were critical sub watershed is SC 7 which needs urgent polluted due to discharge of domestic wastewater. attention by stakeholders. (Refer Figure 3). The From this study, a comprehensive solution for the priority order of sub watersheds that needs surface water pollution in this watershed was attention are; SC 7, SC 4, SC 6, SC 8, SC 5, SC 1, SC identified by analysing the watershed using a water 3 and SC 2. balance model, and by considering Integrated Due to the increasing population with time, the Water Resources Management principles. The water usage values will also increase. The domestic study demonstrates the possibility of successfully and industrial water demand will be increased applying the multiuser concept, the finite nature of along with the increase in population and number water and system water balance, as a mean to of industries in the future. This will result in an overcome the surface water pollution in Dampe increase in the wastewater discharge in the watershed. watershed. In addition to that, continuation of the Fresh water is a finite and vulnerable resource, removal of the forest cover and transferring them essential to sustain life, development and the into urban areas, in order to facilitate and cater for environment. Since water sustains life, effective the increasing demand in human needs would be management of water resources demands a holistic inevitable in the future. Marsh and paddy area land approach, linking social and economic will also be reclaimed. Decrease in the forest area development with protection of natural ecosystems. and increase in the urban area will result in an Effective management links land and water uses increase in the value of the runoff coefficient. This across the whole of a catchment area or increase in the runoff coefficient has resulted in groundwater aquifer. increasing the surface runoff in the future. In this watershed, due to the increasing population However, this increase in the surface runoff would with time, the water usage values will also increase. not be enough to dilute the high pollution levels. More wells will be dug and the extraction rates from Several solutions for management of water in a the wells will also increase. Since water is a finite watershed could be identified by the results of this resource, that will cause a decrease in the study. The irrigation requirement of water could be groundwater storage with time. Furthermore, the optimized if better crop management procedures increasing demand of water for human needs will are introduced to the watershed, such as cultivating cause an increase in the wastewater discharge of crops which need lesser amounts of water, in the this watershed. dry periods of the year. The monitoring of the water Water development and management should be quality and quantity of Dampe watershed should based on a participatory approach, involving users, be done monthly and the developed monthly water planners and policymakers at all levels. The balance model could be used to aid the monitoring participatory approach involves raising awareness process. The key points A, B, C, D, E, F, G and I, of the importance of water among policy-makers could be used as surveillance points for the and the general public. The decisions are taken at monitoring of water quality as well as quantity. By the lowest appropriate level, with full public
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 27 UMCSAWM Water Conference – 2017 consultation and involvement of users in the 6. References planning and implementation of water projects. All water management decisions about this watershed should be taken by a committee Anon., 2012. IWRM Principles. [Online] comprised of all water use stakeholders. Ideas of all Available at: http://www.gwp.org/en/The- water users have to be considered in order to do a Challenge/What-is-IWRM/IWRM-Principles/ proper water resources management. The support [Accessed 15 May 2016]. of all stakeholders is required in the implementing Anon., 2016. www.tradingeconomics.com. [Online] stage of those decisions. Without a combined Available at: support from all users, it would be very difficult to http://www.tradingeconomics.com/sri- manage the water resources in an efficient manner. lanka/population-growth-annual-percent-wb- Women play a central part in the provision, data.html management and safeguarding of water. The role of [Accessed 15 05 2016]. women as providers and users of water and Biswas, A. K., 2008. Integrated Water Resources guardians of the living environment should be Management: Is It Working?. Water Resources reflected in institutional arrangements. Development, 24(No. 1), pp. 5-22. Water has an economic value in all its competing Chow, V. T., Maidment, D. R. & Mays, L. W., 1988. uses and should be recognized as an economic Applied Hydrology. New York: McGraw-Hill. good. It is a basic right of all human beings to have IWMI, 2005. Planning Groundwater Use for access to clean water and sanitation at an affordable Sustainable Rural Development. [Online] price. Failure to recognize the full value of water has Available at: led to wasteful and environmentally damaging uses http://www.iwmi.cgiar.org/Publications/Water_ of the resource. Treating water as an economic good Policy_Briefs/PDF/wpb14.pdf is an important mean for decision making on the [Accessed 15 May 2016]. allocation of water. Ponrajah, A. J. P., 1984. Design of Irrigation By implementing suitable measures to overcome Systems for Small Catchments. 2nd ed. Colombo: the water related issues that have been encountered Irrigation Department. and by managing the utilization of water in a Xiong, L. & Guo, S., 1998. A Two Parameter sustainable manner, satisfactory changes that Monthly Water Balance Model and its Application. would contribute to the preservation of this Journal of Hydrology, December, Volume vol 216, valuable resource in a more pragmatic way, could pp. 111-123. be expected.
28 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Raster GIS Modelling when Selecting a Suitable Solid Waste Dumping Site
R.M.L.U. Rathnayaka and N.T.S. Wijesekera
ABSTRACT Disposal of solid waste is a major problem which is rapidly increasing with the growth of population and development of industries. In a majority of places, open pits have become major disposal locations causing severe environmental and health issues. Since, solid waste disposing is an important part of a waste management system, locating proper sites for solid waste disposal is considering main issue for the management of solid waste. Site selection involves working with several map layers while requiring qualitative assessment for decision making. Multiple layer operations can be carried out by using Geographic Information system and is a suitable method for site selection. Vector and raster data models are the primary data models used in GIS. The present study is intended to demonstrate the capabilities of raster GIS formats in suitability analysis by finding out a suitable site for the disposal of urban solid waste generated from Rathnapura municipality. Concept and the objective function were identified and the factors which are necessary to achieve the aims of study were determined by reviewing literature. AHP technique in combination with GIS overlaying was used to arrive at optimum weights for each parameter. In literature land use, water bodies, flood risk zones, streams, population density, protected area, major roads, landslide prone zones, water supply sources, ground water depth, proximity to roads, rainfall, build-up areas, slope and soil are described as factors affecting land selection. According to the results obtained, 0.59 km2 of area was suitable for solid dumping site. In Raster GIS multilayer operations can be perform and overlaying process is very fast, causing data analysis is quick and easy. GIS technique is a better tool for suitability analysis as it reduce time and cost of site selection..
KEYWORDS: GIS, Raster, Solid waste disposal, Land use
a suitable method for site selection. Vector and 1. Introduction raster data models are the primary data models used in GIS. Present study is intended to 1.1. General demonstrate the capabilities of raster GIS formats in Geographic Information System (GIS) allows users suitability analysis by finding out a suitable site for to view, understand, query, interpret and visualize the disposal of urban solid waste generated from spatial and non-spatial data in many ways that Rathnapura municipality. Rathnapura city reveals relationships, patterns and trends in the generates 28-30 tons of waste per day and 80 % of form of maps, reports and charts (Lui and Mason, them are collected by municipality. Dumping site is 2009; Bhatta, 2010). In Geographic Information located at Kanadola near to Rathnapura town. System human and computer based resources are Waste collection is primarily done by municipal combined with spatially referenced data to achieve council. Waste is not graded as bio-degradable, efficient management and planning of resources. glasses, polybags, paper shreds or hazardous. There GIS is capable to collect, store, retrieve, are pollution problems, because the dumping site is communicate and analysis spatially referenced data located on a hilly area and waste moved down the for product generation. Vector and raster data hill causing environmental pollution. As a result, models are the primary data used in GIS. most paddy lands in the hilly area remain Disposal of solid waste is a major problem which is abandoned. It is very difficult to find dumping site rapidly increasing with the growth of population near Ratnapura town because of the frequent and development of industries. In a majority of flooding. Locating suitable sites for solid waste places, open pits have become major disposal dumping can be easily done with conceptual GIS locations causing severe environmental and health models either using Raster or Vector formats. issues. Since, solid waste disposing is an important Vector GIS provides clear and easy to understand part of a waste management system, locating proper sites for solid waste disposal is considering R.M.L.U. Rathnayaka, B.TEC. (Eng), AMIE(SL), main issue for the management of solid waste. Site Irrigation Engineer, Department of Irrigation, Sri Lanka selection involves working with several map layers N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip while requiring qualitative assessment for decision (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., making. Multiple layer operations can be carried MICE(UK), FIE(SL), Senior Professor, Department of Civil out by using Geographic Information system and is Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 29 UMCSAWM Water Conference – 2017 representations but has the difficulty when working selection process were extracted from national with large projects and many overlays. Though regulations, international guidelines and from raster GIS enables easy working with many previous studies. . Prioritised weights were overlays, they have the problems due to computed using an analytical hierarchy process compromises made in spatial resolutions. (AHP) multi criteria model. Land use, water bodies, Raster data is made up from pixels or grid cells. flood risk zones, streams, population density, These grids also vary with the data type and protected area, major roads, landslide prone zones, representations of either discreet or continuous water supply sources, ground water depth, data. Integer grids represent discrete data and proximity to roads, rainfall, build-up areas, slope, floating point grids represent continuous data. A soil were identified as influencing the waste case study was conducted to demonstrate disposal site selection capabilities of Raster GIS, when selecting a solid Land use helps to identify availability of suitable dumping site. land uses. Build-up areas, forest reserves, wetlands, potential agricultural lands are not considered for 1.2. Study Area selection. Low population density areas are preferred because of the effects on health, nuisance, Study area is the Rathnapura municipality (104 environmental pollution, property values, odour, km2) which comes under administrative district aesthetic aspects etc. Urban towns, residential areas, Rathnapura in the Sabaragamuwa province, Sri protected areas, religious areas, parks, water Lanka. bodies, major roads and streams are areas that need to be at a fair distance away from dumping site. Proximity to roads is a consideration due to concerns of transportation time and cost. Soil type indicates the possibility of pollutant leaching towards groundwater. High elevation and slopes facilitate the travel of polluting material towards lower elevations with the runoff. Locating dumping sites in flood prone areas lead to washing away of waste in to water bodies. Unstable slopes must be avoided and depth to groundwater must be evaluated prior to selecting a site. Accordingly objective function for the site selection model is as below. Suitable solid waste dumping site = f (Socio- Geological Suitability, Aesthetic suitability, Environmental Suitability, Natural Hazard Suitability)
Socio- Geological Suitability = f (Land use + Soil Figure 2 1 Study Area +Slope) Aesthetic Suitability = f (Build-up areas + 1.3. Spatial data and data types Sensitive Places + Major Roads) Digital data was obtained from different Environmental Land Suitability = f (Stream, government authorities and used for the study are Rainfall, Ground water depth) listed in Table 1. Natural Hazard Suitability = f (Flood risk, Land prone hazard) Table 0 Spatial data and data type Ground water depth = f (Land use, Stream, Water No Data Layer Layer Type Resolution bodies) 1 Study area Polygon 1: 50,000 Flood risk Zones = f (Land use, Slope, Soil, 2 Soil Polygon 1: 10,000 Elevation, Rainfall) 3 Land use Polygon 1: 10,000 4 Contours Polyline 1: 10,000 Land slide hazard prone Zones = f (Slope, Soil, 5 Roads Polyline 1: 50,000 Elevation, Rainfall) 6 Streams Polyline 1:10,000 7 Build up areas Polygons 1:10,000 2.1. Raster Analysis 8 Protected areas Points 1:10,000 9 Rainfall points Classified layers were re-classified with the use of raster calculator and added together after 2. METHODOLOGY multiplying each criterion from their weightages. Cell size of 10 is selected for spatial data operation ARC GIS 10.2 was used to create solid dumping site due to easiness of calculations. suitability model. Criteria for solid dumping site
30 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Land Use
Socio Geologica Slope l Suitability Soil
Natural Flood risk Land use, Elevation, Soil, hazard Slope suitability Landslide prone Land use, Soil, Slope, Rainfall
Suitable zones solid Rainfall waste dumping Environm ental land Elevation site Streams suitability
GWD Land Use, Stream, Rainfall
Major roads
Land Use Aesthetic Sensitive places Suitability
Buildup areas
Figure 2 1 Methodology flow chart 2.1.1. Socio Geological suitability Reclassifie Reclassifie Reclassifie Under socio geological suitability, land use, slope d Soil d Land use d Slope and soil were considered as criterion. Slope raster map was created using elevation (1:50000) digital map and after convert it in to TIN and DEM.Layer 53 % importance 14 % importance 33 % importance classifications and the sequence of combining multiple layers at a time are shown in the table 2.1- Raster 1 and Figure 2.1-2. Calculator
Table 2.1 1 Parameter classification Criteria Classification Suitability Land use Bare and grass land area High Scrub, bush land Moderate Socio Geological Build-up, Agriculture Low Suitability Forest, water bodies Un-Suitable
Slope < 10 High (Degrees) Moderate Figure 2 2 Raster Analysis -Socio Geological 15 - 20 Low Suitability >20 Un Suitable
Soil Low Permeable Suitable Moderate Permeable Moderate 2.1.2. Aesthetic Suitability High Permeable Un-Suitable Buffer zones of protected areas, build-up areas, and Classified layers were reclassified to achieve major roads were considered to find out aesthetic common scale ranked from 0 to 9 indicating suitability. Protected area, major roads and build up unsuitable to high suitable in the order of decision areas were converted to raster and buffered by maker’s preference. Weightages were given to each using Euclidean Distance tool. Layer classifications criterion according to their relative importance. and the sequence of combining multiple layers at a Weights were assigned for each reclassified layers time are shown in the table 2.1-2 and Figure 2.1-3. by using AHP. According to British Columbia criteria and EPA guideline, Jayawicrama, N.T. & Weerasinghe, V.P, the landfill footprint must not be located within 300 m of an existing or planned sensitive land use. Major roads should be greater than 250 m (Sener et
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 31 UMCSAWM Water Conference – 2017 al., 2010). According to Rajan S.S., Yeshodah L., >20 Low Suitable Babu S.S., (2014) build-up areas should be not be Un Suitable within 300 m. Soil Low Permeable Suitable Moderate Moderate Table 2.1 2 Parameter classification Permeable Suitable High Permeable Un Suitable Criteria Classification Suitability
0-300 Un Suitable 300-500 Low Suitable Protected areas 500-800 (m) Moderate Suitable Reclassified 800-1500 High Suitable Reclassified Reclassified Rainfall Stream Ground >1500 Extremely HS Water Depth 0-250 Un Suitable 250-500 Low Suitable Major Roads 500-750 (m) Moderate Suitable 33.3 % importance 33.3 % importance 33.3 % importance >750 High Suitable 0-300 Un Suitable 300-500 Low Suitable Raster Calculator Build up areas 500-800 (m) Moderate Suitable 800-1100 High Suitable
>1100 Extremely HS
Environmental Suitability Reclassified Reclassified Reclassified Important Major roads Buildup areas places Buffer Buffer Buffer Figure 2 4 Raster Analysis –Environmental Suitability 2.1.4. Natural Hazard Suitability 38 % importance 47 % importance 15 % importance Natural hazard suitability map was created by
overlaying flood hazard areas layer with land slide Raster prone areas layer. Flooding causative factors such Calculator as rainfall distribution, slope, soil type, land use,
flow accumulation and elevation were integrated
for flood vulnerability mapping in the study area.
Layer classifications and multiple layer operation Aesthetic Suitability for reclassified layers are shown in table 2.1-4 &
Figure 2.1-5. The results were validated with flood Figure 2 3 Raster Analysis -Aesthetic Suitability vulnerability map created by NBRO, Sri Lanka. 2.1.3. Environmental Suitability Land slide was the most common natural hazard in hilly terrains. Soil, slope, rainfall and land use were Under environmental suitability rainfall, ground identified as causative factors in the study area. water depth and distance from stream were Raster parameter layers were classified according to considered. Layer classifications and the sequence the classification system as illustrated in table 2.4. of combining multiple layers at a time are shown in Classified layers were reclassified to achieve the table 2.1-3 and Figure 2.1-4. common scale by ranking from 0 to 9, indicating Stream network was created by using digital unsuitable to high suitable. This ranking system elevation map (1: 50000) with 20 m contour intervals was carried out according to the decision maker’s and created streams were compared with physical preference. Weights were assigned for each streams to identify similarity. There is no ground reclassified layers by using AHP model which water map for study area. Hence, conceptual model analysis was carried out accordance with relative was developed to prepare a ground water map importance of each criteria. Classified soil, slope, using land use, streams and rainfall base data. Very rainfall and land use layers are added by raster close to the paddy and streams are considered as calculator after multiply by weightages to obtain high potential to ground water depth. land slide prone map. Flood zonation layer and Table 2.1 3 Parameter classification landslide prone area layer were added by using raster calculator to obtain natural hazard suitability Criteria Classification Suitability Land use Bare and grass High Suitable map. land area Moderate Table 2.1 4 Flood Hazard - Parameter classification Scrub, bush land Suitable Build-up, Low Suitable Criteria Classification Suitability Agriculture Un Suitable Forest, water bodies Slope < 10 High Suitable Moderate 15 - 20 (Degrees) Suitabl e
32 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Building, Roads, within the municipal council area, MC area was slum area extracted from the study area. According to the Shrub, bush, results obtained, 0.59 km2 of area was suitable for Very High range land High solid dumping site. Suitable areas within the Crop land, Land use Moderate municipal council of Rathnapura were verified with pasture Low Other field data. Table 3-1 shows the percentage values of Low risk agricultural land study area according to suitability conditions. Mixed forest Table 3.1 Area according to suitability level lands No Suitability Area (Km2) Percentage 0-241 Very High level % 241-523 High Flow 1 High 0.76 0.73 523-922 (m) Moderate accumulation Suitable 922-1471 Low 2 Moderate 9.55 9.16 1471-2120 No risk Suitable 0 – 11.4 3 Low 93.77 89.96 Very High 11.4 – 23.2 Suitable High 23.2 – 36.3 4 Un Suitable 0.14 9.8 Slope Moderate (Degrees) Final suitability map of the study are shown on Low 36.3 – 51.9 No risk figure 3.2. 51.9 – 88.3 Low Infiltration capacity High Soil Moderate Moderate High Infiltration Low capacity
Reclassified 26 % importance Land use
Reclassified 15 % importance Flow accu.
18 % Reclassified Importance Raster Slope Calculator
Hazard Flood Reclassified 28 % importance Soil Figure 3.2 Solid Dumping Sites suitability map
4. Conclusion Reclassified 13 % importance Rainfall According to literature review it was found out that many parameters are affected to solid waste disposal site selection. If we can increase the Figure 2 5 Raster Analysis –Flood Hazard number of parameters considered, we can get 2.1.5. High reliable solid dumping site optimum solutions, minimizing environmental and health hazard. In this study many parameters were Socio geological suitability, environmental land handled and analysis without confusion. In Raster suitability, aesthetical land suitability and natural GIS multilayer operations can be perform and hazard suitability maps were added by using raster overlaying process is very fast, causing data calculator to create high reliable solid dumping site. analysis is quick and easy. Hence, GIS technique is 3. Results a better tool for suitability analysis as it reduces time and cost of site selection. According to the AHP method, It was found that Raster models have capabilities to assign weights to build-up areas (21.9 %), land use (18.6 %), slope criteria to get optimum solution and also layers can (16.8 %), soil (14.3%) and flood hazard zones be reclassified to a common scale by using user (11.4%) are the high priority factors that should be preference ranking system. Suitability analysis considered for the study area. In raster model, total models are frequently cooperated with continuous study area covers 104.23 Km2. The final suitability features (elevation) and have to analysis surface map indicates that 0.76 km2 area is suitable for data. Raster GIS facilitate surface analysis for dumping site. To identify suitable dumping sites continuous data and is a highly suitable for
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 33 UMCSAWM Water Conference – 2017 suitability site selection.GIS tool also provides a using Remote Sensing & GIS Techniques. digital data bank for future monitoring programme Unpublished Minor Research Project, BCUD, of the site. Savitribai Phule Pune University, Pune.
5. References Rajan, SS, Yeshodha, L Babu, SS, (2014), RS and GIS Based Site Suitability Analysis for Solid Waste Alavi1, N., Goudarzi1,G., Babaei1,A.K., Disposal in Hosur Municipality, Krishnagiri Jaafarzadeh,N., Hosseinzadeh,M., Municipal solid District,International Journal of Innovative waste landfill site selection with geographic Research in Science, Engineering and Technology. information systems and analytical hierarchy Sener S, Sener E, Nas B and Karagüzel R (2010) process: a case study in Mahshahr County, Iranas. Combining AHP with GISfor landfill site selection: Balasooriya, B. M. R. S.,Vithanage, M.,Nawarathna, A case study in the Lake Beysehir catchment area N. J., Kawamoto, K., Zhang, M., Herath, (Konya, Turkey). Waste Management. G.B.B.,(2014) Mowjood MIMSolid Waste Disposal Sener S, Sener E and Karaguzel R (2011) Solid waste Site Selection for Kandy District, Sri Lanka disposal site selection with GIS and AHP Integrating GIS and Risk Assessment. methodology: a case study in Senient– Bilgehan, N., Tayfun, C., Fatih, I., and Ali, B. Uluborlu(Isparta) Basin, Turkey. Environmental Selection of MSW Landfill Site for Koyna, Turkey Monitoring Assessment. Using GIS and Multi-Criteria Evaluation. Environ Sumathi VR, Natesan U and Sarkar C (2008) GIS- Monit Assess. based approach for optimized siting of municipal Landfill criteria for Municipal Solid Waste, British solid waste landfill. Waste Management. Columbia, Ministry of Environment 1993;14. Tomlinson RF (1990). Geographic Information Jayawicrama, N.T. & Weerasinghe, V.P, GIS Systems - a new frontier. Introductory Readings in application in locating suitable sites for solid waste Geographic Information System, Taylor & Francis landfills. Ltd., Burgess Science Press. London. Mundhe, N.N., and Jaybhaye, R.G., 2014: Site Suitability Analysis for Urban Solid Waste Disposal
34 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Determination of a Design Rainfall Pattern by Comparing with its Effect on Streamflow on Greater Colombo Watershed in Sri Lanka
W.H. Keerthirathne and N.T.S. Wijesekera
ABSTRACT IDF curves provide the rainfall quantity corresponding to a particular critical duration and the design return period. In order to carryout infrastructure designs with the use of high resolution mathematical models it is necessary to select the most appropriate temporal distribution of design rain event. In cases of sufficient data availability, literature recommends the use of pattern based location specific design rainfalls for optimum designs. Present study aimed to develop design rainfall patterns based on rainfall observations, and compare with the Alternating Block, Uniform Intensity, and Greater Colombo Flood Design Patterns by evaluating the runoff response from S CS HEC HMS model developed for a sub watershed of Greater Colombo Region. A literature review was conducted to select the design rainfall pattern presently used for water infrastructure engineering.30 years of 15-minute resolution rainfall data of Colombo Meteorological station were used to separate events. Events separation were carried out by nominating Minimum Inter Event Time (MIT) of 6hrs. 220 observed events were separated into six groups considering event durations. Analysis were carried out by developing dimensionless mass curve and percentile curve for each category. Design patterns were developed from percentile curve for each event duration. Design hyetographs were developed for each duration corresponding to design rainfall depth calculated with IDF curves for Colombo and selected data for analysis. Average recurrence Interval (ARI). Runoff response for all patterns were evaluated using the nature of the outflow hydrographs with reference to flood peak and time to peak . It was observed that highest runoff response was given by Enveloped curve developed with observed data. A high runoff variation was observed between rainfall patterns. ABM base pattern can be used with reliable confidence where there is no data for analysis. Criticality Index was developed to account for the pattern of design event with regards to flood peak and time of occurrence. Enveloped curve and 10% probability distribution pattern showed the highest criticality and ABM showed the most consistent criticality for all event categories. KEYWORDS: IDF Curves, Design Rainfall, Flood management, HEC-HMS, Criticality Index
design rain event is vital for economically feasible 1. Introduction and safe drainage infrastructures. The simplest method of developing a design 1.1. General hyetograph is the Alternating Block Method (Chow, Rainfall is the key input parameter when Maidment, & Mays, 1988 and Haan, Barfield, & streamflow modelling is carried out for the design Hayes, 1981). In cases of sufficient data availability, of hydraulic structures in associated watersheds. literature recommends the use of pattern based Magnitude of the design rainfall, design storm location specific design rainfall for optimum duration and storm pattern are major designs. A typical example is the use of results considerations that have to be taken care of when reported by Soil Conservation Service (SCS) where carrying out risk based water infrastructure rainfall distributions Type I, IA, II, and III, are designs. Design rainfall depth is usually calculated available for applications within specific locations using the IDF curves for the concerned location and in the United States of America (Chow at el., 1978). corresponding to the critical duration and for a predetermined design return period. After the determination of rainfall depth for the critical W.H. Keerthirathne, B.Sc. Eng. , C.Eng., duration, a modeler has to identify the temporal M.Eng.,MIE(SL), Assistant General Manager, Land distribution of the rainfall within that duration. Reclamation and Development Coperation , Sri Lanka This distribution has a very high impact on the N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip streamflow peak both in terms of the magnitude (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., and the time of occurrence. Therefore, the selection MICE(UK), FIE(SL), Senior Professor, Department of Civil Engineering, University of Moratuwa, Sri Lanka. of most appropriate temporal distribution of a
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 35 UMCSAWM Water Conference – 2017
Though there had been occasions where pattern Inter Event Time (MIT) based (Ariff & Jeman, 2012). based design rainfall had been used for major MIT is defined as the time between events, which infrastructure designs in Greater Colombo region of are independent of each other (Dunkerley, 2008). Sri Lanka, there are no reviewed publications, or Literature indicated that there is no established detailed guidelines, or comparative evaluations. criteria for selecting MIT (Dunkerly, 2008) and Hence a study was undertaken to analyze 30 years many researchers defined their own criteria to fix of 15-minute resolution rainfall data of Colombo MIT for event separation. Dunkerly (2008) Meteorological station in order to identify the indicated that irrespective of the location of work design rainfall patterns and then to compute the most researchers have used a MIT value between 6 effect of each pattern on the streamflow response hr to 8 hr when separating independent events from from the Greater Colombo watershed. continuous data
1.2. Study Area 3.2. Event Selection Greater Colombo basin located in the Colombo Time of concentration (TC) and ARI are the main District of Western province in Sri Lanka is in parameters considered when selecting events for Figure 1.1. Project area Covers an approximate land drainage infrastructure design. ARI is directly extent of 100Km2. Consists of two main sub related to the flood safety level and the Irrigation watershed namely Malambe basin (12.8Km2) and Department Guideline (Ponrajah, 1984) Greater Colombo basin (87.5km2). Study are recommends either a 2-year or a 5-year return consists of a well-defined canal network which was period for town drainage infrastructure design. rehabilitated in 1982. 3.3. Design Rainfall Patterns Many countries develop guideline for determination of rainfall magnitude estimated from IDF curve (ARR(1997). MSMA(2013),SCS(1973). Irrigation department guideline (Ponrajah, 1984) has recommended a uniform intensity rainfall for catchments up to 52km2. Studying the impact of design rainfall pattern on safety consideration in Engineering Infrastructure for Water Resource Development, Wijesekara & Wijesinghe (2013) concluded that that Alternating Block Method provides a better and reliable methodology ensuring safety of the structure. The study of Storm water drainage plan for Colombo Metropolitan Region(CMR),carried out by Nippon Koei Co Ltd for Sri Lanka Land Reclamation and Development Corporation (SLLR & DC),an Extreme event was used as pattern to distribute the design event magnitude.
Figure 1.1: Project Area 4. Data And Data Checking
2. Objectives 4.1. Rainfall Data The objective of the present work was to develop Continues rainfall with 15minutes resolution, for a design rainfall patterns based on the observed period of 30 year commencing 1981 and up to 2010 rainfall and then carry out a comparison with the were extracted from pluviograph charts recorded Alternating Block, Uniform Intensity, and the by automatic rain gauge located at Colombo presently used Greater Colombo Design Patterns Meteorological Station. Daily rainfall records for through a comparative evaluation of computed the same period separately recorded using a streamflow from a SCS HEC HMS model developed standard rain gauge located at the same place were for Greater Colombo Watershed. also obtained for data verification. Data were checked with daily data of standard and the data 3. Literature Review which deviated more than 20% were excluded from the analysis. Monthly pattern of the data was also 3.1. Event Separation compared to capture disparities in the rainfall For the purpose of event analysis, event separation records. from continuous data is required. Literature showed that there are two methods for event separation namely Window based and Minimum
36 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
5. Analysis and Results between 0.23hrs to 9hrs. Rainfall value corresponding to minimum TC (0.23hr) and ARI Events separation, from the continuous data was (2year) was selected as rainfall threshold value for carried out by defining Minimum Inter Event Time event selection. Two hundred twenty rain events (MIT). A six hour MIT value guided by the literature identified from the entire dataset was selected for was taken for the event separation. Considering the the analysis. These events were grouped into five lack of watershed information such as initial storage classes of event durations as 6, 12, 18, 24 and 36hrs. the rainfall threshold value was taken as zero for the Summary of the observed events are shown in table determination of MIT. Estimation of TC for all sub 5.1 watersheds of the study basin revealed a variation Table 5.1: Summary of Observed Events
Selected Storm Category
1 2 3 4 5
Event Duration/Hrs <6 6 12 18 24 36
Total number of Events 45 87 35 20 10 24
Duration Range 0-3 3-9 9-15 15-21 21-27 27-48
Max RF Intensity(15minute data resolution) 218.6 188.4 44.9 133.2 30.0 203.3
Max total Rainfall 123.0 207.0 440.2 269.8 496.7 459.6
Average Intensity/mm/Hrs 38.8 14.9 6.9 5.3 6.9 3.7
Time distribution curves were plotted for events groups under the five selected categories. Figure 5.1 showed the pattern under category -3 Rain events of each group were analysis of probability of occurrence (10%-90%).P percentage probability of occurrence illustrate the storm pattern that was occurred in p percentage observed events. Six design events were developed from above probability curve namely Envelope curve, Median curve,25% probability curve, 75% probability curve upper cord and Lower cord. These patterns were compare with “Uniform” and “Alternating Block” rainfall pattern.
Design pattern corresponding to event duration of 24hrs is showed in Figure 5.2. Figure 5.2: Design Rainfall pattern for duration 12h Forty design hyetographs were developed for the entire set of event durations by distributing design rainfall depth calculated from IDF curve of the study area corresponding to 10 year ARI. igure 5.3 shows the design rainfall patterns for the rainfall category 2 of Table 5.1
Figure 5.1: Time distribution of Observed Event duration 18hrs
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 37 UMCSAWM Water Conference – 2017
Figure 5.5 Estimated Streamflow Hydrographs for Design Event Category-2(12hr) Criticality index was developed to account for the pattern of design events with regards to flood peak and time of occurrence. Figure 5.8 showed the variation of criticality with all event categories Enveloped and 10% probability curve pattern showed highest criticality while ABM showed Figure 5.3: Design rainfall hyetograph for duration 12h consistent criticality for all event categories. In order to compare the runoff response for different design rainfall patterns, a HEC- HMS Q (m3/S) (USACE, 2000) rainfall run off model was Event Criticality Index (Cr) = developed for the selected sub watershed of Greater Tp(S) Colombo Main Basin (Figure5.4) Outflow hydrographs for all design events of 12hrs are shown in figure 5.5.
Main characteristic of a hydrograph is Time to Peak Cr of Event % Criticality = (Tp) and the peak flow rate (Qp). These two Max: Cr of Distributions parameters were compared for all patterns within the group and among the group. Figure 5.6 and Figure 5.7 are showed Variation of Qp with event duration. 40 35 30 25 20 15
Time to Peak(hrs) to Time 10 5 0 6hr 12hr 18hr 24hr 36hr Event Duration Figure 5.4: Selected sub Watershed in Greater Colombo ABM Envelope basin for run off model Median 25% Prob 75%Prob LWC(90%Prob)
Figure 5.6. Variation of Tp with Event duration
38 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM)
Q(m3/S) UMCSAWM Water Conference – 2017
Events were grouped into five categories after 450 having considered TC of sub watershed of the main 400 basin. 350 An infinite number of time distributions can be
/s) incorporated for a rain magnitude which is
3 300 determined by the use of IDF curves. Usually these 250 patterns are generated either by selecting a single 200 probability of occurrence or by combining two
150 probabilities. The envelope curve the pattern Discharge(m 100 developed by combining 10% and 90% probability curved produced most highest run off for the study 50 area. Hence it would be more useful designing 0 hydraulic structures with higher safely level. for Six 6 12 18 24 36 different rainfall pattern were developed with Time(hrs) probability curved. Storm pattern with higher ABM Envelope frequency of occurrence(90%) can be used for economical hydraulic structure design. Median 25% Prb An observed pattern of critical rain event was used Figure 5.7. Variation of Peak Streamflow rate with Event by Nippon Koei Consultant for Greater Colombo Duration basin in 2000.this was compared with pattern developed with probability curve and found that highest run off generation was produce by the event developed with enveloped curved. For all event category, Pattern developed with ABM showed consistency behavior compared to the rest of event pattern. Run off response for UD and 50% probable rainfall pattern showed almost similar behavior. UD rainfall pattern was very useful for identifying the Tc of the basin. An indicator to reflect the "criticality" of an event on the watershed would require to have a combination of direct runoff magnitude and the time to peak, thereby reflecting how quickly a flood with a certain magnitude would reach the gauge point. In this study, an “Event Criticality Index” was defined to capture both these factors.
7. Conclusion Figure.5. 8.Variation of % criticality with Event Category 1. An event criticality indicator identified in this 6. Discussions study, enabled capturing of critical events reflecting the severity of peak runoff rate and Rainfall records, by Automatic rain gauge and time to the occurrence of peak runoff standard rain gauge were found differ each other 2. Design Rainfall pattern developed by Envelope for some days in several year in the span of the data curve and ABM generate higher intensity period. Hence, selection of data records were done rainfalls. by identifying missing data and data with 3. Catchment response for uniform rainfall events ambiguous. showed that Tc for a catchment is not consistent Literature survey revealed that no Specific method with rainfall duration. of selecting MIT for event separation. Different 4. ABM based pattern can be used with reliable researchers selected MIT on criteria developed by confidence when there is no sufficient number themselves. MIT directly affected to number of of observed patterns available. event to be selected from continuous data Not all events, separated from the continuous data 8. Acknowledgements were selected for event analysis. Hence, Event threshold value had to define after having extensive The Author would like to express his since gratitude analysis on Tc of each sub watershed in the main to the staff of UNESCO Madanjeet Singh Center for study basin and design return period of rain events South Asia Water Management, University of used in the past. All events with rainfall depth Moratuwa for the continuous encouragement, corresponding to minimum TC and return period guidance and commitment extended throughout and above were selected for analysis. the study
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 39 UMCSAWM Water Conference – 2017
Author take this opportunity to thank to entire staff of Hydrological Engineering, Vol.4 no 3, pp, 209- of Sri Lanka land Reclamation & Development 213, July 1999 Corporation for facilitating him to pursue studies Cabellero, W.L. and Rahman, A. (2013). Variability and providing necessary data for research work. in Rainfall: A Case Study for New South Wales,Austrailia,Journals of Hydrology and 9. References Environmental Research, Vol I, No1, pp41. July 2013. Ariff, N.M, and Jemain.A.A. (2012). Comparisons Chow, ven Te, Maidment, David R. and Mays, between the Window-Based and Storm- Event Larry, W.(1988). Applied Hydrology. McGraw-Hill Analysis. Sains Malaysiana. 41(11)(2012):1377-1387 Education Private Limited, New Delhi. Asquith, W.H., Thompson, D.B., Cleveland, T.G., & Fang, Xing. (2005). Reginal Characteristic of Storm Hetograph. (Report 0-4194-4), Texas Department of Transport, Austin, Texas Australian Rainfall and Run off, Flood Analysis and Design, The Institute of Engineers Australia (1977) Awadallah, A.G., and Younan, N.S. (2012). Conservative design rainfall distribution for application in arid region with sparse data. Journal of Arid Environments. 79, 66-75. Ball, J.E. (1994). The influence of storm temporal patterns on catchment responce,Journal of Hydrology 158(1994) 285-303. Baghirathan, V.R. and Shaw, E.M. (1978). Rainfall depth- duration- frequency studies for Sri Lanka. Benjamin,L. and Richard ,M. (1999). Assessment of Storm Duration for Hydrological Design, Journal
40 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Evaluation of Irrigation Water Issue Practice for Better Water Management at Rajangana Reservoir, Sri Lanka
H. Chemjong and N.T.S. Wijesekera ABSTRACT In most parts of Sri Lanka, water is the critical factor for cultivation. Using the appropriate amount of water is the key factor and therefore efficient water management is very important to increase food production. Common practice of Irrigation water distribution is with the help of Irrigation Department Guidelines. Present work is a study of irrigation water issue practice in Rajangana Irrigation Scheme situated at Anuradhapura which is a district the North Central Province of Sri Lanka. The present study using field data from 2008-2013, computed the theoretical irrigation water requirements as recommended by the Guideline using 75% probable rainfall values and this was named as " Recommended Irrigation Plan", Then this plan was modified with the consideration of actual rainfall that had been experienced during operations. This modification represented the actual water issues that need to be anticipated during operation and hence was named as "Anticipated water use". At the Rajangana Irrigation scheme there is also the actual plan developed for each year along with the water issue at the sluice gate corresponding to the 2008-2013 period. The present research compared the case of Left Bank gravity fed irrigation area which covers an approximate 2500 Ha area with 39 Km tertiary canal network. This area is cultivated mainly with paddy for two main rainy seasons namely "Maha" and "Yala". Water issue model for the study was developed at a weekly time resolution. Comparison of actual water use with the quantities are computed by following Irrigation Department Guidelines disclosed a significant over issue in Maha and Yala seasons amounting to 63% and 52% respectively. In the case of making adjustment to the plan with the receipt of actual rainfall, then a further reduction of water issue by 35% and 8% in Maha and Yala respectively could have been possible. Evaluation revealed the need of gauge network, a spatially distributed performance monitoring system and a critical evaluation on the base of present Guideline in order to suitably manage the water utilization in the Rajangana Left bank irrigation scheme.
