Government of Maharashtra Hydrology Project II Water Resources Department IBRD Loan No: 4749-IN

Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in Maharashtra (RTSF & ROS)

Final Report October 2013

Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River DHI (India) Water & Environment Pvt Ltd Basins in Maharashtra (RTSF & ROS) rd 3 Floor, NSIC Bhawan, Okhla Industrial Estate Final Report New Delhi 11 00 20 India October 2013 Tel:+9111 47034500 +91 11 4703 4500 Fax:+911147034501 +91 11 4703 4501 [email protected] www.dhigroup.com

Client Client’s representative

Chief Engineer, Planning & Hydrology Superintending Engineer

Project Project No Real Time Streamflow Forecasting and Reservoir Operation System for Krishna and Bhima River Basins in 63800247 Maharashtra (RTSF & ROS) Authors Date: Dhananjay Pandit 5 October 2013 Gregers Jorgensen Anders Klinting Approved by Finn Hansen Guna Paudyal

01 Final Report (based on comments from Client & other DJP GNP 05.10.13 stakeholders on the Draft Final Report) Revision Description By Checked Approved Date Key words Classification Real Time, Streamflow, Flood, Forecasting, Open Reservoir Operation, Forecast Models, Hydrology, Hydraulics, River Basin, Capacity Building Internal

Proprietary

Distribution No of copies Client: 50 DHI: PDF file 2 CDs

RTSF&ROS Krishna & Bhima River Basins

List of Acronyms and Abbreviations

BSD Basin Simulation Division CWC Central Water Commission DA Data Assimilation DAS Data Acquisition System DEM Digital Elevation Model DSS Decision Support System FCL Flood Control Level (from rule curve) FCS Full Climate Station FMO Flood meteorological Office (of IMD) FRL Full Reservoir Level GIS Geographic Information System GMRBA Godavari Marathwada River Basin Agency GMS Geostationary Meteorological Satellite GoI Government of India GoM Government of Maharashtra GPRS General Packet Radio Service GSM Global System for Mobile Communications HD Hydrodynamic HIS Hydrological Information system HP-II Hydrology Project Phase II IBRD International Bank for Reconstruction and Development IMD Indian Meteorological Department KRBA Konkan River Basin Agency MERI Maharashtra Engineering Research Institute MKRBA Maharashtra Krishna River Basin Agency MODIS Moderate Resolution Imaging Spectro-radiometer MoWR Ministry of Water Resources MWL Maximum Water Level NIH National Institute of Hydrology, Roorkee NCMRWF National Centre for Medium Range Weather Forecasting NRSA National Remote Sensing Organisation NWP Numerical Weather Prediction QA Quality Assurance ii Final Report QAP Quality Assurance Plan QC Quality Control QPF Quantitative Precipitation Forecast RIMES Regional Integrated Multi Hazard Early Warning System RMC Regional Meteorological Centre (of IMD) RMSE Root Mean Square Error ROS Reservoir Operation System RR Rainfall-Runoff RS Remote Sensing RTDAS Real Time Data Acquisition System RTDSS Real Time Decision Support System RTSF Real Time Streamflow Forecasting SAR Synthetic Aperture Radar SO Structure Operation SRTM Shuttle Radar Topography Mission TAMC Technical Assistance Management Consultancy (HP-II World Bank) TKRBA Tapi Khandesh River Basin Agency VRBA Vidarbha River Basin Agency WALMI Water and Land Management Institute WB World Bank WRD Water Resources Department

Final Report iii RTSF&ROS Krishna & Bhima River Basins

Table of Contents List of Acronyms and Abbreviations ...... ii EXECUTIVE SUMMARY ...... VII 1 PROJECT OBJECTIVES & ACHIEVEMENTS ...... 1 1.1 Background ...... 1 1.2 Krishna and Bhima River Basins ...... 2 1.3 Project Objectives and Outputs ...... 4 1.4 Project Achievements ...... 5 2 KNOWLEDGE BASE SYSTEM ...... 8 2.1 Features of RTSF&ROS ...... 8 2.2 Brief Description of KBS ...... 9 2.3 Hardware ...... 9 2.4 Software ...... 10 2.5 Database ...... 11 2.6 Knowledge management ...... 14 3 THE RTSF&ROS MODELS ...... 18 3.1 Modelling system ...... 18 3.2 Rainfall-runoff Model ...... 19 3.3 Hydrodynamic Model ...... 23 3.3.1 Model Development ...... 23 3.3.2 Model Outputs ...... 27 Model ...... 27 3.3.3 Calibration ...... 27 3.3.4 Model Applications ...... 29 3.4 The Forecasting System ...... 34 3.4.1 Introduction ...... 34 3.4.2 Quantitative Precipitation Forecasts (QPF) ...... 35 3.4.3 The Forecasting and Operation System ...... 36 3.4.4 Forecasts ...... 38 3.4.5 Rainfall forecast scenario ...... 39 4 RESERVOIR OPERATION SYSTEM ...... 40 4.1 Introduction ...... 40 iv Final Report 4.2 Short Term Optimization ...... 41 4.2.1 Methodology ...... 41 4.2.2 Example Applications ...... 43 4.3 Long Term Optimization ...... 48 4.3.1 Optimization of reservoir operation for flood season ...... 48 4.3.2 Example applications ...... 48 4.3.3 Ujjani Reservoir ...... 50 4.3.4 Pawana Reservoir ...... 51 4.4 Optimization of Reservoir Operation for Long-term Water Management ...... 52 4.5 Integrated Operation of Reservoirs ...... 55 4.6 Reservoir Operation Guidance System ...... 60 4.7 Scenario Management ...... 61 4.7.1 Reservoir operation scenarios ...... 61 5 COMMUNICATION AND INFORMATION MANAGEMENT SYSTEM ...... 63 5.1 Flow/Flood Warning Reports and Dissemination ...... 63 5.1.1 RTSF&ROS Website ...... 63 5.1.2 Communication WEB Portal...... 65 5.1.3 Flood Warning Reports/Messages ...... 68 6 CAPACITY BUILDING ...... 73 6.1 Introduction ...... 73 6.2 Trainings Conducted ...... 73 6.3 International Study Tours ...... 74 6.3.1 Study tour to Europe ...... 74 6.3.2 Study tour to USA ...... 76 6.3.3 International training (Proposed) ...... 79 6.4 Workshops ...... 79 6.5 Strategy for Sustainability of RTSF&ROS ...... 81 6.5.1 Institutional Strengthening ...... 81 6.5.2 Proposed Setup and Functions of BSD ...... 81 6.5.3 Operational Control Room ...... 83 7 ACTIVITIES FOR SUPPORT PERIOD ...... 84 7.1 Introduction ...... 84

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7.2 Support to be Provided ...... 84 7.3 Training Plan during the Support Period ...... 86 8 REFERENCES ...... 88 DOCUMENTATION ...... 91 APPENDIX A: LIST OF TRAININGS CONDUCTED ...... 92 APPENDIX B: RESULTS OF RTSF&ROS USING REAL TIME DATA ACQUISITION SYSTEM ...... 95

vi Final Report EXECUTIVE SUMMARY

The Project “Consultancy services for the implementation of real time streamflow forecasting and reservoir operations for Krishna and Bhima River Basins in Maharashtra” commenced with the opening of the project office in Pune on the auspicious day of Ganesh Chaturthi on 17th August 2011. DHI (India) Water and Environment are the Consultants assigned by the Water Resources Department of Government of Maharashtra, India. The assignment was scheduled to be completed in 18 months with an extended technical support period of two years.

The main objective of the RTSF&ROS project is to equip the Water Resources Department of Government of Maharashtra with a web-based real time streamflow monitoring and forecasting system and reservoir operation system for flood management in the Krishna and Bhima basins in Maharashtra.

The principal outputs in relation to the forecasting and operation guidance system are: 1. A hydrological Knowledge Base

2. A Forecasting System for reservoir inflows and floods along the river systems

3. A Reservoir Operation Guidance

4. A Web based interactive Communication System

5. A Capacity Building Programme

All outputs of the above main tasks have been delivered on time. While technical details related to all the tasks and deliverables have been presented in earlier reports, this final report contains a summary of project achievements. Capacity building activities, strategy for sustainability of the developed system and a work plan for the two-year support period are presented in the Report.

A Knowledge Base System (KBS) is developed for the Krishna and Bhima River basins, which consists of a comprehensive database of historical hydrological data, links to real time data with capability of updating as data becomes available. The KBS contains all available data relating to GIS data, topographic data, satellite imageries showing administrative/land use/land cover/cropped and irrigated areas, soils, climate, historical hydro-meteorological data, water levels and flow, water resources including reservoirs, facilities for the generation of daily crop water requirements. In addition to typical

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database functions, KBS is capable of performing a variety of data analysis including resampling and statistical analysis.