KEYWORDS: Efficient Water Management, Irrigation Water Distribution, Water Issue Practice, Irrigation Water Requirement, Probable Rainfall, Recommended Irrigation Plan, Anticipated Water Use, Water Issue Model, Gauge Network
1. Introduction yield is 7-12 MT/Ha. In the review of De Oliveira, about 850 million people of world Sri Lankan farmers are growing paddy which are food insecure and 60% of these is reaching 3876000 MT per annum (DCS, populations are of South Asia and Sub 2008) and it fulfils 90% of national demand Saharan Africa. This clears the critical which was only 40% in 1950 (WRMS, 2010). scenario of food insecurity in South Asia. Sri Lanka has 0.7% approximate rate of Sri Lanka has three zones which are dry zone, population increment which has been intermediate zone and wet zone where increasing the rice consumption about 1.4 MT annual rainfall are less than 1750mm, 1750- per year and its effect for increasing rice 2500mm and 2500mm respectively (DAG, demand 1.1% per year (DAG, 2014b). Case 2014a). In case study of Walawe Basin (2009), Study of Walawe basin (2009) has included there is approximately 43000 MCM surface the rice yield 4.2 MT/Ha and 4.0 MT/Ha in water availability but there is only 28% water Yala and Maha season respectively and is in use of irrigation and 65% water is being WRMS, (2010) has indicated that average rice evaporated, percolated and flowed out to sea. yield 4.5 MT/Ha. But here is potentiality of
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 4141 UMCSAWM Water Conference – 2017
Only 7% is in industrial and domestic use. about sensitivity of paddy to water stress is a This indicates that here is possibility to use major concern with regards to water more surface water by either reducing losses scheduling and its results low yield. Shantha or adapting the alternative ways. Here, et.al. (2012) has carried out the study of climate change effects have reduced 7% of minor tank in Trincomalee and this study has total runoff (Wijesekera, 2011). A rise of recommended to improve the efficiency of temperature is increasing the water resource uses. De Costa (2010) has evapotranspiration thereby causing the stress mentioned the need of good policy for irrigation management and these effects framework and commitment of research area are creating significant challenges for in water sector. Hadad and Bakr (2013) has irrigation system. studied in four climatic zone of Iraq and Water management plays important role for mentioned that rainfall, irrigation scheduling better use of water to support not only for methods, climatic factors, soil factors and more area but also for keeping farmer secure. plant types affect the water issue in irrigation. Average duty in Sri Lanka are 1300 mm and Hamlyin (2004) has also supported its 1750 mm in Maha and Yala respectively conclusion. Faulkner et.al. (2008); Bauman (Imbulana & Merrey, 1995). This mentions and Tuong (2001); De Olivera et.al. (2009); that about 19% area per unit volume Wridt et.al. (2009) mention the need of decrement and increment of irrigation duty evaluating seasonal variation of precipitation in Maha and Yala are 22% and 29% and soil water content to study which helps respectively. Additionally, this mentions to select the suitable agriculture patterns, that irrigation water productivity has technologies and varieties. Bauman and decreases 20% within 1984-1993.This hints to Tuong (2001) has mentioned that reduction of think for other alternatives for better the ponded depth can save 23% water with irrigation water management and efficient reduction of only 6% paddy production. It scheduling of water issue practices. shows that the water volume based taxes has Sri Lanka has been preparing the water better results than conventional area based scheduling and planning by using the taxes. Prasthasarathi et.al. (2012) mentioned Irrigation Department Guideline (Ponrajah, that aerobic rice production-environment 1988). In each season, water schedule is friendly method which can reduce the being prepared and there is discussion with significant volume of water i.e. 50% can have farmers for the consensus. Especially, Minor crop yield 4-6 MT/Ha. De- Olivera et.al. and Medium Systems are being managed by (2009) has also found out the same findings in Irrigation Department of Sri Lanka with Latin America. Rama Rao (2011) has studied consultation of farmer leaders. Generally, about the System of Rice Intensification and water issue practices depends on the crop found out 20.15% increment of productivity types, actual rain, starting time of cropping, and reducing the input about 10.85% time to reach to maturity phase and efficiency coverage. of channel therefore this can be vary from According to Irrigation Department plan. Hence, it is very important to compare Guideline, water issue are planned and both plan and actual practices of water issue implemented which open the way to carryout to manage the water efficiently. In spite of comparative study to evaluate the degree of very limited study of irrigation method and adequacy for efficient water uses. practices in Sri Lanka, Wijesekera (2010) has Rajangana reservoir in North Central reviewed 16 nos. of irrigation reservoir, 3nos. Province of Sri Lanka has capacity of 100.66 of water use and 12 are regarding climate MCM and considered as water abundant. change effect in irrigation sector. De Alwis WMS (1982) states that there was no and Wijesekera (2011) has argued to requirement of water management in 1968 incorporate indicator to capture total water because of high availability but it was use by plant in review of performance managed and maintained poorly. De Alwis assessment indicator for evaluation of (2008) has accepted about the poor irrigation schemes. management of water with water abundance. Wickramaarachchi, Wijesekera and Gamage Considering the importance of water (2000) has mentioned that lack of the concern management, comparative evaluation of
42 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
planned and actual water release in Gravity guidelines, practices and relate research in Sri fed System of Left Bank Canal System is Lanka, Rajangana scheme and elsewhere. important. Objective of this study is Detailed field surveys were undertaken for comparative evaluation of Irrigation Demand both data collection and gap filling of and Actual Water Use in gravity flow system institutional data. A critical evaluation of the of Irrigation scheme to identify suitable results are then discussed and concluded for management options, crop types, scheduling appropriate water management and implementation. recommendations.
1.1. Study Area 3. Analysis and Result Rajangana Irrigation System is located in Anuradhapura district of North Central 3.1. Irrigation Water Requirement Province. For the study, Left bank irrigation system was selected for the comparative One objective of Study is the comparison study where 37 turnouts in gravity flow between actual water use and water demand system. Total coverage area is 2559.44Ha on the base of Irrigation Department where is established 18 pump stations and Guideline. 75% probability and pan these stations are providing water for 334 Ha evaporation data was considered from the of upland area. table of Irrigation Department Guideline Ponrajah (1988). Cropping pattern, its types and extent with crop season commencement date was taken in actual base of the field. Effective rainfall was computed according to the relation in Irrigation Guideline Ponrajah (1988). Collected field data collection and interaction with officials reveal that there is always full extent in both Maha (October- March) and Yala season (April- September).
3.2. Crop Evapotranspiration
Figure 1: Rajangana LB Canal System Evapotranspiration (ET0) is taken of A class pan of Maha-Illupallama station and crop 2. Methodology coefficient (KC) values from the table of Institutional visit and field visits were Irrigation Guideline as well as corn for FAO undertaken to the project area for data No 24 Report. In Yala season, paddy variety collection of 10 years data. Especially, 5 Years is longer i.e. 3.5 month period and in Maha (2008/09-2012/13) was selected for study. season, paddy is cultivated of 3 month period For example, cropping data, L.B. sluice water type. Water availability also guides the issued data, pumping hour data, crop yield selection of paddy variety. In Yala season, and fertilizer data were collected where evapotranspiration is 3.36mm/day with October-September is the period of water assuming 3-4 days watering intervals for corn year. All data were prepared as weekly (Ranaweera et.al, 2002) and Kc is 0.69 for resolution and followed by data checking initial growth stage. Generally, Indian types and incorporating suitable assumptions for are cultivated therefore we assumed the same computation. In this Rajangana Irrigation type and FAO no. 24 has mentioned System, one canal has fed both gravity flow 20/35/40/30 day distribution for this corn and lift irrigation but in study, only gravity (Doorenbos & Pruitt, 1977). This literature flow system was taken for computation has mentioned about Kc values 1.05 and 0.55 which was on the base of Irrigation for mid-season and harvesting. Here is Department Guideline. Prior to the average temperature is 29° to 34° and in computations a detailed literature review coldest season- January, it is within the range was carried out to understand the available of 14° to 17°. After interpolating, its value
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 4343 UMCSAWM Water Conference – 2017
was found out as Kc, 0.69, 0.87, 1.05, 0.80 and 3.5. Farm Loss days are 20, 35, 40 and 30 for initial, In case of farm loss, ID Guideline (Ponrajah, development, maturity and late stages 1988) has recommended quantities of 4 respectively. inches and 6 inches for Maha and Yala respectively. Guidelines do not provide 3.3. Selection of Stagger direct information to determine the farm loss Staggering practices are generally in canal in case of OFC crops. Values corresponding irrigation for optimizing the canal capacities to farm loss for OFC could not be found for and management of equipment power for work done elsewhere in the world. farming. For management of the overloading In the present work, Farm loss for OFC crops condition of the canal and to manage of were based on several assumptions. In Sri machines and draft power, stagger is Lanka, basin irrigation is used for paddy recommended for equal or unequal stagger cultivation. In the Basin irrigation practice, of total extent of cultivation (Ponrajah, 1988). farm loss generally occurs due to the deep However the Rajangana Irrigation System percolation and runoff losses. Paddy fields of does not incorporate the staggering system Hsueh Chia Experimental Station of Taiwan therefore it is avoided in computation. had recorded deep percolation values of 295mm and 273 mm for first and second rice 3.4. Land Preparation Water Requirement crop cultivations respectively (Kuo, Ho & Liu. 2005). Naderi et al. (2013) found that a In Sri Lanka, information of land preparation wheat farm had an average deep percolation work is generally used for the irrigation and runoff loss amounting to 52.9% and 6.7% system planning and design. In Rajangana, of the total applied in Iran respectively. reddish brown earth (RBE) soils are found in These evidences show that the surface upland and low humic gleys (LHG) are irrigation has a high deep percolation loss. prevalent in the low land area (WMS, 1982). Surface Irrigation has a 40%-60% application Based on Irrigation Department Guidelines efficiency in basin irrigation while, field and (Ponrajah 1981), 7 inch water depth for land drip irrigation demonstrate a higher preparation and duration of 15 days were application efficiency 80% to 95 % (Irmak et adopted for weekly water requirement al., 2011). In practice, low flow rate methods computations in the case of lowland paddy. such as micro Irrigation techniques, small Rainfall is a major factor for land preparation pipe irrigation and small ditch irrigation etc., work in Yala season during which OFC crops are used for OFC cultivation. During the Yala are also cultivated. The staff of Rajangana ID OFC cultivation, when the water is scarce, it indicated that the field practices can be safely assumed that the runoff losses demonstrated a usual land preparation time are very low as compared with Paddy. of one week and a cultivation pattern similar Reported values mention that the losses in to upland. In case of upland farming, soil case of micro irrigation are in the range of 5%- saturation is not practiced. 20% while, in the case of basin irrigation the The Irrigation Guideline is only focused on same would be around 40%-60%. As such paddy cultivation. Information available on average farm loss in micro irrigation is OFC does not enable a reasonable approximately 25% of basin irrigation. comparison with paddy. In the case of OFC, Therefore, a value of 38mm which is 25% of grown in upland area a 1.5 inch (38 mm) 152 mm was considered as the farm loss for water depth has been recommended for land OFC. preparation to be issued within 15 day duration. According to Irrigation 3.6. Effective Rainfall Department (ID) guidelines, upland cultivation requires water only for tillage and Effective rainfall computations were carried the indicated period is 4.27 days. A land out using the ID guideline recommended preparation water quantity of 38 mm in one empirical equations. To compare the water week was taken as the recommended plans of the Rajangana ID Office and the amount for OFC cultivation in uplands. Guideline Recommendations, computations were carried out with the use of 75% probable
44 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
rainfall of the DL1 agro ecological region 3.8. Gravity Flow System given in the ID guideline. Effective rainfall Remaining quantity of water in the LB Canal values of each year with using 75% probable is found after deducting the quantity of water values of ID guideline are shown in weekly extracted for Lift Irrigation from the gravity temporal resolution (Figure 2). Accordingly irrigation system. In the present study, the the ID guideline recommended monthly behavior of gravity flow system is evaluated. empirical equation was proportionately Therefore; the total quantity of gravity flow converted to compute weekly effective was computed with the use of water release rainfall values. To compare actual water data and the pumped water quantities of issue with the guideline recommendation, each year. Comparison of pumped water and effective rainfall values for each year were the total water releases indicate that general computed using actual values of rainfall pumped water quantity varies from 0.14% - recorded at Rajangana for the period 2002 - 0.36% per week. In order to present all the 2013. values in a comparative graphic the Weekly effective rainfall experienced at logarithmic plots are used. Rajangana was computed using observed rainfall values instead of 75% probable Table 1: Net Gravity Flow Water Quantity in Maha rainfall are shown in Figure 3. Season Water Issue for Gravity Flow System in 120 Wat. Maha Season (MCM/Month) 100 Year 80 Oct Nov Dec Jan Feb Mar 08/0 15. 10. 13. 60 9.9 6.7 7.0 40 9 5 4 7 20 09/1 0.0 13. 14. 14. 7.1 9.3 0 0 1 5 2 0 10/1 9.7 10. 10. Oct Jan Dec Feb Nov Apr Aug July Mar Sept
June 0.0 12.0 5.3 May 1 7 8 7 Effective Rainfall (mm) Rainfall Effective Time (Month) 11/1 11. 16. 15. 0.1 10.0 6.4 2 8 8 3 12/1 14. 13. 1.1 14.4 9.2 2.4 Figure 2: Effective Rainfall According to Irrigation 3 2 7 Department Guideline
14 Table 2: Net Gravity Flow Water Quantity in 12 10 Yala Season 8 6 Water Issue for Gravity Flow System in 4 Wat. Yala Season (MCM/Month) 2 Year Sep Apr May Jun Jul Aug 0 t Effective rainfall mm rainfallEffective 1st 4th 7th 31st 10th 13th 16th 19th 25th 28th 34th 37th 40th 46th 49th
43rd 08/09 18.2 13.5 11.1 10.6 0.5 0.0 22nd 52nd Time (Week) 09/10 8.0 8.3 10.5 10.2 2.9 0.0 10/11 11.2 18.0 13.0 14.6 7.9 0.6 11/12 12.0 18.9 11.3 11.3 8.8 1.0 Figure 3: Effective Rainfall on the Base of Rajangana 12/13 20.4 15.5 17.5 17.1 5.3 2.7 Station
3.7. Canal Efficiency 3.9. Irrigation Water Requirement Irrigation demand values at the headwork LB main canal of the Rajangana irrigation were computed with the application of canal scheme has both lift and the gravity irrigation conveyance efficiency to canals on the field system. In the case of lift irrigation system, irrigation requirement. In the present work, reliable data of crop types, cultivation computations were carried out with an periods and cultivation extents could not be overall canal conveyance efficiency of 70% as found. With the water extraction data for the recommended by Ponrajah (1980). lift irrigation system, Irrigation water requirements in the gravity fed system were
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 45 UMCSAWM Water Conference – 2017
computed. Crop and cultivation data also rainfall and vice versa. This method enables restricted the comparative evaluation of the the understanding of whether such changes present study to the gravity fed irrigation are significant; therefore the anticipated system. Computation of irrigation water water use which is calculated with historical requirements were done using spreadsheets data, considers the field reality with the prepared in line with the ID guideline. A knowledge of actual Crop type, Cropping typical format demonstrates the use of Crop Calendar, Extent of Cultivation, Rajangana Calendar, Crop Coefficients, Crop rainfall and Evaporation at Maha Evapotranspiration, Land Preparation, Farm Illupallama. Closest location to Rajangana Loss, Effective Rainfall and Canal having evaporation data was at Maha- Efficiencies. The stepwise computational Illupallama. method was used in the study and associated spread sheets. Computations were done for 3.13. Comparison of Rajangana ID Plan and each crop at each tract and then results were Recommended Irrigation Plan (DL1) summed to capture the variations at the LB Comparative monthly plots of monthly water canal level. Availability of actual water quantities corresponding to Rajangana ID issues for the gravity fed irrigation system plan (RID), Recommended Irrigation Plan enabled a comparison. (RIP) and the monthly effective rainfall were computed using 75% probable rainfall of 3.10. Water Requirement Computation DL1. Differences between the Rajangana ID Total water demands were evaluated by Plan and Recommended Irrigation Plan using two methods. One method is to (DL1) were identified. According to seasonal evaluate the planned water quantities at the comparison, there is an over estimation in beginning of each season. The other method most of the months while in some months is to evaluate the actual water issue with the especially in Yala season, there is as under anticipated water use during the season estimation when compared with the ID when actual evaporation and rainfall are Guideline recommended values. taken into consideration. Comparison of the variation of differences over the year, there is a significant deviation 3.11. Recommended Irrigation Plan in the Yala season i.e. approximately 2 MCM per month. Annual variations show a This water manager would prepare prior to a general increase in the recent year except for cultivation season. With the availability of 2009/10. Crop type, Cropping Calendar and Extent of Cultivation, a manager would have to In the water duty comparison for Maha and estimate the evaporation and rainfall. For Yala seasons, average water duty estimations these estimates, Guideline quoted values is in the Rajangana Irrigation Division Plan utilized. In the ID guideline, 75% probable were 1.83 m and 2.13 m respectively for Maha rainfall is given on the basis of agro ecological and Yala seasons. Same from the zones. Rajangana reservoir falls in to the Recommended Irrigation Plan, these were agro ecological zone DL1. Hence this 1.34 m and 1.70 m for both seasons method is termed as "Recommended respectively. Irrigation Plan (DL1). This plan also uses the evaporation values of Kalawewa of 3.14. Comparison of Actual Water Use and guidelines which is closest to Rajangana. Recommended Irrigation Plan (DL1) 3.12. Anticipated Water Use Actual weekly water use values of Gravity Irrigation System of L.B. Canal were This is a modification of the recommended aggregated as monthly and seasonal data in water issue plan to reflect how the system has order to carry out a quantitative evaluation. performed with actual rainfall and evaporation. In other words, a good and Actual water issues showed water releases as efficient irrigation water manager would an environmental flow after the cultivation make attempts to issue more water when the seasons. Environmental flow quantities actual rainfall is less than the 75% probable
46 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
were not separated when seasonal and 3.16. Comparison of Recommended annual comparisons were done. Rajangana Irrigation Plan (DL1) and Anticipated Irrigation Plan, Actual water use and RIP Water Use (DL1) weekly values were plotted on the Recommended Irrigation Plan (RIP) was same graph. Monthly Actual Water Use calculated with effective rainfall of DL1 Agro plotted with monthly effective rainfall. Ecological Region and Evaporation of Monthly values of Recommended Irrigation Kalawewa-ID Guideline. The ANWU was Plan with guideline recommended effective computed with rainfall of Rajangana and rainfall for DL1 and Values and the actual pan evaporation of Maha Illupallama. differences of both plan are considered. The These were compared to each other and this water duty comparison for Maha and Yala monthly and seasonally. seasons for these two cases are found out separately. Comparative evaluation of water Percentage difference was computed using issue was computed for each crop growth the following equation. stage and seasonal and annual variation was found. 푅퐼푃−퐴푁푊푈 ∗ 100……………………. (Eq. 1) 퐴푁푊푈 3.15. Comparison of Actual Water Use and Anticipated Water Use During the study period, average differences in the water duty of these plan and uses for Anticipated water use (ANWU) was Maha and Yala season are 35% and 8% computed considering effective rainfall and it respectively. was compared with the actual water released to L.B. Gravity Irrigation System. The detail 3.17. Water Use, Crop yield and Rainfall comparison summarized as monthly and seasonal data which were compared for a A seasonal comparison Paddy yield, water quantitative evaluation. use and effective rainfall from 2008/09 to 2012/13 are considered. In Maha Season, Monthly actual and anticipated water uses average effective rainfall at Rajangana is 0.64 are plotted with monthly effective rainfall. m and the same in Yala season is 0.16 m. Monthly Seasonal and Annual differences could be seen within the study period. Average actual water duty and recommended ID water duty for Maha Percentage of seasonal water volume season are 2.18 m and 1.34 m respectively. differences between the Actual Water Use The same respective values for Yala season (AWU) and ANWU are computed for Maha are 2.4 m and 1.7 m. Average paddy yield in Season and Yala Season separately. In the Maha season is 6.67 Mt/Ha while almost the Yala Season, the percentage difference is same in Yala season is 6.85 MT/Ha. lower than that of Maha Season. In both seasons high differences were noted during This study indicates that effective rainfall the initial period. The average differences in between seasons is significantly different and Yala and Maha Seasons were 51% and 117% that the paddy yield is in sensitive to effective respectively. In Maha season, the average rainfall. This gives an indication that percentage difference is about 55% in land significant quantity of water for crop growth preparation and it is high in initial stage is made available by irrigation. Paddy yield period which is 372% variation reflects a pattern that closely matches with that of actual water use. With Duty of AWU and ANWU and its difference the increase of water use, the yield has were computed. This water duty difference shown an increase in the Yala season, but is 1.16 m (117% of the water duty of AWU) in it is not so in the Maha season. In the Maha season and 0.82 m in Yala which is 51% Maha season, paddy yield appears to of AWU. reach a limit that indicates a necessity to recognize the other reasons for increasing yield in Yala season.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 4747 UMCSAWM Water Conference – 2017
This behavior is prominent where seasonal 5. References paddy yields are compared with the Abideen, Z.U. (2014). Comparison of crop excess water utilization (i.e. AWU - RIP). water requirements of maize varieties under irrigated condition of semi-arid 4. Conclusions environment. Journal of Environment Rajangana L. B. gravity fed irrigation system and Earth Science, vol.4 (6), 1-3. over the five year study period revealed the need of appropriate canal water Adnan, S., Khan, A.H. (2011). Effective rainfall for irrigated agriculture plains of measurement system and also the need to Pakistan. Pakistan Journal of introduce a spatially distributed performance Meteorology vol.6, 61-72. monitoring system for the identification of critical areas ensuring efficient water Ajmera, S. & Shrivastava, R.K. management. Evaluations pointed to an over (2013).Water distribution schedule issue of water in the LB gravity fed irrigation under Warabandi system considering system throughout the seasons which could seepage losses for an irrigation project. result from many issues such as canal water International Journal of Innovations in losses, poor application, lack of a spatially Engineering and Technology (IJIET), distributed measurement system, availability vol.2, 178-187. of water in abundance and a week based data sets for planning. Irrigation Department Ali,O.O.(2013).A computer program for guidelines should be critically evaluated and calculating the crop water requirements. updated with the incorporation of structured Greener journal of agriculture science, research programs. Comparison of actual vol3 (2), 150-163 water issues at the LB Sluice disclosed a Bauman, B.A.M. & Tuong, T.P. significant over issues of water throughout (2001).Field water management to save the both seasons with showing water and increase its productivity in approximately 63% and 52% higher volume irrigated low land rice. Agriculture of the water requirements. Comparison of water management 49, 11-30 Guideline Based and Actual Water Duty values showed that the actual utilizations are Bos, M.G., Burton, M.A. & Molden, D.J. much more than estimated in both seasons. (2005). Irrigation and drainage On average, Maha Season - actual water duty performance assessment. CABI was 2.18 m while the guideline based value Publishing. was 1.34 m. The respective values for Yala season were 2.40 m and 1.70 m. Evaluation Cabangon R.J & Tong, T.P. of Maha Season water issues during crop (2000).Management of cracked soils for growth stages indicated that on average the water saving during land preparation for Initial Crop Growth Stage used a water rice cultivation. Soil and tillage research, quantity to 4 times of which is anticipated 56,105-116 from ID guidelines. In other Growth Stages, the increment varied between 1.5 -2.4 Times Case study in Walawe basin Sri Lanka (2009).Ministry of Agriculture and Evaluation of Yala Season water issues Development & Agrarian Service Sri during crop growth stages indicated that on Lanka P.18 average the Initial Crop Growth Stage used a water quantity nearly twice of the anticipated Chowdhary, S., Al-Zahrani, M. & Abbas, A. by following ID guidelines. In other Growth (2013).Implication of climate change on Stages the increase varied between 1.25 -1.57 crop water requirement in arid region: times. Paddy Yield per unit of water An example of Al-Jouf, Saudi-Arebia. indicates a highest value of 3.62 MT/m with Journal of King Saud University average value of 2.99. A tendency of Engineering and Science, 1-10. growing water overuse could be noted in the Yala season while in two Maha seasons overuse of water had not resulted in better yield.
48 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
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Kamaladasa, B. (2007). Irrigation Agriculture: Research and Review vol, development in Sri Lanka. Centenary 3(4), 751-756. commemoration publications.Page.179. Pakhale, G., Gupta, P. & Nale, J. Khan, M.A., Islam, M.Z. & Hafeez, M. (2010).Crop and Irrigation water (2011).Irrigation water demand Requirement estimation by remote forecasting-A data preprocessing and sensing and GIS: A Case study of data mining approach based on Spatio- Karnal District of Haryana, India. temporal data. Data Mining and International Journal of Engineering and Analytics CRPIT vol 121,184-194 Technology vol. 2(4), 207-211.
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52 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Incorporation of Water Distribution Network Costs in Water Supply System Design Highlighting the Strength of Raster GIS Modelling
D.M.S.S. Dissanayake and N.T.S. Wijesekera
ABSTRACT Design of Water Supply Scheme is very complex and challenging with the numerous options for source, Towers and Network Layout. It demands a several map based analysis to determine suitable layout with intake locations and intermittent storages. Spatial modelling in GIS using a raster format enables a water supply engineer to incorporate the spatial variability, parameter uncertainty, changes to decision objectives, exploring the conceptualizations, and time saving while providing the facility to not only visually explore the result but also to quantify in a meaningful manner. Raster model was developed to demonstrate the strength of GIS and to analyze tower locations and water distribution network layout options in Hanwella DSD area, Sri Lanka. Demonstrating a simple method to incorporate tertiary level pipe networking costs, this case study demonstrates the evaluation of the least cost distribution network for the two alternative tower locations that would produce the same revenue. To demonstrate raster GIS potential in the Water Supply and Drainage sector through a case study application of cost based tower location selection combining the impact of terrain features and consumer settlement distribution. In the present study, three options were considered in order to supply water to the project area with proposed two source points. After obtaining lease cost paths to lay distribution network under each options considered, path costs were compared in order to identify best alternative. There is a 36% Variation of cost between options and Out of three options, third option with the lowest cost will not be an effective option since even though both source points were used, source 1 will be used supply only for two destination points. Both have capability to supply water effectively and economically to particular area. But supplying water with S2 tower will be the best option with 33% less cost compared to highest cost option and only 2% higher than least option.
KEYWORDS: Water Distribution Network, Pipe laying Cost, Raster GIS, Spatial variations, National Water Supply &Drainage Board
parameters. Geographic features fall in to a many 1. Introduction categories represented by either points, lines polygons or surfaces. The subjective parameters Demanding occupations pushing for time savings also depend on many physical, social and political and improving life styles aiming for more and more factors. Therefore water supply scheme design comforts call for reliable and affordable services at requires a several map layer based complex but the doorstep of almost every human. In a long list flexible analysis to determine a suitable layout with of desires, the demand for safe pipe borne drinking intake locations and intermittent storages. Rural water is in the forefront. Most do not have the communities are the neediest among those who luxury of easy access to their own surface of require pipe borne water supply. Therefore, it is groundwater suitable for consumption. Increase of important to investigate and study in this context. population in one hand demand for more and more Recent GIS technology enables spatial modelling water and their needs on the other hand pollute the which is a proven tool for many resource and available limited quantities. All over the world, infrastructure planning works. Though there are urban units are generally well looked after with applications carried out elsewhere in the world pipe borne water. The present demand is in the (Sitzenfrei, Möderl, & Rauch, 2013), case study rural areas which have greater spatial extents, applications and guidance material for Drinking scattered dwellings, greater surface undulations, larger distances to sources and storage. In Sri Lanka most new water supply projects are in semi urban D.M.S.S. Dissanayake, B.Sc. Eng.(Moratuwa), Area or rural areas. Hence the planning of Water Supply Engineer, National Water Supply & Drainage Board, Sri Schemes is a very complex and a challenging task Lanka a because of the numerous options available for N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip sources, towers and network layouts. It demands (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., decision making based on many geographic MICE(UK), FIE(SL), Senior Professor, Department of Civil Engineering, University of Moratuwa, Sri Lanka. features that are interlinked with many subjective
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 53 UMCSAWM Water Conference – 2017
Water Supply Systems in a Sri Lankan context is a across streams or rivers requiring more time, gap that needs filling. In case of GIS, though Vector machinery, detour paths etc. Excavation costs do formats provide ease of conceptualization, Raster vary with land use. format is the versatile tool for complex data packed Consideration of these factors require careful real life case study applications. Spatial modelling establishment of the objective function and then its in GIS using raster format enables a water supply mathematical representation. The objective engineer to incorporate the spatial variability, function used for the present work is in equation 1. parameter uncertainty, changes to decision The other parameters were assumed as a non- objectives, exploring the conceptualizations, and significant. time saving. Unless raster applications are carefully Cost of Pipe laying = function (Demand, Road type, executed it’s advantage in easy computing is lost Slope, Culvert crossings, Land use) ------(1) due to difficulty in visualizing. In the absence of a proven mathematical Accordingly the present work undertook the task of relationship between the parameters, the present demonstrating the planning potential of GIS in the work conceptualized that, the total effect on the Water Supply and Drainage sector through a case objective would be the cumulative influence of the study application of cost based tower location selected parameters. Accordingly, the selection combining the impact of terrain features mathematical representation was taken as in and consumer settlement distribution. Equation 2. The National Water Supply and Drainage Board, P D Rt S Cu L ------(2) with a preliminary analysis had identified two Where P is the Cost of Pipe laying, D is the demand locations to erect a water tower at Hanwella DSD in for water, Rt is the road type, S is terrain variation, the Western province of Sri Lanka consisting 42 Cu is culvert crossings and L is the land use. GNDs spread over nearly 64 km2. The planning requirement is to identify the best distribution Table 1. Objective function in systems concept network by considering factors such as, pipe laying Objective Parameters expenditure associated with costs of road and 1 Cost of pipe laying Terrain(1a), Road(1b), stream crossings, safety of road user community, Culvert(1c), Land use(1d), Demand(1e) variation of excavation and backfilling costs. 1a Terrain Elevation, Slope 1b Roads Road type, Land use 2. Objective 1c Culvert Watershed area, Rainfall Aim of this study is to demonstrate the planning 1d Demand Population potential of GIS in the Water Supply and Drainage When it comes to systems concept, cost of the sector through a case study application of cost terrain is again a function of cost of elevation and based tower location selection combining the slope. Hence, that has been considered when assign impact of terrain features and consumer settlement values and weights. Cost of roads may vary with distribution. the type and land use of relative area. Based on 3. Materials and Methods amount of rainfall and watershed area, cost of culvert crossings may vary. Similarly, according to 3.1. Objective Function the population cost related to demand may vary. Therefore assigning values and weights for creating To identify an economical solution it is necessary to cost surface have been carefully done by given due consider cost of network establishment since the respect to these relationships. Further, it is assumed problem reduces to selecting an alternative with the that cost of each main parameter linearly least cost distribution network. Since, water proportionate to the cost of above discussed sub distribution is done only by the NWSDB, the water parameters. Quantification (Valuation) of each tariffs would depend only on the consumption. parameter has been carried out based on general Since the total revenue generated will depend only notion and using judgmental decision-making. on the location of tower, the cost of laying the network becomes the selection criteria. 3.2. Base Layers Spatial distribution of water demand, road type , and terrain along which the network has to be laid, Point, Polyline and Polygon data and Raster images Culverts or stream crossings in the pipe route and are used with their attributes to create required map Land use variability are the main parameters layers. Existing Road Network GIS vector map affecting pipe laying costs. According to the (1:50,000) was available as a polyline shape file with demand, pipe diameters, types, fittings and other type and length available as attributes. Land use accessories vary. Road Development Authority vector GIS map of the area was digitized from charges for road repair and maintenance vary based 1:50,000 topo maps as a polygon shape file having 9 on the road type which needs excavating. Terrain land use categories attributes. Contour map of the variations demand extra effort, tools, material and study area available was a polyline shape file vector skills. Special care and design is needed to lay pipes version and attributes of elevation. Stream network,
54 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 was also digitized using 1:50000 topo sheets. Details of GIS data are in Table 2. Table 5. Slope Classification
Slope % Value Justification Table 2. Spatial data and data types Mild slope less complicated < 2% 1 Units of construction. Resoluti Attribut Data Type measurem Relatively complicated on es 2% - 7% 5 ent construction Road Poly Type, 1:50000 Meters network line length > 7% 9 Very complicated Contour Poly Elevatio 1:50000 Meters map Line n Polyg Square Area, Watersheds were generated for each culvert Landuse 1:50000 on meters Type locations using watershed tool. Peak flow for each Stream Poly 1:50000 Meters Length culvert point was estimated based on catchment network Line area since rainfall variation is negligible over the Populati Polyg populati GND Number project area. Runoff coefficient assumed to be on on on similar over the catchment. When assigning values, Rainfall Millimeter Higher value is given for higher peak flows. Gauging Point Monthly Rainfall s stations Stream network was generated using the DEM which was burned with the physical streams. Flow direction computation, filling of sinks, flow 3.3. Analysis accumulation etc., were carried out using the flow Vector road network map was converted to a raster direction, fill and watershed tools. layer and then reclassified to 4 classes of roads and A comparison of stream network generated with values were assigned to the type. Raster resolution the threshold flow accumulation value of 3000 was of 5m was adopted for this whole study. Land use selected after matching with the existing physical map which was polygon layer converted to raster streams. Raster to Vector conversion tool was used and reclassified in to six main classes based on type to create the stream network polylines. Stream and of land use. road network enabled the identification of Culvert locations. Watersheds at each culvert location were Table 3. Road Classification generated with the use of watershed tool. Road Type Value Justification Vector map of GND polygons with population as attributes was converted to raster and reclassified as RDA charge high & A 7 given in Table 3. excavation hard Table 6. Demand Classification RDA charge less than A AB 5 Population Type Value Justification class roads Low charge by RDA and >2000 9 High demand B 2 excavation relatively 2000 - 800 5 Medium easy Less or no charge and Other 1 < 800 1 Less demand excavation easy
Table 4. Land use classification Then the cost surface raster was created by Land use Value overlaying the all five raster layers reclassified as in Table 3 to 6 using Raster Calculator tool. Rubber 3
Paddy 4 Three options were considered in order to supply Coconut 5 water to the project area with proposed two source Homestead 7 points. First option was to supply water to all area Marsh 8 with source point 1. Provide water using source point 2 was second option while supply water to the Stream 9 project area using both source points was considered as third option. Cost distance raster for Triangulated Irregular Network (TIN) was the three options were created using cost surface as developed using 5m Contours and Spot Heights the input cost raster and service reservoir points as and then the TIN model was converted to the the source points. While creating the cost distance Digital Elevation Model (DEM). The slope raster raster cost backlink raster was also created as a was created from the DEM and then reclassified in requirement to create the cost path in the next step. to 3 classes. Cost Path for the three options was created using
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 55 UMCSAWM Water Conference – 2017 cost distance, cost backlink as input Raster and GND centroids as the destination points. Centroids of each GND were obtained by mean of point shape file using ‘feature to point’ tool. Cost Path for the three options was created using cost distance, cost backlink as input rasters.
Figure 4 Cost distance map for option 2 There is a 36% Variation of cost between options and Out of three options, third option with the lowest cost will not be an effective option since even though both source points were used, source 1 will be used supply only for two destination points. Both have capability to supply water effectively and
economically to particular area. But supplying Figure 4 Project Area map water with S2 tower will be the best option with 33% less cost compared to highest cost option and only 2% higher than least option. Table 7. Path cost for each option Option Path Cost Option 1 5,211,315 Option 2 3,905,357 Option 3 3,832,779
Figure 2 Triangulated Irregular Network (TIN) Generated cost maps indicated that higher cost should be born to supply water to Eastern part of the project area. It is higher with the source point 1 and lesser with option 2.
Figure 5 Least Cost path for Option 2
4. Discussion
Since design of water distribution network (WDN) is a very complex procedure, it is vital to know how each parameter varied in space. Using raster GIS modeling it was able to demonstrate that how each affected parameters towards WDN are varied over Figure 3 Cost distance map for option 1 the project area. Conversion of parameter vector map layers to raster format enables obtain continues variation surface for each parameter. Apart from the land use pattern, road type and terrain, it was very much useful in incorporating rainfall variation and peak flow calculations in culvert and bridge crossing design. That shows how easily those
56 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 complex scenarios incorporated in to process with giving the opportunity. Also acknowledge the GIS modeling. Survey Department and National Water Supply In this present study, it was assumed that WDN and Drainage Board of Sri Lanka for providing the pipe laying cost depends on only considered necessary data to carry out the study. parameters. Apart from that it was assumed that no significant variation of considered parameters 7. References within 5m intervals. Therefore, 5m resolution was Morad, M., & Connolly, T. (n.d.). A Concise used in GIS modeling. Even coarser resolution like Introduction to Geographical Information Systems 10m or 20m may do not harm much to the result and Science. since this study shows variation is not much in finer Sitzenfrei, R., Möderl, M., & Rauch, W. (2013). resolutions. Automatic generation of water distribution systems This study was able to give comparatively good based on GIS data. Environmental Modelling & results since it shows significant improvements to Software, 47. traditional judgmental designs. Comparison indicated that better output generated through GIS modeling.