The Real Time Streamflow Forecasting and Reservoir Operation System (RTSF&ROS) is built upon the MIKE11 modelling system which comprises the hydrological rainfall-runoff model, the hydraulic river routing model based on a fully dynamic solution of the St. Venant’s equations, the data assimilation process used in real time flow and flood forecasting. The hydrodynamic model contains updated river cross sections from the recent field surveys carried out in 2012. The streamflow and flood forecasting model has been tested with historical events in hindcast mode capturing all types of average, dry and flood events that occurred in the Krishna and Bhima basins in the recent past. In absence of real time from RTDAS the system was tested and demonstrated with data from various Government Websites in 2012. The RTSF&ROS has now been fully tested with real time data from RTDAS during the monsoon (July-August) of 2013. The “live test” and implementation of the RTSF&ROS during the monsoon season of 2013 has been completed satisfactorily.

The RTSF&ROS is used for providing reservoir operation guidance for an integrated operation of the reservoirs in the two basins. The reservoir operation is also aided by including both short term optimization of reservoir operation during flood emergencies as well as for long term operation. A comprehensive river basin simulation model is also developed for the two basins based on the MIKEBASIN system. This simulation model together with optimization of reservoir operation provides a basis of optimum releases for irrigation, water supply and flood control and hydropower in the entire system.

The communication and information management system consists of three main components: Flow/Flood Warning Reports and Dissemination, the RTSF&ROS Website and the main communication Web Portal (Krishna Bhima Online). A variety of flow/flood warning reports and messages are developed to be disseminated to concerned authority, organisation and communities. Also a variety of dissemination mechanisms are developed. A website of the RTSF&ROS project has been developed for wider dissemination of information. The Krishna-Bhima Online system is the main Web based real time interactive information and decision support portal developed as the front end user interface of the RTSF&ROS. viii Final Report In order to build the capacity of WRD, especially the Basin Simulation Division, a variety of trainings have been conducted. The BSD officers are capable of operating the RTSF&ROS. Detailed training materials, user guides and scientific references of the modelling software have been provided. Six sets of MIKE software along with technical documentation and user manuals have been delivered to various WRD offices as stipulated in the contract and as instructed by WRD. The capacity building activities, especially training of WRD/BSD officers in modelling, has been a continuous process. A series of trainings have been provided to WRD officials. Selected WRD officers are now able to use the developed models. Hands-on-training will be continued during the 2-year support period. The database and models and the forecasting system together with computer hardware and software have been installed in the operational control room of the Basin Simulation Division at 1st floor of Sinchan Bhawan, Pune. The control room is fully functional and the network and servers are fully integrated with the RTDAS.

The RTSFA&ROS development and outputs of all the components were discussed in four workshops well attended by WRD and other stakeholders. Suggestions and feedback from workshop participants and review committee members have been incorporated. The Draft Final Report was submitted to WRD in early January 20123 for comments and suggestions. This Final report incorporates all comments received from WRD, Review Committee members, TAMC and others. The Report was presented at the Fifth and Final workshop held at YASHDA centre Pune on 3rd October. The workshop was well attended by WRD, officials from other states of HP-II, World Bank Task Team Leader and other officials managing the HP-II project, review committee members and other stakeholders. The achievements of the project were appreciated by all the participants and WRD and it was agreed that the stipulated objectives were fulfilled and satisfactory outputs delivered. The sustainability of the technology was discussed and was noted that WRD will be in a position to sustain the RTSF&ROS with the involvement of trained and qualified staff to maintain and update the system.

As stipulated in the TOR a work plan has been provided for the two-year support period. The work plan includes an intensive input of experts during the 2013 monsoon, four trainings and further support through the two-year period.

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Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

1 PROJECT OBJECTIVES & ACHIEVEMENTS 1.1 Background The geographical area of Maharashtra state is 308,000 km2. Major river basins in the state are the Krishna river with its major tributary as Bhima, Godavari, Tapi and the West flowing rivers of Konkan strip (Figure 1.1). Maharashtra receives rainfall from both south-west and north-east monsoon. The state has very highly variable rainfall ranging from 6000 mm in upper catchments to 400 mm in shadow areas of lower catchments. Majority of rainfall mainly occurs in a four months period between June to September with the number of rainy days varying between 40 to 100. The state experiences flash floods particularly in Western Ghats including Krishna and Upper Bhima basins. For instance, Sangli, Satara and Kolhapur districts in Krishna Basin and Pune and Solapur districts in Bhima basin experienced severe flood several times during recent decade.

Figure 1-1 River Basins of Maharashtra The Water Resources Department (WRD) of Government of Maharashtra (GoM) is entrusted with the surface water resources planning, development and management. A large number of major, medium and minor water resources development projects (reservoirs and weirs) have been constructed in Maharashtra. Though, the reservoirs in Maharashtra are not specifically provided with flood cushion, they have moderated flood peaks to considerable extent by proper reservoir operations. The reservoirs are multipurpose including hydropower, irrigation, domestic and industrial uses and are operated with rigid schedules as single entities based on the historical hydro-meteorological data and experience gained. These methods are often not adequate for establishing optimal operational decisions, especially where integrated operation of multiple reservoirs for flood management is contemplated. In addition, manual data observation and transmission results in a considerable time lag, between data observed in field and its communication to decision making level which sometime leaves little time, for flood forecasts. The Ministry of Water Resources (MoWR), Government of India (GoI) has initiated Hydrology Project Phase II (HP-II), which is a follow-on to the concluded Hydrology Project-I (HP-I:1995-2003). During HP-I, the Hydrological Information

Final Report 1 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

System (HIS) was developed for the entire state of Maharashtra and the data is monitored manually 1-2 times a day. Under HP-II project, real time decision support system inflow forecasting in Bhakra Beas system and Decision Support System (DSS) for water resources planning and management are being developed. The Upper Bhima basin has been selected as a pilot basin for latter one i.e. DSS (planning). In addition, Government of Maharashtra has proposed to upgrade the existing HIS with real time data acquisition system (RTDAS) for Krishna and Bhima basins. Simultaneously, it is proposed to develop a real time streamflow forecasting (RTSF) and reservoir operation system (ROS) in Krishna and Bhima river basins to manage the floods and operate reservoirs optimally for multiple uses. It is envisaged that the system would facilitate reservoir operators to act on time and prepare stakeholders for the floods. The forecast of river flow and mapping of flood zone will help in taking the decisions such as evacuation of the likely affecting areas well in advance. In addition, the reservoir operation system would facilitate the optimization of the storages for ensuring flood cushion and improving agricultural productivity. 1.2 Krishna and Bhima River Basins The Krishna River Basin, of which Bhīma is a major tributary, covers an area of 258,000 sq.km (nearly 8% of India) in three large states—Karnataka, Maharashtra, Andhra Pradesh. Maharashtra covers 69,967 km2 of Bhima & Krishna basin area (Figure 1.2). As Bhima joins Krishna only in Karnataka, these two rivers basins are generally treated as separate basins. This part is one of the fasted economically growing regions and hence there is an ever growing competition for water among different sectors viz. agriculture, industries and domestic users. There are 46 reservoirs in Bhima & Krishna out of which 30 are Major Projects and 16 are Medium Projects. The river Krishna which is one of the major rivers of Maharashtra covering an area of 21,114 km2 is 282 km long. Krishna originates from Mahabaleshwar in Satara district and flows through Satara, Sangali and Kolhapur Districts. It mainly flows from north to south. Three of its main tributaries namely, Koyna, Warana, Panchaganga flow from west to east and the fourth main tributary Yerala flows from east to west. There are 19 reservoirs in Krishna basin, out of which 10 are major projects viz. Dhom, Kanher, Urmodi, Tarali, Koyna, Warna, Radhanagari, Dudhganga, Tembhu Barrage and Satpewadi Barrage. The 9 medium projects are Dhom Balkawadi, Mahu, Uttarmand, Morna(Gureghar), Wang, Kadvi, Kasari, Kumbhi and Dhamni. Figure 1.3 shows locations of reservoirs in the Krishna Basin.