In case of further improvement to this study. It is proposed to consider incorporate zonal demarcation and valve location determination of the distribution network. If reliable data used for terrain and other such parameters it will be very much effective in doing so.
5. Conclusions and Recommendations
GIS analysis can be effectively used in the design process of water supply network apart from the monitoring and management tool. Pipe laying Cost incorporation is successfully demonstrated and reliable data and furthers improvements to objective function may lead to better estimations. The main issue and constraint was lack of data availability since approximations and assumptions had to be incorporated in computations in order to arrive to objective of the study. If the reliable data is available, GIS can be used to identify valve locations and zone demarcations. It will be more effective designing water supply schemes for rural areas.
6. Acknowledgments
The authors are grateful to the Unesco Madanjeet
Singh Center for South Asia Water Management for
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 57 UMCSAWM Water Conference – 2017
58 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Climate Change Impacts and Adaptation Measures for Pahala Divul Wewa, Anuradhapura, Sri Lanka
P. S. Thakuri and N.T.S Wijesekera
ABSTRACT Present study was carried out to identify possible threats of various climate change scenario and suggest the possible adaptation measures for the food and water security corresponding to irrigation reservoir scale. Pahala Divul Wewa with a catchment area 5.12 km2, in Anuradhapura is located within DL1 agro-ecological zone was selected. The Irrigation Guide-line model was optimized for present situation of irrigable area. Five (5) scenarios of climate change were developed based on literature. Change in the precipitation due Climate change were used for a reservoir operation. The worst climate change scenario for Pahala Divul wewa was identified as the with 22% increase in South- East monsoon and 42% decrease in North East monsoon. The cropping intensity under this scenario was reduced from 0.678 to 0.55 a decrease of 13%. Since, Cropping Intensity of Pahala Divul Wewa was noted to reduce, several adaptation measures were identified to minimize the effects. Increasing Canal Efficiency was found to be most effective adaptation measure though it is less economical. It is recommended to incorporate climate change while designing the new schemes and Existing design rainfall, evaporation and other inputs shown in the guidelines need updating.
KEYWORDS: Prioritization, Community Based Water Supply Scheme, Raster GIS, Spatial Modelling
hydrologic cycle, changes to the amount, timing, 1. Introduction form, and intensity of precipitation will continue. Agriculture is the most important sector of the Sri Water is the primary medium through which Lankan economy. Even though its contribution to climate change influences Earth’s ecosystem and the gross domestic product declined substantially thus the livelihood and well-being of societies. during the past 3 decades (from 30 percent in 1970 Climate Change danger was first highlighted to 21 percent in 2000), it is the most important globally at the UN Conference on Development and source of economy for the majority of the Sri Environment (UNCED) in Stockholm (1972). Lankans. So, impacts of climate change on Greatest of all threats is the Human Induced agriculture would have immediate effect on Climate Change, due to the buildup of Green House national economy of Sri Lanka. Gases such as CO2 (Carbon Dioxide), This study was carried out on a minor irrigation CH4(Methane), N2O (Nitrous Oxide) and some scheme to identify the impacts of climate change other Industrial Chemicals. Temperature and and to demonstrate that systematic planning and Rainfall are the main factors on climate change. The management of water resources can be done to intergovernmental Panel on Climate change (IPCC) manage climate change effect. reports evidence of climate change and put forward 4(four) concerns of climate change: the warming of 2. Study Area atmosphere and ocean, diminishing the amounts of snow and ice, rise sea level, and the concentrations Pahala Divul Wewa, with catchment area of 5.12 of greenhouse gases have increased (IPPC, 2008) km2, in Anuradhapura district was selected for the Higher temperatures and changes in extreme study. This reservoir falls under DL1 agro- weather conditions are projected to affect ecological zone of Sri Lanka. availability and distribution of rainfall, snowmelt, river flow and groundwater, and further deteriorate water quality. The relationship between water for agriculture and climate is a significant one. More and more, that relationship is falling out of balance jeopardizing water and food security. Climate P.S. Thakuri, B. Tech (Kathmandu), Graduate Research change is a phenomenon that no longer can be Assistant at UMSCSAWM, University of Moratuwa, Sri Lanka denied as its effects have become increasingly evident worldwide. Climate change is changing our N.T.S. Wijesekera, B.Sc. Eng. Hons (Sri Lanka), PG. Dip assumptions about water resources. As climate (Moratuwa), M. Eng. (Tokyo), Ph. D(Tokyo), C.Eng., MICE(UK), FIE(SL), Senior Professor, Department of Civil change warms the atmosphere, altering the Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 59 UMCSAWM Water Conference – 2017
cultivation extent and cropping intensity.
Figure 1. Study Area Inset
3. Methodology and Data Fig 2. Methodology flowchart of the study 3.1. Data 4. Analysis For the purpose of this study, Topographic map and Area-Capacity curve of the reservoir were collected 4.1. Climate Change Scenarios from Survey department and Irrigation Department With reference of literature, climate change scenario respectively. 75 % probable monthly rainfall data, was formulated and are described below: monthly evaporation, reference crop evaporation Scenario-1: and seasonal water yield from Irrigation Guidelines 20% rainfall increase for North-East monsoon of Sri Lanka (1984) used for water balance (December to February) and 30% rainfall increase computations. Reservoir is with a capacity of 55 for South-West monsoon (May to September) Ha.m. Full Supply level was 30.5 m MSL and Scenario-2: Minimum operating level was 28 m MSL. The area 30% rainfall increase in South-west monsoon (May covered by FSL level is 47.9 Ha. to September) and 30% rainfall decrease in North- east monsoon (December to February) 3.2. Methodology Scenario-3: Initially, Irrigation demand was calculated for three 10% increase in rainfall in North-east monsoon stager irrigation. Reservoir operation for water (December to February) and South-west monsoon balance was per Irrigation Guideline model was (May to September). carried out in order to calculate feasible irrigable Scenario-4: area both in maha and yala season under the current 22% increase of higher rainfall and 42% decrease of situation. Data for the computation were fed from rainfall in Lower Rainfall. the Irrigation department guidelines. Model Scenario-5: calibration was done by trial and error optimizing Rainfall shift by one month backward while initial storage at beginning of October is closer to storage at the end of water year. Calibrated 4.2. Reservoir System Water Balance model outputs were verified with actual cultivated Equation-1 and 2 are the reservoir system water land area. balance based on continuity equation used for the With literature, several scenario of climate change purpose of the study were developed. Changes in 75% probable rainfall due to climate change were estimated and tabulated. Inflow – Outflow = Change in Storage…………….1 The tabulated 75% probable rainfall were used for I – (Ei – Sei - Spi – ID) = Si – Si-1………….……....…………...….2 the water balance with calibrated reservoir I is the inflow of water through catchment, E is the operation model in order to find impacts on surface evaporation from reservoir, Se is the seepage form the bottom of the reservoir, Sp is the spillage form the reservoir and ID is irrigation demand. On the right-hand side, the S denotes Storages. The I in subscript denotes time interval and the tie interval of the monthly model is 1 month. Si-1 denotes at the beginning of the month or Storage at end of the previous month.
60 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Irrigation demand for each month separated as Table 5.3. Irrigation Demand of Scenarios Maha and Yala were calculated according irrigation Scenario Maha Yala Total department guidelines (ID, 1984). Present 1773.57 2051.54 3825.12 Field water requirement (FWR) = ETc + LP + S-1 1729.81 2029.66 3759.48 FL………………………………………………………3 S-2 1707.93 1968.88 3676.82 Field Irrigation Requirement (FIR)= FWR-Pe….….4 Irrigation Demand (ID)= FIR/n…………………….5 S-3 1793.02 2056.40 3849.43 S-4 1739.05 2071.96 3811.02
Above Equation 3, 4 and 5 leads to compute the S-5b 1773.57 1978.61 3752.18 Irrigation demand of the field where ETc is crop evapotranspiration, LP is land preparation, FL is Table 5.4. Irrigable Area for Scenarios water requirement to compensate farm losses. With Field Water Requirement (FWR), Field Irrigation Scenario Maha Yala Total requirement can be calculated by subtracting it by Present 47.89 12.21 60.10 effective rainfall Pe and Thus Irrigation demand is S-1 51.1 15.33 66.43 calculated by dividing FIR by canal efficiency (n). S-2 51.1 13.03 64.13
5. Results S-3 45.26 11.68 56.94
Monthly Storage at beginning of month (Si-1), S-4 40.15 10.04 50.19 Inflow(Ii), Evaporation(Ei), Seepage (Sei), S-5b 37.96 11.39 49.35 Demand(D), Seepage(Sp), Storage at the end of the month(Si)for maha and yala Season are given in the Table 5.5. Cropping Pattern for the Scenarios Table 4.1 1and 4.2 Scenario Maha Yala Total
5.1. Present Situation in Paha Divul Wewa Present 0.65 0.25 0.68
Table 5.1. System Water Balance for Maha Season S-1 0.7 0.3 0.73 S-2 0.7 0.25 0.72 Oct Nov Dec Jan Feb Mar S-3 0.62 0.25 0.64 Si-1 1.50 12.40 23.27 28.72 22.04 4.90 S-4 0.55 0.25 0.57 Ii 22.76 27.31 22.76 13.66 4.55 9.10 S-5b 0.52 0.3 0.55
Ei 0.79 1.82 2.71 3.03 3.00 2.04
Sei 0.01 0.06 0.12 0.14 0.11 0.02 0.75 D 11.07 14.55 14.49 17.16 18.59 9.07 0.7 Sp ------0.65 Si 12.40 23.27 28.72 22.04 4.90 2.86
Table 5.2. System Water Balance for Yala Season 0.6
Apr May June July Aug Sep 0.55
Si-1 2.86 24.37 25.91 17.75 7.92 1.56 Intensity CroppingAnnual 0.5 S 1 S 2 S 3 S 4 S 5 Ii 22.76 9.10 2.28 0.00 2.28 4.55 Senario Ei 1.24 3.71 4.01 3.20 2.54 1.09 Scenarios Present Senario
Sei 0.01 0.12 0.13 0.09 0.04 0.01 Fig 3. Variation of cropping Intensity with scenario D 0.00 3.73 6.30 6.53 6.06 2.43 6. Discussion Sp ------It is noted that in scenario-1, 20% rainfall increase Si 24.37 25.91 17.75 7.92 1.56 2.58 for North-East monsoon (December to February) Irrigation demand, Irrigable area, cropping and 30% rainfall increase for South-West monsoon intensity of all 5 scenarios are given in Table 4.3, 4.4, (May to September) and scenario-2, 30% rainfall 4.5. Among which most critical scenario and look increase in South-west monsoon (May to after the adaptation. September) and 30% rainfall decrease in North-east monsoon (December to February) both have
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 61 UMCSAWM Water Conference – 2017 positive impacts on system efficiency as cultivation and climate change. In: Proceedings of workshop on extent and cropping pattern are rising for these Sri Lanka National Water Development Report scenarios. Among other three Scenario 5 scenarios Eriyagama, N., & Smakhtin, V. (2010). Observed backward shift of the rainfall pattern and 22% and projected climatic changes, their impacts and increase of NE monsoon and 42% decrease of adaptation options for Sri Lanka: a review. rainfall in WS monsoon are seen critical as cropping intensity drops from 0.68 to 0.55 and 0.57. The drop in cropping intensity in the most critical scenario: Backward shift of rainfall pattern was 14% from the base present scenario. Hence considering this situation, adaptation measures were identified and quantified. Among various adaptation measures identified, increasing Canal efficiency was found to be most effective. The cropping intensity rose up from 0.55 to 0.67 with the increase in cannel efficiency 0.7 to 0.8.
7. Conclusion
According to Climate change prediction and scenario analysis water resources sector in minor irrigation reservoirs are susceptible. Cropping intensity and cultivable extent are mostly like to decrease in most of the scenarios. Shifting the rainfall patterns backward was found to be most critical scenarios where cropping intensity had changed abruptly from 0.68 initial condition to 0.55.
8. Recommendations
It is recommended to consider climate change for water resources planning and management for sustainable development. Adaption measures should be taken by the respective authority for avoid the crisis and hazard from the climate change.
9. Acknowledgement
Authors would like to express sincere gratitude
UNSECO Madanjeet Singh Centre for South Asia
Water Management and South Asia Foundation
(SAF) for all their supports.
10. References
Ponrajh A.J.P, Design Irrigation Headword for small catchment (1984)
IPPC (2008): Climate Change, 2008; Climate change
& Water Technical Paper of the Intergovernmental
Panel on Climate Change
Jayatillake, H. M.; Chandrapala, L.; Basnayake, B. R. S. B.; Dharmaratne, G. H. P. 2005. Water resources
62 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
TECHNICAL PAPERS
SESSION 2
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 63 UMCSAWM Water Conference – 2017
64 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Study of Urban Water Demand and Distribution System Reliability – A Case Study of Maharagama Water Supply Scheme, Sri Lanka
D.M.S.S. Dissanayake and R.L.H.L. Rajapakse
ABSTRACT Significant variation of flow could be identified during the day for Maharagama water supply scheme. Diurnal problem curve indicates that there is a significant problem level, which is more than 40% of service level, during the day. The system operates at a low Hourly Peak Factor (HPF) value of 1.5, moderate Minimum Night Flow Factor (MNF) of 0.4 and Daily Peak Factor (DPF) of 1.1. Water supply system pumping capacity was found to be inadequate to cater the peak demand of the scheme. It reveals that elevation and the distance have a considerable effect on Level of service for Maharagama WSS and Service level has a significant effect on consumption quantity as well, affecting overall revenue. Aim of this study is to assess water demand, evaluate distribution performance of semi urban water supply scheme, and propose management recommendations as an initial approach that will eventually lead to the development of established guidelines for system assessment and operation. In the present study, monthly consumption per connection derived for the past 13 years from 2002 to 2014 and the daily average flow obtained for Mondays through Sunday for five weeks were studied by applying multiple statistical analysis using Small Samples Theory (SMT). A System Water Balance Model was used to generate the instant flow rate time series of demand from the available service reservoir level data and pumping data. Generated out-flow time series was analyzed using Large Sample Theory of statistics. Level of service variation with the proposed parameters was assessed with Principle Component Analysis (PCA) and simple tabular methods. Results were verified with field surveys con-ducted across the study area. The purpose of a water supply distribution system is to provide safe drinking water to each consumer with adequate quantity and acceptable quality. For the operational as well as designing aspects, it is crucial to estimate water demand that is how much water is needed and the variation in demand that is when it is needed. Every year, more than 100,000 new consumers are added to the National Water Supply and Drainage Board (NWSDB) database and the demand for pipe borne water is ever increasing. Out of the piped schemes maintained by NWSDB, only 36% has the capacity to provide 24 hour supply (NWSDB, 1998). Hence, the demand is a very important parameter which requires due consideration when considering urban water supplies.
KEYWORDS: Water Demand, Level of Service, Water Distribution Systems, Hourly Peak Factor, Minimum Night Flow, Daily Peak Factor.
population. At present, 80% of this population has 1. Introduction access to safe drinking water where 43.7% is provided with pipe borne water supplies (Annual The purpose of a water supply distribution system Report, NWSDB 2013). Out of the piped schemes is to provide an uninterrupted, pressurized service maintained by the National Water Supply and of safe drinking water with adequate quantity and Drainage Board (NWSDB), only 36% has the acceptable quality to all consumers. The rapid capacity to maintain an uninterrupted 24-hour increase in population density in a service area, supply, while majority of the other schemes have a increased number of connections, increased 12-hour continuous supply on average (Urban demand, etc., in combination with various other Water Supply Policy, NWSDB). Every year, more limiting factors could lead to numerous issues of than 100,000 new consumers are added to the inadequate supply and low pressure. Piped water is NWSDB database and the demand for pipe borne supplied to 43.4% of the population at present, water is ever increasing. Hence, the demand is a which is over 8.5 million people in Sri Lanka very important parameter which requires due (Annual Report, NWSDB 2013). However, disparities in service coverage across regions are still prominent, despite the massive investments D.M.S.S. Dissanayake, B.Sc. Eng.(Moratuwa), Area made (over rupees 20,000 million a year) during the Engineer, National Water Supply & Drainage Board, Sri Lanka a last few decades in the water sector in Sri Lanka. The total population in Sri Lanka was 20.30 million R. L. H. L. Rajapakse, BSc Eng (Moratuwa), MSc in the year 2012 (Census & Statistics Department, (Saitama), PhD ( Saitama ), C.Eng., Senior Lecturer (Grade II), Department of Civil Engineering, University of 2012 Census). Out of this, 3.7 million are living in Moratuwa, Sri Lanka. urban areas, which amounts to 18.3% of the total
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 65 UMCSAWM Water Conference – 2017 consideration in the planning and design of urban balance of the ecosystem, and it demands to use water supply schemes. water in a more conscious and sustainable way. Water demand in an area is the result of water Even though the main concern is the supply side in consumption by individual people and industries in the modern context, demand is the main governing that area, reflecting their behavior and habits. For parameter that allows efficient management of the operation as well as the designing aspects, it is water (Candelieri & Archetti, 2014). crucial to estimate water demand, that is how much water is needed, and the variation in demand, that 2. Objective is when it is needed (De Silva, 2011). The current Aim of this study is to assess water demand, practice in Sri Lanka is to use basic statistical data evaluate distribution performance of semi urban such as population growth rate and per capita water supply scheme, and propose management consumption to estimate the water demand. In the recommendations as an initial approach that will recently designed water supply projects, assumed eventually lead to the development of established diurnal variations and peak factors based on the guidelines for system assessment and operation. results of foreign studies have been used without much insight. 3. Materials and Methods The term demand generally used is based upon the average consumption of water. Nevertheless, when Maharagama Water Supply Scheme (WSS) supplies it comes to planning and design, this average water to 29 Grama Niladari Divisions (GND) in consumption alone is not sufficient. Significant Maharagama and Kesbewa District Secretariat variations can be observed in the water Divisions (DSD) in Sri Lanka with 28950 individual consumption in seasonal resolution, monthly connections. From that, 26726 are domestic resolution, daily resolution and hourly time scale. connections while 2220 are commercial connections. Further, even in different minutes of the hour, Population density in this area is 5141/km2 and demand variations of even finer scale can be household occupants 3.8 persons (Census & observed. Thus, it is clear that assessing the statistics department, 2012 census). Average daily variations in demand in the entire water supply water consumption is 22711m3 with 15-20% system is imperative. The accurate assessments will network leakage or non-revenue water (NRW) produce a near optimal design as well as proper whereas it is going up to 33.43% in western province operation of the scheme, which leads to the (NWSDB Annual Report, 2013). Average household improved service to the consumers. monthly consumption was 16.9 m3 in 2013 Any underestimation of demand variations will (NWSDB Annual Report, 2013). Average per capita result in an undersized water supply scheme, which consumption is approximately 148 l/h/d. Domestic will fail to deliver the required quantity of water at connections are growing at a rate and demand for the correct pressure to the consumer. Although water is increasing with the growth of population such schemes are capable of providing the required as well. Figure 1 shows the study area map. service levels at the beginning, they fail to do so in the middle or toward the end of the design period. In other words, they reach the design year quite prematurely (Abunada, Trifunović, Kennedy, & Babel, 2014; De Silva, 2011). Since water supply related services tend to be of primary importance to guarantee good service levels in a sustainable way, the performance of water supply systems must be evaluated. The incorporation of performance assessment techniques in the management practices encourages efficient operation and continuous improvement. Managing water supply distribution network
(WDN) is becoming difficult with the increasing population and the demand. A lack of available Figure 1 Study area map water, a higher and more uneven water demand In order to represent monthly variation of the resulting from population growth in concentrated demand monthly usage of domestic and areas, unplanned development and urbanisation, commercial consumers of 15 years from January more intense use of water to improve general well- 2000 to December 2014 were collected. Daily inflow being, and the challenge to improve water and daily pumping data were collected from 2005 governance already pose a tremendous challenge to to 2014. It is believed that the consumption has a providing and maintaining of satisfactory water monthly and weekly variation. Hence, hourly services. The ever increasing demand for water has pumping data, 10 minutes resolution telemetry data led to environmental problems such as that is levels of service reservoir were collected for overexploitation of water resources and shifts in the five weeks corresponded to five months
66 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 representing each monsoon period of the year from 2012 to 2014. From the above five months, all 7 days of one complete week (for which the most regular flow data were available) were selected as shown in Table 1. Using this data, the following parameters have been estimated: average day demand, which is the average daily water use for the year; maximum day demand, which is the highest daily use for the year; and peak hour demand, which is the estimated maximum hour of water use during the year. Table 1 Data duration details for dynamic analysis Year Month Date Figure 3 Monthly consumption comparisons of 15 years for From To Maharagama WSS 2013 December 22 28 2014 April 13 19 4. Methodology 2014 June 22 28 2014 July 06 12 In the present study, monthly consumption per 2014 Aug 03 09 connection derived for the past 13 years from 2002 2014 Oct 10 16 to 2014 and the daily average flow obtained for Mondays through Sunday for five weeks were studied by applying multiple statistical analysis Data were checked for missing periods and visual examinations were also carried out. Consumption using Small Samples Theory (SMT). A System data were checked against inflow data and Water Balance Model was used to generate the difference compared with Non-Revenue Water instant flow rate time series of demand from the (NRW) percentage calculated by NWSDB. It shows available service reservoir level data and pumping no significant deviation of data. Abnormal data. Generated out-flow time series was analyzed deviations of monthly consumption were observed using Large Sample Theory of statistics. Level of during visual checking and corrected identified rap service variation with the proposed parameters was around values of monthly usage by distributing off assessed with Principle Component Analysis (PCA) through respective months. Some years of data and simple tabular methods. Results were verified were removed from the study set since they found with field surveys conducted across the study area. to be not reliable. Year 2000, 2001 and part of year 5. Discussion 2002 were removed. This error may due to early years just after commissioning the system. Figure 2 Significant seasonal variation in water consumption and figure 3 show some important results. could not be observed in the study for Maharagama area and this is presumably due to the year round tropical climate in Sri Lanka with no significant seasonal variations. Past studies also have confirmed that there is no seasonal variation in domestic water consumption in the country (De Silva, 2011). Moreover, no monthly variation of consumption could be observed for Maharagama Water Supply Scheme. Further, the two month average and quarterly average consumption were estimated and studied and any significant trend could not be observed in those parameters as well. Figure 2 Annual consumption comparisons with inflow for That implies that the consumers in Maharagama Maharagama WSS have adapted to a routine lifestyle throughout the year and system of supply remains constant (Rajapakshe & Gunaratne, 2005; Domene & Saurí, 2006; Jansen & Schulz, 2006). As a tropical country, Sri Lanka does not experience significant variation in temperature during the year. A statistical analysis of water use in New York City has shown that daily per capita water use on days above 25°C increases by 11 litres/°C (roughly 2% of current daily per capita use) (Protopapas et al., 2000). Hence, the uniform temperature over the year could be another reason for constant water consumption pattern.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 67 UMCSAWM Water Conference – 2017
Domestic consumption as well as the commercial In can be deduced then that the peak water supply consumption follows no monthly patterns and any demand in Maharagama WSS is not met even monthly variation was not observed in per during the morning hours. Even though the connection consumption. In Maharagama, the morning peak is as high as 1.5 times the average domestic consumption per month per connection is hourly demand, the highest problem level recorded 20±3 m3. This is increased to 26.3±4 m3 in at the same time. That indirectly indicates the un- commercial category of consumers. In catered demand at the peak time. Hence, the Maharagama, still a significant part being rural obtained flow variation curve can be considered as areas, it was reported that the people still use the consumption pattern of the Maharagama area groundwater for a portion of their daily and obviously not the demand pattern. consumption and the recorded consumption is The estimated Mid-night Flow factor (MNF) of 0.4 slightly low due partly to this. Two peaks could be indicates that there still is a significant flow during identified and the morning peak is the highest while the mid-night and early morning. This may be due the evening peak is relatively flattened. The to the filling up of domestic (household) storage consumption follows a similar pattern almost every tanks and leakages, which further indicates that day regardless of minor changes from day to day. there exists a large number of domestic storage Flow is minimum at the early hours of the day and tanks in the area and thus, the system is less reliable this generally represents leakage and filling up of in consumer point of view. storage tanks specially in high elevated and distant The distribution system possibly is of domestic areas from the service reservoir. These storage tanks nature. High Hourly Peak Factor (HPF), Low MNF are not filled up during the daytime due to low are inherent properties of a system where the pressure in the system. This is reflected in the tank consumption is mainly domestic. Very low evening water level variation, too. Flow increases sharply as HPF of 1.20 could be due to the insufficiency of the the day advances, reaching a peak value around hydraulic capacity of the distribution system. The 7:00 to 8:00 a.m. Afterwards, the consumption drops system can meet only a HPF of 1.20 during the down raises slightly again during early hours of the evening peak and the remaining quantity of water night as people use more water when they return is delivered through the enhanced flow during lean home. However, this peak did not grow as expected hours. A survey conducted in most part of the and as it should have been, otherwise. This fact distribution area revealed a large number of implies that the evening demand is not adequately household storage tanks and it was reported that met up to the level of morning demand by some of the low pressure areas receive water only Maharagama WSS and the supply is prematurely in the night time. curtailed. Then the consumption gradually drops to a minimum towards the midnight and early hours of the next day (Fig. 4). It is further observed that the peak is less even when the water level is highin the balancing tank, implying that the mid-day peak is not that significant for Maharagama WSS. The hourly flow oscillates within almost similar minimum levels (MNF) and maximum levels (HPF).
Figure 5 Diurnal Problem Curve The existing systems operating at very low HPF and Daily Peak Factor (DPF) values should be augmented to improve the supply (De Silva, 2011). Under such augmentation, the availability of water at the service reservoirs should be increased and the pump capacity should also be upgraded as Figure 4 Diurnal Flow Variation required. The capacities of the service reservoirs Diurnal problem curve derived from the field should also be increased if necessary, to allow for survey data indicates that there is a significant the increased rates of withdrawals during peak problem level, which is more than 40%, during the hours. The distribution system should be reinforced day (Fig.5). It is noted that a good service level with to convey the increased demand to the consumers lesser number of issues reported prevails only living in all parts of the service area without any during early hours of the day. When the demand inconvenience. Level of service shows significantly increases, the reported problem level also increases.
68 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 low indices in high-elevated areas above 20 m MSL Comparatively, Maharagama consumption pattern for the Mahragama area. From the identified has a two-peak variation and Colombo problem areas of Maharagama, except one area consumption pattern follows three-peak variation. (528), the elevation has a significant effect on service Morning peak occurs at the same time at 07.00 for level. Distance also indicates to have an effect but both Colombo and Maharagama whereas evening threshold value could not be identified. When the peak shifted one hour early at 18.00 for combined effect of elevation and distance are Maharagama WSS. considered, a threshold value of 44 can be identified There is a considerable level of problems on water for deteriorated level of service (Fig 6). There are supply service during the day, specially during the three outliers from this threshold from the peak hours, for Maharagama Area. identified seven problem areas. Those three outliers This type of study is very important prior to system indicates higher pipe diameter than others and pipe upgrade or augmentation in order to plan better diameter can also be a governing parameter results. determining the level of service for those areas. For This study should continue to cover the the present study, however only three parameters comparatively old systems in Colombo and contributing towards the level of service were outstations. namely Pipe diameter, Distance and Elevation Such studies are helpful and essential to understand considered. There can be similar other combined the behavior of the systems and to check the effects of these three and perhaps other parameters effectiveness of the design. This also helps to plan affecting the level of service and these should be the augmentation work and to develop design further studied. guidelines for the forthcoming schemes of similar Low level of service areas show less per connection nature. consumption than in other areas. and the fact Focus should be made to zoning of the distribution implies restrained supply to those areas while the system based on critical parameters identified on data from the last 6 years shows a greater decrease level of service and threshold values of technical in level of service than that observed during the first parameters such as HPF, MNF and Tank water 6 years, presumably due to higher demand and level. This will help to improve performance of the high connection density. scheme as well as the operations.
7. Acknowledgments
The authors are grateful to the UNESCO Madanjeet Singh Center for South Asia Water Management for giving the opportunity. Also acknowledge the Survey Department and National Water Supply and Drainage Board of Sri Lanka for providing the necessary data to carry out the study.
8. References Figure 6 Combined effects of Distance and Elevation on level ć of service Abunada, M., Trifunovi , N., Kennedy, M., & Babel, M. (2014). Optimization and Reliability Assessment 6. Conclusions and Recommendations of Water Distribution Networks Incorporating Demand Balancing Tanks. Procedia Engineering, 70, System Water Balance study for service reservoir 4–13. and sample consumer survey alone is capable https://doi.org/10.1016/j.proeng.2014.02.002 enough to identify major deficiencies in the water Candelieri, A., & Archetti, F. (2014). Identifying distribution network. Typical Urban Water Demand Patterns for a Elevation, distance and pipe diameter have a Reliable Short-Term Forecasting – The Icewater considerable effect on determining Level of service Project Approach. Procedia Engineering, 89, 1004 – in a water supply scheme. 1012. Service level has a significant effect on consumption De Silva, W. J. (2011). Study of flow variations in quantity and it is more significant in last six years. Greater Colombo water supply scheme. Retrieved There is no monthly consumption variation can be from http://dl.lib.mrt.ac.lk/handle/123/1017 observed in Maharagama Water Supply Scheme as Domene, E., & Saurí, D. (2006). Urbanisation and whole and for domestic and commercial categories Water Consumption: Influencing Factors in the separately as well. Metropolitan Region of Barcelona. Urban Studies, The diurnal flow curve observed is actually not 43(9), 1605–1623. representing the real demand of the Maharagama https://doi.org/10.1080/00420980600749969 area. It can be interpreted as a present consumption Jansen, A., & Schulz, C. (2006). Water Demand and pattern. the Urban Poor: A Study of the Factors Influencing Water Consumption Among Housholds in Cape
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Town, South Africa. South African Journal of Economics, 74(3), 593–609. https://doi.org/10.1111/j.1813-6982.2006.00084.x Rajapakshe, P. S. K., & Gunaratne, L. H. P. (2005). Comparison of Residential Water Demand among Rural Semi-Urban and Urban Sectors in the Central Province of Sri Lanka. Tropical Agricultural Research, 17.
70 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
A Quantitative Analysis of Surface water in the Uruboku Oya basin Demonstrating the Application Potential of IWRM Principles to Complex Irrigation Systems
P.M. Jayadeera and N.T.S. Wijesekera
ABSTRACT Utilizing IWRM principals to manage water resources is often limited to policy and institutional options which are qualitative in nature (Mehta et al., 2016). Though application friendly modelling examples which satisfactorily incorporate both water quantity and thresholds of quality are essential for watershed managers to ensure educated participatory management the lack of detailed case studies has been noted as a gap that needs to be filled. Muruthawela irrigation scheme of Uruboku Oya basin in Hambantota district of Sri Lanka having a medium scale reservoir of 47.8 MCM capacity, a source area of 4400 ha, and a command area of 1710 ha was taken as a case study. Irrigation, water supply & sanitation, hydro power, inland fishery and environment are the competing water use sectors associated with the system. This system which frequently experiences water conflict situations has limited data to evaluate sectoral water uses. A water balance model for this system was developed to assess multiple water uses by incorporating both water quantity and quality. A situation analysis was carried out with available measurements, guidelines and rational approximations using field observations. This study with an order of magnitude water balance study demonstrated the capability to evaluate the present water conflict scenario and then propose a solution to manage the water quantity and water quality of the system to satisfy all stakeholders. The study concluded that the alternative of IWRM can increase the cropping intensity of Muruthewela scheme by 35% (up to 100%) in maha with introduction of cowpea and allocation of 55.6 MCM for total Irrigation demand while allocating 0.9 MCM annually for water supply and sanitation sector. Pollution status in downstream of Muruthewela tank were evaluated at three locations, Node A –Udukiriwila, Node B-Wakamulla & Node C-Andupelena in order to identify the most vulnerable section for pollution due to agricultural & domestic return flows. The threshold value of dilution was taken as 8 as recommended by Central Environmental Authority (Central Environmental Authority, 1980). The study found that Node C-Andepelena is the most vulnerable section for pollution and the priority area which needs attention by all stakeholders. Pollution level at Node B-Wakamulla can be managed to a certain extent by releasing an environmental flow of 2.4 MCM (4.3% of Irrigation demand) annually
KEYWORDS: IWRM, Complex Irrigation Systems, Uruboku Oya
model based on first principles that enables order of 1. Introduction magnitude evaluations would enable river basin managers to carryout sub basin level evaluations Water is an essential commodity for both human leading to easy consensus building and environmental sustainability and demonstrates Hence a water balance modelling task was a non-uniform distribution. Spatial and temporal undertaken to evaluate the Muruthawela Irrigation irregularity of rain, varying watershed system in the southern Sri Lanka where many water characteristics determining runoff and storage, the use sectors compete with each other. Since IWRM changes observed in the climate, and the uneven is to maximize of social and economic well being nature of sectoral water demands creates the need without affecting the essential ecosystem while for sustainable water resources management. utilizing water resources under equitable Determining sectoral water policies to overcome conditions, it is expected that this model would water crisis situations requires consensus among contribute towards educated IWRM through various water users. Integrated Water Resources rational thresholds and allocations. Management which is commonly known as IWRM has been recognized as the way to achieve this uphill task (Karthe et al., 2015). Application of the concepts has been questioned and evaluated many including Biswas (2004), Jacobs et al. (2016). It could P.M. Jayadeera, C.Eng., MIE(SL),B.Sc.Eng. (Moratuwa), M.Eng., Chief Engineer, Irrigation Department, Sri Lanka. be recognized that the missing building block for the fulfillment of IWRM is a rational water balance N.T.S. Wijesekera, B.Sc. Eng. Hons (Sri Lanka), PG. Dip model which can operate in a data scarce situation (Moratuwa), M. Eng. (Tokyo), Ph. D(Tokyo), C.Eng., MICE(UK), FIE(SL), Senior Professor, Department of Civil while incorporating both water quantity and Engineering, University of Moratuwa, Sri Lanka. quality concerns. A simple easy to understand
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 71 UMCSAWM Water Conference – 2017
2. Study area diagram of the system and the sub watersheds indicating the flow of water within the system is in Muruthawela reservoir and irrigation scheme in the Figure 3-1. Urruboku Oya basin in Hambantota district of Sri Lanka constructed in 1970’s has a storage capacity of 47.8 MCM, a source area of 4400 ha, and a command area of 1710 ha (Figure 2-1). Command area consists of 1710 ha of Muruthewela new lands in Tract I(T-1), Tract II(T-2) & Tract III(T-3) under the Left Bank Main Canal(LBMC); 324 ha of lands under Right Bank Main Canal(RBMC), 2430 ha of existing lands in Uruboku oya scheme. Lands in Tract I area cultivated in both yala and Maha seasons. Full extent of Tracts II & III are not cultivated in both seasons. In both seasons, due to riparian rights, Urubokka Oya Scheme receives priority when releasing irrigation water from the reservoir. In addition, the RBMC receives a 3 discharge of 0.7 m /s for a period of 10 days for both Figure 0-1 Schematic diagram of the system July and August to fulfill the water shortage under cascade tank system in RBMC. The National Water The entire system was considered as three sub Supply & Drainage Board (NWS&DB) extracts 2500 systems namely, Sub System 1: Upper Catchment; m3/day from the reservoir to fulfill the drinking & Sub System 2: Reservoir; Sub System 3: domestic requirements in the Weeraketiya and Downstream system. A stakeholder questionnaire Walasmulla urban areas. Though areas away from survey within the system which was conducted to the reservoir system receives pipe borne water, the identify the priority problems in the project area Muruthewela new lands, T-1, T-2 and T-3 area revealed that the burning issue was inadequate within the system are yet to be served. There are water availability for cultivations. Accordingly, the approximately 2200 farmer families in study targeted to investigate the alternatives to Muruthewela, T-1, T-2, and T-3 whose main increase the cropping intensity while satisfactorily livelihood is from irrigated agriculture. These providing water for other water users. Reservoir families are facing many hardships due to operation data were available with the Department inadequate irrigation water. There are consistent of Irrigation. The study area was in the IL2 agro- conflicts between the farmers of the Muruthawela ecological region. Evaporation data were obtained Scheme and Urubokka Oya Scheme over irrigation from the closest station which was at Ridiyagama. water releases while there is another conflict A monthly water balance model for a water year between Muruthawela farmers and the NWSDB encompassing all three systems was developed because of the water extractions for the domestic using the planning guideline of the irrigation pipe networks. department (Department of Irrigation,1984). The rainfall, water demands and practices of an average year were incorporated to the water balance study to calibrate the model and to evaluate the present situation. Afterwards, the guideline recommended, 75% probable rainfall was used as the input to evaluate the water requirements at critical points within the watershed. In order to overcome the data scarce situation, order of magnitude computations were carried out using the guideline recommendations to fill the gaps in observations. Steps incorporated in the water balance computations for each system and the associated equations are described below.