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Figure 1-2 The Krishna and Bhima River Basins in Maharashtra

The Bhima River rises from Bhimashankar near Karjat on the western side of the Western Ghats known as Sahyadri hill ranges at an altitude of about 945 m above the sea level. The Bhima River flows in the southeast direction for 745 km covering the states of Maharashtra and Karnataka. The Bhima River drains an area of 48,853 km2 in Maharashtra. The length of Bhima in Maharashtra is 451 km and it joins Krishna on the Karnataka – Andhra Pradesh boundary near near Kudlu in Raichur District. In the course of the journey it meets many small rivers. The major tributaries of this river around Pune are Kundali, Ghod, Bhama, Indrayani, Mula, Mutha and Pawana. The Indrayani, Mula, Mutha and Pawana flow through Pune and Pimpri Chinchwad city. The major tributaries of Bhima in Solapur are Chandani, Kamini, Moshi, Bori, Sina, Man, Bhogwati and Nira. The Bhima meets the Nira River in Narsinghpur in Malshiras taluka in Solapur district. The last 298 km of its course is in Karnataka where it merges with the Krishna River. The banks of the Bhima River are densely populated and form a fertile agricultural land. The river also causes floods due to heavy rainfall it receives during the monsoon. Bhima basin has 27 reservoirs out of which 20 are major projects and 7 are medium projects. The major projects are Pimpalgaon Joga, Manikdoh, Yedgaon, Wadaj, Dimbe, Chaskaman, Bhama Askheda, Pawana, Mulshi, Temghar, Warasgaon, Panshet, Khadakwasla, Ghod, Ujjani, Sina-Kolegaon, Gunjawani, Bhatghar, Vir and Nira Deoghar. The medium projects are Chilewadi, Kalmodi, Andhra, Wadiwale, Kasar Sai, Sina (Nimgaon) and Nazare.

Final Report 3 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

Some areas of the Krishna and Bhima basins suffer from floods. Figure 1.3 shows reaches of Krishna and Bhima and their tributaries which are flooded. The years 2005 and 2006 observed heavy floods in the basins. Due to heavy rains in the catchment of Krishna, Warna and Panchganga rivers created flood havocs in Sangli, Satara and Kolhapur districts in July 2005. Sangli city is one of the most flood prone areas in the Krishna basin. Pandharpur city on Bhima basin is another flood prone area. Some areas in Pune city gets flooded from the Mutha and Mula rivers.

Figure 1-3 Flood Prone Reaches (in red) in Krishna and Bhima Basins 1.3 Project Objectives and Outputs The objective of this project is to equip the Water Resources Department of Government of Maharashtra with a web-based real time streamflow monitoring and forecasting system and reservoir operation system for flood management in the Krishna and Bhima basins in Maharashtra. The specific objective of the Project is to develop a Real Time Streamflow Forecasting and Reservoir Operation System (RTSF&ROS) for the Krishna and Bhima River Basins in Maharashtra. The principal outputs of the project are:

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(1) A Knowledge Base System comprising historical and real time hydro- meteorological data, GIS data incorporated in a Knowledge Management System for ease of access, display and maintenance of the knowledge base.

(2) A Forecasting System for reservoirs and river systems including inflows and floods levels efficiently utilising weather forecasts and real time data from the RTDAS.

(3) A Reservoir Operation Guidance System.

(4) A web based interactive Communication System allowing access to the Knowledge Base, and the Forecasting and Guidance Systems for WRD offices and stakeholders.

(5) A comprehensive Capacity Building programme for WRD comprising formal training courses, on-the-job training, workshops, study tours and hotline support. 1.4 Project Achievements A summary of project tasks, works carried out to achieve the outputs and related deliverables are presented in Table 1.1 Table 1.1 Summary of Project Tasks and Deliverables

Main task Works Carried Out and outputs Deliverables

Task 1 After reviewing the current Inception Report forecasting, reservoir operation, Review Current warning dissemination and Forecasting and emergency response capabilities in Operational the Krishna and Bhima Basins the Capabilities needs of WRD and stakeholders for effective water resources and flood management in Krishna and Bhima Basins have been identified.

Sources of weather forecasts, and flow forecasting and reservoir operation tools have been identified and assessed.

Reviewed all available hydro- climatological data and data management systems, the RTDAS network, real time satellite data, and identified critical gaps and recommend strategies to fill these.

Options and scenarios for optimal multiple reservoir operation have

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been defined.

Reviewed institutional capacity of WRD, and recommended improvements for human resource development, and facilities for effective functioning.

Task 2 The functional specifications for Interim report, the WRD Krishna-Bhima Knowledge Base knowledge base have been Initial model demos Development developed. Knowledge Base System Designed and developed database management system.

Developed knowledge base.

Developed the knowledge management system.

Task 3 The modelling system consisting of Interim Report hydrological and hydrodynamic Real-Time models based on MIKE11 was Model Development Streamflow / established for the Krishna and Report Flood Forecasting Bhima River Basins and calibrated Model against historical and current data.

Model results were used to identify critical reaches for forecasts.

The modelling system has been integrated with weather forecasts Final Report (QPF) and the RTDAS.

Data assimilation has been applied to ensure the maximum information is extracted from the real time data to ensure the best possible forecasts.

Flood maps have been prepared for critical historical events, and tools have been developed for flood forecast mapping.

Task 4 The simulation models have been Interim Report extended with optimisation for Reservoir water resources and flood Reservoir Operation & Operational management. communication & Guidance System information management Operational guidance system for 6 Final Report 6 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

multiple, multi-purpose reservoir Report operation have been established. Task 5 A communication Strategy and Reservoir Operation & Protocol supporting information communication & Communication channels and dissemination has information management and Information been developed. Report Management Systems Designed, prepared specifications for the Operational Control Room, and supported the development, necessary equipment have been procured.

The Web Portal has been developed to provide access and disseminate information from the Knowledge Base and the RTSF- ROS.

Task 6 WRD staff was engaged in and Training Materials supported the development of the Capacity Building Streamflow and Reservoir Workshop reports and Operation Guidance System. User guides Several trainings were conducted. Final report Facilitated Workshops organised by WRD.

International study tours for senior managers of WRD were organized.

Prepared operational user and reference manuals, online context dependent help, documented demonstration cases, training materials.

A plan for technical support, with further training courses and hotline support has been prepared.

A strategy for long term sustainability and enhancement of the developed system including an institutional strengthening plan has been developed.

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2 KNOWLEDGE BASE SYSTEM 2.1 Features of RTSF&ROS The specific objective of the Project is to develop a Real Time Streamflow Forecasting and Reservoir Operation System (RTSF&ROS) for the Krishna and Bhima River Basins in Maharashtra. The System integrates the real time Data Acquisition System (RTDAS) with data from external sources, meteorological forecasts, flow forecast modelling, analysis and decision support tools in an IT system designed for ease of use by operators. The main features of the RTSF&ROS are:  Comprehensive database  Comprehensive facilities for integrated presentation of the dynamics of the hydrology and water resources of the basin  A range of hydrological, river basin water resources and hydrodynamic river models  Predictions of the future hydrologic state of the catchment and river system  Reservoir Operation Guidance system At the core of the RTSF&ROS, also called a Real Time Decision Support System (RTDSS) are mathematical models which describe the state of the catchment, reservoirs and main rivers, and predict future states for a range of scenarios relating to natural events and human intervention. The models require data:  describing the physical features of the catchments, rivers, reservoirs and other hydraulic structures  hydrologic data describing the state of the catchment and rivers – historical data for model calibration  real time and forecast data for making forecasts of future catchment states  water demand data for optimizing the operation of reservoirs All data used for modelling purposes and output from model simulations are stored and maintained in the database of the Knowledge Base System (KBS). The KBS provides a large number of functionalities for working with data, comprising database input and output tools, data visualisation and data processing (filtering, gap filling, etc). Modelling-wise the RTSF&ROS includes functionality for automatically extracting and arranging the necessary data for the model simulations and subsequently for importing the generated data to the database. This ensures that data (covering both observations and model output) are readily available in the RTSF&ROS user interface and that system management becomes easier compared to having data stored in file system folders.

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2.2 Brief Description of KBS The main output of Task 2 – Knowledge Base development is Knowledge Base System (KBS), designed and installed with all historical hydro-meteorological data, river flows and levels, irrigation data, available satellite images and other GIS data collected and populated in the database. The GIS data include topographic data, satellite imageries showing administrative/land use/land cover/cropped and irrigated areas, soils. The KBS has also a facility of generation of daily crop water requirements using data from real time full climate stations (FCS). Data from the reservoirs have been collected and included in the database. The database system is flexible to receive any additional data from other sources. Also the features include update and incorporation new data. For the real time data, facilities and links have been developed to import al RTDAS data. Real time data flow protocol has been developed and tested, which ensures seamless flow of data from RTDAS to the KBS. The knowledge base also has the capability of analysing historical hydro- climatic time series data. Figure 2-1 shows overall contents of the KBS.

In addition to providing the input data for the mathematical models, the database will also store the results from the models. The database will be used to store historical hydrologic data on the basin and data collected through the RTDAS, definitions of the various scenarios that WRD will utilise for short and long term planning, and input that can be used to operate the dams and other controls.

Figure 2-1 Over all Contents of the Knowledge Base System 2.3 Hardware The main hardware of the KBS is a Database Server - Dell(TM) PowerEdge(TM) T710. It is a powerful machine with 24GB RAM and 1 TB Hard Drive with additional Hard Drive for data backup. The Database Server hosts all the historical as well as Real Time data received from the RTDAS as well as various sources and model results. The KBS uses the data from Database server.

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A Web Server Dell(TM) PowerEdge(TM) T110 II has 4GB RAM and 500 GB Hard Drive. The Web Server is mainly for dissemination modelling results, warnings and any other information which WRD wants to publish.

Two high end machines are Lenovo Think Center DeskTop 1607G7Q with Intel Core I3, 4GB RAM and 500 GB Hard Drive. The desktops are for running the models as well as KBS. The results from the models are sent to Web Server for publishing. 2.4 Software The database component of KBS is a relational database management system (RDBMS) storing data in the form of related tables. Relational databases require few assumptions about how data is related or how it will be extracted from the database. As a result, the same database can be viewed in many different ways. The RDBMS is prepared for handling all types of DSS data: GIS (spatial) data, time series data and scenario/model data. The Database components used in the system comprise:  PostgreSQL – a standard well-proven Enterprise-level RDBMS:  PostGIS – an extension to PostgreSQL that makes it possible to maintain and process GIS data PostgreSQL is an object-relational database management system. It is released under a Berkeley Software Distribution (BSD) style license and is thus free and open source software. As with many other open source programs, PostgreSQL is not controlled by any single company, but has a global community of developers and companies to develop it. The development of PostgreSQL dates back to the early 1980s. The main features of PostgreSQL comprise:  Stored procedures can be written in high-level languages like Python, C++ and Java  Indexes – based both on column values and expressions. Partial indexes are also supported  Triggers can also be coded in high-level languages  Multi-version concurrency control which provides individual user snapshots of the database  Updatable views  A wide variety of data types  User defined objects  Inheritance – tables can inherit characteristics from a parent table. This can be used to implement table partitioning The PostgreSQL database is described in more detail on the PostgreSQL home page (http://www.postgresql.org). The input to PostgreSQL is SQL statements and the output is result sets from the executed SQL statements.

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PostGIS is an open source software program that adds support for geographic objects to the PostgreSQL object-relational database. PostGIS follows the Simple Features for SQL specification from the Open Geospatial Consortium. The first version of PostGIS was released in 2001. The main features of PostGIS comprise:  Geometry types for points, linestrings, polygons, multipoints, multilinestrings, multipolygons and geometrycollections  Spatial predicates for determining the interactions of geometries using the 3x3 Egenhofer matrix (provided by the GEOS software library)  Spatial operators for determining geospatial measurements like area, distance, length and perimeter  Spatial operators for determining geospatial set operations, like union, difference, symmetric difference and buffers (provided by GEOS)  R-tree-over-GiST (Generalised Search Tree) spatial indexes for high speed spatial querying  Index selectivity support, to provide high performance query plans for mixed spatial/non-spatial queries Raster data in the form of ASCII grids and GeoTiffs as gridded rasters and geo- referenced images (BMP, JPG, GIF, PNG). 2.5 Database The Krishna-Bhima Database is a tailored database system developed using the above described software. The database stores a wide range of data. The data are categorised according to the format in which they are stored. The link between the data types, which essentially describes how the data are collected, and the data categories is set out in Table 2.2. Table 2.2 Data Categories INPUT CATEGORY TYPES FORMAT Spatial Data Shapefile DEM Image Remote Sensing Grid Meteorological Forecasts Temporal Time Series Ground Based Point Data Data (historical) Remote Sensing RTDAS Meteorological Forecasts Numerical Rainfall-Runoff Model Parameter Models (NAM) Files

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Water Resources Reservoir (MIKE Basin) Bathymetry Scenario Definitions Hydrodynamics River Cross Sections (MIKE 11) Structure Geometry

The shapefile format is the most common file format for storing spatial related information. The format is developed by Environmental System Research Institute (ERSI) and is an open and well defined format supported by most providers of spatial information. Some data types appear in both spatial and temporal data categories, i.e. remote sensing and meteorological forecasts. Figure 2-2 shows the folder structure of GIS data.

Figure 2-2 Folder Structure of GIS Data The time series data types are classified according to the frequency at which the data change, and also reflect the means of data collection:  Real Time Data – comprise the data from RTDAS, WRD sources for Rainfall and Reservoir Levels, and Rainfall Forecast Sources.

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 Historical Time Series Data – comprise point based measurements of meteorological and hydrometric data made at variable intervals.  Other Modelling Data – comprise surveys updated annually or every few years, such as river cross sections and reservoir bathymetry. Water level-discharge rating curves are also included in this category. Rating curves for gates and power stations are included in this category. This also covers the daily crop water requirement data, generated in KBS. A comprehensive range of high quality ground based point measured data describing the state of the basin and the rivers and reservoirs will become available in real time with implementation of the Real Time Data Acquisition System (RTDAS). The real time network includes rainfall, climatic, reservoir water level and discharge data. Although the commissioning of RTDAS has been delayed, a data transfer protocol has been developed and tested. Real time data from the RTDAS will be stored in the database in a similar folder structure as the historical data. All data quality check will take place in the RTDAS. When data becomes available in RTDAS it will be automatically transferred and stored in the RTDSS database. A status message will be parsed for each station every time a new set of measurements is received from the RTDAS. Historical time series data have been imported to the database and organized in the folder structure shown in Figure 2-3.

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Figure 2-3 Historical Time Series 2.6 Knowledge management The Time series manager of the KBS provides management and analysis functionalities for storing, querying, importing, exporting and quality checking. In addition, the manager offers a suite of tools for visualising, statistical analysis and processing one or more time series. It may also be used to view data prior to model simulations and to analyse and visualise model simulation outputs. Typical uses of the time series manager are listed in Table 2.3. Table 2.3 Examples of the time series manager Task Principal activities Create Time Series A new time series can be created in the database by: directly creating a series using the tool, importing a time series from a variety of sources including RTDAS. Edit Time Series An existing time series can be edited for all its components (time, value)

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Export Time Series A time series may be exported to Excel, a modelling system or an external file to a prescribed format. Filter Time Series This function is very useful for large databases. Defining a search criteria for looking-up time series in the database, such as name, type data, scenarios etc. Import Time Series Importing Time series data from Excel, etc. Inspect Time Series Looking at the time series attributes and meta data Visualize Time Activities include display time series data in tabular or Series graphical forms, adding time series to an existing series or chart, customizing the chart or table Using/Processing This functionality is the most useful in data processing, Time Series quality checking, gap analysis, resampling, statistical analysis, etc.

In order to illustrate the time series analysis capabilities of the database, rainfall data form Mahabaleshwar and discharge data from Karad G-D station were selected. Data gaps are clearly indicated. Figures 2-4 to 2-6 show the performed analyses. The analyses include re-sampling, duration curve and statistical analysis. Further details of the KBS are presented in the Knowledge Base System Documentation (June 2012).

Figure 2-4 The Daily Rainfall at Mahabaleshwar (top graph) has been re- sampled into monthly (middle graph) and yearly (bottom graph).

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Figure 2-5 Discharge data at Karad G-D Station (top graph) has been used for duration analysis (middle graph) and statistical analysis (seasonal annual maximum)

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Figure 2-6 Cumulative probability distribution function (CDF) of discharge at Karad G-D Station

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3 THE RTSF&ROS MODELS 3.1 Modelling system The modelling system developed in the project consists of:  A hydrological model (Rainfall-Runoff Model) for generating runoff from a number of catchments schematized in the two basins.

 A Hydrodynamic Model for routing flows through the river and reservoir system to compute flows, water levels and flood maps.

 A real time flood forecast module for computing streamflow and flood forecast for period of 3 days from the time of forecast.

 An user interface integrating the above models for operational forecasts and for providing reservoir operation guidance, scenarios management and flood warning and dissemination.

 A river basin water resources simulation model for water allocation including optimizing water use and reservoir operation.

The MIKE software system, developed by DHI, based primarily on the need for advanced data assimilation for optimal flood forecasting, options for reservoir operation, has been adopted for this project. This package fulfils the entire features and functionality required for the Krishna-Bhima RTSF & ROS. Figure 3-1 shows a modular structure of the MIKE11 modelling system.