3.2. System 1- Upper Catchment Figure 2 1 Location Map of the project area System 1 consisted of a model that receives rainfall and generates direct runoff based on a runoff 3. Methodology coefficient, enhances soil moisture and then facilitates evaporation depending on the 3.1. Situation Analysis availability of soil moisture. The equations used to The watershed of the reservoir and the command evaluate monthly water balance was, area were mapped (Figure 2-1). A schematic
72 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
[QRF -(Q SRO+Q Deep+ Q ET)] = QGWSM(t) – Q GWSM(t-1) Q ET = Evaporation loss = 0 ------(1) Q Seep = Seepage loss Where, QRF = Rainfall Volume QSRO = Surface After the MHP, the environmental flow is assumed Runoff; QDeep= Deep percolation; Q ET as 90 % probability of exceedance from the flow =Evapotranspiration; QSM=Soil Moisture; Q duration curve and it was assumed that the MHP GWSM=Ground Water Soil Moisture loss is 5%. Coefficients used when developing the water balance model for system 1, are shown in Table 3-1. 3.3. System 2 – Reservoir water balance
Reservoir water balance was computed using the Table 3 1 Coefficients and Factors used equation (2), Name of Coefficient / Factor Value Q In+ Q Initial – Q Evapo – Q seep – Q ID – Q domes = Change Soil moisture coefficient 0.607 in storage ------(2) Initial GW soil moisture content 3.0 MCM Where, Surface Runoff Coefficient 0.383 Q In = Inflows to the tank Deep percolation coefficient 0.01 Q Initial = Initial tank storage Pan evaporation coefficient 0.51 Q Evapo =Evaporation ; Q seep = Seepage loss Runoff coefficient for the watershed was initially Q ID = Irrigation Demand computed using the land cover and other physical Q domes = Domestic Demand parameters (Chow 1988). A spreadsheet model was developed to compute monthly runoff over the 3.4. System 3- Downstream Area selected year. The pattern of watershed streamflow Water balance of the downstream area requires the observed during field visits, annual water balance, consideration of irrigation water to Muruthawela watershed runoff coefficient were observed and RB, LB, Old lands under Uruboku Oya. In each area fine-tuned to obtain the most plausible direct runoff water requirement was taken on the purpose of in the stream. water use. The water balance equation for the Muruthewela reservoir data was obtained from system 3 is shown in the equation (3). Irrigation Department. 75% probability rainfall data QLB+QRB+QU’oya+ Q Heen -QDeep- QET- corresponding to IL2 agro ecological region and N1*Qpest(return) -N2*QDomes(return) =0 ------(3) evaporation data of Ridiyagama were used in the Where, study (Department of Irrigation, 1984). Watershed water balance components are in Figure 3-2. QLB = Issues for Muruthewela LB QRB = Issues for Muruthewela RB QU’oya = Issues for Uruboku oya Q Heen =Inflow from Heen Ara QDeep = Deep percolation QET = Evapotranspiration N1 = Dilution factor for pesticides return flow N2 = Dilution factor for domestic return flow Qpest(return) = Return flow contaminated with pesticides and weedicides QDomes(return) =contaminated domestic return flow Return flow from the irrigable area taken as 30% as per Irrigation Department practice is contaminated with pesticides and weedicides. Crop factors, Crop water requirements, Staggers etc., were determined using ID guidelines and discussions with field officers. Environmental flow is the water quantity that should prevail in the downstream of the reservoir to water quality and environmental sustainability. The downstream area is cultivated with Cowpea and Paddy. There are several types of water issues, Figure 3 2 Water Balance components in the system namely, QLB, QRB, QU’oya as in the equation. Water The notations in Figure 3-2 are described below. demand from the reservoir was initially computed QIn = Inflow to the tank using the known water uses and then developing a QHeen = Inflow from Heen Ara spreadsheet model reflecting the temporal variation Q ID(LB) = Irrigation Demand for M’wela LB of water demands by each downstream water Q ID(RB) = Irrigation Demand for M’wela RB release. There is a direct water demand from the Q = Water issues for Uruboku oya U’Oya reservoir for the NWSDB distribution. Q = Water issues for Environmental flow E Flow The past data facilitated the determination of Q Domes Demand = Domestic Demand temporal variation of water releases during a
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 73 UMCSAWM Water Conference – 2017 typical year. The parameter suitability, order of magnitude of inputs and outputs were fine-tuned by considering the spillage and reservoir water level fluctuations. Reservoir water balance results for the year 2014/2015 are shown in the Figure 3-3.
Table 3 5 Sub Components and Nodes At each node, water balance computations evaluated unpolluted water and polluted water. Initially the total fresh/unpristene water quantity Figure 3 3 Water Balance results with actual Rainfall for was estimated, then the polluted inflows from Present situation domestic and agriculture were identified by The individual assessments were combined to assigning pollution levels. Then the balance of the establish the water quantity balance in the project water at each node (Figure 3-6) was computed to area. This enabled the assessment of present evaluate the state of water at each identified node. situation with an order of magnitude perspective. Unpolluted water was the water which was Parameter values, evaluation of inputs and outputs polluted to a level below the threshold dilution were holistically evaluated to determine the permitted by the authorities and for this the CEA behavior of surface water under a data scarce guide (Central Environmental Autority, 1980) was situation for watershed evaluation in a distributed used. Following Irrigation Department practice, manner. Subsequent to the establishment of the return flow from the irrigable area contaminated present set up, the 75% probable rainfall was taken with pesticides and weedicides was taken as 30%. as the input to determine whether the system The return flow from domestic water was taken as performance is satisfactory as per planning 15% and taken as polluted to a level exceeding the guidelines. Corresponding system outputs are threshold value of 8. As an example, the water shown in Figure 3-4. quantity and quality at node A & B are shown in Figure 3-7 & 3-8.
Figure 3 6 Water Balance at Nodes
Figure 3 4 Water balance outputs for 75% Probable Rainfall
3.5. Water Quantity and Quality In case of water quality incorporation, 03 sub components and 03 nodes (Node A-Udukiriwila, Node B -Wakamulla & Node C-Andupelena) in the downstream area were used (Figure 3-5).
74 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Jan 1.2 0.1 0.0 2.6 0.15 Feb 5.0 0.1 0.0 0.9 Mar 1.3 0.1 1.1 0.6 Apr 2.3 0.1 1.3 0.9 May 9.9 0.1 0.0 0.2 Jun 10.7 0.1 0.0 0.0 Jul 11.2 0.1 0.0 0.1 Aug 5.1 0.1 0.0 0.1 Sep 0.0 0.1 0.0 0.5 Oct 3.3 0.1 0.0 1.3 Nov 2.3 0.1 0.0 2.1 Dec 1.1 0.1 0.0 2.8 Total 55.6 0.9 2.4 11.9 0.15 Final water allocation for each sector is shown in Figure 4-1. It is proposed to release an Table 3 7 Polluted & Unpolluted flows at Node A environmental flow of 1.1 MCM & 1.3 MCM in March & April respectively (2.4 MCM annually) from the tank in order to minimize the level of pollution at Node B. The tank spills only in January and lowest storage is 6.15 MCM in August
Table 3 8 Polluted & Unpolluted flows at Node B
3.6. Water Management Options The situation analysis with the planning guidelines confirmed that there is a water quantity problem if the present demand level of water users is maintained. The main reason is that at the present Figure 0-2 Final water allocation level there is a water quantity deficit with a polluted 4.2. Proposed Cropping Pattern status in the system. If water demands for irrigation can be managed at a low level with low water The cropping intensity will be increased in Maha by requiring crops, then farmers may be able to 35% (up to 100%) and that of Yala will remain same increase cropping intensity while balancing sectoral at 59% with introduction of low water consumption water requirements. The water allocation was crop like cowpea in Muruthewela Tr.I, Tr.II & Tr. III carried out while looking at the water quality areas while allocating water for other sectors. concerns at critical nodes. The cropping pattern and Proposed cropping pattern in Muruthewela area is the final water allocation details are shown in the shown in Figure 4-2. Figure 4-1 & 4-2.
4. Results
4.1. Multi sector water Allocation Annual water balance which was carried out using 75% probability rainfall values recognized the following multi sector water demands as shown in the Table 4-1.
Table 4 1 Multi Sector water Demands Figure 4 2 Proposed cropping pattern Water Demands in MCM Irrigatio Water Enviro Hydro Spillag 4.3. Pollution status in downstream area n Supply nment Power e Month & Pollution level of Uruboku oya flow at Node A Sanitati (Udukiriwila) is satisfactory which is below the on threshold value of 8 recommended by Central Environmental Authority (Figure 3-7). But, at Node
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B (Wakamulla), pollution levels in March, April, moisture content where as in reality, a fraction of May & June are higher than the threshold value. An the surface runoff and ground water soil moisture environmental flow of 1.1 MCM & 1.3 MCM are also contribute to the total evaporation in the area. released in March and April (2.4 MCM per year) to But, when ground water soil moisture is concerned, minimize the pollution level at Node B. But in the it is very unlikely to evaporate from that component months of May & June, still the status of water or it can be neglected. When surface runoff is pollution is higher than the allowable threshold considered, there is a possibility to evaporate from value of 8 (Figure 3-8). this component. But, surface runoff may not be Node C (Andupelena) is the most vulnerable there throughout the year. So, it is reasonable to section in the river for pollution. Pollution status at assume that the evaporation takes place from the Node C is shown in Figure 4-3 top most part of soil moisture. The model was developed using the initial values of soil moisture coefficient, deep percolation coefficient, pan coefficient etc. these parameters needs to be verified. 75% probable rainfall, reference crop evapotranspiration and monthly evaporation of Ridiyagama were used as the main inputs in the annual water balance study (Department of Irrigation, 1984). But, due to the consequences of climate change, change in land use and runoff coefficients, further refinement of these values are necessary Water balance model verification was done using Figure 4 3 Pollution status at Node C the monthly average rainfall of year 2014/2015 with the existing condition. 4.4. Catchment Parameters 5.2. Water Quality i). During the annual water balance, some catchment parameters were adjusted. Initial To get the exact figures of pollution, it is necessary soil moisture content was adjusted to 3.0 MCM to do water quality measurements. But, this is an and soil moisture coefficient was 0.607. Other order of magnitude evaluation of water quality and adjusted parameters were, runoff coefficient as quantity in a watershed. This will help water 0.383, deep percolation coefficient as 0.01 and planners in watershed planning in terms of crop pan evaporation coefficient as 0.51. management, pollution control etc. in a data scarce ii). A seepage loss of 5% was unadjusted and situation. Normally in seasonal planning, only accepted parameter values. water quantity is concerned at present. But, this iii). Irrigation return flow of 30% from irrigation study discusses the pollution aspect too especially demand & domestic return flow of 15% were identify the most troubled areas, introduces unadjusted which are still questionable environmental flows in order to maintain the water parameters that require further studies. quality below the threshold limit etc. Still there is no such literature attempting a planning level water 5. Discussion quantity and water quality estimation so far. This is a very simple method. Once the most vulnerable 5.1. The System Water Balance area for pollution is identified, detailed and continuous data collection program can be done to In order to carry out a system water balance for a improve this order of magnitude study. This is an data scarce scheme like Muruthewela, an order of advantage of this study. magnitude evaluations were done. With the absence of streamflow data in Uruboku Oya 5.3. Critical parameters and sub watersheds upstream of Muruthewela tank, it was necessary to find the runoff coefficient to calculate the inflow. In system 1 water balance, runoff coefficient is the Initial value for runoff coefficient was assumed and most critical parameter which depends on the it was verified using Iso- yield curves (Department various catchment characteristics such as land use of Irrigation, 1984) and at the field by field type, soil type etc. The inflows to the tank depends observations. on the runoff coefficient. The model was developed based on various In system 2, pan evaporation coefficient is the assumptions as we don’t know exactly how the critical parameter. catchment area behaves when rainfall comes and In system 3, level of pollution in the agricultural and how each component contributes to the catchment. domestic return flows is the most important factor The main assumption made in this study is that the in the water balance. In this study, it is assumed that evaporation takes place only from the top most soil the level of pollution in these return flows is greater
76 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 than the threshold value of 8 by considering it as identified as the safest section with respect to polluted water. pollution due to agricultural and domestic After carrying out water balance study for three sub return flows. Pollution level at Node B components (three Nodes) separately in the (Wakamulla) can be minimized by releasing an downstream area, the most critical Nodes could be environmental flow of 2.4 MCM annually (0.11 identified. By evaluating polluted water from MCM & 0.13 MCM for March & April return flows and unpolluted water in the river and respectively) so that a healthy riverine by allocating a quantity of water that needs to dilute ecosystem downstream of the reservoir upto the contaminated return flow to the threshold value Node B is ensured. Node C (Andupelena) was of 8, the state of pollution at each Node was identified as the most vulnerable section for identified. At Node B, water balance in March, pollution. To overcome this problem, a water April, May & June months are negative values manager has either to release sufficient which indicates that there is no water available in environmental flow while forgoing the the river to dilute the polluted water as cultivation or to organize awareness programs recommended. By releasing an environmental flow for farmers and take action to minimize the of 1.1 MCM & 1.3 MCM in March and April months usage of pesticides and weedicides. If the respectively from the tank, this pollution status can threshold value of 8 for dilution (Central be minimized and then the pollution will exist only Environmental Authority, 1980) is revised to a in May and June. At Node C, except in September further low value in future, one of the above and December, pollution will exist in all other two options has to be followed. months. Hence, sub component C (Node C- Andupelena) is the most vulnerable section for pollution. After this study, priority order of sub 7. References components / Nodes that need attention by Biswas, Asit K. "Integrated water resources stakeholders can be identified. management: a reassessment: a water forum 6. Conclusions contribution." Water international 29.2 (2004): 248- 256. 1) Cropping intensity of Muruthewela scheme can Chow, V.T., Maidment, D.R., & Mays, L.W. (1988). be increased by 35% (up to 100%) in Maha with Applied Hydrology. McGraw- Hill, New York. introduction of other field crop (cowpea) and in Department of Irrigation, Sri Lanka (1984 , May). Yala, it will remain same as 59%. Cropping Design of Irrigation Headworks for small catchments intensity of Uruboku oya can be maintained at (2nd Edition, revised) 200% which is the existing condition. Annual Jacobs, Katharine, et al. "Linking knowledge with water allocation for irrigation sector is 55.59 action in the pursuit of sustainable water-resources MCM management." Proceedings of the National Academy of 2) Existing annual water allocation of 0.9 MCM Sciences 113.17 (2016): 4591-4596. can be maintained for water supply & Mehta L., Movik S., Bolding A., Derman B. & sanitation sector. Manzungu E. (2016). Introduction to special issue – 3) River water use and healthy ecosystem Flows and Practices : The politics of Integrated downstream of mini hydro power weir can be Water Resources Management (IWRM) in Southern ensured by releasing a monthly environmental Africa. Water Alternatives 9(3), pp. 389-411 flow of 0.05 MCM from the weir Karthe et al. (2015), Science-Based IWRM 4) Environmental sustainability of the reservoir Implementation in a Data-Scarce Central Asian area and inland fishing activity can be Region: Experiences from a Research and enhanced by keeping the reservoir capacity Development Project in the Kharaa River Basin, more than the capacity at minimum operating Mongolia. Water 2015(7), pp.3486-3514 level. 5) The following catchment parameters were adjusted - Initial soil moisture content – 3.0 MCM - Soil moisture coefficient - 0.607 - Runoff coefficient - 0.383 - Deep percolation coefficient - 0.01 - Pan evaporation coefficient - 0.51 6) Irrigation return flow of 30% from the irrigation demand & domestic return flow of 15% were unadjusted which are still questionable parameters that require further studies 7) Sub component A, Node A (Udukiriwila) section downstream of the reservoir was
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78 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Increasing the Cropping Intensity by Changing the Cropping Pattern in a Minor Tank
R.M.M.R Alawatugoda and N.T.S. Wijesekera
ABSTRACT Water scarcity is the main course for the poor cropping intensities and crop failures in most of the minor tanks located in dry zone. This situation can be addressed in several ways. This study focused on changing the cropping pattern to increase the cropping intensity because this method can be implemented immediately. A minor tank located in Anuradhapura district was selected for the study. Water resources in the catchment was analyzed using the method described in the irrigation department guide line. As the catchment is ungauged 75% probable rainfall of the zone in which the tank belongs was used in analyzing the water availability. Combinations of crop types were considered and paddy and soya bean were selected as the type of crops. Water requirement for both crops were calculated and a water balance study was done for three scenarios. An income comparison between three scenarios were done to find the most beneficial scenario out of the three. As the study was based on the parameters given in the irrigation guideline, present situation was analyzed for the variation of parameters within a range of 25%.
KEYWORDS: Cropping intensity, Irrigation and crop yield options
1. Introduction Therefore, the objective of this study was to demonstrate the potential of systematic analysis Sri Lanka has a proud history of irrigation and critical evaluation of irrigation and irrigation development with a hydraulic civilization dating water management to evaluate solutions for better back to over 2000 years. Primary purpose of food and water security in Sri Lanka. irrigation development in Sri Lanka is for paddy cultivation as rice is the nation’s staple food and 2. Project Area and Data farmers treat paddy as their life blood. In Sri Lanka there are over 30,000 small irrigation reservoirs (Data Base – Department of Agrarian Services). Tank is categorized as a minor tank when its command area is less than 200 acres (ID 1984). Inflow of a minor tank is usually by the surface runoff from its own catchment and therefore depends on the rainfall and the characteristics of the catchment. In Sri Lanka there are two growing seasons namely North East Monsoon (NEM) called the Maha Season and the South West Monsoon (SWM) called the Yala season. The dry zone experiences a low rainfall volume com-pared to the other areas of the country especially in the Yala season. Due to the variation of rainfall pat-tern and the low storage capacities in Figure 2.1 Location map of the project area minor tanks, farmers are unable to cultivate their full extent of lands under minor irrigation schemes A minor tank named Pahala Diulwewa, located in mainly in the Yala season thus leading to low Anuradhapura district and within Yan Oya river cropping intensities. The ratio of effective crop area basin was selected for the case study. (207758mE, harvested during a given water year to the physical 386620mN). Tank has a catchment area of 5.12km2 area is known as the cropping intensity. One option to ensure a higher cropping intensity is to grow low R.M.M.R Alawatugoda, C.Eng, MIE (Sri Lanka), B.Sc. water consuming crops that enables a harvest with Eng (Peredeniya), PG Dip (Moratuwa), Director of a higher monetary value. However, case studies Irrigation, Department of Irrigation, Sri Lanka with systematic application of engineering concepts N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip are not available for practicing engineers to perform (Moratuwa), M.Eng. (Tokyo), Ph.D (Tokyo), C.Eng., better by confirming or modifying the prevailing MICE(UK), FIE(SL), Senior Professor, Department of Civil Irrigation Department Guidelines. Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 79 UMCSAWM Water Conference – 2017 and command area of 73Ha. Capacity at full supply other field crops. . In the absence of project specific level is 83 Ha.m. Location map of the project area is values, an application efficiency of 60% and a in Figure 2.1. conveyance efficiency of 70% were used. 1:50,000 Topographic map of the survey Paddy is selected as the main crop. Department of department enabled the preparation of maps. agriculture was consulted and based on the Irrigation Department Guideline (ID 1984) was the statistics on demand, marketing trend etc., source for 75% probable rainfall, reference crop recommendation for the other crop was Soya bean evapotranspiration, crop factors & growth stages, and Chilies. Out of the two. Soya bean was selected the Area Capacity curve of the tank was from the considering the post-harvest facilities such as irrigation department regional office at marketing assistance and the pre cultivation Anuradhapura. Data used in the study are in Table support such as seeds. 2.1. Irrigation demand for paddy and soya bean was Table 2.1 General data used calculated based on three stagers. For this analysis, crop water requirement, field water requirement Description Unit Value and irrigation demand were analyzed. Conveyance Catchment area Sq.km 5.12 Command area Ha 73 efficiency was taken as 70%. Table 3.2 presents the Yield - Maha m 0.656 irrigation demand for paddy and soya bean. Yield - Yala m 0.185 Table 3.2 Irrigation demand for paddy and soya bean Minimum m MSL 28 operation level Month paddy/mm Soya Spill level m MSL 30.8 Bean/mm Seepage factor 0.005 October 231.13 106.47 Capacity at FSL Ha.m 83 November 303.87 103.73 Capacily at Ha.m 1.5 December 302.58 164.94 MOL January 358.32 145.19 February 388.18 0.00 March 189.49 0.00 April 0.00 95.75 3. Methodology and Analysis May 305.50 290.63 June 515.78 383.38 3.1. Water Resources Availability July 534.89 313.02 Guideline ID (1984) procedure recommended for August 496.08 0.00 September 199.29 0.00 un-gauged catchments was used in this analysis. Inflow to the tank was considered as the surface 3.3. Water Balance runoff from the catchment. Since this tank is located in the agro ecological region DL1, 75% probability Available water resources to meet the demand for rainfall data corresponding to the above region was cultivation of crops was studied using the water used. Monthly inflow to the tank was calculated by balance of the reservoir with the use of: inflow, using the specific yield from the seasonal iso yield demand, losses and spillage. Monthly water maps. Monthly inflow obtained are present in the balance equation used is in equation 1. table 3.1. Storage at the beginning of month +Inflow- Table 3.1 Monthly inflow of the catchment Evaporation-Seepage-Demand-Spillage = Storage at the end of month ------(1) Month Inflow/Ha.m The monthly water balance enabled the evaluation October 22.76 November 27.31 of reservoir operation and the adequacy of the avail- December 22.76 able water resources to meet the demand for the January 13.66 cultivation of crops. In this work reservoir February 4.55 operation study was carried out to determine the March 9.10 smallest capacity of the tank that would be required April 22.76 for the cultivation of the irrigable area for a desired May 9.10 cropping pattern and intensity following the ID June 2.28 (1984). July 0.00 August 2.28 The operation study was commenced with the September 4.55 storage at the minimum operating level as the initial storage. This was for a period of one year and at a 3.2. Irrigation Requirement monthly temporal resolution.
Irrigation requirement for paddy and other field 3.4. Comparison of Scenario crops were calculated as stated in the irrigation guide lines. It was assumed that the reference crop Studied scenario were i) present condition: only evapotranspiration at Maha Iluppallama was paddy for both Maha and Yala seasons, ii) Future representative of the study area. A three stagger option I: paddy for Maha and OFC for Yala and iii) water issue method was used for both paddy and future option II, paddy for Maha and both crops for
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Yala season. The largest possible irrigable area for Table 4.3 Income comparison combination of crops was determined through trial Scenario Annual Income/Rs and error operation. Scenario evaluation was (million) carried out with an income comparison. The market Present 8.8 value of crops were taken and income was Future option I 9.4 calculated for the land extents cultivated under each Future option II 9.9 scenario. Cropping pattern which provided a 5. DISCUSSION higher income was selected for implementation. Statistics from Hector Kobbekaduwa agrarian This study focused on changing the cropping research centre were used for this comparison (this pattern to increase the cropping intensity. This analysis is presented in table 3.3). method does not include any time taking activities Table 3.3 Statistics used in income comparison such as physical changes, rehabilitation to the existing tank or conveyance system, and need not Description Unit Value Yield/paddy Bushels/acre 90 any extra financial support. Therefore, this proposal Yield/soya bean Kg/acre 445 can be implemented immediately. Farm gate Rs/kg 30 Based on the income comparison, future option II is price/paddy giving more income. Therefore, the cropping Farm gate Rs/kg 95 pattern in future option II is selected for price/paddy implementation. However, there are other options also to conserve 4. Results water in the system and thereby increase the crop- ping intensity. Raising of tank spillway to increase 4.1. Water Balance the capacity and store more water, improve the The water balance results of the scenario iii is in efficiency of the system to minimize the losses and table 4.1. on farm water management like shallow water Table 4.1 Water Balance results for option iii (all values are in depth method and wet & dry method are some of Ha.m) the other methods that can be implemented to increase the crop-ping intensity. However, those are Mont Inflo Losse Deman Spillag End h w s d e Storag not verified in this study. e Oct 22.76 3.40 14.57 0.00 32.46 5.1. Issues and constraints Nov 27.31 3.06 18.50 0.00 38.21 Dec 22.76 3.47 19.53 0.00 37.98 Most of the data were taken from the irrigation Jan 13.66 3.56 22.23 0.00 25.84 department guide line published in 1984. The Feb 4.55 3.38 21.25 0.00 5.76 rainfall was given for a region and evaporation was Mar 9.10 2.21 10.37 0.00 2.28 given based on the data at Mahailluppallama. Apr 22.76 1.11 2.06 0.00 21.87 Catchment yield was taken from the seasonal iso May 9.10 3.58 6.26 0.00 21.12 yield curves given in the guide line. June 2.28 3.69 8.26 0.00 11.44 The analysis was based on the past records of data. July 0.00 2.76 6.75 0.00 1.94 Aug 2.28 1.23 0.00 0.00 2.99 But it was checked against the actual long term rain- Sep 4.55 1.51 0.00 0.00 6.03 fall of Mahailuppallama. Therefore, the option I (paddy only) was analyzed 4.2. Cropping Pattern if those data change within a range of 25%. Parameters considered were, rainfall, losses and The cropping pattern comparison obtained from the demand. three crop type combinations is in Table 4.2. When the rainfall increases, cultivation area was Table 4.2 Comparison of Cropping patterns (Extents in Ha) also increased. Increase of evaporation and demand Scenario Paddy OFC Total has resulted a decrease in area while the increase of Present 60.1 0.00 60.1 seepage has no significant effect on the area Future 47.9 22.5 70.4 cultivated. option I With the 25% increase of parameters, the area that Future 52.2 21.5 73.3 can be cultivated is in table 5.1. option II
4.3. Income Comparison
Annual income comparison for the three scenario is in Table 4.3.
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7. REFERENCES
Table 5.1 Cropping pattern with 25% increase of parameters Ponrajah A.J.P. Design of irrigation head works for (extents in Ha) small catchments (1984) Parameter Maha Yala Total Rainfall 60.1 17.0 77.0 Evaporation 45.2 10.4 55.6 Seepage 47.9 12.2 60.1 Demand 39.1 9.4 48.5
The option i is analyzed for the 25% decrease of parameters too. When rainfall decreases, the cultivation area also decreases and for the decrease in evaporation and demand the cultivable area increased. In addition, the decrease of seepage has no significant change in cropping pattern.
With the 25% decrease of parameters, the area that can be cultivated is in table 5.2.
Table 5.2 Cropping pattern with 25% decrease of parameters (extents in Ha) Parameter Maha Yala Total Rainfall 35.5 8.0 43.0 Evaporation 50.4 13.6 64.0 Seepage 47.9 12.2 60.1 Demand 62.4 16.9 79.3
The percentage variation of the cropping intensity due to the change of parameters also calculated and presented in table 5.3
Table 5.3 Variation of cropping intensity when parameters changed by 25%
Percentage variation in Parameter cultivation area +25% -25% Rainfall +28 -28 Evaporation -7 +6 Seepage 0 0 Demand -35 +32
6. CONCLUSION
Three scenarios were considered in the study including the present situation and it is revealed that the command area of the scheme can be increased by changing the cropping pattern. This study based on the parameters given in the irrigation guideline. Variation of rainfall and demand showed a significant variation of the cropping pattern while losses indicated a less significant variation.
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Computation and Optimization of Snyder’s Synthetic Unit Hydrograph Parameters
G. Thapa and N.T.S. Wijesekera
ABSTRACT In Sri Lanka, the availability of Snyder’s Synthetic Unit Hydrograph (SSUH) parameters are reported only in the Irrigation Department Guidelines and those are limited to only 19 locations. The present study is to determine the SSUH parameters and their applicability to the Karasnagala watershed (52.58 KM2). 60 events corresponding to both North East and South West monsoons during the 1971-1989 period were selected for the model calibration and verification. Considering a balanced representation of both seasons, 30 events were selected for model calibration while the rest were taken for model verification. Events were separated using a minimum inter-event time of 2 days. Effective rainfall corresponding to each event was determined using Phi-Index and incorporating the baseflow separation with the use of Concave method. A one day triangular SUH computed for each event was then converted to curvilinear SUH with the help of SCS dimensionless hydrograph. Mean Ratio of Absolute Error (MRAE) was chosen as the objective function for the evaluation of the total, high, intermediate and low flow estimated by the model. Model verification used the averaged parameter values optimized for each event during model calibration. Averaged calibrated parameters Ct and Cp for Attanagalu Oya Basin at Karasnagala were 3.75 and 0.38 respectively with MRAE value of 0.2. The results obtained were further compared with the recommended ID guideline parameters. The value of Ct and Cp can be applied to the other ungauged areas of the Attanagalu river basin and regions having similar characteristics and consider as the basis for further studies with shorter temporal data resolution.
KEYWORDS: Ungauged, Events, Concave method, Snyder’s Synthetic Unit Hydrograph, Parameters Ct & Cp, Sri Lanka.
Hydrograph, Snyder, and Clark methods were 1. Introduction applied to develop a Synthetic Unit Hydrograph (SUH) and found that the peak flow value obtained Engineers working in new developments often from Snyder’s method was much closer to the need to work with ungauged watersheds. In Sri observed values. Limantara (2009) in a study on Lanka out of 103 river basins, many are not gauged Garang watershed in Indonesia having a catchment and there are only about 40 river gauges maintained area of 73.5 km2 reflected that the Synthetic Unit by the Department of Irrigation. Hence most Hydrograph (SUH) has been a great utility when development planning works require models to planning hydraulic structures in a field with data estimate streamflow at various locations. deficient situation. Calibrated and verified model parameters for Miller et al. (1983) in their studies suggested that the gauged watersheds are at rarity in Sri Lanka. There Snyder’s non-dimensional constants Ct and Cp can are no reviewed publications to confidently use vary in the range of 1.01-4.33and 0.23-0.67 available model parameters of gauged watersheds. respectively. Similarly, Hudlow and Clark (1969) Reviewing approximately 100 Sri Lankan studies on proposed Ct and Cp value can range from 0.4-2.26 water resources and modeling, Wijesekera (2010) and 0.31-1.22 respectively. revealed that there exists only very limited The aim of the present work is to calibrate and hydrological modeling efforts. Hence, there is a gap verify SSUH parameters for Karasnagala when attempting to extrapolate model parameters watershed, evaluate the performance of SSUH from gauged to ungauged watersheds. Present model and to make recommendations on work is an attempt to establish the Snyder’s applications. Synthetic Unit Hydrograph (SSUH) parameters for the Karasnagala watershed (Figure 1) with the aim of facilitating reliable parameters for the use in similar ungauged locations. SSUH was selected for G. Thapa, M.. Eng., Project Manager National Adaptation many reasons. SSUH is a method commonly Programme of Action (,NAPA-II) Project applied to generate direct runoff hydrographs in Phuentsholing,Bhutan many engineering applications (Mays, 2004). In a N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip study conducted by Salami (2009) on Lower Niger (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., River Basin with catchment area of 906 km2, MICE(UK), FIE(SL), Senior Professor, Department of Civil different methods like SCS Dimensionless Unit Engineering, University of Moratuwa, Sri Lanka.
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2. Study Area and Data verification. Longest duration of events of calibration and verification dataset was 9 and 8 days Karasnagala is a sub-watershed of Attanagalu Oya respectively. Respective event distribution river basin. It is in the Gampaha district, falling corresponding to Maha and Yala seasons were 57% inside of the Western province of Sri Lanka. The and 43% for calibration events while the same were catchment which is approximately 52.58 km2 53% and 47% for verification events. mainly consists of cultivatable land (72.82%) as Baseflow was separated using Concave Method and reported by Perera, (2010). Data of daily temporal as per recommendations in Pettyjohn and Henning resolution from 1971 to 1989 were available for the (1979). Baseflow separation of all 60 events was streamflow gauging station at Karasnagala and for carried out while carefully observing both the the two rain gauging stations at Vincit & normal and semi logarithmic plots of streamflow. A Karasnagala (Figure 1). 1:10,000 Topographic maps spreadsheet model balancing the effective rainfall from the Department of Survey, Sri Lanka were and direct runoff was developed to compute rainfall used for the study. Thiessen averaged annual loss by Phi-index method (Chow et al. 2013). rainfall and observed streamflow of the watershed Another spreadsheet model was developed to amounted to 258 and 190 mm respectively. compute the Synthetic Unit Hydrograph and to Calibrate the regional parameters (Ct and Cp) for each selected events. SRI LANKA Geometric parameters were derived from the Arc- Attanagalu Oya Basin GIS and Empirical equations 1, 2 and 3 were used to compute the, Basin lag (tp), standard duration (tr) for the watershed and Peak discharge (Qp) of the standard SUH tp 0.75 * Ct * ( Lc * L )^0.3 (1) tp tr (2) 5.5 2.75 * Cp * Q * A Qp (3) tp where, Lc = distance in kilometers from the outlet to a point on the stream nearest the centroid of the watershed area L = length of main stream in kilometers A = area of watershed Q = discharge in m3/s Since the base data were of daily temporal resolution, the SSUH considered 24 hours as the Figure 7: Map of Study area required duration. The triangular UH was then converted to a curvilinear unit hydrograph with the 3. Methodology help of SCS dimensionless hydrograph (Ritzema, 1984) while maintaining the area under the Dunkley (2008) with references to published studies hydrograph as one unit. Effective rainfall and using MIT from 15 minutes to 24 hrs, showed computed by the first spreadsheet model was then that longer MIT values would be useful for the applied to generate Direct Runoff (DRO) identification of independent events because of hydrograph. In this model the regional parameters extensive intra-event gaps. The popular empirical for each calibration event were optimized to fit equation for N days proposed by Linsley et al. observed and computed hydrographs. Objective (1958), was used to compute the Minimum Inter- function selection was guided mainly by WMO event Time (MIT). As suggested by Pettyjohn and (1975), and Wijesekera & Musiake (1990). Mean Henning (1979), the value of “N” computed for the Ratio of Absolute Error (MRAE) was taken as the study area was 2 days. Miller et al. (1983) used primary objective function while Ratio of Absolute samples ranging from 12 to 27 events for model Error to Mean (RAEM) was also applied during calibration and verifications from different optimization and verification to cross verify the catchments. In the present work, a total of 60 events performance level as shown in equation 4 and 5. The were separated and the first 30 were used for model modelling efficiency values pertaining to peak calibration while remaining 30 were taken for discharge, time to peak, base time and streamflow
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volume were also compared during each Figure 2b: Variation of Cp in each calibration event optimization and verification.
Where Qo = Observed discharge Qc = Computed discharge n = Number of events Figure 3a: Variation of MRAE & RAEM in each In case of event based modelling, the calibration calibration event event parameters need averaging to apply for model verifications. Hence the calibrated regional parameter values were averaged to verify the performance of each verification period events with the averaged calibration parameters. This practice is the same as that reported in the studies carried out by Miller et al. (1983).
4. Result
Optimized Ct and Cp obtained from calibration events and sorted for peak discharge of each event Figure 3b: Variation of MRAE & RAEM in each are as shown in Figure 2a and Figure 2b. verification event Averaged value of MRAE and RAEM during verification were 0.20 and 0.21 respectively. Hydrograph matching samples during calibration is shown in Figure 4 while the same corresponding the verification are shown in Figure 5. The events were classified as high, medium and low based on peak flow. The respective simulated peak flow value in calibration and verification ranges were 0.76 m3/s-36.63 m3/s and 0.38m3/s –62.87m3/s. The most frequent values of Ct and Cp for high flow Figure 2a: Variation of Cp in each calibration event were 4.3 and 0.42 respectively. The same for Averaged value of Ct was 3.75 while the same for medium flow were 4 and 0.37, while for low flow Cp was 0.38. Standard deviation of the Ct and Cp events, the range was 3.5 and 0.35. values during calibration were 0.55 and 0.04 All verification events were then subjected to respectively. individual optimization in order evaluate the The MRAE during calibration varied between 0.03 difference between the behavior of parameters with and 0.44 while the same for RAEM varied between each event and with a set of events. And on the 0.03 and 0.56. Model verification results showed calibration events averaged Ct and Cp were applied that averaged Ct and Cp parameters produced a to check the overall performance of the model. larger error compared to individual event The summary of output from model calibration and optimization (Figure 3a & 3b). verification and model estimation is in Table 1. The computed value of average loss rate from a set of 60 events was 1.20mm/hr. (loss rate variation in the calibration events was between 0.18 and 2.86 mm/hr., while the same for verification events were 0.03 and 3.12 mm/hr). The average loss rate during Maha and Yala season was 1.32 mm/hr. and 2.52mm/hr. respectively.