Figure 3-1 Modular Structure of MIKE 11

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3.2 Rainfall-runoff Model To simulate the spatial variation in the lateral inflow to the river system, the two basins have been subdivided into 122 sub-catchments as shown in Figure 3-2. The sub-catchment delineation is to a large degree been based on gauging station location to make it possible to calibrate the model at as many locations as possible. Further sub-catchments have been defined at locations where important tributaries join the main rivers and where spatial variation in precipitation or terrain indicate the need for a subdivision. Further details of the model are presented in the Interim report (March 2012) and the Model Development Report (September 2012).

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Figure 3-2 Sub-Catchment Delineation of Krishna and Bhima River Basins (Showing rainfall stations, evaporation stations, reservoirs and G-D stations) The hydrological model has been calibrated to obtain the best possible model performance in terms of its ability to replicate the historical observed hydrographs

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on the basis of the historical input. If the model is able to simulate the historical hydrographs well it will also perform well in future simulations. The final model parameters were chosen so the best compromise was achieved between three criteria: matching the peaks, matching the cumulative water balance (Wbl) curve and reaching as high as possible the coefficient of determination (R2). The water balance error (Wbl) is attempted to be as low as possible. The model has been calibrated on all the available discharge gauging stations and reservoir inflow data. The quality of model calibration depends on density, frequency and quality of input data. In order to illustrate a good NAM calibration, the case of Koyna catchment is presented in Figure 3-4, which shows an excellent calibration of the NAM rainfall-runoff model for the years 2005 to 2006. Figure 3-5 shows a calibration for Bhima_R2 Catchment. In all cases, the opportunity for a much improved calibration will arise with the availability of the higher frequency and higher density observations from the RTDAS. In addition, the advanced data assimilation in the MIKE 11 software, compensates for any deficiencies in the weather forecast and real time data, and in the model setup, in relation to the actual current catchment response. It can be concluded that the model calibration is satisfactory.

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Figure 3-3 Comparison of Simulated and Observed Discharges for Koyna Catchment (R2=0.95, Wbl=0.00% (Obs=5660mm/y, Sim=5660mm/y))

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Figure 3-4 Comparison of Simulated and Observed Discharges for Catchment Bhima_R2 (R2=0.80, Wbl=-1.2% (Obs=1886mm/y, Sim=1863mm/y)) 3.3 Hydrodynamic Model 3.3.1 Model Development The Hydrodynamic River Model takes the rainfall-runoff from the NAM, and carries out a continuous routing of the flows and flood waves through the main rivers and reservoirs of the basin. The model outputs discharges and water levels throughout, for application to short term Flood Forecasting and Optimisation. The hydrodynamic river model for short term flood forecasting is established for the two basins combined. Figure 3-5 shows the river network with information on the river cross sections used from different sources, including the recent river survey programme of WRD (2012). A total of 1,550 cross sections are applied in the model. In order to produce flood inundation maps accurate flood plain transects and a high resolution digital elevation model (DEM) is required. Since the DEM of a reasonable resolution is not available for the Krishna and Bhima Basin, flood plain levels obtained from the recent surveys have been used. The model describes the propagation of flood waves through the river and reservoir system. The same

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model, incorporating data assimilation at all the real time discharge and water level stations, is used in real time streamflow and flood forecasting. A detailed description of how the model is developed is presented in the Interim Report (March 2012) and the Model Development Report (September 2012). Figure 3-6 shows a MIKE11 schematic of the hydrodynamic model.

Figure 3-5 MIKE 11 Model Network showing cross section sources

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Catchment runoffs from the NAM Rainfall-Runoff model are used as upstream boundaries and intermediate inflows. The hydrodynamic model has an automatic coupling to the rainfall-runoff model. The entire area of the two basins is subdivided into 122 catchments. Each catchment is connected to the river model either by a point connection in the case of a major tributary, or distributed in the case of minor tributaries. Figure 3-7 shows the river network with NAM runoff catchments.

Figure 3-7 River Network showing runoff catchments A total of 43 reservoirs are included in the model as shown in Figure 3-7.

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Figure 3-8 Reservoirs in the MIKE11 Model

In the Krishna-Bhima model, reservoir spillway gates, irrigation outlets, hydro power releases and leakage are incorporated as “control structures”. The functions of the gated control structures can be simulated for different types of control variables, such as water level, discharge, gate level etc. The MIKE 11 Structure Operation (SO) module is being set up to describe the present and future reservoir operation rules for the reservoirs within the Krishna and Bhima river basins. The SO module is applied whenever the flows through spillways and sluice gates are regulated by operation of movable gates or controlled directly as in turbines and pumps. The operation rules are applied via a number of logical statements combined with Control Strategies as per the existing operation rule curves.

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3.3.2 Model Outputs The basic outputs of the MIKE 11 hydrodynamic model are discharges and water levels in the main rivers and reservoirs. The model provides additional outputs like flooded area at each cross section, and the total flooded area downstream. Outputs can be obtained for any time steps. However, the frequency of the output has to be compatible to the frequency of input data. Hydrographs at daily, hourly and 15 minutes may be produced once the RTDAS provides data at every 15 minutes.

3.3.3 Model Calibration A detailed description of model calibration is given in the Model Development Report (September 2012). Figures 3-9 to 3-12 show some sample calibration results. It can be concluded that a satisfactory calibration of the Hydrodynamic model has been achieved. When the model is used in real time flood forecasting, then the data assimilation compensates for both amplitude and phase errors in routing flood waves. In addition, more detailed data will enable fine tuning the calibration and routing the runoff. This issue will be further addressed in the RTSF&ROS testing and operation phase, when the RTDAS is producing useful and reliable results.

[m^3/s] Narsinphur Discharge Time Series Discharge Simulated 8000.0 External TS 1 Observed 6000.0

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Figure 3-10 Water level calibration at Narsingpur and Barur gauging stations - (Blue line: simulated, red line: observed)

Figure 3-11 Water Level calibration of Panchganga at Ichalkaranji (black line: simulated, blue line: observed)

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Figure 3-12 Discharge calibration of Mula-Mutha at Khamgaon (black line: simulated, blue line: observed)

3.3.4 Model Applications Identification of Critical River Reaches

The calibrated MIKE11 model has been used to simulate large historical floods as well as with some probabilistic inflows to identify critical river reaches. Based on information available from WRD as well from the historical model results, the alert and warning values of discharge and water level are generated for further validation. The model also generates flood map, which indicates the reaches which have crossed the alert or danger levels for a particular event. This information is integrated with the administrative boundaries as well as the inferences drawn from satellite data. A Taluka level Flood Affected Map (Figure 3-13) has been prepared, which shows that the Haveli Taluka (including Pune city) in Pune District, Pandharpur Taluka (Including Pandharpur Town) in Solapur district, Miraj Taluka (Including Sangli city) in Sangli district, Shirol and Gagan-Bawda in Kolhapur disctrict are highly flood affected taluks. Maval and Daund Taluks in Pune district; Karad in Satara district; Karvir and Harkalangale in Kolhapur district are Moderately flood affected taluks. Shirur, Purandar, Baramati and Indapur in Pune district; Madha, Mohol, Mangalvedhe, Solapur South and Akkalkot taluks in Solapur district; Patan in Satara district; Shirala, Walwa and Palis taluks in Sangli district; Shahunagari, Panhala and Radhanagari in Kolhapur district are Less Flood affected taluks. Once the RTDAS is in place, these maps can be refined further, if required during the testing phase.

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Figure 3-13 Identification of critical river reaches with administrative boundaries Figures 3-14 to 3-16 show longitudinal profiles of the river reaches with high flood levels simulated for past flood event of 2006. Also inset are river cross –sections at critical locations (chainages) illustrating bank overtopping at high floods. The longitudinal profiles show clearly the critical river reaches where the high flood level over tops the banks.

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Figure 3-14 L-S along Mula-Mutha showing bank overtopping

Figure 3-15 L-S along Bhima showing bank overtopping

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Figure 3-16 L-S along Krishna showing bank overtopping

Flood Mapping

Using the flood mapping facilities of MIKE11, a series of flood maps have been generated in three flood prone areas: Pune, Sangli and Pandarpur. The recently surveyed flood plain levels along with river cross sections have been used in the flood mapping exercise. Figures 3-17 shows simulated flood maps around Pune city during the floods of August 2005. Figure 3-18 shows a simulated flood map for Pandarpur area in 2008. The sample flood maps presented below show the capabilities of MIKE11 to generate flood maps. However, it should be noted that the floods maps are generated by the 1-dimensional model and are reasonably accurate when the flood plain flooding is governed by river flooding. For a more accurate and detailed flood risk mapping a 2-dimensional flood modelling and mapping tool is required.

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Figure 3-17 Model simulated flood map near Dattawadi in 2005

Figure 3-18 Pandarpur flood (2008)

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3.4 The Forecasting System 3.4.1 Introduction The hydrological model maintains a quantitative memory of the water accumulated in the catchments in the form of soil moisture, and ground water. This accumulated water volume will be released as runoff to the main rivers during the succeeding periods, simulated by the hydrological model. Converting the predicted precipitation to runoff hydrographs, the model provides a quantitative response to the predicted weather forecast. The output from the model is fed into the MIKE 11 river model for forecasts. Quantitative precipitation forecasts have large uncertainties for extended lead time times, and the runoff becomes correspondingly uncertain when the lead time exceeds a few days. Therefore, the flow/flood forecast in the RTSF&ROS refers to short-term forecast up to three days in advance. The short term forecasting model is similar to the hydrodynamic model. The forecasting model uses rule operation instead of scheduled releases at the reservoirs, and the data assimilation mode is activated. The setup of the short term forecasting model implies that the model handles both historical data and estimated future inflows and scheduled releases. The period during which historical data are applied is termed the hindcast period, and the period representing the future is termed the forecast period. Figure 3-19 illustrates the concepts and steps of a short-term forecasting system.

Figure 3-19 Illustrations of a short-term forecasting system

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Another aspect of forecasting is Data Assimilation, which enables the model to assimilate measured water levels and discharges into the model results during hindcast. Corrections made in order to match simulated and measured results are analysed and used to forecast the error that can be expected in the simulated results for the near future. This error forecast increases the reliability of the forecast results. Using data assimilation of discharges in the rivers (or water levels in combination with stage:discharge relations) has two purposes. Firstly, assimilating the data ensures that the correct amount of water is conveyed downstream during the hindcast period. Secondly, the error forecast ensures that the recognised error in the inflow is forecast into the near future, thereby improving the validity of the inflow forecast. In this way the best inflow forecast to the reservoirs are achieved. The required model inputs are:  Operation of reservoirs - rule operated meaning that in order to make forecasts it is necessary to know which rules apply. For the hindcast period measured discharge will be used. For the forecast period, scheduled releases (or user defined releases) are used. A combined time series will be supplied to the model by the system.  Information for data assimilation and error forecast - comprises measured water levels and discharges that can improve the accuracy of the forecasts. These will be provided in time series (Discharge measurements at model boundaries will be assimilated in the hydrologic model.)  Boundary inflows will be drawn from the database (NAM outputs derived from weather forecasts and the RTDAS) and supplied to the model as time series representing the inflow for both the hindcast and forecast period.

3.4.2 Quantitative Precipitation Forecasts (QPF) Many organizations both inside and outside of India are generating rainfall forecasts with some lead time and spatial resolution. For this basin area, rainfall forecast could be available from several sources: Indian Meteorological Department (IMD), National Centre for Medium Range Weather Forecast (NCMRWF), India, National Oceanographic and Atmospheric Administration (NOAA), and Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES) ) www.rimes.org. RIMES is an inter-governmental organisation based in Bangkok, Thailand. A review was also made in the Inception report (December 2011). Among them, in order to be able to use in a real time forecast with a lead time of 3 days and a good spatial resolution, rainfall forecast provided by RIMES and NCRMWF has been selected.

RIMES in cooperation with NCMWRF produces rainfall, with 3 days lead time with a spatial resolution of 9 km × 9 km grid and temporal resolution of 6 hours using Numerical Weather (NWP) model. Data is received as ASCII format for the study area with 9km X 9km grid as well as a PDF. The RIMES Servers sends the 3-day forecasts automatically to a dedicated E-mail address ([email protected]) every morning before 7 AM local time. A procedure has been developed in RTFS&ROS to download the QPF automatically from the RTSF gmail address and store in the model database for use in the forecast Final Report 35 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

operation. At the same time, the QPF is exported to the KBS data server. Also forecasts of rainfall and other weather parameters may be downloaded on a daily basis from the IMD’s website (www.imd.gov.in) so that alternative scenarios of rainfall forecasts may be compared by the operator. The IMD website also provides a link to satellite data

3.4.3 The Forecasting and Operation System The real time forecasting and operation system is based on calibrated rainfall-runoff and hydrodynamic models. The system works as a stand-alone Windows application, which does not require in-depth knowledge of complicated models and GIS applications. However, based on a very user friendly interface developed for this project, it is possible to have full control on the on-line forecasting. The system once configured may also run automatically. The forecasting system has also the provision to run different scenarios in offline mode so that comparisons can be made with historical floods forecasted on hindcast mode. The offline mode can also be used during an interactive operational decision making. The setup is an open system in which modifications of key parameters such as forecast locations, time steps, warning levels etc., can easily be incorporated by a trained operator. Figure 3-20 shows the User Interface of the operational forecasting system. The Interface can be used to manage the most common activities in the daily operation of a forecasting system.

Figure 3-20 User Interface for the operational forecasting system

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The RTSF & ROS User Interface contains (referring to Figure 3-20): A) Tools, selection boxes and status (left column) B) An overview (as bitmap) of the model setup and stations included (upper right) C) Graphical and Tabular View (lower right)

Tools, selection boxes and status information Following tools and settings are possible Selection of the Actual Model Setup in Online or Offline mode 1) Selection of Model 2) Selection of Time of Forecast 3) Status line 4) Setup – configuration of Model setup in RTSF & ROS 5) RTSF & ROS batch Jobs 6) MIKE11 tools 7) View Flood Map 8) WEB page 9) Scenario management 10) Dissemination of Results

The RTSF & ROS Overview The Overview shows, the river network, the flood status (warning level) for a selected date at forecast locations on the river system (shown as coloured squares at each forecasting location) and the accumulated catchment rainfall (shown as values in grey squares) for a selected period in the modelled catchments.

Graphical and Tabular View Graphs and tables can be selected from the map, when clicking on a station on a map. It is possible to select between water level and discharge from the selection box just above the graph to the left. Zoom facilities are available when right clicking on the map or clicking on the button in the upper left corner. In the upper right corner it is possible to select flood status for different time steps after Time of Forecast. The graphical and tabular view of catchment rainfall can be selected when clicking on a number on the bitmap. The number represents the accumulated rainfall during the period selected in the lower left corner of the graph. The accumulation period represents hours before time of forecast (first selection box) up to hours after time of forecast (second selection box). The tabular view shows the actual rainfall and accumulated rainfall. Similarly, reservoir status can be seen from the reservoir mode selected in the map. The reservoir symbol indicates approximate percentage of fullness of a reservoir. The graphical and tabular views show the reservoir level, inflow and outflow.

Online and Offline mode RTSF & ROS can be applied in Online and Offline modes. When running RTSF & ROS in Online mode, the Overviews are automatically updated as soon as a new forecast is ready. Latest Time of Forecast is updated in (2), while the simulation

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status will appear in the Status box (3). When running in Offline mode it is possible to load historical forecasts and test various scenarios. Details of the RTSF&ROS are presented in the User Guide Version 2 (September 2012). Detailed overview of results from the forecast simulation using MIKE VIEW, with a predefined setup specified via the configuration editor. Figure 3-21 shows an example, which include the river network, a longitudinal section along a selected river, river cross section at a selected location and time series of discharge and water level.

Figure 3-21 Detailed overview of MIKE11 results from a forecast simulation

3.4.4 Forecasts Using the above described system, forecast of inflows to reservoir and then corresponding outflows can be made. Figure 3-22 illustrates the forecast results.

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Figure 3-22 Example of inflow forecasts for 6,12,36 and 48 hours

3.4.5 Rainfall forecast scenario The Rainfall Editor can be used to modify the rainfall to a catchment (or a group of catchments) from the original simulation to test alternative rainfall events. The rainfall time series is subdivided into user defined periods, where the rainfall editor provides an overview of the accumulated rainfall within specified periods and has a provision to change the values. In Figure 3-23, periods for the last 24 hours up to time of forecast and the following 12, 24 and 48 hours into the forecasting period can be specified. The 122 catchments in the model setup have been grouped into 18 larger areas with similar rainfall characteristics. The user can now change the original accumulated rainfall with new estimations for each period – each value of the original catchment rainfall time series will then be multiplied with the ratio between estimated and original values.