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4a 4b
Figure 4: Hydrographs during calibration with sample from very good matching (4a) and poor matching (4b)
5a 5b
Figure 5: Hydrographs during verification with sample from very good matching (5a) and poor matching (5b)
Table 1: Summary of model performance result
Model Calibration and Verification Model Estimations
Details Calibration Verification with Applying Averaged Ct Optimization of Ct & (30 Events) Averaged Ct & Cp & Cp on Calibration Cp on verification (30 Events) data set (30 Events) data set (30 Events) Averaged MRAE 0.17 0.20 0.21 0.18
Averaged RAEM 0.19 0.21 0.22 0.20
Averaged RAE Qp 0.16 0.17 0.18 0.18 Averaged RAE Tp 0.06 0.10 0.06 0.10 Ct 2.4-6.0 3.75 3.75 2.0-4.0
Cp 0.25-0.44 0.38 0.38 0.3-0.45
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5. Discussion Management (UMCSAWM). The scholarship was awarded by the South Asia Foundation (SAF). In course of analysis, it is confirmed the suitability I sincerely acknowledge Shri Madanjeet Singh for of Snyder’s model to simulate flow discharges in visionary idea and his noble contribution. Attanagalu Oya. A comparison on discharge data I extend my profound and heartfelt gratitude to and modelled output hydrograph graph also Professor N.T.S. Wijesekera for his continuous showed good model performance during model guidance, support, encouragement and valuable calibrations and verifications with a MRAE value advice as a mentor throughout the study. I am of 0.20. Comparison with the values from the thankful to Dr. R.L.H Lalith Rajapakse for rendering Irrigation Guidelines recommended values of Ct his never-ending support. I wish to extend my and Cp for the closest location of the adjacent river gratitude to all the support staffs who have kindly basin approximately 22 km away are 3.76 and 0.55 supported me during the research work. respectively. And the values are pretty close to the I dedicated this work to my late mother for her care result from simulation of SSUH model. and wisdom and to all my family members for their A systematic model calibration and verification unwavering support and guidance. demonstrated a methodology to carryout parameter evaluations from time to time as and 7. References when more data becomes available. The modelling effort showed the need to Chow, V.T., Maidment, D.R & Mays, L.W.,(2013), consider the range of flows to obtain the Applied Hydrology (7th ed). New Delhi, India: Mc appropriate set of parameters. Graw Hill Edu-cation. New York. Hudlow MD, Clark DM. Hydrological synthesis by Modelling showed that even though each digital computers. J Hydrol Div ASCE 1969, 95(3), individual events are calibrated, a 839-60 representative value has to be identified for Limantara,L.,M.,(2009). Evaluation of Roughness verification and for guidelines (unless there is a constant of river in Synthetic Unit Hydrograph. very large set of observations). World Applied Sciences Journal, 7 (9), 1209-1211. The results from the model depends on the loss Linsley, R.K., & Kholer, M.A.(1951). Predicting the rates and baseflow separation, hence it is Runoff from storm rainfall (Report no.34).Weather important to consider the effects of same on the Bureau, U.S Department of Commerce. parameters. Mays, L.W., (2004). Water Resources Engineering. The data resolution was found too coarse as the John Wiley and Sons Inc. most available data are daily, This factor also Miller, A.C., Kerr, S.N., Spaeder, D.J., (1983). should be investigated. Calibration of Snyder Coefficients for Pennsylvania. The average Ct and Cp values of 0.38 and 3.75 American Water Resource Association, Vol.19. respectively showed a very good reproduction MUSIAKE, Katumi, and Sohan WIJESEKERA. "研 of observed event runoff for water 究 速 報 : Stream Flow Modelling of Sri Lankan infrastructure designs. Catchments (1): Mabaweli River Catchment at The averaged parameter values of Ct and Cp Peradeniya." (1990). can be applied to the other ungauged areas of MUSIAKE, Katumi, and Sohan WIJESEKERA. "研 the Attanagalu Oya river basin and other 究 速 報 : Stream Flow Modelling of Sri Lankan regions having similar catchment Catchments (2): Kalu River Catchment at characteristics. Putupaula." (1990). During the studies it has been realised that the Pettyjohn, W.A., & Henning, R. (1979). Preliminary value of Cp is more sensitive than Ct while Estimate of Ground Water Recharge Rates, Related computation of discharges and hydrograph Streamflow and Water Quality in Ohio (Report matching. While the standard deviation shows No.552). Ohio, USA: Ohio State University, that the Cp value merely deviates from the Department of Geology and Mineralogy. mean of Optimised Parameters. Ritzema, H. P. (1994). Drainage Principles and These parameters can be considered as the basis Applications. Wageningen, The Netherlands: for further studies on the region with shorter International Institute for Land Reclamation and temporal data resolution. Improvement. 6. Acknowledgment Salami, A. W., (2009), Evaluation of methods of Strom Hy-drograph Development, International e- This work was completed as a part fulfilment of the Journal of Engineer-ing Mathematics: Theory and Master Degree in Water Resources Engineering Application, Vol.(6), pp.17-28. and Management conducted by the UNESCO Wijesekera, N.T.S. (2010a). Surface Water Madanjeet Singh Center for South Asia Water Resources and Climate Change. National Science
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Foundation Ministry of Irrigation and water resources management, Sri Lanka. WMO. 1974. Guide to Hydrometeorological Practices, 3rd edition. World Meteorological Organization: Geneva. (Helfer, Lemckert & Zang, 2012). Impacts of climate change on temperature and evaporation from a large reservoir in Australia. Journal of Hydrology, 475, 365–378
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Sustainable Solutions for the Drying Up of Groundwater Wells – A Case Study in a Selected Watershed in Dampe, Sri Lanka
A.C. Dahanayake and R.L.H.L. Rajapakse
ABSTRACT Groundwater has now become a limited resource due to the adverse impacts of various natural and anthropogenic causes. Due to the increasing population and rapid urbanization, the demand for groundwater has been ever in- creasing. Consequently, the occurrence of declining groundwater tables and drying up of wells have been reported in different parts of the country. In order to identify adverse impacts and facilitate early decision making, it is necessary to assess and evaluate ungauged small watersheds with simple, easy to apply but quantitative tools. This paper demonstrates the possibility of successfully applying a conceptual, lumped parameter rainfall-runoff model based on water balance approach (The ABCD model) in combination with a basic (Single Basin) HEC-HMS model to identify a comprehensive solution for the drying up of groundwater wells, for Dampe watershed (0.62km2), Sri Lanka. The model was used to carry out a quantitative analysis of groundwater storage and identify the interaction with land use pattern, and it was developed by using gathered and simulated usage and recharge data of the surface and groundwater basins. Several scenarios have been analysed using the ABCD model, in order to identify the ground- water depletion at the present condition, in the future condition (with 50% increase in the impervious area of the catchment) and the proposed solution scenario, which is to increase the pervious area of the catchment. The developed single basin HEC-HMS model has been used in order to determine the peak flow associated with a 10-year re-turn period storm event. Remedial measures to overcome the problem and sustainable methods to preserve water for the future generation are proposed based on the findings of the study. KEYWORDS: Groundwater depletion, ABCD model, scenario analysis, sustainability
1. Introduction 2. Methodology
Groundwater, being the most widely used source of 2.1. Study Area obtaining water in Sri Lanka (Hettiarachchi, 2008), has now become a limited resource due to the Dampe watershed (0.62 km2) located in the adverse impacts of various natural and Kesbewa Divisional Secretariat Division of the anthropogenic causes. Due to the increasing Colombo district, Sri Lanka (Figure 1) was chosen population and rapid urbanization, the demand for as the study area. This ungauged watershed groundwater has been increasing drastically. In consists mainly of residential areas, a few addition, the number of shallow and deep wells industries, open forest areas, paddy fields and a extracting groundwater has increased during the wetland. last few decades (Panabokke & Perea, 2005). In Water for most residential and industrial areas is consequence of unplanned and excessive use of supplied by the National Water Supply and groundwater resources, and due to the absence of Drainage Board (NWSDB) and few use dug wells as means to regulate the usage of groundwater, drying their main source of water. Water for cultivation of up of wells have occurred (Endersbee, 2006). In Sri paddy is extracted from the stream and the excess is Lanka, since most of the groundwater wells were released back. Main water use sectors included constructed neglecting the appropriate technical water supply and sanitation, agriculture, irrigation, norms, drying up of those have been experienced industries and the environment. very often, along with a lowering of the Water related issues were identified by conducting groundwater tables in the respective areas a reconnaissance survey including field interviews (Jayakody, et al., 2006). Since groundwater is a A. C. Dahanayake, B.Sc. Eng. Hons. (Moratuwa), limited resource, sustainable methods of extracting this invaluable resource with proper utilization AMIE (Sri Lanka), Graduate Research Assistant, control and future development plans must be Department of Civil Engineering, University of adopted (International Water Management Moratuwa, Sri Lanka. Institute (IWMI), 2005). R. L. H. L. Rajapakse, BSc Eng (Moratuwa), MSc (Saitama), PhD ( Saitama ), C.Eng., Senior Lecturer (Grade II), Department of Civil Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 89 UMCSAWM Water Conference – 2017 with community stakeholders in the watershed. soil moisture gains water from precipitation and After prioritizing the problems, drying up of loses water to evapotranspiration (ET), surface groundwater wells has come up as the most severe runoff and groundwater recharge. The problem in this watershed that requires urgent groundwater compartment gains water from solutions. This problem has drastically affected the recharge and loses water as discharge. The total quantity of groundwater, not only affecting the streamflow is the sum of surface runoff from the soil social but also the aquatic and terrestrial moisture and groundwater discharge. environment. The entire catchment was divided 2.3.1. Input Data into eight sub basins in accordance with the terrain and distribution of stream paths. (Figure 1). The model runs on a daily time step and requires input time series of precipitation, minimum and maximum air temperature, and observed streamflow. The air temperature data are used to compute potential evapotranspiration (PET) from observed air temperature and latitude, using the method described by Shuttleworth (Shuttleworth, 1993). 2.3.2. Model Parameters The ABCD model has four parameters, a, b, c, and d, each having a specific physical interpretation. The parameter a reflects the propensity of runoff to occur before the soil is fully saturated (Thomas et al., 1983). The parameter b is an upper limit on the Figure 1: Delineation of Sub-catchments sum of actual evapotranspiration and soil moisture storage in a given month. Presumably this 2.2. Water Balance Concept parameter depends on the ability of the catchment Water balance, also known as the water budget, is to hold water within the upper soil horizon. The the application of principle of continuity at any pre- parameter c is equal to the fraction of streamflow determined time interval, to a control volume. The which arises from groundwater discharge in a given dynamic water balance of a river basin can thus be month. Over the long term, c is then defined simply expressed as the difference between the inflow and as the base flow index (BFI), an index used the outflow which is equal to the rate of change of commonly in studies which develop relationships storage, or in other terms, all water stored within between drainage basin characteristics and the basin. groundwater discharge to a stream channel. The reciprocal of the parameter d is equal to the average 2.3. The ABCD Water Balance Model groundwater residence time (Al-Lafta, et al., 2013). The upper and lower limits of a, b, c and d were found to be (Martinez & Gupta, 2010); 0.873 ≤ a ≤ 0.999 133 ≤ b ≤ 922 0 ≤ c ≤ 1 0 ≤ d ≤ 1 2.3.3. Equations Used for the Model Soil Moisture
Wt = St−1+Pt = St+ETt+GRt+DRt ------(1)
푊푡+푏 푊푡+푏 2 푏푊푡 Yt = St+ETt = ( ) − √( ) − ------(2) 2푎 2푎 푎
푃퐸푇푡 −( ) St = Yt푒 푏 ------(3)
푃퐸푇푡 −( ) Figure 2: ABCD Water Balance Model ETt = Yt(1−푒 푏 ) ------(4) The ABCD water balance model is a simple hydrologic model developed by Thomas (Thomas DRt = (1−c)∗(Wt−Yt) ------(5) Jr., 1981) for simulating streamflow in response to precipitation and potential evapotranspiration. GRt = c∗(Wt−Yt) ------(6) The model is comprised of two storage compartments: soil moisture and groundwater. The (Walker, 2014) where;
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Wt =Available Soil Water the major problem in that watershed – the drying Yt =Evapotranspiration Potential up of groundwater wells. The initial soil moisture Pt =Precipitation storage and the initial groundwater storage were St =Soil Moisture assumed to be 50 inches on 01/01/2009. PETt =Potential Evapotranspiration 2.5.3. Future Condition (with 50% increase in ETt =Actual Evapotranspiration Impermeable area) DRt =Direct Runoff GRt =Groundwater Recharge The only parameter corresponding to the change in the runoff coefficient of a particular catchment is Groundwater parameter “a”. For the future condition model, the
Gt+GDt = Gt−1+GRt ------(7) impervious area has been increased by 50%. As a 1 result, the runoff coefficient will change in the Gt = (G + 퐺푅 ) ------(8) 1+푑 푡−1 푡 future condition. It could be assumed that there would be less forest GDt = dGt ------(9) cover and less vegetation on the land. Furthermore, most of the land area would now be covered by an Where; impervious material. As a result, the actual evapotranspiration [ETt] will be less. In addition, Gt =Groundwater Storage the St (soil moisture storage) would be less. GRt =Groundwater Recharge Therefore, according to the equation (2) the GDt =Groundwater Discharge evapotranspiration potential [Yt] would now be less. 2.4. Calibration and Validation of The ABCD Since it is assumed the precipitation values will not Water Balance Model be changed in the future, according to equation (1) Due to the unavailability of measured streamflow the Wt (available soil water) will be less. data in this catchment, a general streamflow data Therefore, according to the expanded equation (2) set was used for calculations. Data from 2011 to 2013 the value of parameter “a” will be increased in the was used for calibration and data from 2009 to 2010 future condition. were used for validation of the spreadsheet version A sensitivity analysis should be carried out to find of the ABCD model. The hydrograph for observed the quantitative relationship between a change of and simulated flows, and the error/optimization the runoff coefficient and the parameter “a”. For the coefficients including Pearson product-moment purpose aforementioned, the model should be run correlation coefficient (R), r-squared value (R2 or for several different catchments which have RSQ), Root Mean Squared Error (RMSE), Mean different (known) runoff coefficients. The models Relative Absolute Error (MRAE), and Nash– should be calibrated and verified using reliable data Sutcliffe model efficiency coefficient (Nash– sets for those respective catchments. Then the Sutcliffe Coef.) were used for calibration and behaviour of parameter “a” in those models with validation procedure. the runoff coefficient of the corresponding The latitude of Dampe watershed (0.1183 radians) catchment could be plotted and the associated was used in the model computations. relationship could be established and used in subsequent modeling. This procedure has not been 2.5. Scenario Analysis Using the ABCD Water carried out in this project, and it has been Balance Model conservatively assumed that 1% increase/decrease in the runoff coefficient results in 10% 2.5.1. Present Condition increase/decrease in the parameter “a”. The calibrated and validated model was used to The area weighted average runoff coefficient for the analyse the present condition of the watershed. The future condition was found to be increased by flow duration curve for the observed and simulated 0.096% and according to that the value of parameter flows in the calibration and the validation period “a” had to be increased by 0.96%. Therefore, in the were drawn, and the 25% and 75% percent future condition model, all the parameters were probability exceedance flow rates (m3/s) were kept the same as in the present condition model, but calculated. the value of “a” had been increased by 0.96%. This increased value for “a” was applied in the 2.5.2. Groundwater Depletion in the Present calibration of the future condition model. Then the Condition other parameter values were adjusted such that the The model with this general data set does not error coefficient values give the best result, based on accurately depict the actual situation in the Dampe the selected objective function. watershed. Therefore, the rainfall data of the nearest The calibrated model parameter values were used rainfall gauge station - Rathmalana, was applied in as the initial values of the validation period. Then the model, and the model parameter (a, b, c and d) the parameter values were adjusted such that, values were changed such that the model illustrates hydrograph for observed and simulated flows, and
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 91 UMCSAWM Water Conference – 2017 the error/optimization coefficients give best results 2.6. A Basic (Single Basin) HEC-HMS Model for for the validation procedure. The flow duration the Dampe Watershed curve for the observed and stimulated flows in the calibration and the validation period were drawn, and the 25% and 75% percent probability exceedance flow rates (m3/s) were calculated.
2.5.4 Groundwater Depletion in the Future Condition
The rainfall data of the nearest rainfall gauge station - Rathmalana, was applied in the model, and the model parameter (only b, c and d) values were changed such that the model illustrates the groundwater depletion. In this (groundwater related) future condition model, all the parameters Figure 3: The HEC-HMS Basin Model were kept the same as in the (groundwater storage related) present condition model, but the value of A single basin HEC-HMS model for the data of the “a” was increased by 0.96% (as found earlier under Dampe watershed was prepared, in order to section 2.5.3). determine the peak flow associated with a 10-year This value for parameter “a” was applied in the return period storm event. For simplification, the calibration of the future condition model used in entire catchment was divided into two sub basins in assessing the possible groundwater depletion. The accordance with the terrain and distribution of initial soil moisture storage and the initial stream paths. Two basin models were created to groundwater storage were assumed to be 30 inches represent current situation of the basin and future on the starting date. situation of the basin with the increase of impermeable area by 50%. (Figure 3). 2.5.5 Solution Scenario (Impermeable area in The SCS CN (Curve Number method of the Soil the present condition is reduced by 50%) Conservation Service, USA) method was used as As a solution to the prevailing problem of the loss method. Curve numbers and imperious groundwater depletion of the catchment, it has been areas were calculated according to the land use of proposed to reduce the impervious area by 50% by the catchment. The SCS unit hydrograph method is using pervious paving materials. It was found that used as the transform method. Lag times (TL) and in the solution scenario, the runoff coefficient will time of concentration (TC) for each sub catchment be decreased by 0.096%, and hence “a” would be were calculated using Irrigation Department decreased by 0.96%. Therefore, in the solution guidelines (Ponrajah, 1984). Since the watershed is scenario model, all the parameters were kept the located in a flat terrain, at any point the average same as in the present condition (groundwater gradient of the stream is taken to be less than 1%. depletion) model, but the value of “a” has been The base flow was not modelled using this HEC- decreased by 0.96%. This reduced value for HMS model due to relatively short model duration. parameter “a” was applied in the solution scenario For the meteorological model, the precipitation was model for assessing the impact on the groundwater input as “specified hydrograph” and the rainfall storage under the future scenario. event was estimated using the alternate block The other parameter values (b, c and d) values were method. Evaporation has been input as monthly also kept unchanged such that the model illustrates averages and the values have been obtained for the the future conditions that would lead to the drying Colombo station (Ponrajah, 1984). The simulation up of groundwater wells. The initial soil moisture time interval was selected as one minute. First, the storage and the initial groundwater storage were model for the present condition was simulated and assumed to be 50 inches on 01/01/2009. then the future condition model with the 50% increase in the impervious area was analysed.
3. Results
3.1. Present Condition The values of the four parameters a, b, c and d, before and after calibration and validation, are tabulated in Table 1.
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Error Coef. For Calibration For Validation Pearson 0.929 0.948 RSQ 0.863 0.900 Table 1: Parameter Values before and after Calibration and Validation RMSE 0.024 0.023 Nash 0.863 0.895
MAPE 0.193 0.418 Parameter Before After After Calibration Calibration Validation The streamflow hydrographs for calibration and a 0.95 0.88 0.93 validation periods of the present condition model b 133.0 139.6 133.0 c 0.341 0.555 0.446 are shown in Figures 4 and 5, respectively. The flow d 0.045 0.00001 0.00001 duration curves for the calibration period and the validation period are shown in Figures 6 and 7,
respectively.
The associated error coefficients are tabulated in For the 2011-2013 (calibration) period both low flows and high flows are over estimated. For the Table 2. 2009-2010 (validation) period the low flows are
under estimated and the high flows are over Table 2: Error Coefficients estimated.
1 0 0.9 2 0.8 4 0.7 6 0.6 8 0.5 10 0.4 12 0.3 14
Streamflow Streamflow (inches) 0.2 16 Precipitation(inches) 0.1 18 0 20 8/10/2010 2/26/2011 9/14/2011 4/1/2012 10/18/2012 5/6/2013 Date Simulated streamflow (inches) Observed Streamflow (inches) Precipitation (inches)
Figure 4: Hydrograph for Calibration
1 0 0.9 2 0.8 4 0.7 6 0.6 8 0.5 10 0.4 12
0.3 14 Precipitation(inches)
Streamflow Streamflow (inches) 0.2 16 0.1 18 0 20 6/1/2008 12/18/2008 7/6/2009 1/22/2010 8/10/2010 2/26/2011 Date Simulated streamflow (inches) Observed streamflow (inches) Precipitation (inches)
Figure 5: Hydrograph for Validation
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0.5 0.45 0.4 0.35 0.3 0.25 0.2
Flow Flow (inches) 0.15 0.1 0.05 0 0% 25% 50% 75% 100% Percentage Exceedance Flow Rate
Observed Flows (inches) Simulated Flows (inches)
Figure 6: Flow Duration Curve for Calibration Period (2011 - 2013)
0.45 0.4 0.35 0.3 0.25 0.2
0.15 Flow Flow (inches) 0.1 0.05 0 0% 25% 50% 75% 100% Percentage Exceedance Flow Rate Observed Flows (inches) Simulated Flows (inches)
Figure 7: Flow Duration Curve for Validation Period (2009 - 2010)
60
50
40
30
20
Groundwater (inches) Storage 10
0 2/22/2008 7/6/2009 11/18/2010 4/1/2012 8/14/2013 12/27/2014 Date Groundwater Storage (inches)
Figure 8: Variation of Groundwater Storage with Time
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scenario, the average value of groundwater storage 3.2. Groundwater Depletion in the Present was found to be 10.67 inches. Condition Table 6: Model Parameter Values for Calibration and The model parameter values for calibration and Validation validation of the groundwater depletion in present Parameters Calibration Validation condition model are listed in Table 3. The variation a 0.897 0.875 of groundwater storage with time in this b groundwater depletion present condition model is 140 600 shown in Fig. 8. Based on the results, the average c 0.356 0.346 value of groundwater storage was found to be 12.16 d 0.01 0.01 inches.
Table 3: Model Parameter Values for Calibration and Validation 3.5. Solution Scenario (Impermeable area in the Parameter Calibration Validation present condition reduced by 50%) a 0.888 0.875 The model parameter values for calibration and b 140 600 validation of the groundwater depletion in future c 0.356 0.346 condition model are listed in Table 7. For this particular scenario, the average value of d 0.01 0.01 groundwater storage was found to be 12.21 inches. By considering the average values of groundwater storage in the Present, Future and Solution 3.3. Future Condition (Impermeable area is scenarios, it is evident that by applying the increased by 50%) conditions of the Solution scenario, the groundwater storage could be significantly The values of the four parameters a, b, c and d, increased. before and after calibration and validation, are tabulated in Table 4. Table 7: Model Parameter Values for Calibration and Validation Table 4: Model Parameter Values for Calibration and Validation Parameters Calibration Validation Parameter After Calibration After Validation a 0.872 0.875 b 140 600 a 0.888 0.927 c 0.356 0.346 b 139.6 133.0 c 0.555 0.445 d 0.01 0.01 d 0.00001 0.00001
The associated error coefficients are tabulated in 3.6. HEC-HMS Model Results Table 5. From the results of the HEC-HMS model analysis, it Table 5: Error Coefficients was found that, the peak discharge for the total Error Coef. For Calibration For Validation catchment in the present and future conditions are, 3 3 Pearson 0.927 0.949 11.7m /s and 19.9 m /s, respectively. RSQ 0.859 0.900 RMSE 0.024 0.023 4. Discussion Nash 0.857 0.895 It is evident from the results of the ABCD model MAPE 0.198 0.418 simulations that the groundwater storage varies with peaks and troughs over the time, depending From the flow duration curves for the future on the recharge and losses. In some periods of the condition model, for the 2011-2013 (calibration) year, the groundwater storage depletes due to the period, both low flows and high flows are over amount of precipitation received in the basin, estimated. For the 2009-2010 (validation) period, the extraction from the wells, as well as the other losses low flows are under estimated and the high flows from the groundwater storage. The increase in the are over estimated. groundwater storage or replenishment in some other periods of the year can also be explained 3.4. Groundwater Depletion in the Future similarly. Condition Furthermore, an insight into the rate of depletion of groundwater could be deduced by considering the The model parameter values for calibration and average values of groundwater storage for the three validation of the groundwater depletion in future scenarios that have been analysed. The average condition model are listed in Table 6. For this value of groundwater storage in the Present
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 95 UMCSAWM Water Conference – 2017
(groundwater depletion) model, Future groundwater resources is needed to identify where (groundwater depletion) model and the Solution pump irrigation should be encouraged and where scenario model are, 12.16 inches, 10.67 inches and the danger zones are located. For areas that can be 12.21 inches, respectively. Therefore, the further developed, researchers must calculate all groundwater storage values will further decrease in the key elements of the hydrological cycle, the future. On the other hand, by increasing the including recharge rates, to determine how much pervious area (decreasing the impervious area), the water can be extracted, how fast and by how many rate of groundwater depletion could be reduced. pumps (safe yield). The groundwater and surface There can be numerous reasons for this decreasing water resources (especially tank cascade systems) trend (with time) that has been observed. Due to the should be managed jointly in the hard rock areas, increasing population with time, the water usage which constitute a large part of the dry zone. All values will also increase. If pipe borne water is not wells should be registered, to monitor trends in made available, growing population masses will groundwater development and use. The coastal dig more wells in order to satisfy their water needs. aquifers should be monitored vigilantly, as there is The extraction rates from the existing wells may a danger of seawater intrusion. Monitoring and also increase due to the changes in utilization addressing agrochemical pollution of aquifers and patterns. This might lead to a further decrease in the soil salinization should be done, particularly in groundwater storage with time, aggravating the areas where groundwater is used for drinking and consequences. where there is not enough rainfall to flush out salts Moreover, rapid urbanization will lead to and other contaminants. The growth of the continued removal the forest cover, transfer in them groundwater economy in areas where groundwater into urban areas, in order to facilitate and cater for is renewable, and base management strategies on the increasing demand due to escalating human existing groundwater-use patterns and socio- needs. A decrease in the forest cover with economic conditions, must be encouraged. It should subsequent increase in the urban area will lead to be ensured that the groundwater development an increased runoff coefficient value, resulting in activities of different government agencies and augmented runoff generation causing aggravated NGOs are coordinated by an apex body. The public adverse impacts in the basin. awareness of aquifer capacities and vulnerability to pollution should be increased, especially in danger 5. Conclusions and Recommendations zones. Several approaches for sustainable groundwater Fresh water is a finite and vulnerable resource, management plans could be adopted. One of them essential to sustain life, development and the is the direct approaches, which include creating environment. Since water sustains life, effective appropriate rules and regulatory mechanisms that management of water resources demands a holistic can be applied to groundwater management. This approach, linking social and economic includes imposing groundwater regulations and development with protection of natural ecosystems. implementing limits on extraction. Another Effective management links land and water uses approach is based on the indirect approaches, across the whole of a catchment area or which include; supplying agricultural subsidies, groundwater aquifer. energy pricing food procurement policies, rural This project mainly focused on the studying of the employment policies, agricultural trade and tariff catchment characteristics on the recent depletion of policies, etc. The other approach type is the groundwater as observed in several aquifer basins technical approaches, which include supply in Sri Lanka. The better awareness of depletion- management methods such as managed aquifer recharge characteristics and role of aquifer recharge and rain water harvesting, as well as characteristics in governing well behaviour is demand management techniques such as artificial expected to be extremely useful in proposing recharge. The final approach is the awareness and sustainable new methods of preserving invaluable education based approach, which includes groundwater resources for future generations. community participation. Catchment characteristics directly and indirectly Further changes in the climate can be expected in affecting the groundwater recharge pattern of the the future. These changes may occur due mainly to basin should be well recognized for deriving the impacts on the nature caused by anthropogenic remedial measures and continuing further studies activities. As a result, we can expect a reduction in on drying up of wells. In this study, runoff the precipitation in future in some parts of the coefficient was considered as a major catchment world, including India in the South Asian groin. characteristic affecting this phenomenon. This reduction of rainfall will affect the Several feasible recommendations for enhancing groundwater storage in a drastic amount. In order sustainable groundwater usage in Sri Lanka have to get an idea about the impact of the climate change been discussed below. The policymakers and water on the groundwater storage, and the future managers should be provided with reliable condition model could be modified by using the information in a usable form, enabling early decision making. An island-wide assessment of
96 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 precipitation values reduced by a certain percent amount. The remedial measures that can be adopted to reduce the reduction in the groundwater storage could be further investigated. Rainwater harvesting has come up as one of the solutions for this problem. Therefore, the effect of rain water harvesting on the groundwater storage could be studied in detail. It can be concluded that it is necessary to implement remedial actions to preserve the groundwater to our future generations. By implementing suitable measures to overcome the groundwater problems that have been encountered and managing the utilization of groundwater in a sustainable manner, satisfactory changes that would contribute to the preservation of this valuable resource in a more pragmatic way, could be expected.
6. References
Al-Lafta, H. S., Al-Tawash, B. S. & Al-Baldawi, B. A., 2013. Applying the “abcd” Monthly Water Balance Model for Some Regions in the United States. Advances in Physics Theories and Applications, Volume 25, pp. 36-48. Endersbee, L., 2006. World's Water Wells are Drying Up. Science and Technology. Hettiarachchi, I., 2008. A Review on Groundwater Management Issues in The Dry Zone of Sri Lanka. BALWOIS 2008- Ohrid, Republic of Macedonia – 27. International Water Mangement Institute (IWMI), 2005. Planning Groundwater Use for Sustainable Rural Development. [Online] Available at: http://www.iwmi.cgiar.org/Publications/Water_ Policy_Briefs/PDF/wpb14.pdf [Accessed 15 May 2016]. Jayakody, P., Raschid-Sally, L. & Abayawardana, S., 2006. Urban growth and wastewater agriculture: A study from Sri Lanka. Colombo, s.n., pp. 105-111. Martinez, G. F. & Gupta, H. V., 2010. Toward improved identification of hydrological models: A diagnostic evaluation of the “abcd” monthly waterbalance model for the conterminous United States. Water Resources Research, 46(W08507). Panabokke, C. R. & Perea, A. P. G. R. L., 2005. Groundwater Resources of Sri Lanka. Water Resources Board. Ponrajah, A. J. P., 1984. Design of Irrigation Systems for Small Catchments. 2nd ed. Colombo: Irrigation Department. Shuttleworth, W. J., 1993. Chapter 4: Evaporation. In: D. R. Maidment, ed. Handbook of Hydrology. New York: McGraw-Hill, Inc., pp. 4.1-4.53. Thomas Jr., H. A., 1981. Improved Methods for National Water Assessment, Water Resources Contract: WR15249270, s.l.: Harvard Water Resources Group. Walker, J. D., 2014. ABCD Model. [Online] Available at: http://abcd.walkerenvres.com/theory.html [Accessed 27 05 2016].
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98 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Investigating the Impacts of Climate Change and Adaptation Options in Handegama Tank for Irrigation Water Management
Kinley Wangmo and N.T.S. Wijesekera
ABSTRACT Under the changing climate, major effects are likely to arise from changes to the freshwater resources systems. The water resources under Hadegama scheme are already stressed and under climate change the availability of irrigation water is expected to become a major issue. This study would help investigate impacts of climate change and adaptation options in Handegama tank for water security. Future scenarios for climate change were selected based on predicted climate information from literature and a reservoir operation was performed under changing irrigation demand. Behavior of the system pertaining to the changes in climatic parameters such as rainfall and evaporation is useful for planning purpose and identifying possible adaptation measures. The worst climate change scenario for Handegama tank was identified as the fifth scenario with decrease in the annual rainfall by 14% and an increase in temperature by 2°C while increasing evaporation by 8 % by 2050. The cropping intensity under this scenario reduced from 1.53 to 1.25, a decrease of 28%. The identified adaptation options were crop diversification and improvement of canal efficiency; both of them increased the cropping intensity by almost 18 %. Reduction in available water under the worst climate change scenario would cause a 28 % reduction in the cropping intensity. These results indicate the need for adaptation under climate change. The adaptation options identified in this study helps to increase the cropping intensity thereby proving to be beneficial to the water users within the system.
KEYWORDS: Climate Change, Water resources, Irrigation
system in Auradhapura District, Sri Lanka (Figure 1) and recommend possible adaptation strategies to 1. Introduction aid in planning and management of water Sri Lanka’s water requirements are met mainly by resources. surface water resources. Water scarcity is expected 2. Data to be a major challenge for most of the region as a result of increased water demand and lack of good Handegama tank is in the Agro Ecological Zone management. Water is the first sector to be affected DL1 (ID, 1984). The tank has a capacity of 85.4 Ha by changes in climate and these changes in climate and a catchment area of approximately 19.4 km². leads to intensification of the hydrological cycle and 75% probable rainfall, reference crop subsequently it has serious effects on the frequency evapotranspiration and crop factors were taken as and intensity of extreme events (Cap-net, 2011). The per the Irrigation guideline (ID, 1984). Area capacity impact of climate change on water resources is curve and cultivation extents were collected from caused by climatic factors, which mainly include the Irrigation Department. Climate information rainfall, and temperature changes (Nan, Bao-hui & from reviewed literature are taken as future Chunkun, 2011). scenarios. Water plays a critical role in food security. Uncertainty in climate will affect the seasonal yields since food production depends on water not only in the form of precipitation but also in the form of available water resources for irrigation. Kinley Wangmo, B.E Civil Engineering, Bangalore Under the changing climate, the operational rules, Graduate Research assistant at UMCSAWM, University system design and size, current policies and water of Moratuwa, Sri Lanka use strategies will get affected. Climate change N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip poses costly impacts in terms of maintenance, (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., repairs and functionality; hence incorporating MICE(UK), FIE(SL), Senior Professor, Department of possible climate change impacts in infrastructure Civil Engineering, University of Moratuwa, Sri Lanka. planning and water resource planning is of major importance. This study aims to investigate the impacts of climate change on Handegama tank
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maha season will increase due to reductions in average rainfall, increase in potential evapotranspiration and early ending of rainfall (De Siva, 2007). Hence in the current scenario, 34 % decrease in the NEM rainfall and 38 % increase in the SWM rainfall by 2050 (other months remaining same), for 1.6°C increase in temperature with increase in annual evaporation of 8% for every 0.9°C increase in temperature is considered and the future demand is calculated and the reservoir operation is performed.
3.2.2 Second Scenario
Figure 1: Study area Under A2 scenario (AR3), increase in temperature of 0.9°C and increase in rainfall of 402 mm and 54 3. Analysis mm respectively for SWM and NEM respectively by 2050. 3.1. System Water Balance 3.2.3 Third Scenario The monthly water balance equation used for this study is as given below; As per IPCC, significant acceleration of warming in South Asia with higher warming is projected Storage at beginning of month + Inflow – losses – during the NEM than during the SWM (IPCC, Demand– Spillage = Storage at end of the month. 2008). Basnayake (2008) predicts 2.9 °C in NEM season and 2.5 °C in SWM season with increases in Inflow to the reservoir is the yield from the both NEM and SWM, with SWM having higher catchment and demand is the Irrigation increase than NEM. Hence in this scenario, increase requirement. Irrigation Demand for paddy in rainfall of 20% for NEM and 30% for SWM with cultivation of 135 days and 105 days for Maha and temperature increases of 2.9°C increase in NEM and Yala was calculated according to the Irrigation 2.5°C in SWM respectively are selected. guideline for a three stagger system. Application and conveyance losses were accounted for in the demand. Evaporation from water surface of reservoir and seepage were taken as losses. Spillage 3.2.4 Fourth Scenario is the amount of inflow that flows out/ spills from the reservoir when it is full. Reservoir operation for IPCC states that, there is a possibility that the the present scenario was performed assuming monsoon onset dates are likely to become earlier or initial storage at minimum operating level. would not change significantly. A recent study by the Purdue University, especially on the South 3.2. Selection of Scenarios Asian summer monsoon also projects a weakened and delayed (by 5-15 days by the end of the twenty- In the current study, climate change scenarios were first century) SWM over the majority of South Asia. selected based on literature. The irrigation demand Regional climate models for South Asia also project was calculated under these scenarios and reservoir widespread warming in the region, including in Sri operation performance is checked. The scenarios Lanka (rise in annual mean temperature in the are described below. range 2.5–4°C for IPCC scenario A2 and 2–3°C for B2) by 2050 (Kumar et al. 2006: Islam and Rehman 3.2.1 First Scenario 2004). In this scenario, a shift in monsoon by one IPCC have stated that the future increases in month and temperature increase of 2.5°C by 2050 is precipitation extremes related to the monsoon are considered with equivalent increase in evaporation very likely in East, South, and Southeast Asia (IPCC, of 8% for every 0.9°C increase in temperature. 2008). De Silva (2006) predicts a 26-34 % decrease in the Northeast Monsoon (NEM) rainfall and a 16-38 3.2.5 Fifth Scenario % increase in the Southwest Monsoon (SWM) IPCC states that the wet areas will get wetter and rainfall compared to 1961-1990 for scenarios B2-A2. the dry areas will get drier. Few authors have The author predicts increases of 1.6°C under A2 and predicted decrease in mean annual rainfall, 1.2°C under B2 by 2050 and these increases would particularly in the dry zones. Reduced rainfall in be mainly in the north, north-eastern and north- dry zone areas such as Anuradhapura, Batticaloa western regions (all within the dry zone). The and Trincomalee have been predicted (Basanayake, author further suggests that by 2050, the average 2004). In this scenario a decrease in the annual paddy irrigation water requirement during the
100 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 rainfall by 14% and increase in temperature of 2°C was done. The cropping intensity for the future with increasing evaporation of 8 % by 2050 is scenarios was found to be 4% and 10% more than considered. the base scenario because of the increase in rainfall in both seasons and the evaporative demand being 4. Results much lesser than the increase in rainfall.
4.1. Present Scenario In the fourth scenario, the shift in the monsoon In the current scenario, there is insufficient water for onset dates by a month and the corresponding cultivation in the Yala season. Actual rainfall data temperature increase causes a reduction in the from 2010 to 2015 was substituted in place of 75% cultivation extent in the Yala season. The decrease probable rainfall and the reservoir operation was in the cultivation extent was found to be only 2% of performed. The cultivation extent under actual the present situation. rainfall was found to be 100 % for both seasons but, since the actual rainfall is only for a short period, it It was identified that the worst scenario for the is not representative of long term rainfall, hence it is current tank was scenario 5, where there is annual not considered. The reservoir operation for the reduction in the rainfall with increase in current scenario with 75% probable rainfall is temperature. The cultivation extent in the Maha is presented in Table 4.1 and 4.2. reduced to 22% compared to the base scenario and 11% in case of Yala season. The comparison of the Table: 4.1 Reservoir operation (Maha) cultivation extents and the cropping intensities are mentioned in Table 4.3.
Maha season oct nov dec jan feb mar Table: 4.3 Comparison of scenario St-1 5.60 63.43 124.62 134.80 133.20 92.21 Scenario BS S1 S2 S3 S4 S5 It 86.34 103.61 86.34 51.81 17.27 34.54 Cultivation Maha 100 100 100 100 100 77.86 Et 1.27 5.36 8.22 8.85 9.80 10.95 extent % Yala 53 60 56.8 62.5 52 47 Set 0.03 0.32 0.62 0.67 0.67 0.46 Cropping Intensity 1.53 1.6 1.56 1.62 1.52 1.24 Dt 27.22 36.75 36.58 43.88 47.79 21.76 Spt - - 30.74 - - - 5. Adaptation Options St 63.43 124.62 134.80 133.20 92.21 93.58 5.1. Crop Diversification Table: 4.2 Reservoir operation (Yala) Out of the different crops selected, green gram was Yala season the most suitable crop which could increase the apr may jun jul aug sep cropping intensity with minimum water St-1 93.58 134.80 134.80 95.56 47.75 14.91 requirement. The cultivation extent could be It 86.34 34.54 8.63 - 8.63 17.27 increased up to 17% in Yala season under the Et 9.20 11.51 12.17 10.19 7.57 3.45 available water. The comparison of the irrigation Set 0.47 0.67 0.67 0.48 0.24 0.07 demand for different crops is mentioned in Table Dt - 19.59 35.03 37.14 33.67 23.05 4.3 and the corresponding cropping intensities are Spt 35.45 2.77 - - - - mentioned in Table 4.3. St 134.80 134.80 95.56 47.75 14.91 5.60 Table: 4.4 Irrigation demand for different crops 4.2. Comparison of Scenarios Green gram The irrigation demand for the Yala decreases under Yala Maha the first scenario due to increase in the rainfall of ID/unit area 1101.05 1707.84 SEM by 38% but there is an increase in the irrigation Soya bean demand in the Maha season due to decrease in rainfall in the NEM by 34%. . The cropping intensity Yala Maha is thus 7% higher in the first scenario compared to ID/unit area 1,591.06 1707.84 the base scenario, because of the increase in rainfall Ground nut in the Yala season. Yala Maha ID/unit area 1618.19 1707.84 In the second scenario and third scenario, the rainfall in both seasons is increasing and hence Table 4.5 Cropping intensity for different crops there is a decrease in the irrigation demand in both seasons but there is increase in temperature with increasing evaporation. After incorporating evaporation losses of 8 %, the reservoir operation
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Cultivation extent Cropping suitable adaptation and management options in Crop type Maha Yala Intensity order to sustainably manage water resources and to avoid disastrous situation in the future. Paddy 100 53 1.53 Greengram 100 70 1.7 Improving water management practices and land soya bean 100 68 1.68 use management practices can have important Groundnut 100 69 1.69 impacts on water. A change of land cover will either lead to a decrease or increase in annual stream flow. 5.2. Improving the System Efficiency Catchment zoning and training in land use management can be taken as an option to increase Canal efficiency can be improved by improving the water use efficiency. Conducting awareness water delivering efficiency. In the current study programs among farmers about climate change and conveyance efficiency is increased upto 80%. The their consequences, and the importance of efficient increase in the efficiency increases the cropping water management can assure water security for intensity by 18% compared to the current situation. irrigation needs. Cropping intensity for the two adaptation options are mentioned in Table 4.6. 7. References:
Table 4.6 Cropping intensity with adaptation Ponrajah A.J.P Design of Irrigation Headworks for options for present scenario. Small Catchments (1984)
Adaptation options IPCC. (2008). Climate Change 2008: Climate Change and Water. Technical Paper of the Cultivation Cultivation Intergovernmental Panel on Climate Change extent after extent after improving crop Cap-net. (2011). IWRM as a Tool for Adaptation to Cimate Change. Retrieved January10,2017, from canal efficiency diversification http://www.gwp.org/Global/GWP- Maha 100 100 Cultivation CACENA_Files/en/pdf/capnet-adapt-to-climate- extent % Yala 70.5 70 manual_en.pdf Cropping Intensity 1.705 1.7 Nan, Y., Bao-hui, & Chunkun, L. (2011). Impact Under the worst scenario, incorporating adaptation Analysis of Climate Change on Water Resources. options considerably increases the cropping intensity. An increase of 25 % and 30% with Eriyagama, N., & Smakhtin, V. (2010). Observed improvement of system efficiency and crop and Projected Climatic Changes, Their Impacts and diversification was identified in the study. Adaptation Options for Sri Lanka: A Review.
Both crop diversification and improvement of canal De Silva, C. S. 2006. ‘Impacts of Climate Change on efficiency increases the cropping intensity, the Potential Soil Moisture Deficit and It’s Use as a Irrigation demand is reduced in terms of crop Climate Indicator to Forecast Irrigation Need in Sri diversification, and the water can be used efficiently Lanka’. In: Symposium Proceedings of the Water for other purposes. These options may help in Professionals’ securing irrigation water needs. Basnayake, B. R. S. B. 2008. ‘Climate Change: 6. Conclusion and Recommendations Present and Future Perspective of Sri Lanka’. Reduction in cropping intensity of 28% was identified under the worst climate change scenario. Cropping intensity can be increased by 25% and 30% with improvement of system efficiency and crop diversification under the worst climate change scenario. These results indicate the need for adaptation under climate change and the importance of incorporating adaptation policies under climate change.
Under the future climate change, the already stressed water resources are projected to be further stressed. Moreover, the population is expected to increase and hence food security will become an issue. Hence it is important to come up with
102 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
TECHNICAL PAPERS
SESSION 3
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104 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
A Raster GIS Model for Water Supply Tower and Source Option Prioritisation in Community Based Water Supply Schemes at Attanagalla, Sri Lanka
T.K.N.K. Kumari and N.T.S. Wijesekera
ABSTRACT Optimum location identification for the water tower and source is very important for any water supply scheme mainly due to storage capacity, elevation, landuse, yield of the source throughout the year, and the costs for transmission and distribution system. Towers need water from several alternative sources. Construction of distribution pipe lines is expensive due to physical features, terrain, water and urbanisation. Considering these factors design option prioritisation can be carried out by using Raster GIS. To demonstrate the potential of Raster GIS a case study was undertaken for the prioritisation of source locations for a Community Based Water Supply Scheme (CBWSS) to deliver safe and reliable drinking water for rural community living in approximately 64 km2 within Attanagalla of Gampaha District. A Raster GIS model was developed to prioritise the community based water supply scheme by using terrain features with the resolution of 10 m. Base layers for the key parameters of population, roads, elevation, land use, soil, rainfall and streams were prepared and analysed to obtain the final output. Four options of two tower and two source locations for CBWSS were evaluated and Ihalagama & Algama were selected for water tower & source respectively. This paper demonstrates the weighted overlay for the cost surface (60% Road +30% Slope+10% Soil) and the least cost path for transmission and distribution (5,486,173.50 in Cost units) and close proximity to the urban area was selected. Raster GIS can overlay the layers easily, has terrain modelling capability and incorporates cost functions. Therefore Raster GIS is a great facilitator for spatial modelling for the prioritisation of planning and management of water supply schemes.
KEYWORDS: Prioritisation, Community Based Water Supply Scheme, Raster GIS, Spatial Modelling
1. Introduction 1.2. Vector GIS
1.1. General Advantages of Vector GIS are data can be represented at its original resolution and form Safe water, suitable for human consumption is a without generalisation, graphic outputs is usually scarce resource which is indispensable for the more aesthetically pleasing, since most data is in sustenance of life on the planet. This contributes vector form and no conversion is required and health, social development and overall economy of accurate geographic location of data is maintained. the country. Access to safe drinking water is Disadvantages of Vector GIS are location of each considered as an inalienable right of people. Rural vertex needs to be stored explicitly, for efficient communities face many hardships due to lack of analysis, vector data must be converted into a access to safe drinking water. topological structure, algorithms for manipulative In Sri Lanka the piped water supply coverage is and analysis functions are complex and may be reported as 47 % (NWSDB 2016). Out of the rural processing intensive, continuous data is not areas only about 22.8% has been covered. Sri Lanka effectively represented in vector form and spatial urgently needs to provide potable pipe borne water analysis and filtering within polygons is impossible. to rural communities. This causes many problems, In real life problems decision making involves in such as, i) rural areas have lower population many types, layers and attributes. Therefore, when densities, ii) coverage extents are large and iii) vector data are used for overlay modelling, it is available funding is limited. Therefore, in order to inherent that the data bases need to grow provide potable water to all, the planners and exponentially leading to errors and loss of speed of designers need to find the optimum design operations. ensuring that the stakeholder needs are well looked after. GIS is a very powerful tool to carryout T.K.N.K. Kumari, B.Sc. Eng. (Hons), Senior Engineer, planning and management of spatially distributed National Water Supply & Drainage Board, Sri Lanka resources and it provides the strength for the N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip engineers to evaluate options for the optimum (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., design. There are two GIS formats that can be used MICE(UK), FIE(SL), Senior Professor, Department of for modelling. They are vector and raster formats. Civil Engineering, University of Moratuwa, Sri Lanka.
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1.3. Raster GIS Raster GIS is the most suitable data format for spatial modelling. Main factor is the comparatively big advantage in the data handling technique which requires less space while enabling easy computing. Hence this format is ideally suited for mathematical modelling and quantitative analysis. In Raster format geographic location of each cell is implied by its position in a regular cell matrix. Accordingly, other than origin point no geographic coordinates has to be stored. In raster, discrete data is accommodated equally well as continuous data and grid cell systems are highly compatible with output devices. Though the spatial data storage technique has tremendous advantages in handling, if the Figure 1: Study Area Map modeller is not careful then the raster data causes accuracy problems. Though these differences are known in theory, Table 1: Data there are no detailed case study examples of using Layer Resolution raster models for real life applications and No Data Layer especially in the planning and design of Water Type Supply and Drainage projects in Sri Lanka. However there are raster application to real life 1 Project Area Polygon 1: 50,000 problems and demonstration of advantages in other 2 DSDs Polygon 1: 50,000 parts of the world (Al-Sabhan et.al, 2003, Joerin et 3 Population Polygon 1: 50,000 al., 2001). 4 Waterdensity Tower Points 1: 10,000 Though NWSDB with its mandate needs to execute 5 WaterLocations Source Points 1:10,000 rational planning and design of potable pipe borne locations water systems, there is a void in demonstrating the 6 Land use pattern Polygon 1:10,000 potential of GIS when decision making is 7 Contours Polylines 1:10,000 challenging. Hence a community based case study 8 Elevation spot Points 1:10,000 application was undertaken. 9 Soilheights layer Polygon 1:10,000 The coverage of existing water supply schemes of 10 Road Network Polylines 1:10,000 NWSDB is limited for town areas in Attanagalla. 11 Stream Network Polylines 1:10,000 Available capacity of these urban systems are not sufficient to cater the adjacent rural communities. Hence the need to provide optimal drinking water 1.5. Data supply systems for the rural community has Spatial data, format of base data and the resolution become a very important task. used for the study are in the Table 1. Land use pattern has 05 types (Built-up area, 1.4. Study Area Cultivation area, Forest area, Rock area and Water Rural hilly areas of the Attanagalla, Mirigama, area) and road raster has 03 types. Slope raster Warakapola and Ruwanwella Divisional Secretariet consist of 09 classes and soil raster consists of 03 Divisions with an overall extent of 64 km2 were the classes. study area falling within the Gampaha and Kegalle 2. Methodology Districts (Figure 1). Study area which consisted of 41 Grama Niladari Divisions having Gampaha as Parameters selected for objective function were the closest major city had a total Population of 41511 water demand, water source capacity and the Cost with a mixed culture including middle and low (Transmission cost, Distribution Cost, Treatment income families. cost, Cost for construction of water Tower) as shown in table 2. Water demand is very important factor when designing a Community Based Water Supply Scheme. Therefore, water demand for the project area is calculated using the population density of the area and according to that capacity of the water source is evaluated. Water source capacity is based on the catchment area, rainfall intensity of the area and the water quantity extracted. Locations for water sources
106 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 were selected with the same capacity. Therefore, it is necessary to ensure that those two locations which have the equal catchment area and the same rainfall intensity. And also this capacity would meet the water requirement. Watershed delineation for the source location was used as the outlet for the catchment. Cost is depending on the length of the road, slope of the area and the soil type. Supply and laying cost of pipes were represented by the road length for transmission and distribution cost. Construction cost of water tower and the treatment cost were assumed constant for locations with same elevation and land use. Figure 2: Digital Elevation Model Table 2 : Objective Function Two water tower locations (Ihalagama and No Objective System Concept Uduwaka) which having same elevation and and parameters landuse of the area were selected by using GIS 1 Selection of a Water f (Water Demand, operations. (Overlay elevation layer & landuse Source Water Source Capacity, Cost) layer and reclassify). Flow direction raster was created by using GIS with 2 Water Demand f (Population) the DEM. Sinks were identified and filled then flow 3 Source Capacity f (Rainfall, direction was created again. Sinks were found after Catchment area) the flow direction has created and then flow 4 Cost (Transmission f (Road Length, accumulation raster was created. Actual streams cost, Distribution Slope, Soil ) raster was burned to the DEM to find the Sinks Cost, Treatment cost, again using raster GIS and again flow accumulation Cost for construction raster was created. After that Stream network has of water Tower) been identified with the threshold value to match with the physical stream network in the area. Base layers for the key parameters namely, Watersheds were delineated along the streamline population, roads, elevation, landuse, soil, rainfall and find out two locations for sources which having and streams were prepared using GIS operations to the same catchment area. convert from vector format to raster format. Digital IDW, one of the rainfall interpolation methods in Elevation Model (DEM) shown was created by GIS was used for the study area to ensure that the using Triangular Irregular Network (TIN) with the two water source locations which having same use of contours and spot heights of the area. 10m rainfall intensity. contour interval and raster resolution of 10m was Two water source locations (Algama and used. Uduwaka) which having same catchment area and Environmental settings is the workspace into which rainfall intensity were selected by using GIS to place results, the cell size, processing extent or operations. output coordinate system to apply to results and a Road raster was created and reclassified by using mask to limit the area that will be processed. The GIS operations to find the cost for pipe laying and settings for GIS were established at three levels; for road reinstatement. the working application so that settings apply to all Slope raster was created by using GIS with DEM to processes within the model and for a particular identify the slope in the area, which affects to the process within a model. pipe laying cost for transmission lines and Possible combinations for water tower and source distribution lines. are as follows to optimize the cost of pipelines. Soil raster was created and classified to find the Water Tower location at Tower_1 and Source excavation cost for pipe laying. location at Source_1 In GIS, weighted overlaying was used to overlay the Water Tower location at Tower_2 and Source three layers of road, slope and the soil rasters. Then location at Source _1 the Cost surface raster which incorporates cost was Water Tower location at Tower_1 and Source created by using road length, slope of the terrain location at Source_2 and soil type. Water Tower location at Tower_2 and Source Cost surface = Road layer * 60% + location at Source_2 Slope layer * 30% + Soil layer * 10% These percentages decided by considering rates involved in the NWSDB rate book 2014. Cost distance raster from each water tower location to
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 107 UMCSAWM Water Conference – 2017 the delivery points (centroid of each DSD areas) and Table 3.1 : Cost for Transmission and Distribution cost distance raster from each water source location Total Cost, in to tower locations were prepared. Cost distance tool Options Locations million cost take into account that distance can also be measured units in cost. Water Tower location at T1 and Cost paths from each tower to delivery points and 1 5.49 Source location at from each source location to tower locations. S1 Alternatives were evaluated to find the locations for Water Tower water tower and the source. location at T2 and 2 5.64 Economical route is identified by comparing path Source location at costs shown in Figure 3 . S1 Water Tower
location at T1 and 3 5.50 Source location at S2 Water Tower location at T2 and 4 5.66 Source location at S2
From the above table, two options were selected and then considering close proximity to urban areas was selected. Figure 3: Cost paths from tower locations to Centre of the The Tower 1 at Ihalagama and Source 1 at Algama DSDs were selected as the water tower and water source locations for the community based water supply system in Attanagalla area. Results verified with the field data.
3.1. Assumptions made Both source locations have same capacity with the required water quantity and the water quality throughout the year Both Water Tower locations have similar construction cost and water treatment cost. For that Figure 4 : Cost paths from source locations to tower 1 tower locations are selected those having the same elevation and landuse type. Because the
construction difficulties due to elevation and the landuse is similar when the tower locations are having the same characteristics. Therefore cost will depend only on the transmission cost from Source location to the Tower location and distribution cost from Water Tower location to the delivery points. Material cost for pipe laying were constant for both locations.
4. Discussion Figure 5 : Cost paths from source locations to tower 2 The cell size determines the resolution at which the Vector to raster conversion was verified by data is represented. Cell size = 10 is used for the overlaying. study due to the easiness of calculations and match with the contour interval = 10 m. 3. Results Water demand is very important factor when designing a Community Based Water Supply Identified key parameters were population, roads, Scheme. Therefore, water demand for the study elevation, landuse, soil, rainfall and streams in the area is calculated using the population density of study area. the area and according to that capacity of the water Cost for transmission and distribution were source is evaluated. calculated and tabulated in table 3.1. Water demand = Population x Percapita consumption of water per day Percapita consumption of water per day = 120 l/day
108 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Population = Population density of each DSD x area Do you think your objective function is fully of relevant DSD addressing the problem or you later realized that Water Supply System is designed to provide the you had missed something out ? Say that and water demand of each DSD to its centroid. Water discuss how to do it in the next occasion. demand for each DSD is applied to its centroid. Raster resolution selected for the study was 10 m Two water tower locations were selected by and the extent of the study area was 64 km2. overlaying elevation and road layer which has the Contour interval used for the study was 10. same elevation and road condition. For example; Water source locations are selected with the similar If we use cell size = 1, It is very accurate but it takes capacity with the required water quantity and the more time consuming comparatively. i.e. high water quality. Therefore, it is necessary to ensure resolution those two locations which have the equal catchment If we use cell size = 20, It is less accurate compared area and the same rainfall intensity. IDW method to cell size = 1 and less time consuming was used for Rainfall interpolation. Rainfall comparatively. i.e. low resolution interpolation method was selected on the lowest Cell size = 10 is used for the study due to the rainfall for those locations from the above three easiness of calculations and match with the contour methods for worst case. Watershed delineation for interval = 10 m. the source location was used as the outlet for the When doing this type of studies in future the finer catchment. resolution would be recommended to improve the There were four alternatives for optimize the cost of accuracy of the study. pipelines. Transmission and distribution cost Drawbacks of the present study was Material cost depends on the length of the road, slope of the area of pipelines were not incorporated according to and the soil type. Supply and laying cost of pipes pipeline network design and it would be were represented by the road length for both incorporated when doing in future studies. Water situations. quality and quantity data of the river throughout Assuming both Water Tower locations have similar the year are required to do a better study using GIS. construction cost and water treatment cost, tower locations were selected those having the same 5. Conclusion elevation and landuse type. Because of the The Water Tower at Ihalagama and Source at construction difficulties due to elevation and the Algama were selected as the water tower and water landuse is similar when the tower locations are source locations for the community based water having the similar characteristics. supply system in Attanagalla area. Therefore cost depends on the transmission cost Raster GIS can overlay the layers easily, has terrain from Source location to the Tower location and modelling capability and incorporates cost distribution cost from Water Tower location to the functions. Therefore Raster GIS is a great facilitator delivery points. for spatial modelling for the prioritisation of Cost distances from tower locations and two source planning and management of water supply locations were calculated by using cost distance schemes. tool. Three parameters used to calculate the path Select the water source location by using this Arc cost were Road length (distance), Slope and Soil GIS model. layers. Road distance is the most important directly affects to the path cost factor when consider the pipe 6. Acknowledgements laying. Road distance is two times important than the slope of the terrain. Laying cost of pipes in The main author is grateful to the UNESCO sloping terrain is higher than the flat terrain and Soil Madanjeet Singh Center for South Asia Water type affects to the path cost. Therefore slope was Management for the full scholarship granted to taken in to consideration due to laying cost of pipe pursue the Post Graduate Studies in Water is varied with the soil type. Soil type is the least Resources Engineering and Management. important factor comparing the other two. Encouragement and Nomination by the National GIS Learning Objectives are Vector to Raster Water Supply and Drainage Board of Sri Lanka is conversion, Raster to Vector conversion (Point, Line gratefully acknowledged. ,Polygon), Reclassification, Spatial interpolation (IDW), Spatial overlaying (Weighted overlaying), 7. References Raster analysis, creating Triangular Irregular Wijesekara N T S, Peiris T C. The Status of Network (TIN), Digital Elevation Model (DEM), RS/GIS/GPS Applications in Sri Lanka A Survey of Slope raster, Soil raster, Cost distance raster, Cost Public, Private and Non Governmental path Generation of stream network and Watershed Organisations, “Engineer” Journal of the Institution delineation. of Engineers, Sri Lanka Vector to Raster and Raster to Vector conversions Al-Sabhan W, Mulligan M & Blackburn G.A (2003). are used for the verifications. A real time hydrological model for flood prediction using GIS and WWW
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 109 UMCSAWM Water Conference – 2017
Joerin F, Theriault M & Musy A (2001). Using GIS and outranking multicriteria analysis for land –use suitability assessment. International Journal of Geographic Information Science NWSDB Rate Book, 2015 NWSDB Annual Report, 2009
110 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Hydrological Modelling Approach for Flood and Water Pollution Control in an Ungauged Catchment - A Case Study in Erewwala Catchment in Bolgoda River Basin, Sri Lanka
S. N. Jayasinghe and R. L. H. L. Rajapakse
ABSTRACT The data scarcity is a widespread, global issue and unavailability of reliable hydro meteorological data is one of the major issues the hydrologists and researchers are facing in Sri Lanka when it comes to water resources planning and management. A significant increase in occurrence of flash flood incidents and water quality degradation in surface water bodies have been noted in the recent past. Hence, developing an approach to identify underlying causes and recommend mitigation or preventive measures for floods and water pollution is a timely requirement that planners, designers and researchers should attempt. The objective of this project is to formulate a hydrological modeling approach to recommend preventive or migratory measures for floods and water pollution in ungauged catchments based on the findings of a case study in Erewwala catchment in Bolgoda River Basin, Sri Lanka. The parameters of hydrological models for ungauged catchments can be estimated using regional information. For this case study, a rainfall-runoff model was developed in spreadsheet and graphical format where the monthly runoff coefficient and base flow were the model calibration parameters. The model was calibrated based on observed data for three years and validated for two years. Observed discharge data at Millakanda gauging station, basin rainfall obtained from Rakwana, Horagoda and Usk Valley rainfall stations and evaporation data from Colombo were used for the model developed for Kaluganga. The calibrated parameters of Kaluganga basin were used for the water resources assessment in Erewwala catchment (2.9 km2). The catchment was divided into three sub-catchments for water pollution control purpose and the incremental runoff at the each sub-catchment outlet node was estimated using the rainfall- runoff model. The types of water uses were identified for each sub-catchment unit and the discharges due to each water use in individual catchments were calculated, subsequently deriving the contribution of each catchment to its overall water pollution. These values were compared with the stipulated permissible pollutant level in surface water bodies. For flood control measures, the HEC-HMS (US-ACE) software was used to estimate the peak discharge with 10 year return period storm event and the peak discharge in each catchment node was obtained. The required flood controlling measures were identified and recommended for the critical catchments which contribute to the highest discharge leading to flashflood conditions in the downstream areas. Based on the peak flow and pollutant source analyses, the sub-catchment No. 1 was identified as the most polluted catchment as well as the one which contributes the most to the flash floods in Erewwala catchment.
KEYWORDS: Data scarcity, Flash flood, Hydro meteorological data, Rainfall-runoff model, Water pollution.
area is “Red-yellow podzolic soils with soft or hard 1. Introduction laterite rolling and undulating terrain” (De Alwis & Panabokke, n.d.). Runoff estimation for ungauged catchments is a In terms of hydrology, this area receives rainfall typical issue in Water Resources Management. This during South-West monsoon and intermediate paper aims to introduce a practically viable monsoon periods. approach to establish flood mitigation and water According to the Meteorological department data, quality control measures focusing on an ungauged annual rainfall in the study area is around 2500 mm catchment. This method will be more appropriate and the annual evaporation is around 1500 mm. for the catchments with relatively uniform climate Though there are multi-sector water users in the conditions and land use patterns. study area, none of them extract water from surface 1.1. Study Area S. N. Jayasinghe, B.Sc. Eng. (Ruhuna), Civil Erewwala sub catchment which is in the Bolgoda Engineer, SMEC International Pvt. Ltd., Sri river basin spatially spreads over an area extent of Lanka 2.9 km2. A significant variation in land use pattern can be observed within this area and the dominant R. L. H. L. Rajapakse, BSc Eng (Moratuwa), MSc land use pattern amongst all is the homestead (Saitama), PhD ( Saitama ), C.Eng., Senior garden (Figure 1). This area can be categorized as a Lecturer (Grade II), Department of Civil semi-urbanized area. Available soil group in the Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 111 UMCSAWM Water Conference – 2017 water bodies. Only rain-fed irrigation is being most prone areas to inundation during such practiced in this area. The surface water bodies in periods. Therefore, immediate action should be the river basin ultimately drain into the Bolgoda planned and implemented to avoid aforementioned Lake in which water quality is becoming gradually adverse situations. deteriorated (Illeperuma, 2001). This is an indirect indication that the surface water bodies are carrying 2. Approach and Methodology pollutants to the Bolgoda Lake. 2.1. Data Collection As the preliminary step for the study, a social survey was carried out to identify the issues related to water sector in the area. The interviewees for the survey were selected representing all groups of stakeholders including farmers, residents, business and industrial owners, etc. The individual personals for the survey were however arbitrarily selected. Table 2: Social Survey- Issues Related to Water Sector
Category Response Farmers Inundation of paddy lands during rainy season Residents Inundation of roads during rainy seasons Once the social survey was completed, next objective was to quantify the available water in the area. There is no way to quantify the groundwater in the area. The information available related to Figure 4: Location Map groundwater is very limited in Sri Lanka (Panabokke & Perera, 2005). Therefore, the objective was narrowed down to quantify only the surface water resources in the intended area. Accordingly, it was decided to develop a spreadsheet based rainfall runoff model based on water balance concept. The next challenge was to collect hydo- meteorological data for the rainfall runoff model. There were no any established hydo-meteorological monitoring stations within the study area. Hence, it was decided to develop a hydrological model for an area in which the functioning hydo-meteorological stations are available (Mwakalila, 2003). The model with the calibrated parameters was then used to generate discharge for the intended area. Further, the area was selected in such a way that the topography, land use pattern and climate in the selected area is similar to those of the Erewwala sub catchment. After a careful study, the observed hydro- Figure 2: Delineated Sub-catchments in Study Area meteorological data in Millakanda sub catchment in Kaluganga basin was selected to develop the Though the lake is situated outside of the study rainfall-runoff (RR) model for Erewwala area. The area, it is a part of the interconnected surface water collected data for this analysis are shown in Table 2. bodies in the study area and ultimately drains into the Bolgoda Lake. In the environmental and social Table 2: Hydro-meteorological data- Kalu Basin point of view, it is a vital requirement to avoid such Station Data type Duration possibilities of getting the surface waterbodies Millakanda Daily discharge 01/10/95 ~ 30/09/98 polluted. Further, the groundwater level in the Rakwana Daily rainfall Do - Horagoda Do - Do - study area is shallow. Hence, there is a high risk of Uskvally Do - Do - associated groundwater pollution if the surface Colombo Do - 1/01/95 ~ 31/12/14 water is affected. Colombo Evaporation data Monthly average data The frequent flooding during monsoonal periods is another critical issue in the downstream settlement areas while the paddy lands and the roads are the
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2.2. Data Checking and Pre-Processing 2.5. Spread Sheet based Rainfall- Runoff Model The raw data was checked for outliers, The developed spreadsheet based rainfall-runoff inconsistencies and missing values and pre- model consists of two calibration parameters as processed in accordance with the Dahmen and Hall listed below. (1990). i. Monthly runoff coefficient First, the collected rainfall data for the three stations ii. Base-flow were plotted in one graph. The trend, variation of The inputs for the model were daily basin rainfall the rainfall pattern and the missing data were and daily evaporation (derived from monthly checked. Then the outlier test was carried out for all evaporation), while output was the daily discharge. the stations. Once the outlier test was carried out, The model calibration was carried out for the period data consistency for each station was checked using of 01 Oct 1995 - 30 Sep 1997. Model validation was single and double mass curves. checked for the period of 01 Oct 1997 - 30 Sep 1998. The Thiessen polygon method was used to calculate the basin rainfall. Further, the calculated basin 2.6. Peak Flow Calculation rainfall was plotted with the observed discharge in The peak-flow estimation for each sub-catchment order to check whether any mismatch available was carried out for a 10 year return period storm with the two data sets (Figure 3). event, by considering the severity of the possible damages and based on the information collected during the reconnaissance and subsequent field surveys. During the social survey, it was identified that the most downstream area of the catchment is vulnerable to damages due to flood. The HEC- HMS model was used for peak flow estimation. The Intensity-Frequency-Duration (IDF) curves prepared for Colombo rainfall was used for designing the relevant 2 hr storm event (Ranatunga, 2001). Figure 3: Observed discharge Vs Basin Rainfall in Kalu Ganga Basin 2.7. Central Environmental Authority (CEA) Recommendation 2.3. Catchment Delineation of the Study Area According to the guideline stipulated by the Central The most widely practiced method for catchment Environmental Authority of Sri Lanka (CEA) for delineation is to use a Digital Elevation Model discharges into waterways, there should be a (DEM) in the area. For this study area, there is no minimum permissible dilution of 1 is to 8. Thus, such DEM available except for the 30 m and 90 m based on the recommended dilution factor, the resolution digital elevation models from the Shuttle maximum permissible grey water discharge Radar Topography Mission (SRTM) which are volume for each catchment node was calculated. available in United State Geological Survey (USGS) website. As the study area is relatively small, such 3. Results low resolution DEM will not accurately represent The extent of the delineated catchments are listed the actual elevation profile in the area. Hence, the below. catchment delineation was carried out manually i.Upper catchment (U/S) - 1.20 km2 after careful observation of the topography in the ii.Intermediate catchment (IM) - 1.09 km2 area during the site visits and with the use of 1: iii.Downstream Catchment (D/S) - 0.53 km2 50,000 topographic maps (Survey Department, Sri Lanka). The Erewwala catchment was delineated The Table 3 shows the data collected during the into three (03) sub-catchments as shown in Figure 2. social survey as well as from the 1: 50,000 topographic base maps (Survey Department, Sri 2.4. Sub-Catchment Contribution to Net Outflow Lanka) for each sub-catchment shown in Fig. 2. The net flow to each catchment outlet node was simulated using the aforementioned spreadsheet based rainfall runoff model. The runoff for each catchment was calculated by using the calibrated parameters and using the rainfall data collected from Colombo rainfall station and by changing the catchment area.
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Table 3: Land Use in Erewwala Catchment
Catchments
U/S IM D/S Canopy 216,936 270,675 44,578 Layers (m2)
Population 5,584 3,648 1,788 Other Cultivation 19,045 - - (m2) Paddy Land Figure 7: Model Verification 175,277 238,008 105,484 (m2) The calibrated parameters used for the spreadsheet
model are shown in Table 4. The runoff coefficient The spreadsheet based hydrological model was selected based on the land-use pattern and the calibration plot for Kaluganga- Millakanda sub- average slope of the area (Chow, Maidment, & catchment is shown in Fig. 4. The calibration period Mays, n.d.). The monthly runoff coefficient during was selected from 01 Oct 1995 to 30 Sep 1997. The the dry season of the year is less than that of the wet correlation between the observed and simulated season as the soil moisture content is lesser during flows during the wet season has indicated a better the dry season. agreement (R2=0.74) compared to that of the dry season (R2=0.62). The variation of cumulative Table 4: Calibration Parameter observed and simulated discharges are shown in Fig. 5. Month Runoff Coefficient Further, the model verification was carried out for January 0.30 the period of 01 Oct 1997 to 30 Sep 1998 and the February 0.30 March 0.30 correlation of the observed and the simulated April 0.35 discharge is shown in Fig. 6. May 0.35 June 0.40 July 0.40 August 0.40 September 0.40 October 0.51 November 0.45 December 0.35 Initial flow 4.5 mm
The Fig. 7 to Fig. 9 illustrate comparison of the total flow, permissible greywater volume and the actual
greywater volume each catchment outlet node. The Figure 5: Model Calibration (Observed Vs Simulated Discharge in Kalu basin) greywater component consist with the return flow from paddy cultivation and the domestic water users. None of the return flows are measured figures. Irrigation return flow was calculated based on the demand calculation procedure following Irrigation guideline (Ponrajah, 1984). In the domestic return flow calculation process, it was assumed 80% of the demand will be discharged as the grey water component. Both National Water Supply and Drainage Board (NWS&DB) consumers and the water users fromdug wells were taken into
account. Consumer data for potable water demand Figure 6: Variation of Cumulative Observed and Simulated calculation was carried out based on the data Discharges collected from NWS&DB and the Water Resources Board, Sri Lanka. The per capita demand for domestic water was considered as 120 l/day.
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Figure 11: Generated Hydrograph for the Catchment outlet Figure 7: Volume Comparison at Outlet of Upstream Catchment 4. Conclusion and Recommendation In each catchment, the actual grey water content is higher than the maximum permissible levels stipulated by the Central Environmental Agency (CEA). Therefore, it is recommended to construct a separate grey water collection channel and direct it to a treatment plant. In this particular case, the upstream catchment contribution to water pollution is more significant compared to the other two catchments. The most downstream catchment is vulnerable to Figure 8: Volume Comparison at Outlet of Intermediate the flood hazard. The highest contribution to the Catchment runoff is from the upstream most catchment. The estimated flow to the catchment outlet for 10-year return period event is 0.25 MCM. Hence, it is recommended to have detention ponds within the catchment to retard and regulate the flow. Further, most of the farmers mentioned that if water is available during the dry season, they can continue their crop cultivation without limiting it only to monsoon periods. Therefore, having detention ponds would facilitate soil moisture replenishment and continuous irrigation water supply in the area. Further, it is recommended to setup a hydro Figure 8: Volume Comparison at Outlet of Downstream meteorological station either within the catchment Catchment or in a nearby area, if this basin is intended to be The Fig. 10 shows the generated 2 hr storm event as developed as a pilot research area for further mentioned in Section 2.6. In peak flow generation, improving the rainfall runoff model. the flow loss method was set as Initial and constant method (Initial loss- 0.1 mm, Constant rate 0.05 5. Acknowledgement mm/hr and Impervious – 10%) while the transform The author would like to extend her sincere method was specified as SCS Unit hydrograph .The gratitude towards the UNESCO Madanjeet Singh generated peak flow at the catchment outlet is Center for South Asia Water Management for shown in Fig. 11. Peak discharge in 10 year return selecting her for the Post-graduate Study period event is 71.9 m3/s. Programme in Water Resources Engineering and Management.
6. References
Dahmen, E. R., & Hall, M. (1990). Screening of Hydrological Data (No. 49). Netherlands: International Institue of Land Reclamation and Improvement. Dahmen, E. R., & Hall, M. (1990). Screening of Hydrological Data (No. 49). Netherlands: In- ternational Institue of Land Reclamation and Improvement. Figure 10: Design Storm - 10 year return Period De Alwis, K. A., & Panabokke, C. R. (n.d.). Hand Book of the soils in Sri Lanka. Soil Scie-nce Society.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 115 UMCSAWM Water Conference – 2017
Illeperuma, O. (2001). Environmental Pollution in Sri Lanka. National Science Foundation Sri Lanka, (28(4)), 301–325. Mwakalila, S. (2003). Estimation of Stream Flows of Unguaged Catchments for River Basin Management. In Physics and Chemistry of the Earth (pp. 935–942). Panabokke, C. R., & Perera, A. P. G. R. (2005). Ground Water Resources in Sri Lanka. Wa-ter Resources Board. Ponrajah, A. J. P. (1984). Design of Irrigation Systems for Small Catchments. 2nd ed. Colombo: Irrigation Department. Ranatunga, D. G. L. (2001). Towards more Efficient Hydraulic & Hydrological Design of Cross Drainage Structures Using New De-veloped Intensity Duration Frequency Equations. “Engineer”, Journal of the Institution of Engineers, Sri Lanka.