Figure 3-23 Rainfall forecast editor

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4 RESERVOIR OPERATION SYSTEM 4.1 Introduction The deliverable under Task 4 is a reservoir operation guidance system based on stream flow forecasts as produced by the RTSF&ROS described above. The simulation models of RTSF&ROS are integrated with a suite of optimization tools for optimum operation of the reservoirs both for the short-term operation during the flood season and for round the year optimal water allocation. Three sets of optimization exercises have been carried out for developing optimum reservoir operation guidance system. The first set is the short term optimization, which is aimed at providing an improved reservoir operation guidance during floods when an inflow forecast is available from the RTSF&ROS. The recommended short term rule curve is a switch from the long term rule curve established by WRD for the major reservoirs in the Krishna and Bhima River basins. It has been demonstrated that using the short term optimization of reservoir operation a considerable reduction in flood release can be achieved during the forecast period without compromising on the storage at the end of the forecast period. In a way, the reservoir state follows the prescribed rule curve at the end of the optimization/forecast period. The second type of optimization model developed is for long term reservoir operation guidance system. The optimization system is developed for round the year water allocation for irrigation and water supply considering power development. The third type of optimization model developed is seasonal operation of the reservoirs to minimise downstream flooding while considering the need of keeping the reservoirs full at the end of the rainy season. The reservoir operation guidance derived from the second and third types of optimization models are incorporated in the overall basin simulation model (MIKE BASIN) for the entire Krishna and Bhima basins in Maharashtra. Illustrative applications have been developed for typical hydrological years (dry, average and flood years) based on historical data. Reservoir operation often involves a large number of stakeholders with different objectives, such as domestic and industrial water use, irrigation, flood control, hydropower generation, and navigation. Thus, optimisation of reservoir operation is a complex, multi- purpose optimization problem where balanced solutions between the often conflicting objectives are required. In addition, operation of multiple reservoirs or other water supply sources should be considered jointly, hence adding additional complexity to the optimization. Traditionally, fixed reservoir rule curves are used for guiding and managing the reservoir operation. These curves typically specify reservoir releases according to the current reservoir level, hydrological conditions, water demands and time of the year. Established rule curves, however, are often not very efficient for balancing the demands from the different water users. Moreover, reservoir operation often includes subjective judgments by the operators. Thus, there is a potential for improving reservoir operating policies and small improvements can lead to large benefits. For optimization of reservoir systems, procedures based on coupling simulation models with numerical search methods have been developed. Traditionally, the simulation- optimization problem has been solved using mathematical programming techniques such as linear or non-linear programming. Application of these methods, however, puts severe restrictions on the formulation of the optimisation problem with respect to description of water flow in the system, and definition of control variables to be optimised and associated

40 Final Report 40 Krishna & Bhima River Basins RTSF&ROS optimization objectives. Recently, procedures that directly couples simulation models with heuristic optimization procedures such as evolutionary algorithms have been proposed (Ngo et al., 2007). These methods have proven to be effective for optimisation of reservoir systems (Pedersen, et al., 2007). Details of the optimization systems are given in the Reservoir Operation System and Communication Management Report (November 2012). Sample results are presented in this Chapter. 4.2 Short Term Optimization 4.2.1 Methodology The purpose of the short term optimization during floods is to assist in decision making in situations where high inflows are forecasted to result in water levels above the guide curve for the reservoir. The optimization will suggest release hydrographs that ensures that the reservoir water level will comply with the guide curve at the end of the forecast period (3 days) and that the water level will be below the maximum allowed water level during the whole forecast period. At the same time the release hydrographs will aim at minimizing downstream peak flow. This purpose is believed to comply with WRD’s statements, as described in the DAM Safety Manual, regarding rule curves quoted below: “Guide curve is the target level planned to be achieved in a reservoir under different probabilities of inflows and / or withdrawals during various periods. It means that the reservoir level is to be maintained as per upper guide curve during normal inflows. During the heavy floods, the normal reservoir operation schedule should be switched over to the emergency flood moderation schedule. The criterion for switching over is the occurrence of heavy to very heavy rainfall in the catchments of the dam or the intimations of heavy to very heavy flows into the reservoir. This switching over process should be well studied and implemented in sub basin/basin existing in the state. During the emergency reservoir operation, the reservoir levels are allowed to rise temporarily above upper guide curve but below MWL for making flood absorption capacity to greater possible extent.”

In this Project, the MIKE 11 modelling system is adopted for simulating the flow in the river system and reservoir operations. The structure operation module in MIKE 11 allows implementation of complex control strategies, whereby reservoirs can be operated by defining a number of different control strategies with various conditions. The use of several control strategies makes it possible to simulate multi-purpose reservoirs, which take into account a large number of objectives. The MIKE 11 model is combined with a numerical optimization tool AutoCal (DHI, 2011) that is used for optimising different control variables defined for the reservoir operation strategies. The optimisation tool includes a general multi-objective optimization framework that searches for the set of non- dominated or Pareto-optimal solutions according to the trade-offs between the various objectives. The simulation-optimization procedure can be used in an off-line mode for optimisation of reservoir operation rule curves using historical data. This operation can be further improved in real-time by fine-tuning the reservoir releases using real-time and forecast information. In this case, the MIKE 11 modelling and reservoir control system uses weather forecasts to provide forecasts of reservoir inflows This is done by combined use of a rainfall runoff model and a hydrodynamic model, both running in real time forecast model, and a generic optimization tool. A two-step approach has been implemented as illustrated in Error! Reference source not found.Figure 4-1. Final Report 41 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS he first step corresponds to a standard forecast during which measured water levels and discharges are assimilated into the model results during the hind cast period. This ensures that the model complies with the real life situation at the time of forecast (TOF). During the forecast period scheduled releases from the reservoirs are applied. Thus, the model will predict water levels in the reservoirs for a situation in which no measures beyond the already planned are taken to avoid too high reservoir water level.

Figure 4-1 Figure illustrating the two-step approach adopted for the optimization A second step can now be performed in case the water levels predicted in the first step do not comply with the guide curve. Here the effect on applying additional releases is evaluated against the optimization objectives which are:  Comply with the guide curve at the end of the forecast period  Never exceed the maximum allowed water level  Mitigate peak discharge downstream  Spill as little water as possible How this works is illustrated in Figure 4-2. The optimizer AutoCal suggests different spill hydrographs. The consequences of applying these hydrographs are evaluated using MIKE11. Selected results from MIKE11 (reservoir water levels and downstream peak discharges) are evaluated against the targets and AutoCal will adjust the suggested hydrographs.

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Figure 4-2 Figure illustrating the two-step approach adopted for the optimization

4.2.2 Example Applications The optimization models are first applied for the major reservoirs in which flood control is a major concern. The optimization models are tested for the flood events during the monsoon in 2006. Then, the entire MIKE11 hydrodynamic model of the Krishna-Bhima basin is run in optimization mode to see the effect of an integrated reservoir operation. Tests have been made on the optimization of the Ujjani Reservoir for a period where spilling occurred. The results are presented and discussed below. In Figure 4-3 a comparison is made between optimized and measured water level at Ujjani Reservoir during a spilling event in 2006. It is apparent that optimization utilizing an early warning of high inflow enables a better management of the reservoir water level. Not only is it possible to avoid excessive exceedance of the guide curve, it has also been possible to maintain a higher water level at the end of the period.

Comparison between optimized and measured water level at Ujjani reservoir 497.5

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495.5 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-3 Graph comparing optimized and measured water level with the guide curve for the Ujjani Reservoir When comparing the optimized and measured release during the test period (Figure 4-4), it is apparent that the amount spilled is considerably less than what happened

Final Report 43 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

during the event. This is also reflected in the downstream discharge at Pandharpur (Figure 4-5). The peak discharge has been reduced from approximately 7,800 m3/s to approximately 7,100 m3/s.

Comparison between optimized and measured release at Ujjani reservoir 9000

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0 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-4 Graph showing a comparison between optimized and measured release at Ujjani Reservoir during 2006

Optimized and measured discharge at Pandharpur 8000

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0 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-5 Comparison of optimized and measured release at Pandharpur The optimization has also been tested for Koyna Reservoir. The optimized water level is compared with measured water level in Figure 4-6. It is apparent that better compliance with the guide curve can be achieved that when the forecasted inflow is taken into account when deciding about spilling. Figure 4-7 shows a comparison between the optimized and the measured releases. It is seen that the peak discharge is lowered from approximately 2500 m3/s to approximately 1500 m3/s.

44 Final Report 44 Krishna & Bhima River Basins RTSF&ROS

Comparison between optimized and measured water level at Koyna Reservoir 660

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652 13/07/2006 28/07/2006 12/08/2006 27/08/2006 Figure 4-6 Graph comparing optimized and measured water levels at Koyna Reservoir

Optimized and measured discharge at Koyna Reservoir 3000

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0 13/07/2006 28/07/2006 12/08/2006 27/08/2006 Figure 4-7 Graph comparing optimized and measured release from Koyna Reservoir For the Kadakwasla Complex, selected results are presented below. The water levels for Panshet Reservoir, Temghar Reservoir and Warasgaon Reservoir are depicted in Figure 4-8, Figure 4-9 and Figure 4-10, respectively. It is seen that the optimization is able to maintain the water levels within acceptable limits. For Temghar Reservoir it seems like the optimizer ensures that a larger amount of water is stored and the end of the period. The optimized releases are compared with measured releases in Figure 4-11, Figure 4-12 and Figure 4-13. For all three reservoirs the optimization has lowered the peak discharges supporting the flood mitigation purpose.