116 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Attempting to improve seasonal performance of Land and water productivity through systematic analysis: Case study of Dahanaka Minor Irrigation Tank in Anuradhapura District of Sri Lanka P.R. Gamage and N.T.S. Wijesekera
ABSTRACT Water conservation in small and medium tanks for agriculture in dry, semi dry and intermediate zones of Sri Lanka are considered as the reason for successful rice cultivation during the period of our ancestors. However, it is often mentioned that the available statistics during last few decades also point to the lower productivity of agriculture under minor irrigation tank systems. The aim is to apply the present guideline recommendations to evaluate a typical dry zone irrigation reservoir system and to make recommendations for farmer livelihood enhancement considering seasonal performance, crop water requirements for paddy and other Food Crops (OFC) and possibilities of suitable crop diversification. System water balance is used to obtain the results in each case and financial analysis used to calculate the income of the farmers. Also it is important to maintain a database for each minor tank because more than 192,000 ha of lands are cultivated under these tanks by contributing considerably to the Sri Lanka economy. Therefore, it is important to find, what are the suitable methods that can be applied to improve the land and water productivity. KEYWORDS: Irrigation Demand, Water balance study model, Cropping Intensity
importance are highlighted in guidelines, there is a 1. Introduction void in critical applications. Therefore, the present case study is intended to contribute towards the 1.1. General industry requirement to achieve better land and Total number of minor tanks in use and abandoned water productivity. condition are about 30,000. (Medagama, 1982; Dahanaka tank is situated in Anuradhapura District FFHC 1979). According to Department of Agrarian which is the case study reservoir receives water Services, small tanks or the village tanks are those only from its own catchment and there are no other tanks, which command area not more than 80 ha. inputs from diversions and this is an ungauged There are about 8500 operational minor tanks in the reservoir. dry zone alone (Dayarathna, 1990). There are about 2. Objective 192,085 ha are under minor Irrigation system (S. Somasiri), 1987). If better water management The objective of the study is to systematically apply techniques can be identified then these agricultural the ID (1984) guideline recommendations to lands are capable of contributing to the Gross evaluate a typical dry zone irrigation reservoir National Product (GNP) while achieving national system and to make recommendations for farmer food security. Since a very large section of the rural livelihood enhancement considering seasonal population of Sri Lanka depends on minor performance, crop water requirements for paddy irrigation tanks for their livelihood, it is very and other Food Crops (OFC) and possibilities of important to make every attempt to increase land suitable crop diversification. Accordingly, the and water productivity in these systems. Reported specific objectives were as follows. cropping intensities are as low as 1.25 in minor a) To find the crop water requirement for tanks, while production is most unstable even in paddy and OFC. areas where there are tanks at a high density. It has b) To carry out an operation study to evaluate been noted that year after year, a high proportion of alternatives for land and water irrigation lands remain unutilized reportedly due to productivity. lack of water. Hence, there is an urgent need to improve the management of water availability in P.R. Gamage, IESL (Sri Lanka), AMIE (Sri Lanka), irrigation tanks of Sri Lanka to reach higher Irrigation Department, Sri Lanka cropping intensities. Water balance models are N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip versatile tools for water and land management (Moratuwa), M.Eng. (Tokyo), Ph.D (Tokyo), C.Eng., ensuring better levels of productivity. Though MICE(UK), FIE(SL), Senior Professor, Department of Civil application of water balance models and their Engineering, University of Moratuwa, Sri Lanka.
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c) To evaluate a cropping pattern to increase 3. Design the cropping intensity, increase farmer income and uplift the living standard of the Reservoir area capacity curves, field observations farmers in the area using water balance on number of times the reservoir would reach study. minimum and maximum water levels in a given year, farmer crop preferences, approximate extents 2.1. Project Area cultivated in each season from 2007 Yala to 2014 were available for the analysis. An Irrigation water The project area is located at Kahatagasdigiliya requirement study and a reservoir operation were Divisional Secretary’s Divisions (DSD) in carried out while considering the influence of Anuradhapura District. Co-ordinate of the tank is associated parameters and a variety of trial according to Irrigation Department Guideline (ID cultivation options. System water balance 1984) is F/5(12.6 *1.0). Conventional coordinates computation was assumed the guideline (ID 1984) are 8021’58” N, 80042’06”E. (figure 1). The tank is recommended coefficients for seepage, effective operated and maintained by the Koon wewa office rainfall, yield thresholds, canal efficiency and of the Department of Agrarian Development. evaporation. Aththikka-Gaha is the name of the associated The schematic diagram of the water balance model, farmer organization and it is reported that 130 which is applied to the system shown in Figure 2. Acres of land is cultivated under this tank. Evaporation Table 1: Basic Data of Dahanaka Tank Data Type Description Irrigable Area Rainfall Catchment Area 2.1 sq. miles Location Lat. 8 21’58” Lon. 800 42’06” Return Flow Capacity at FSL 391 Ac.ft. Inflow Tank Outflow Length of the Bund 945 m B.T.L, 107 m M.S.L. F.S.L. 106.42 m M.S.L. Seepage H.F.L. 106.8 m M.S.L. B.T.L, 107 m M.S.L. Figure2: Schematic Diagram of the water Balance Model Side Slope 1:2 Table 2: 75% probability rainfall Month 75% Month 75% probability probabilit rainfall(m y m) rainfall(m m) October 127 April 127 November 152 May 51 December 127 June 13 January 76 July 0 February 25 August 13 March 51 September 25
Figure 1: Study area showing Dahanaka Tank
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Table 3: Data used for the Study Data Source Water balance for the system was carried out in 1:50 1:50,000 topo maps Department of Survey order of magnitude evaluation of the system components. Water balance was done for both Monthly 75% Irrigation Department seasons in a typical water year. probability rainfall Guidelines Crop factors & growth Irrigation Department The reservoir water balance was done, considering stages Guidelines Inflow, Irrigation Demand, Seepage, Evaporation Reservoir Bed Survey DI’s office Anuradhapura and Farm Losses. The water balance was computed Monthly Evaporation Irrigation Department using equation (1). Data Guidelines Storage at the beginning of the month +Inflow to the Monthly rainfall Hydrological Annual, Reservoir - Evaporation - Seepage - Irrigation Irrigation Department Demand- = Storage of the Reservoir ------(1) Cultivation Department of Agrarian performance previous Development years Si + I – EP – SP – D = Se Economic data CIC Institute of Agro business, November 2010
Table 5: References and Assumptions used for the system water Balance
Description Purpose for Water Balance Reference/Assumption Inflow to Reservoir and calculate Field 1 75% Probability rainfall Irrigation Requirement. ID(1984) 2 Runoff Coefficient as 0.3 Calculate monthly yield ID(1984) 3 Evaporation (Pan Evaporation) Reservoir Evaporation ID(1984) 4 Water Release for Land Preparation Field Irrigation Requirement ID(1984) 5 Farm Losses Field Irrigation Requirement ID(1984) 6 Conveyance efficiency as 60% Water Demand from Reservoir ID(1984) 7 Effective Rainfall Inflow calculation and Irrigation Requirement ID(1984) 8 Seasonal Yield from Iso Yield Curves To calculate monthly yield ID (1984) 9 Yield Thresholds as 35% and 7.5% To adjust the specific yield ID (1984) 10 Initial storage as MOL To take the storage at ID (1984) Calculate the seepage volume from the 11 Seepage Losses - 0.5% of Storage reservoir ID (1984) Crop factors for Paddy and Other Food 12 Calculate Irrigation Demand ID (1984) Crops 13 Depth Area –Capacity curve To calculate the seepage, evaporation
5. Farm losses are assumed as 152 mm. 3.1. Assumption Made during the Study 6. Conveyance efficiency is assumed as 60% Lack of adequate measured data required the 7. Seepage Losses - 0.5% of Storage present study to make assumptions to evaluate the 8. Crop Factors for Paddy and Other Food system. Therefore, recommendations made by the Crops ID (1984) and other appropriate for the situation 9. Effective Rainfall were used for the system evaluation. Assumptions 10. Initial storage is at Minimum Operation made during the study are as follows. Details are Level (MOL) given in table no 5. 1. 75% Probability rainfall values are from the ID (1984) 2. Runoff Coefficient for calculation of inflow to the tank is assumed as 0.3. 3. Evaporation Data based on the values in ID (1984). 4. Water Requirement for land preparation is assumed as 172mm for 15 days.
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4. Result and Discussion ha.m, Minimum Operating Level is 105.3 m MSL Reservoir water balance was done for different 2) Reservoir filling once in two years and cropping pattern and did economic evaluation to reservoir empting is twice in one year find the best option. according to the data collected from the Koon Weva office of the Department of Agrarian Development. Table 4: Option privatization for the water balance model 3) Spilling months are November and Option Irrigable Income December. Number Crop Type Area (Ha.) (Rs.Mn ) 4) Minimum inflow months are March, April, 1 105 Days Paddy 16.47 3.4 June, July and August. 2 90 Days Paddy 19.59 3.6 3 Soya Beans 20.0 4.5 4.3. Cultivation Extents 4 Cowpea 23.15 2.8 1) We can cultivate both seasons with paddy 90 days Paddy 5 and Soya beans 19.59 4.1 to a cropping intensity (CI) of 1.32 90 days Paddy 2) Water utilization for paddy both seasons 6 and Cowpea 20.03 3.3 1.92m/season/ha for Yala and 1.79 m 105 days Paddy season/ha Maha from reservoir when 7 and Soya 18.70 4.0 effective rainfall is taken into 105 days Paddy consideration. 8 and Cowpea 17.81 3.2 3) Max cropping intensity can be achieved is 1.5 with cowpea for Yala season and paddy 4.1. General: Command area for the Maha season. Water utilization 1) Soya Beans and Cowpea were the OFC during max cropping intensity is crops preferred by the farmers while the 90 1.39m/season/ha Yala and 1.79 m/season days paddy and 105 days paddy were the /ha for Maha from reservoir when varieties cultivated in Yala and 135 days effective rainfall is taken into paddy for Maha seasons. consideration. 4) Comparison of farmer financial status was 2) For the existing situation, Reservoir carried out for the all options by doing operation study was carried out for paddy income expenditure analysis, to select both Yala and Maha seasons. suitable options. Cultivation of paddy only for both seasons income is nearly 3.5 3) Cultivation Extent for Maha season is 44.52 million rupees for Yala season only. ha and the Irrigation water requirement is Maximum income is generated from Yala 1790 mm. For Yala season, average season is 4.51 million rupees with soya cultivation extent is 19.15 ha and the beans. Irrigation Water Requirement is 1658 mm. 5) Comparison of food security, maximum Peak months for water requirements in yield received for the Yala season is 105 Yala season are June and July while days paddy for Yala season. October and January are for Maha season. Peak requirements for Yala and Maha 4.4. Options Prioritization seasons, when cultivating paddy for both 1) Considering Income only, it is most seasons 526 mm and 490 mm. suitable to cultivate Soya Beans for Yala
season cultivation. It can be cultivated 21.3 4) Difficulties in the assumptions Ha of Soya Beans. Canal efficiency based on field inspections and the 2) Considering Income and cultivation extent guidelines given in the Guidelines ID -1984, in Yala season, it is most suitable effective rainfall and 75% probability rainfall are combination of Soya Beans and 105 days based on Guidelines ID -1984. Farm losses are also paddy. 19.59 Ha can be cultivated it is the based on Guidelines in ID -1984. After applying, the 2nd highest extent can be cultivated. all values, results should be checked and verified 3) Cultivation extent is highest for only using the actual cultivation data from the office and Cowpea is cultivated in Yala season. but by Google maps. income is less.
4.2. General - Reservoir 5. Conclusion and Recommendations 1) Average Seasonal inflow in Yala Season There should be a good database for each minor 43.09 hectare meter and Maha Season tank to evaluate alternatives, which are helps to 104.99 hectare meter Dead Storage is 0.52 increase the land and water productivity. Considering the climate change in Sri Lanka water
120 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 scarcity will be the major problem and it will cause arise the problems in food security also. According to the recent data, more than 5000 Acres of lands have been fully destroyed in Ampara District, 1000 acres in Anuradhapura District and large amount in other Districts due to prevailing drought. Storage of considerable number of major and medium tanks become 26% of capacity at Full Supply Level in mid of January 2017. The condition of minor tanks are worst compare to major and medium tanks in Sri Lanka. This is the time we have to introduce Other Food Crops to farmers with low Irrigation Requirement. Depth Area capacity curve to be developed for each minor tanks to do a better study and also the actual quantity of lands cultivated under these minor tanks separately.
5.1. Recommendations 1) Farmers should be trained and aware on OFC cultivation. Training should be carried out to change their habits. 2) Land preparation and land soaking should be done rainwater if possible. 3) For selling agricultural products there should be suitable convenience method. 4) Database for each minor tanks should be maintained to achieve better land and water productivity.
6. Acknowledgement
The authors are grateful to the UNESCO Madanjeet Singh Center for South Asia Water Management for the great contribution to pursue the Post Graduate Studies in Water Resources Engineering and Management. Encouragement, and the necessary data provided by Irrigation Department of Sri Lanka is also gratefully acknowledged.
7. References
Design of irrigation Head works for small catchment by Eng. A.J.P.Ponraj in 1984 Technical Guidelines for Irrigation works Source: Hand Book on Cost of Production Vegetables, Grains and Pulses, CIC Institute of Agribusinesses, November 2010 Small tank system in Sri Lanka: Issues and consideration by C.R. Panabokke, M.U.A. Tennakoon and R.de. S. Ariyabandu Physical and Hydrological Aspects Different scholars have made different estimates of the number of small tanks in Sri Lanka.
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122 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Climate Change Impacts and Adaptation Measures in Giritale Reservoir in Polonnaruwa Sri Lanka
M.Kamran and N.T.S. Wijesekera
ABSTRACT Climate change is one of the most important global environmental challenges, which affects the overall system by affecting food production, water supply, health, energy, etc. For study purpose Giritale reservoir in Polonnaruwa district of dry zone in Sri Lanka was selected. Catchment area of the reservoir is 24.3 sq.km and command area is 3075 ha. Data for the reservoir was collected from irrigation department, Colombo and 6 year (2010-2015) rainfall data collected also from irrigation department. This study investigated the impact of climate change, adaption and mitigation measures reservoir system. After a review three scenarios were identified. Scenario 1 rainfall increase 15.8% and temperature increase 8% and scenario2 rainfall increase 14% and temperature increase1.6% and scenario 3 is rainfall is projected to increase by 48% for the Southwest Monsoon by 2050 and Northeast Monsoon, which occurs in the drier northern region, is predicted to decrease by 27–29%. For the worst scenario four adaptation measures were proposed. Among the four only two adaptations could be quantified, and the best adaptation measure was identified. Among scenario option’s, the scenario 2 is the worst scenario and adaptation measure taken for scenario2consist of two options. Option1 is changing the crop type and option 2 is increasing the canal efficiency. For option 1 105 days paddy for Maha and Yala was taken and also green gram for both Maha and Yala was considered and for option2 canal efficiency increased by 10% . Therefore comparing the results adaptation use of green gram improved the cropping intensity by 13%.For verification of result actual rainfall data is not enough and also for predicting the climate trend. Future climate projections indicate that the climate is changing and impacts on agriculture sector can be expected and Worst climate change scenario for the Gritale scheme is when increasing rainfall 14% and also increase the evaporation 6.4%. KEYWORDS: Climate change, Irrigation scheme, Adaptation
15%.More than half of Sri Lankan food grain 1. Introduction production is dependent on irrigated rice. Sri Lanka depends primarily on its surface water Sri Lanka is situated between 6 and 10 degrees to resources for agricultural, domestic and industrial the North of the equator has predominantly uses. Amarasinghe et al. (1999) described that one monsoonal and tropical climate. A recent review by half of all Sri Lanka rivers have either zero or IWMI on the status of climate change negligible flow during the Yala (dry) season. research/activities in Sri Lanka suggests that Sri Agriculture in Sri Lanka is largely sustained by Lanka’s mean temperature by the year 2100 may direct rainfall and irrigation water extractions from increase by about 0.9-40 °C over the baseline of rivers. However according to Basnayake (2008); 1961-1990, this accompanying change in the Basnayake et al. (2004); Basnayake and Vithanage quantity and spatial distribution of rainfall. So (2004b); De Silva (2006b) it is difficult to conclude therefore it is likely that these impacts significantly about climate change impacts on water resources affect Sri Lanka’s food production, water supply, due to contradicting rainfall projections. Economic energy production, fisheries and infrastructure etc. and Social Survey of Asia and the Pacific (2010) Agriculture accounts for a little over 20 percent of stated that climate change certainly would set GDP and provides nearly 70 percent of the rural serious impacts on the food insecurity and employment. Irrigation is the major user of fresh vulnerability patterns and Sri Lanka would be one water consuming over 90 percent of the total annual of the of food insecurity hotspots in the Asia-Pacific captured water. The competing demand for water region .Therefore present work carried out a study from other water-use, sectors (domestic, industrial, to evaluate the potential impacts on agriculture in hydro-power and environmental needs) are continuously undergoing an increasing trend. M. Kamran Research Assistant & post graduate (Water According to the International Food Policy resource engineering and management) scholar in Research Institute (IFPRI) climate change impact UMCSAWM, University of Moratuwa, Sri Lanka BSc.(Civil Engineering), Pakistan had been on agriculture and costs of adaptation forecast that by 2050 rice prices will increase N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., between 32 and 37% climate change also… in rice MICE(UK), FIE(SL), Senior Professor, Department of Civil yield losses in rice could be between 10 and Engineering, University of Moratuwa, Sri Lanka.
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Sri Lanka by carrying out a study of Gritale Tank in The Sri Lanka Country Report on Climate Change Polonnaruwa district and this study expects to (ADB, 1994) has shown that the increase in contribute towards water management in temperature by 2070 will be in the range of +0.4 °C agriculture sector and develope water management to +3.0 °C. As per the rainfall predictions, the Wet policy for food scarcity under climate change Zone will record 10% increase per year in both dry scenario. and wet seasons. Basnayake, (2008) stated that unlike in the case of temperature, no clear pattern 2. Literature Review or trend has been observed in precipitation. Some researchers, comparing the mean annual Jayatillake et al. (2005) stated that though there had precipitation of recent and earlier periods, suggest not been a significant trend in Sri Lanka’s mean that average rainfall is showing a decreasing trend. annual rainfall (MAR) during the past century, a According to Chandrapala (1996), temperature higher variability is evident. Shantha and increase of 0.016ºC per year between 1961 and 1990 Jayasundara (2005) have also observed a 39.12 % is observed in Sri Lanka. decrease in MAR in the Mahaweli upper watershed from 1880 to 1974. Bandara and Wickramagamage 3. Methodology (2004) reveal that rainfall on the western slopes of the central highlands has declined significantly For the Gritale Tank water balance calculations 75% from 1900 to 2002 due to reduced SWM rainfall (this probability rainfall data was used as recommended region has the highest MAR in the country, often in irrigation guide line (1984). Actual rainfall value exceeding 5,000 mm). In the country as a whole, the compared with 75% probability rainfall for number of consecutive dry days has increased feasibility study. Irrigation model was developed while the number of consecutive wet days has for 75% probability rainfall and the behaviour of reduced (Ratnayake and Herath, 2005; Premalal reservoir of model was checked and verified with 2009). actual rainfall and field data. A literature survey was carried out to find probable climate variations According to Chandrapala (1996), a temperature expected future and then irrigation demand and increase of 0.016ºC per year between 1961 and 1990 cropping intensity for each scenario was compared has been observed in Sri Lanka but according to to identify the worst climate scenario for the scheme IPCC (2007),this is higher than the global average after that for critical scenario adaptation measures rate of 0.013°C per year for the period 1956 to 2005 proposed for agriculture and food security. Sri Lanka’s 100 year warming trend from 1896 to 1996 is 0.003°C per year, while it is 0.025°C per year 4. Data and Study Area for the 10-year period of 1987-1996.Basnayake et al. (2002) described that Seasonal mean temperature Actual rainfall data collected from irrigation for the agricultural seasons Yala (April - September) department from 2010-2015 for Giritale reservoir. and Maha (October – March) also display similar For the present study area capacity curve and tank warming. Zubair et al. (2005) indicates that highest data were collected from irrigation department warming trends in the country have been observed Colombo. Crop factor and growth stage, in Anuradhapura and Badulla. evaporation and seepage loss data were obtained Manawadu & Nelun, (2008) described that climate from the Irrigation Department guideline (1984). change will alter runoff patterns in cold and Giritale reservoir in Pollonnaruwa district of Sri mountainous regions; increasing evaporation with Lanka’s was selected in dry zone. Catchment area implications for significant changes in runoff of the reservoir is 24.3 sq.km and command area is variability. Parry & Canziani, (2007) stated in IPCC 3075 ha. Location of the tank is shown in the Figure report 2007 that there is evidence to suggest that the 9 climate of South Asian region has already changed. According to Manawadu & Nelun, (2008) the number of rainy days has decreased at all meteorological stations except for the Nuwara Eliya station while shrinking the 2000mm isohyet – demarcating the wet zone of the country. Herath and Ranayake (2004) revealed that the First inter- monsoon period shows the highest decrease in rainfall and in addition to this the numbers of rainy days have reduced giving rise to an increasing rain intensity trend. De Silva, (2009) using a climate modeling study that, the North-East monsoon rains are predicted to Figure 9: Study area decrease by 34% (A2, the scenario showing the worst impact of climate change-) across the country.
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5. Analysis
In this study for analysis three climate scenarios were selected. Following three scenario were selected Scenario 1: Ahmed and Supachalasai (2014), based on a RCM, predicted that by 2050.temperature and rainfall could rise by 1.8 °C and 15.8 % respectively under A2, scenario. Result of scenario 1 is shown in figure 2. Scenario 2: De Silva (2006b) predicted increases of 1.6 °C under A2 and 1.2 °C under B2 by 2050 and Figure 12 :Predicted scenario 3 that such increases will be mainly in the north, north-eastern and north-western regions (all within 5.1. System water Balance the dry zone). Also De Silva (2006b) elaborates that I − (퐸 + 푆 + 푆 + 퐷 ) = 푆 − 푆 (1) these increases will be 14 % for A2 and 5 % for B2 푡 푡 푒𝑖 푝푡 푡 푡 푡−1 In equation (1) I is the monthly inflow and t is the by 2050 with reference to 1961-1990. . Result of t time step in month, E is the evaporation from the scenario 2 is shown in figure 3. t reservoir, Sp is the spillage from the reservoir, D is Scenario 3: According to WMO by 2050 rainfall is the irrigation, St is the storage at the end of time step projected to increase by 48% for the Southwest and St−1 is the storage at the beginning of time step. Monsoon and for the Northeast Monsoon, the occurs in the drier northern region, the same is 5.2. Irrigation demand predicted to decrease by 27–29%. Result of scenario 3 is shown in figure 3 For calculation of irrigation demand following equation is used
(FWR) = (퐿푃) + (퐸 ) + (퐹퐿) 푡 푡 푡푐 푡 푡 (2)
(FIR)t = (FWR)t − (ER)t (3)
(퐅퐈퐑)퐭 = (퐅퐈퐑)퐭/퐧 (4) In these equations, t is the considered as time step in month, FWR is the field water requirement, ER is the effective rainfall, D is the irrigation demand, n is the project efficiency and FL is the water requirement to compensate for farm losses, LP is the water requirement for land preparation and Etc is the water requirement for crop evaporation.
Figure 10: Predicted scenario 1 6. Results
6.1. Irrigation demand for present situation Irrigation demand for situation Irrigation demand is calculated for present situation for each month for 135 paddy days and 105 paddy days cultivation for Maha and Yala season respectively and then compared with Actual rainfall. Comparisons of irrigation demand are shown in figure 5.
Figure 11: Predicted scenario 2
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temperature increased by 1.6 °c and rainfall is increased by 14% for A2 scenario by a 2050. In this scenario it was assumed that 10% reduction of diversion flow was taken due to climate change. In the 3rd scenario rainfall increased by 48% for Southwest monsoon by 2050 and in North West decrease of 29% was assumed. The result of water balance of each scenario is shown in figure 8 and figure 9
Figure 13: Irrigation demand
6.2. Present situation in Giritale Reservoir For present situation 75% probability rainfall and diversion inflow is used as an input into the system and monthly storage at the beginning is taken as 1333.1 Ha.m and irrigation demand is calculated for 135 days paddy in Maha and 105 days paddy in Yala seasons. The result shows in Figure 6 and then verified model with actual rainfall data as shown in figure 7. It showed that reservoir spill two times in Figure 16: Catchment yield for Yala season under once a year with actual rainfall data and then once climate scenario time it is near to the minimum operating level.
Figure 17 : Catchment yield for Maha season under Figure 14: Reservoir operation of present situation climate scenario Reservoir operation of present situation with 75% probability rainfall It could be observed that for scenario 1, 2 and scenario 3 the specific yield is the same and that this increases in Maha season and decreases in yala season.
6.4. Irrigation demand Irrigation demand was calculated for each scenario assumed 135 day paddy for Maha season and 105 day paddy for Yala season. The figure10 shows that the irrigation demand is increased for scenario 2.
Figure 15: Reservoir operation of present situation with actual rainfall
6.3. Identification of critical scenarios In scenario 1, temperature increase by 1.8 °c and, 15.8% rainfall increase under A2 scenario in this scenario it was assumed that by increase 2 °c in temperature increased evaporation by 8% and also diversion gets reduced by 10 % and in Scenario 2
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1. Early Warning Systems (EWS) 2. Crop Diversification (CD) 3. Education on Water Management (EWM) 4. Increasing the System Efficiency (ISE) With crop diversion method two crops were selected: 105 day paddy for Yala and 105 day paddy days for Maha season and the other crops green gram. For system efficiency option canal efficiency is increased by 10 %. The adoption result in the figure 12 shows that the best option is green gram which increasing the cropping intensity up to 1.5.
Figure 18: Irrigation demand for each scenario
6.5. Cropping Intensity
Cropping intensity and cultivation extent for each scenario was calculated. Result show that for scenario 2 cropping intensity is less and for Maha season the cultivation extent is less .Therefore this result shows in table1 and figure 11 that scenario 2 is the worst scenario.
Table 5: Cultivation extent and cropping intensity for each scenario
Figure 20: Cropping intensity after adaptation
Scenario Scenario 1 Scenario 2 Scenario 3 8. Conclusion and Recommendation
Cultivation 1) Future climate projections indicate that the extent for 81 80 100 Maha (Ha) climate is changing and impacts on Cultivation agriculture sector can be expected extent for 47 47 47 2) Worst climate change scenario for the Yala (Ha) Gritale scheme is when rainfall increases by 14% with an increase of evaporation Cropping 1.28 1.27 1.47 intensity by 6.4% 3) Worst climate scenario will reduce the cropping intensity of from 1.46 to 1.27. 4) Population growth in the future is also expected to increase and hence a food scarcity is predicted in the future 5) Implementing adaptation options for future is essential for Gritale scheme 6) Crop diversification is the most suitable option to minimize the impacts in the scheme 7) Farmer education on water management for farmers and increasing conveyance of efficiency of the system would minimize the climate impacts of the worst climate scenario Figure 19 : Cropping intensity result for scenario 9. Acknowledgements 7. Climate change adoption The authors are grateful to the UNESCO Madanjeet Following four adaptations method were selected. Singh Center for South Asia Water Management For evaluation crop diversification crop diversion and the South Asia Foundation for conducting the and increasing the system efficiency increase were international masters degree program in water quantified and compare. resources engineering and management. The
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 127 UMCSAWM Water Conference – 2017 support given by the Irrigation Department of Sri Food Security, and Climate Change in Sri Lanka, 2, Lanka by providing necessary data tis also 99. acknowledged. (Helfer, Lemckert & Zang, 2012). Impacts of climate change on temperature and evaporation from a 10. References large reservoir in Australia. Journal of Hydrology, 475, 365–378. Basnayake, B. R. S. . (2008). Climate Change inThe IPCC. (2014). Summary for Policy Makers: In National Atlas of Sri Lanka. Survey Department of Climate Change 2014: Impacts, Adaptation, and Sri Lanka, Colombo, Sri Lanka, 54–55. Vulnerability. IPCC. De Silva, S. S (2009). Climate change and Manawadu, L., & Nelun, F. (2008). CLIMATE aquaculture: potential impacts, adaptation and CHANGES IN SRI LANKA. mitigation, 151–212.
Eriyagama, N., & Smakhtin, V. (2010). Observed Parry, M. ., & Canziani, J. . (2007). IPCC Fourth and projected climatic changes, their impacts and Assessment Report: Climate Change 2007 (AR4). adaptation options for Sri Lanka: a review. Proceedings of the National Conference on Water,
128 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Possibility of Increasing the Land and Water Productivity of Command Area in Labunoruwa Irrigation Tank, Anuradapura, Sri Lanka M.B. Sharifi and N.T.S. Wijesekera
ABSTRACT In Sri Lanka, farmers prefer to grow paddy because it is their staple food. The most common reason given for the shortfall is the lack of sufficient irrigation water to rescue crop when the rainfall is lean. The lack of irrigation water is dependant of two aspects. One is the lack of storage and the other is the poor water management. Out of the two, the latter is considered very important because it is an activity that can be easily influenced from the first day of recognition. Therefore, the aim of this study is to carry out a systematic case study application demonstrating the potential to investigate the possibility of increasing land and water productivity through the management of crop types (Paddy, green gram, soya bean and cowpea) grown in each season. Irrigation department guidelines were used for computation of irrigation demand, evapotranspiration requirements and selection of the value of crop growth stages, crop factors and land preparation for Maha season and Yala season with 105 days and 135 days duration for paddy and OFC respectively. Land preparation water requirement, farm loss and the project efficiency were assumed as uniform inputs for all spatial units. Reservoir water balance model based on Irrigation Department guideline was applied to determine the smallest capacity of reservoir that would be required for cultivation of the largest required irrigable area for a pre-determined cropping pattern and intensity for both seasons. After computation of irrigation demand and reservoir water balance modeling, it was found that in all four options, full command area (100%) could be cultivated while in Yala season this result differs as follows. In option 1, paddy was considered for 16% of the command area, while in option 2 this cultivation could be as 10 % of the command area paddy and 28% of the command area green gram. In option 3 and option 4, the cultivable areas were found as 10% for paddy along with 19% for soya beans and 10% for paddy along with 21% for cowpea respectively. Consequently, the second option in which 10 % of the command area was considered for paddy and 28% of the command area for Green Gram was found as a best option to be practiced under Labunoruwa Irrigation Tank in order to increase the water productivity. KEYWORDS: Irrigation, Water Productivity, Irrigation demand, Crop changing, Paddy & Green Gram, Labunoruwa Tank Sri Lanka
a water crisis, characterized by water scarcity and 1. Introduction competition, pollution and malnutrition (Molden, 2003). Experts’ estimates Water availability plays an important role in That demand for food crops will double during the agricultural. The world population is growing at a next 50 years with limited land and water resources, fast rate resulting in rising demand for household farmers need to increase their output from existing and irrigation water. Therefore, in the past decades cultivated areas to satisfy the food demand of irrigation water supply systems are under huge increasing population. Irrigation systems will be pressure in fulfilling the irrigation water essential to enhance crop productivity in order to requirement (Khan et al. 2009). Water resources can meet future food needs and ensure food security. play a significant role in improving food security However, the irrigation sector must be revitalized and household income. Irrigation is the most to unlock its potential, by introducing innovative common means of ensuring sustainable agriculture management practices and changing the way it is and coping with periods of inadequate rainfall and governed. (G. Pakhale et al, 2011). drought (Dessalegn, 1999). Food security is becoming a major issue in today’s society and Irrigation management is normally defined as “a irrigated agriculture is in the center of this process by which institutions or individuals set discussion not only because it constitutes objectives for irrigation systems, establish approximately 20% of the world’s total cultivated appropriate conditions and identify, mobilize and farmland, but mainly because it responds for 40% use resources so as to attain these objectives of the food and fiber production (Hoffman and Evans, 2007). In the 20th century, worldwide irrigated area experienced a huge expansion of M.B. Sharifi, Hydrology Adviser, CTI Engineering more than 500% with an increasing from 40 million International Co., Ltd, Kabul, Afghanistan to 270 million ha of irrigated land. Such numbers N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip are part of the ability of humankind to produce food (Moratuwa), M.Eng. (Tokyo), Ph.D (Tokyo), C.Eng., fast enough to meet population growth. But that MICE(UK), FIE(SL), Senior Professor, Department of Civil remarkable ability, on the other hand, has its cost – Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 129 UMCSAWM Water Conference – 2017 while ensuring that all activities are performed productivity ranges between 0.2-0.5 kilograms without causing adverse effects” (IIMI, 1992). (kg)/cubic meter (m3), the irrigation efficiency at Participatory irrigation management has been systems level is about 35-45% (IWMI, 2010). In Sri considered as the driving force in the effective and Lanka water schedule preparation and planning is efficient irrigation management by participating done using the guidelines of the Department of and involving the farmers in planning, operation Irrigation (Ponrajah,A.J.P, 1988). and maintenance of the irrigation system (Gulati et In this case study, full command area cannot be al. 2005). Farmer- managed irrigation systems are cultivated in Yala seasons therefore it will affect found in varied environments and exploit a wide living standard due to low income hence, to study range of technologies to take advantage of different the possibility of increasing land and water types of water sources for production of a diversity productivity of the scheme, irrigation management of crops. All these irrigation systems, however, plays an important role because a better use of require that certain indispensable tasks be water not only supports more area to be reliably accomplished if the system is to function cultivated but also keeps the farmers secure. productively (Edward and Robert, 1987). Small multi-purpose reservoirs are a widely used form of 1.1. Study Area infrastructure for the provision of water. They Labunoruwa Tank is situated in Anuradapura supply water for domestic use, livestock watering, district of Sri Lanka. Its geographical coordinate is small scale irrigation, and other beneficial uses. Latitude 80 9’ 55” and longitude 800 36’ 38”. The Although clusters of reservoirs store significant tank is fed from rain through 7.55 km² of catchments quantities of water and effect on downstream flows, area and its water is used for paddy cultivation of they have rarely been considered as systems, with around 259 Ha of command area in Yala and Maha synergies and tradeoffs resulting from their seasons. numbers and their density. (Simonne et al, 2012). Sri Lanka has an average production of Paddy reaching 3,876,000 MT per annum (Department of Census and Statistics Sri Lanka [DCS], 2008). The rural economy in Sri Lanka has revolved around paddy cultivation. Rice forming is not merely a livelihood; it is considered a way of life. With the advent of colonial rule, the domestic agriculture sector, especially farming in the dry zone areas was neglected. Historically the minor tanks have played a vital role in cultivation of crops in the dry zone of Sri Lanka, due to lack of maintenance of the head- works and distribution systems. Sri Lanka’s dry zone consists of a vast number of minor reservoirs called village irrigation tanks Wijesekera (2011). He has quoted Fernando (1982) reports that there had been 35000 minor reservoirs in the island and more were being discovered. Theses reservoir are the pivotal point of dry zone farming communities. Sivayoganathan et al (2003) quoting, Merry et al (1988), reports that Irrigation systems under gravity irrigation in Sri Lanka can be categorized according to the size, water source and management. Major irrigation system is defined as one that has a command area of more than 1000 ha and medium schemes between 80 and 1000 ha. Small tanks or minor irrigation systems are those having an Figure 1. Area Map irrigated command area of 80 ha or less. Presently average duty of water use in Sri Lanka is 2. Approach and Methodology approximately 1300 mm in the Maha season and 1770 mm in Yala the season (Imbulana & Merrey, 2.1. Data Collection 1995). There are over 600,000 hectares (ha) of 75% probable monthly rainfall, evaporation, irrigated farmland in Sri Lanka. Cultivation takes reference crop evapotranspiration and yield map place during the two seasons with an average for Maha and Yala seasons were collected from Eng. cropping intensity of 1.65. The main irrigated crop A.J.P. Ponarajah’s book (Head works for small in the country is paddy (94% of irrigated area), with catchments), while tank data, crop data and an average yield of 4.3 tones (t)/ha, and a surplus is catchment data were collected from Irrigation being produced at the moment. While the current department. The prepared spreadsheets (based on
130 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Irrigation Department guideline) by Pro. depending on its crop development stage would N.T.S.Sohan.Wijesekera were used for reservoir require an amount of water as irrigation demand, operation and calculation of irrigation water given the land preparation requirements, farm requirement. losses and project efficiencies. Leading equations used for the computations are as follows. 2.2. Methodology (FWR)t=(LP)t+(ETc)t+(FL)t …………..….. (1) a) The required data was collected. (FIR)t=(FWR)t-(ER)t ………………... (2) b) Situation analysis was done to know about (ID)t=(FIR)t/ƞ ……………...…. (3) the past and current performance of the n area. (ID)seasonal =∑t (ID)t …………....… (4) c) Water requirements for different crops and paddy were calculated. In these equations t is the time step for computation d) Reservoir operation was done to determine and n is the number of time steps per period. FWR the smallest capacity of reservoir that is field water requirement, LP is water requirement would be required for cultivation of the for land preparation, ETc is the water requirement largest required irrigable area for a pre- for crop evapotranspiration and FL is the water determined cropping pattern and intensity requirement to recompense for farm losses. FIR is for both seasons. the field irrigation requirement, ER is the effective e) Crop patterns were changed to find the rainfall, ID is the irrigation demand and ƞ is the maximum area to be cultivated in Yala project efficiency. season. f) All options were evaluated and finally the Rainfall and evapotranspiration data were taken as best option was found and proposed to be input for model computations. Crop types were practiced in order to get more productivity selected by farmers for both seasons Land with less water consumption. preparation water requirement, farm loss and the project efficiency were assumed as uniform inputs 3. Analysis and Calculations for all spatial units since no spatially distributed data on crop types, planting dates etc., were 3.1. Cultivation Performance available.
Full command area is being cultivated in Maha There are two types of paddy cultivation in Sri season while in Yala season the full command area Lanka. These are with 105 days and 135 days cannot be cultivated due to water shortage. Since duration and are recommended for Maha and Yala the farmers prefer the cultivation of paddy over seasons respectively (Ponrajah, 1988). Accordingly other crops in both seasons therefore, they cannot the irrigation demand was computed for Maha get sufficient producs in Yala season due to less season and Yala season with 105 days and 135 days products. The crop intensity in Yala season is duration respectively. In the OFC cultivation area, maintained in Figure 2. it was assumed that the same crop was cultivated and these crops were taken as green gram, soya 1.6 bean and cowpea. For the computation of temporally distributed evapotranspiration 1.2 requirements, the value of crop growth stages and crop factors given in the Irrigation Department 0.8 guideline were used. According to the irrigation department, information for land preparation work given in the ID guidelines are generally used for
Crop Intensity Intensity Crop 0.4 irrigation system planning and design in Sri Lanka, and, therefore the ID guidelines for land 0 preparations were used and land preparation for 2008/092009/102010/112011/122012/13 the Maha and Yala seasons was taken to commence Time (Year) in the months of October and May respectively.
3.3. Reservoir Operation Figure 2. Crop intensity from 2008 to 2013 An operation study is carried out for Labunoruwa Tank to forecast the performance of cultivation 3.2. Calculation of Irrigation Demand under the tank in Maha and Yala season and to An irrigation water demand model in monthly time monitor the water management. In other word, step according to the irrigation department reservoir operation was done to determine the guideline was applied for selected crops. Because, smallest capacity of reservoir that would be each crop has a specific crop water requirement required for cultivation of the largest required
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 131 UMCSAWM Water Conference – 2017 irrigable area for a pre-determined cropping Irrigation Requirement for Option 1 pattern and intensity for both seasons, considering 600 to changes in inflow from rainfall, evaporation on reservoir water, irrigation demand due to crop 500 Maha season water requirements of paddy for Maha season and 400 paddy along with one OFC for Yala season. Model computations were based on reservoir water 300 Yala balance systems described in the guideline of 200 season Irrigation Department (ID 1984). Leading equation for water balance of reservoir system is shown in 100 equation 5. (mm) Requirement Irrigation 0 It - (Et + Sei + Spt + Dt) =St - St-1 ...... … (5) Oct Dec Feb Apr Jun Aug In this equation, t is the time step which was considered as one month, I is the inflow, E is Time (month) evaporation from water surface, Se is the seepage from the reservoir bed, Sp is the spillage from the Figure 3: Irrigation Requirement for Option reservoir. Irrigation Requirement for Yala Season (Option 1) After reservoir operation it was found that, full command area (100%) can be cultivated in Maha 600 season but, in Yala season full command area cannot be cultivated due to water shortage. 500 Therefore to increase the water productivity in Yala 400 IR in Yala season, crop types was changed and the Season (Paddy) investigation was done for the following four 300 options to find the best option. In option one paddy 200 IR in Yala was selected and it was found that 16% of the (mm) Requirement Irrigation season (paddy) for 16% of Area command area could be cultivated due to the water 100 availability. For option 2, option 3 and option 4, for 0 10% of the command area paddy was allocated and May Jun Jul Aug Sep for the rest of water different crops were selected as follows. Accordingly, for option 2, option 3, and Time (month) option 4; green gram in 28% of the command area, soya bean in 19% of the command area and cowpea Figure 4: Irrigation Requirement in Yala Season (Option 1) in 21% of the command area could be cultivated 4.1.2. Option 2 respectively. In this option for Yala season, paddy along with 4. Results and Discussion green gram was considered (shown in Figure 5). Accordingly the irrigation demand was calculated 4.1. Calculation of Irrigation Demand as 1860.56 mm for Yala season. The irrigation demand for Yala season (Figure 6) for the 10% In Maha season, full command area can be paddy and 28% green gram was found as 47.96mm cultivated while in Yala season it cannot be and 57.75 mm respectively cultivated and differs due to water shortage. Irrigation Requirement for Option 2 Therefore, different types of crops were considered 1000 for Yala season to find the option with less water 900 consumption and more productivity. The irrigation 800 demand for all four options for paddy cultivation in 700 Maha Maha season was calculated as 1054.58 mm, and for 600 season Yala season it was found as 1860mm. 500 400 4.1.1. Option 1 300 Yala 200 season In this option paddy was considered. Accordingly 100
the irrigation demand was calculated as 1860.56 0
Irrigation Requirement (mm) Requirement Irrigation
Jul
Jan
Jun
Oct
Feb Sep
mm for Yala season. In Yala season for 16% of the Apr
Dec
Mar
Nov Aug May area this value was found as 76.73 mm. Irrigation requirements for option 1 for both season and for Time (month) the cultivable area are indicated in Figure 3 and Figure 5: Irrigation Requirement for Option 2 Figure 4 respectively.
132 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Irrigation Requirement for Yala Season (Option 2) 1054.98 were the calculated irrigation requirement 30 for Yala and Maha seasona respectively. The irrigation requirement for Yala season for the 25 cultivable area of 10% paddy and 21% cowpea were IR in Yala found as 47.9 mm and 61.1 mm respectively. Figure 20 season (paddy) 9 and Figure 10 show the irrigation requirement for for 10% of Area 15 option 4 and Yala season respectively. Irrigation Requirement for Option 4 10 IR in Yala 1200 season (Green 5 gram) for 28% 1000 Maha Irrigation Requirement (mm) Requirement Irrigation of Area 800 0 season May Jun Jul Aug Sep 600 Time (month) 400 Yala season 200
Figure 6: Irrigation Requirement in Yala Season (Option 2) 0
Jul
Jan
Jun
Oct
Feb Sep
Apr
Irrigation Requirement (mm) Requirement Irrigation
Dec
Mar
Nov Aug 4.1.3. Option 3 May Time (month For option 3 paddy with soya bean for Yala season were considered. The irrigation requirement for Figure 9: Irrigation Requirement for Option 3 Maha season and Yala season were found as 1054.58 mm and 1231.03 mm respectively. These values in Yala season for the Cultivable area each 10% paddy Irrigation Requirement for Yala Season (Option 3) and 19% soya beans were found as 47.96 mm and 30 60.29 mm respectively. Figure 7 and Figure 8 shows the irrigation requirement for option 3 and 25 specifically for Yala season. IR in Yala season 20 (paddy) for 10% Irrigation Requirement for Option 3 of Area 15 1200 10 1000 IR in Yala season Maha 5 (Cowpea) for
800 season 21% of Area Irrigation Requirement (mm) Requirement Irrigation 600 0 May Jun Jul Aug Sep 400 Yala season Time (month) 200 Figure 10: Irrigation Requirement in Yala Season (Option 4)
Irrigation Requirement (mm) Requirement Irrigation 0
Jul
Jan
Jun
Oct
Feb Sep
Apr
Dec
Mar
Nov Aug
May 4.2. Reservoir Water Balance Modeling Time (month Reservoir water balance model was applied for the
irrigable area under the reservoir for Maha and Yala Figure 7: Irrigation Requirement for Option 3 season considering changes to the inflow from Irrigation Requirement for Yala Season (Option 3) rainfall, evaporation, irrigation demand due to 25 changes in crop water requirement etc. All computations for reservoir water balance modeling 20 IR in Yala were described in irrigation guideline ID (1984). season (paddy) 15 for 10% of Area After comparison of all four options it was realized 10 that the second option which was 10% of the IR in Yala command area paddy and 28 % of the command 5 season (Soya bean) for 28% area green gram was found as the best option in 0 of Area terms of less water requirement and more Irrigation Requirement (mm) Requirement Irrigation May Jun Jul Aug Sep productivity.
Time (month) 4.2.1. Option 1 Figure 8: Irrigation Requirement in Yala Season (Option 3) For both seasons paddy was considered and 4.1.4. Option 4 consequently it was revealed that full command area could be cultivated in Maha season while 16% Cowpea and paddy in Yala season and paddy for (41.24 ha) of the total area is cultivable in Yala Maha season were considered. 1128.45 mm and
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 133 UMCSAWM Water Conference – 2017 season. Reservoir water balance modeling for 100 option one is shown in Figure 11. 100 80 Inflow 80 60 Irrigation Inflow 40 60 Demand Evaporation Irrigation 20 40 Demand Evaporation Operation Reservoir 0
20
Jul
Jan
Jun
Oct
Feb Sep
Apr
Dec
Reservoir Operation Reservoir
Mar
Nov Aug May
0 Time (month)
Jul Jan
Jun
Oct
Feb Sep
Apr
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Aug Nov May Figure 13: Irrigation Requirement in Yala Season (Option 3) Time (month) 4.2.4. Option 4 Figure 11: Irrigation Requirement in Yala Season (Option 1) Paddy and cowpea are the crops that were 4.2.2. Option 2 considered for option 4. After reservoir operation Paddy and green gram for Yala season and Paddy (Figure 14), it was realized that full command area for Maha season was considered. After application can be cultivated in Maha season while, 10% (25.77 of reservoir water balance model, it was found that ha) paddy and 21% (54.13 ha) cowpea could be in Yala season 10% (41.24 ha) paddy and 28% (72.17 irrigated due to available water in Yala season. ha) green gram could be cultivated according to the 100 available water, while the full command area can be cultivated in Maha season. Figure 12 shows 80 Inflow reservoir water balance for option 2. 60 100 Irrigation 40 Demand 80 Evaporation 20
60 Reservoir Operation Reservoir Inflow 0
40
Jul
Jan
Jun
Oct
Feb Sep
Apr
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Nov Aug May 20 Irrigation Demand Time (month)
Reservoir Operation Reservoir 0
Evaporation Figure 14: Irrigation Requirement in Yala Season (Option 2)
Jul
Jan
Jun
Oct
Feb Sep
Apr
Dec
Mar
Nov Aug May Among the all four options, the second option was Time (month) identified as best and suitable option due to less water demand (3.77 MCM) and more productivity. In this option, there is possibility of cultivation in Figure 12: Irrigation Requirement in Yala Season (Option 2) Maha season 100% Paddy (257.78 ha), while in Yala 4.2.3. Option 3 season there could be possibility to cultivate 10 % Paddy for full command area in Maha season and Paddy (41.24 ha) with 28% Green Gram (72.17 ha). paddy with soya bean for Yala season was 5. Conclusions considered for option 3. Reservoir operation was done and it was revealed that in Yala season 10% 1) All necessary data were collected. Situation (25.77 ha) paddy and 19% (48.97 ha) soya bean analysis was done to see the cropping could be cultivated. Figure 13 indicates reservoir intensity and cultivation performance and it water balance for option 3. was realized that full command area in Yala season cannot be cultivated due to water shortage. 2) After evaluation of cultivation performance, paddy, green gram, soya bean and cowpea were selected and the irrigation demand was calculated for each crop. 3) Reservoir water balance model was applied for all four options to find out the best option in order to improve water productivity. After computation, it was found that full command area can be cultivated while this result differs
134 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
for Yala season as follows. For option 1, only Engineering and Technology Vol.2 (4), 2010, 207- paddy was considered and it was found that 211. 16% of the command area can be cultivated. Gulati, Ashok, Ruth Meinzen-Dick, K.V.Raju (2005). Since paddy need more water therefore, the Institutional Reforms in Indian Irrigation. Sage percentage of paddy cultivation was reduced Publications, New Delhi. from 16% to 10% and one more crop was Hoffman, G.J., and R.E. Evans. (2007). Introduction. selected along with paddy for option 2, option p. 1-32. In Hoffman, G.J., et al. Design and operation 3 and option 4, in order to improve the water of farm irrigation systems. 2nd ed. American productivity. After computations, Green gram Society of Agricultural and Biological Engineers, St. for the 28% of the command area, soya bean Joseph, Michigan, USA. for 19% of the command area and cowpea for IIMI, (1992). Improving the Performance of 21% of the command area were found for Irrigated Agriculture: IIMI’s Strategy for the 1990s, option 2, option3, and option 4 respectively. IIMI, Colombo, Sri Lanka. 4) After comparison of all four options, the best Imbulana,K.A.U.S.& Merrey,D.J. (1995). Impact of option which is 100% Paddy in Maha and 10% management interventions on the performance of paddy Yala with 28% Green gram was five irrigation schemes in Sri Lanka (Working Paper selected as best option to be practiced in order No. 35, 23-24). to improve the water productivity under Khan, S., Rana, T., Dassanayake, D., Abbas, A., Labunoruwa Irrigation Tank. Blackwell, J., Akbar, S., and Gabriel, H. F. (2009). Spatially Distributed Assessment of Channel 6. Acknowledgement Seepage Using Geophysics and Artificial Intelligence, Irrigation and Drainage 58: 307 – 320. I would like to express my sincere gratitude to Molden, D. (2003). Pathways to improving Professor N.T.S.Wijesekera for the continuous Productivity of water. p. 1-4. In Jinendradasa, S.S. support in completion of this paper. I place on (ed.) Issues of water management in agriculture: record, my sincere thank you to Madanjeet Singh compilation of essays. International Water for providing scholarship to pursue a Masters Management Institute, Colombo, Sri Lanka. degree in Water Resources Engineering and Merrey DJ Rao PS and Martin E. (1988) Irrigation Management. Management Research in Sri Lanka: A Review of 7. References Selected Literature. IIM1 Occasional Paper, International Irrigation C. Sivayoganathan and M. I.M. Mowjood. (2003). Management Institute, Colombo, Sri Lanka. Role of Extension in Irrigation Water Management Ponrajah, A. J, P., (1988). Technical Guideline of in Sri Lanka. Tropical Agricultural Research and Irrigation Work. Irrigation Department, Colombo, Extension. Sri Lanka. DCS: Department of Census and Statistics. (2014, Simonne, E., Studstill, D., Hochmuth, R.C., Olczyk, May5). Paddy Statistics. Retrieved from T., Dukes, M., Munoz-Carpena, R., Yuncong, C.L. http://www.statistics.gov.lk/agriculture/Paddy% (2012). Drip Irrigation: The BMP Era - An Integrated 20Statistics/PaddyStats.htm. Approach to Water and Fertilizer Management for Dessalegn Rahmato. (1999). Water resource Vegetables Grown with Plasticulture. Univ. Florida development in Ethiopia: Issues of sustainability IFAS Ext. and participation. Forum for social studies Addis Wijesekera, N.T.S. (2011) Irrigation Infrastructure Ababa, Ethiopia. management requirements to ensure water Edward, D., Martin and Robert Yoder. (1987). scarcity for impoverished rural populations Institutions for Irrigation Management in farmer- under climate change scenario. Journal of the Managed Systems. Examples from the hills of Institution of Engineer, Sri Lanka. Nepal: IIMI research paper no. 5. Evans, A.; Jinapala, K. (2009). Proceedings of the National Conference on Water, Food Security and Climate Change in Sri Lanka, IWMI Research Report, Colombo: International Water Management Institute. Fernando, A.DN., The Ancient Hydraulic Civilization of Sri Lanka in Relation to Natural Resources, Journal of the Sri Lanka Branch of the Royal Asiatic Society, Reid Avenue, Colombo 7, 1982. G. Pakhale, Gupta and Nale. (2011). Crop and Irrigation Water Requirement Estimation by Remote Sensing and GIS. International Journal of
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 135 UMCSAWM Water Conference – 2017
136 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Drainage Management in an Urban Watershed under Climate Change Scenario using IWRM Concepts
J.P.G. Jayaratne and N.T.S. Wijesekera
ABSTRACT Surface water and ground water pollution becomes a critical factor in urban areas because having high density of population and infrastructure. Drainage management is very critical and final results is poor water quality status in natural streams when fails to manage the system. This paper aims to demonstrate the capability of developing a water balance model facilitating a quantified watershed management with incorporation of IWRM principles to give solutions for an urban watershed. Then watershed is to be divided in to sub watersheds as necessary in a spatially distributed manner by inspecting the stream network. After that water balance model can be developed considering rainfall, surface runoff, water consumption, return waste discharges of industries and domestic, pan evaporation values and dilution factors etc. Then possible solution can be proposed to achieve a satisfactory water environment for each sub watershed. Subsequently, the situation of growing domestic and industrial units by year 2025 can be evaluated after incorporating a solution for the present situation. In case of climate change, the three scenarios considered a decrease in rainfall of 7%, an increase of 8% in evaporation, a decrease of lowest rainfall and an increase in peak flow. The final output demonstrated the solutions suggested for the worst case scenario.
KEYWORDS: Drainage Management, Urban Watershed, Climate Change, Scenario, IWRM
incorporation of participatory approach becomes 1. Introduction very complex without acceptable quantifications considering diverse water uses, associated sectors, In urban watersheds, high density of resident environmental thresholds and water balance. In this population, associated infrastructure such as roads, backdrop, a case study application was undertaken supermarkets, shops, and industrial compounds to study the possibility of using IWRM principles to cause water pollution due to huge quantities of manage the Attidiya watershed in the Western solid and liquid wastes. This pollution is often high Province of Sri Lanka. in areas where there is noticeable domination of Watershed at Attidiya (4.5 sq. km) with a brown land area over green areas. Hence surface population of about 47,300 is in the middle of the water and groundwater pollution has become a oldest industrial zone of Colombo district, Sri Lanka critical factor in case of urban drainage (Figure 1). This basin with a central drainage management. Isolated, independent nature of stream which barely carries water appears as operations, lesser shouldering of social heavily polluted. The head office of National Water responsibilities, un availability for collective Supply Drainage Board (NWSDB) Sri Lanka is actions, higher political interference etc., are the located at very close proximity to this main stream nature of most operations in these regions and the (Show all these locations in the map and label repercussions are well reflected by the poor water properly). Hence this area was selected for a case quality status of natural streams which mostly study with the intention of promoting an IWRM appear artificial lined drains with dirty coloured demonstration exercise that may be taken up by the water almost with no life. Integrated Water NWSDB. Accordingly, a water resources Resources Management (IWRM) is the most widely assessment using catchment water balance to accepted concept for water resources management. quantitatively study the drainage water from IWRM provides the framework to manage water domestic units and industries units and then to compromising with various sectoral uses. Though evaluate the situation of Attidiya watershed under there are many water resources and hydrologic the expected climate change scenario. research carried out in Sri Lanka, there are no case study examples to demonstrate the potential of using IWRM for drainage management in urban J.P.G. Jayaratne, AMIE(SL) , Deputy Project Director, watersheds. Waste Water Disposal Systems forRatmalana/Moratuwa and Ja-Ela/Ekala Areas, National Water Supply & Drainage Drainage management in urban area while Board, Sri Lanka adhering to IWRM principles especially with the N.T.S. Wijesekera, B.Sc.Eng. Hons (Sri Lanka), PG. Dip (Moratuwa), M.Eng. (Tokyo), Ph.D(Tokyo), C.Eng., MICE(UK), FIE(SL), Senior Professor, Department of Civil Engineering, University of Moratuwa, Sri Lanka.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 137 UMCSAWM Water Conference – 2017
Fig. 1 Map of selected watershed of Attidiya
2. Design from each sub catchment was evaluated to finally capture the cumulative effect at the outlet of main 2.1. Situation Analysis and Scenario watershed. The water balance model developed using a spreadsheet initially used the actual rainfall After inspecting the stream network, Attiditya to evaluate model performance by matching the watershed was divided into four sub watersheds in computed flow values with those observed and order to monitor the area in a spatially distributed captured during field visits. After the calibration of manner. Drainage direction maps, location of models parameters while observing the soil industries, distribution of housing etc., were also moisture levels, runoff coefficients and the pattern identified. Absence of paddy lands, the of stream flow, the spreadsheet was used to study demarcation of rain fed green areas, identification the watershed with 75% probable rainfall which is of areas with domestic and industrial water the recommendation in the design guidelines supplied externally by NWSDB were major land (Irrigation Guide 1984 – Design of Irrigation Head use considerations. Water balance model for each works for Small Catchments). The situation sub catchment was developed by considering a analysis was identified the order of magnitude of domestic consumption of 120 liter/person/day and water status in each sub catchment. Possible a return waste water discharge of 80% according to solutions with quantifications to convince the water the design manuals of NWSDB. Pan evaporation users in the watershed were proposed. values from the Irrigation Department Guidelines Subsequently, the situation of growing domestic and rainfall corresponding to the Ratmalana units and industrial units by the year 2025 was principal meteorological station were used. In case evaluated. of industry and domestic wastewater, the model considered a factor of 0.5 for a surface runoff 2.2. Incorporation of Climate change discharge after the flowing through the soaking pits. Pollution threshold values were incorporated Water balance model also enabled the evaluating by using the Central Environmental Agency the watershed in case of climate change. Three recommendation of 8 times dilution. The water scenarios were considered and they were 1) Annual balance model in a step by step manner computed rainfall decrease by 7%, 2) Evaporation increase of and considered the available room to discharge 8%, and 3) an increase in the high rainfall and a pollutants to water while ensuring that the water decrease in the low rainfall. Final outputs status is within the CEA thresholds. Water outflow demonstrate the solutions suggested for the worst
138 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 case scenario when there is a collective effective Table 2. Rainfall and Pan Evaporation from all the scenario. Month Rainfall mm Pan Evaporation mm Jan 93 93 3. Data and Analysis Feb 69 94 Mar 134 106 3.1. Area and population density in sub Apr 268 101 watersheds May 301 95 Jun 171 89 Jul 119 94 Aug 107 105 Sep 199 98 Oct 93 79 Nov 414 78 Dec 160 89 Total 2,128 Analysis was based on the water balance of the watershed first considering the rain that generated unpolluted runoff depending on the land use, soil moisture and other physical parameters subjected to the influence of evaporation. Then the next step of the water balance was to consider the return flow from domestic units and industries together with the direct runoff from rain. At each sub catchment node, the water quantity balance was checked with the use of equations 1 and 2. 푅푎𝑖푛푓푎푙푙 − 퐸푣푎푝표푟푎푡𝑖표푛 − 푅푢푛표푓푓 − 퐷푒푒푝 푝푒푟푐표푙푎푡𝑖표푛 = 퐶ℎ푎푛푔푒 표푓 푆푡표푟푎푔푒…… (1)
푆푡푟푒푎푚푓푙표푤 = 푅푢푛표푓푓 + 푊푎푠푡푒푤푎푡푒푟(퐷표푚푒푠푡𝑖푐 푈푛𝑖푡푠 + 퐼푛푑푢푠푡푟𝑖푒푠) …………………………………… (2)
Water balance with the incorporation of water Fig. 2 Map of sub watersheds and system diagram quality was computed considering that the Population, industry and social data were obtained freshwater from the rain could be polluted up to the from divisional secretariat offices of Ratmalana and threshold value stipulated by the Central Dehiwala and were tabulated according to sub Environmental Authority (General Standards watersheds (Table 1). Criteria for the Discharge of Industrial Effluents into Inland Surface Waters). In this exercise the equation 3 was utilized. 푄 푅푢푛표푓푓 퐷𝑖푙푢푡𝑖표푛 푓푎푐푡표푟 휂 = ………… … (3) Table 1. Area, Population density, no of industries and no of 푄 푤푎푠푡푒푤푎푡푒푟 houses in sub watersheds Sub Area Population Number No of 3.3. Institutions involvement in the area Watersh Sq.k Density of Large Housi ed m Persons/Sq. Industri ng Many institutions involve for varies kind of km es Units activities in the area. Therefore participatory Sub 1 1.15 12,689 0 2,722 approach is to be applied according to the Sub 2 1.88 9,892 7 4,632 Integrated Water Resources Management. Sub 3 0.64 14,247 1 1,685 Sub 4 0.87 5,790 1 659
Total 4.54 10,425 9 9,698
3.2. Rainfall and pan evaporation Ratmalana rainfall data from 1931-1990 were averaged for the annual water balance. Monthly Pan Evaporation values were taken from the Irrigation Department Guidelines.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 139 UMCSAWM Water Conference – 2017
Table 3. Institutions involvement in the area
Institution Activities Involvement Table 4. Monthly variation in the watershed at outlet point Divisional Secretariat Administration &
– Ratmalana & Coordination activities in the
Dehiwala area Urban Council Solid Waste Management, (Dehiwala./Mt. Small Developments, Health
Lavinia) Management
CEA Environment Management
NWSDB Water Supply & Sewerage Month Rain Volume m3 Fresh water Runoff m3 Total WW Runoff m3 Fresh requirement to dilute WW m3 Water Available Fresh water at out let within CEA Threshold m3 Management Jan 412,236 251,464 76,888 628,123 -376,659 SLRDC Flood Control & Drainage Feb 305,853 186,570 69,447 567,337 -380,767 Management Mar 593,975 362,325 76,888 628,123 -265,799 Irrigation Department Irrigation Water Apr 1,187,950 724,649 74,408 607,861 116,788 Management May 1,334,227 813,879 76,888 628,123 185,755 UDA Urban Development Jun 757,983 462,370 74,408 607,861 -145,492 Activities Jul 527,485 321,766 76,888 628,123 -306,357 NHDA Housing Development Aug 474,293 289,319 76,888 628,123 -338,804 Activities Sep 882,097 538,079 74,408 607,861 -69,782 RDA, PRDA, UC Road Construction & Maintenance Oct 412,236 251,464 76,888 628,123 -376,659 Metrological Metrological Activities Nov 1,835,117 1,119,421 74,408 607,861 511,560 Department Dec 709,224 432,627 76,888 628,123 -195,497 - CEB Power Supply 7,395,648 Telecom Communication 9,432,677 5,753,933 905,293 1,641,715 Education Scholl Children Education According to the table 4 it can be seen that in the last Department column the values are plus only in 3 months such as Government Health Maintenance April, May & November. That means those three Hospitals months the out let water quality is satisfactory according to the CEA threshold value. In the other 4. Results words all the other 9 months in the year water quality at the out let of the watershed is 4.1. Present Status unsatisfactory that is polluted according to the CEA Present status at key sub watershed node and at the threshold value. In figure 3, it shows in graphically main watershed outlet is shown by results in Table the values in the table 4. 3. All watersheds reflected a highly polluted status 2,000 while the sub catchment 2 demonstrated the most polluted state. The sub watershed 4 proved to be in 1,500 the best state with a water quality level below the pollution thresholds stipulated by the CEA. Thousands 1,000 Table 3. Present Status of the Watershed
500
0 Rain Water Fresh water Total WW Fress Water Available fresh
1000 1000 m3 runoff Runoff Requirement water within
to Dilute WW CEA threshold tal WW Runoff Runoff WW tal -500
Sub Watershed Sub Node Watershed m3 Rain Volume off Run water Fresh m3 To m3 Water Fresh to requirement m3 WW dilute Fresh Available CEA within water m3 threshold 2,386,7 1,455,9 255,2 2,041,7 - 1 A 56 21 14 11 585,789 Fig. 3 Monthly variation in graphically - 3,921,1 2,391,8 413,0 3,476,3 2 B 1,084,4 00 71 11 65 Therefore to increase the available fresh water at the 94 out let of watershed the total wastewater quantities - 6,307,8 3,847,7 635,9 5,195,0 2+3 C 1,347,2 should be reduced because runoff fresh water 56 92 22 51 59 cannot be increased that is rainfall cannot be 1,320,2 180,4 1,487,0 - 3 D 805,322 increased. Therefore wastewater of domestic and 01 03 28 681,705 1,804,6 1,100,8 102,6 industries should be treated to reduce wastewater 4 E 850,444 250,374 21 19 56 runoff quantities and quality. - 1+2+3 9,432,6 5,753,9 905,2 7,395,6 F 1,641,7 +4 77 33 93 48 15 To reduce the domestic wastewater it should either be treated at individual house premises or collected to a central point and treated. Actually industrial To show the monthly variation at the outlet of the wastewater can be treated at the site and can be watershed is shown in the table 4. discharged to streams to reduce dilution water requirement. However it can be seen that if treating
140 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 of 68% domestic wastewater and 60% of industrial Runoff Coefficient, Deep Percolation Coefficient, wastewater the resultant runoff will be sustained at Soil Moisture Coefficient, Pan Evaporation Value, the out let of the watershed. Evapotranspiration factor, Initial Ground Water Surface Moisture Content, Inflow and Out flow 4.2. Pollution variation in three options quantities from the system etc. to do the system incorporation of climate change water balance. Up dated geographical Maps to calculate the Watershed areas and land use patterns According to the model results for the 3 scenarios also needed to calculate the runoff factors etc. In incorporation of climate change as mentioned in the addition to that to run the model, population, no of section 2.2 for the 2025 the worst case was housing units, no of industries, Water developed in the option 1(decrease rainfall by 7%). Consumptions of domestic industries and others, That means most pollution level become by Wastewater factors for Domestic Industries and decreasing rainfall of the watershed. Therefore others, Wastewater Runoff Factors, Wastewater solutions are to be given for the option 1. Deep Percolation Factors, Wastewater Quality, Table 5. Pollution variation in three options at the outlet Standard Criteria for Discharge of effluents in to point of watershed inland surface etc. will be needed. All the date and
Parameters available are to be verified whether
those values can be matched to this area and
situations. For example, runoff factors should be verified because this watershed lies in urbanized
area and land use patter is directly affected to it. Field visits also are to be done to identify and verify
the data available.
Option Water Rain Runoff Water Fresh Runoff WW Total Water Fresh Dilute to Requirement WW water Fresh Available Threshold CEA within - The model was developed based on various 1 9,432,677 5,753,933 1,040,482 8,492,488 2,738,555 assumptions and few of them are; wastewater - 2 9,432,677 5,753,933 1,032,817 8,415,838 produce 80% of water consumption in houses, 2,661,905 - wastewater produce 40% of water consumption in 3 9,767,435 6,076,321 905,293 7,395,648 1,319,326 industries, 50% runoff from domestic wastewater and other 50% deep percolation, 8 times fresh water 4.3. Solutions requires to treat domestic water, 10 times fresh water requires to treat industrial water etc. According to the results of the model it can be observed that generally 71.5% wastewater quantity 5.2. Water Quality should be reduced or treated to become best stat at the out let of the watershed if consider whole Actually to handle this type of analysis water watershed. However according to the population qualities at the end point of sub watersheds, out let density, no of industries availability and pollution points of industries etc. should be measured to levels of sub watersheds wastewater reduce or calculate actual fresh water requirements to treat treatment percentage will be varied sub watershed polluted water. In addition to that this study wise as following table 6. Sub watershed 3 is most average pollution conditions were used, but actual critical and sub watershed 4 is not critical. condition is different because pollution level Table 6. Wastewater reduce or treatment % requirement in variation occur in different places. Therefore, doing sub watersheds in the year 2025 actual designs water planners should obtain the water quality measurements periodically in varies Sub % of WW treatment requirement watershed Domestic Industries locations to represent whole area to decide exact 1 76% 70% level of pollutions. 2 76% 70% 3 80% 80% 5.3. Literature Attempting 4 55% 55% Water planners should attempt to find historical 5. Discussion data relevant to the area such as water quantity, water quality, water flows, environmental flows, 5.1. System water balance flood levels etc. If not it should be started data collection programme. When doing system water balance, the accuracy depends on the required data availability to the 5.4. Critical Parameters relevant area, verification of the data and assumptions made. This study was done under data In this analysis three scenarios were used to scare situation and used available literature and evaluating case of climate change as decreasing assumptions. rainfall, increasing evaporation and stream event of However, for accuracy of this type of analysis increasing highest rainfall and decreasing lowest accurate data should be needed such as Rainfall, rainfall. When selecting these critical parameters, it
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 141 UMCSAWM Water Conference – 2017 should be refer literature, past records and papers 7. Acknowledgement to identify correct parameters. Main author thanks to National Water Supply & 5.5. Critical Watershed Drainage Board for giving him sponsorship to follow up the course of Msc./PG. Diploma in Water In this area the land use pattern is different in each Resources Engineering & Management at sub watershed. According to the Table 1 it can be University of Moratuwa. seen that in sub watershed1population density is medium, in sub watershed 2 availability of industry 8. References is high but population density is medium, in Irrigation Department Guide Book of Design of watershed 3 population density is very high and in Irrigation Head works for Small Catchments May watershed 4 very low population densities. 1984. According to the analysis it shows that in watershed Sampath Pathikada publications 2012 of Ratmalana 3 wastewater pollution level is high and required Divisional Secretariat office and Dehiwala wastewater treatment percentage is very high to Secretariat office. come state situation. In addition to that sub National Water Supply & Drainage Board Design watershed 1 & 2 domestic wastewater pollution is Manual D7. high.
Therefore, stake holders should give more attention to sub watershed 3 because situation becomes critical in future if it is not given attention to that.
However, sewer central collection system will be needed in future for sub watershed 1, 2 & 3 because population density is increasing day by day. In addition to that IWRM principals in participatory approach will be needed to overcome the critical situation.
6. Conclusion
Model demonstrates pollution level of surface water and ground water in an urban watershed when fails to manage. It quantifies the critical situations. Then possible solutions can be proposed to achieve a satisfactory water environment for each sub watershed. Prediction of climate change impact gives in advance how to create mitigate options and what can be adaptions applied to the watershed. Awareness of stakeholders, land users according to the IWRM principals as required time is essential because after become the worst situation it is very difficult to overcome and come back to ecofriendly situation.
142 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
THE UNESCO MADANJEET SINGH CENTRE FOR SOUTH ASIA WATER MANAGEMENT
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 143 UMCSAWM Water Conference – 2017
144 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 UNESCO Madanjeet Singh Centre for South Asia Water Management
The UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) established in April 2013 attached to the Department of Civil Engineering, University of Moratuwa, Sri Lanka is another member of UNESCO Madanjeet Singh Institutions of Excellence. UMCSAWM is a landmark in the Sri Lankan university history as the first international centre established to conduct fulltime postgraduate degree programmes. The objective of the UMCSAWM is to promote regional cooperation through South Asian water management education and to conduct pioneering research in the areas of water management and water resources engineering with relevance to South Asian countries. The UMCSAWM is located in a three storied building adjacent to the Civil Engineering Complex of University of Moratuwa facilitating postgraduate education. The center has dedicated space for all UMCSAWM and other students with two lecture rooms, a computer room, staff and student rooms, areas for research and self-study, space for individual/group work, a conference room, library space, administrative space, and other common areas. Outdoor experimental areas are also available to demonstrate practical applications in three distinct water specialties, namely, Irrigation, Urban Storm Water Drainage, and Riverine and Estuary Ecosystems. These facilities will ensure an extensive exposure and hands on research experiences at an advanced level of application to the participants of all UMCSAWM programmes.
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 145 UMCSAWM Water Conference – 2017 Irrigation and Hydraulic Urban Research Facility - 1
146 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017 Irrigation and Hydraulic Urban Research Facility -2
UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 147 UMCSAWM Water Conference – 2017
Hybrid Irrigation Research facility
148 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Meteorological Observation Station
The meteorological observation station donated to the UMCSAWM of University of Moratuwa by the
Ministry of Mahaweli Development and Environment (MMDE) is under construction and nearing completion. This station is one out of a total of 122 network stations installed under the Dam Safety Project
of Mahaweli Authority of Sri Lanka. Out of the total, 88 stations will be managed by the Hydrology Division of the Irrigation Department while 34 stations will be managed by the Mahaweli Authority.
The station at UMCSAWM will be installed with modern instruments to gather data pertaining to water and hydrology. The type of data collected consist of water levels, water discharges, rainfall, wind speed,
sunshine, temperature, evaporation etc. All except evaporation data will be collected automatically and will be stored in a data logger at the site. From the data logger the collected data will be automatically transmitted through two channels of transmission. The first channel uses the Meteosat weather satellite operated by the World Meteorological Organisation (WMO) to transmit the collected data every hour. The second channel uses GPRS technology to transmit the collected data. The officers of the project have indicated that the data of the network will be collected by the two principal users of data, Irrigation Department and Mahaweli Authority and then will be shared with other users as appropriate. It has been indicated that the modalities of the data sharing will be worked out and it is expected that the national data collections programs will share these data keeping in line with the Right to Information Act no. 12 of 2016. A Typical installation is shown below.
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UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) 149 UMCSAWM Water Conference – 2017
Acknowledgements This conference was made possible due to the generosity of the following groups and individuals. Acknowledgement are extended to: Madame France Marquet (Madanjeet Singh Fund (MSF )Principal Trustee and South Asian Foundation (SAF) Trustee), Mr. Nath Rao (MSF President and SAF Advisor), Mr. Navin Chawla (SAF Trustee) the SAF Governing council members, and SAF-India officials including Mr. P K Prabhakaran, Mr. Sunil Binjola, and all others Her Excellency Madame Chandrika Bandaranaike Kumaratunga, Chairperson of SAF-Sri Lanka, the Board members and SAF-SL office staff including Ms. Swinitha Perera (Secretary, SAF-SL) Prof. Ananda Jayawardane (Vice-Chancellor), Prof. Rahula Atalage (Deputy vice-chancellor), Prof. Kapila Perea (Dean-Faculty of Engineering), Prof. Saman Bandara (Head-Civil Engineering), Mr. A.L.J. Sadique (Registrar), Mr. K.A.D. Pushpakeerthi (Bursar), Mrs. R.C. Kodikara (Librarian) and staff of their divisions Prof. Mrs. C. Jayasinghe (Director-Postgraduate Studies Division, Faculty of Engineering) and all support staff Industry and organizations extending support through field visits, discussions, and participation Department of Civil Engineering, the Academic staff, Non-academic staff, and all support staff Hydraulic and Water Resources Engineering Division and all support staff for support UMCSAWM Alumni, Present students and all support staff for untiring efforts Invitees, well-wishers and other guests for gracing the occasion The postgraduates who contributed with their comprehensive papers and presentations
150 UNESCO Madanjeet Singh Centre for South Asia Water Management (UMCSAWM) UMCSAWM Water Conference – 2017
Organizing Committee
Conference Chair Dr. Lalith Rajapakse
Chief Advisor and Overall Programme Coordinator Professor Sohan Wijesekera
Conference Advisors Professor Saman Bandara Mr. Harsha Rathnasooriya
Technical Coordinators Mr. Wajira Kumarasinghe Mr. Kasun Panditharathne Mr. Waruna Wijeweera
Proceedings Compilers Ms. Amali Dahanayake Ms. Thisuni Kodippili
Editorial Assistants Ms. K.A.Vinu Kalanika Ms. Vindula Fernando Ms. Lakshini Gomes Ms. Ireshika Perera
Logistic Support Assistant Mr. Samantha Ranaweera