Final Report 45 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

I Comparison between optimized and measured water level at Panshet Reservoir 637

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627 18/07/2006 02/08/2006 17/08/2006 01/09/2006 Figure 4-8 Graph comparing optimized and measured water level at Panshet Reservoir

Comparison between optimized and measured water level at Temghar Reservoir 700

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695 18/07/2006 02/08/2006 17/08/2006 01/09/2006 Figure 4-9 Graph comparing optimized and measured water level at Temghar Reservoir

Comparison between optimized and measured water level at Warasgaon Reservoir 640

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631 18/07/2006 02/08/2006 17/08/2006 01/09/2006 Figure 4-10 Graph comparing optimized and measure water level at Warasgaon Reservoir

46 Final Report 46 Krishna & Bhima River Basins RTSF&ROS

Comparison between optimized and measured release at Panshet Reservoir 500

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0 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-11 Graph comparing optimized and measured release from Panshet Reservoir

Optimized and measured discharge at Temghar Reservoir 160

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0 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-12 Graph comparing optimized and measured releases from Temghar Reservoir

Optimized and measured discharge at Warasgaon Reservoir 600

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300 Optimized Discharge Measured Discharge

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0 26/07/2006 31/07/2006 05/08/2006 10/08/2006 15/08/2006 20/08/2006 25/08/2006 Figure 4-13 Graph comparing optimized and measured release from Warasgaon Reservoir

Final Report 47 Krishna & Bhima River Basins RTSF&ROS RTSF&ROS

4.3 Long Term Optimization 4.3.1 Optimization of reservoir operation for flood season Though, the reservoirs in Maharashtra are multipurpose including hydropower, irrigation, domestic and industrial uses, they are not operated specifically for flood control due to lack of adequate provision of flood cushion. However, they have moderated flood peaks to considerable extent by proper reservoir operations. The schedules of reservoir operation are based on rule curves derived from historical hydro-meteorological data and experience gained. These methods are often not adequate for establishing optimal operational decisions, especially for flood management. Therefore, the objective function for deriving a season operation guidance selected in this study is to minimize the maximum peak flood release over the flood season. A set of constraints such as reservoir storage limits, daily water balance, minimum downstream flow requirements, hydropower release requirements etc. are applied to the optimization model.

4.3.2 Example applications The flood year of 2006 has been selected for application of the optimization system developed for operating the reservoirs during a flood season. It is also possible to run the optimization from any time during the flood season to the end of the season, using the current state of the system from observed data and assuming that the rest of the season will follow a typical flood year, say 2006. In the future, if a higher flood year occurs, then the optimization can be performed for that particular year. The optimization results provided for various reservoirs below serve as a guideline on how to operate a reservoir or the system of reservoir for a typical flood year. It may be noted that the operational guidelines derived from optimization are only slightly different from the prescribed rule curves. However, these guidance are of indicative only because the operators cannot ensure that a particular year in hand will be a flood year similar to 2006. If an optimization is carried out routinely from the start of the monsoon, then the operation might improve as the season progresses. Khadakwasala complex

Figure 4-14 The Khadakwasala Complex Figure 4-15 shows optimum releases as compared to historical releases during the flood season of 2006. It can be seen that an optimized operation of the reservoir for

48 Final Report 48 Krishna & Bhima River Basins RTSF&ROS

2006 would reduce the flood peak from 1,376 m3/s to 1,082 m3/s on July 29 (Figure 4-16). It also shows that an optimization based release would avoid drastic changes in the release pattern following the peak release on July.

1600

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River Release (m^3/s) 0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 Day from July 1

Historical Release (m^3/s) Optimized Release (m^3/s)

Figure 4-15 Optimized Release from Khadakwasala system (for 2006 flood season)

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1400 1200 1000 800 600 Historical release 400 Optimized Release RiverRelease (m^3/s) 200 0

Figure 4-16 Detailed view of release pattern during 22 July to 11 August 2006 Figure 4-17 shows the optimized storage compared to the historic storage in the Khadakwasala system for the flood season of 2006. It can be seen (from Figure 4- 18) that in order to reduce the peak release to an optimum level, the operation of the reservoir has to deviate from the historical operation, which is derived from the rule curve mainly during July 25 to August 8. As this is a temporary switch from the long term rule curve to a flood operation guidance, it shows that the rule curve is a followed during the remaining part of the season so that the reservoir is kept full at the end of the season. Results for other reservoirs are presented in the Reservoir Operation and Communication Management Report (November 2012).

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900 800

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300 Storage(MCM) 200 100 0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 Day from July 1

Historical Storage (MCM Optimal Storage (MCM)

Figure 4-17 Optimum Storage of Khadakwasala system for the flood season 2006

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Storage(MCM) 600

Optimum Storage (MCM) 550

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Figure 4-18 Detailed view of the Khadakwasala system storage during 25 July to 8 August 2006

4.3.3 Ujjani Reservoir

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8000

7000 6000 5000 4000

3000 RiverRelaese (m^3/s) 2000 1000 0

Historical Release (m^3/s) Optimized Release (m^3/s)

Figure 4-19 Optimized Release from Ujjani Dam (2006 flood year) Figure 3-6 shows optimum releases from Ujjani Dam as compared to historical releases during the flood season of 2006. It can be seen that an optimized operation of the reservoir for 2006 would reduce the flood peak by almost half thus reducing flood damage downstream. It also shows that an optimization based release would avoid drastic changes in the release pattern following the peak release on July. Similarly, Figure 3-7 shows the corresponding storage resulting from the optimized release. The storage comes back to the historical levels from 17th August following the rule curves.

Figure 4-20 Optimized Storage of Ujjani Reservoir (2006 flood season)

4.3.4 Pawana Reservoir

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400 350 300 250 200 150 100

RiverRelease (m^3/s) 50 0 1 8 15 22 29 36 43 50 57 64 71 78 85 92 Day from July 1

Historical Release (m^3/s) Optimized Release (m^3/s)

Figure 4-21 Optimized release from Pawana Dam (2006 flood season) Figure 3-8 shows optimum releases from Pawana Dam as compared to historical releases during the flood season of 2006. It can be seen that an optimized operation of the reservoir for 2006 would reduce the flood peak from 376 m3/s to 226 m3/s, thus reducing flood damage downstream. Figure 3-9 shows the corresponding storage resulting from the optimized release. The storage comes back to the historical levels from 25th August following the rule curves.

300

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200 Max Storage at 275 MCM 150 100

Storage(MCM 50 0 1 8 15 22 29 36 43 50 57 64 71 78 85 92 Day from July 1

Historical Storage (MCM) Optimized Storage (MCM)

Figure 4-22 Optimized Storage in Pawana Reservoir (2006 flood season) 4.4 Optimization of Reservoir Operation for Long-term Water Management An optimization methodology has also been developed for optimized operations of the reservoir system considering round the year water resources management. An economic optimization to find out an optimum cropping pattern in a command is developed first. Then reservoir water allocation is optimized to satisfy the water requirement for the optimal cropping pattern keeping other water allocation as constraints. Although the reservoirs are multipurpose, the competition is mainly between irrigation and water supply (domestic and industrial). In almost all the reservoirs considered, water released for hydropower goes for irrigation use. In 52 Final Report 52 Krishna & Bhima River Basins RTSF&ROS

Koyna dam, the release to the powerhouse below the dam goes for irrigation. Releases to large hydropower plants on the west side flow out of the basin. In principle, the decision between releases to water supply and irrigation is not taken as a multi-objective problem. It is rather taken as a quota priority. Different types of formulations have been considered to optimize the water allocation between irrigation and water supply. A set of water supply factors are used for supplying water to major urban areas in the basin. An iterative optimization-simulation process is used to optimize the long-term water allocation from all the reservoirs in the in the basin. The optimization models have been applied for three typical years namely an average year (2001), a dry year (2003) and a flood year (2006) from historical data and long term simulations carried out using the MIKE BASIN model developed for the entire Krishna-Bhima Basin. Table 4.1 lists the optimization scenarios are presented. Detailed results, which provide a guidance to long-term reservoir operation are provided in the Report “Reservoir Operation System and Communication Management System (November 2012).” Some sample results for selected reservoirs are presented in the following sections. Table 4.1 Optimization Scenarios Scenario Year Reservoir operation Water supply target No. optimization considering constraints (supply factor) 1 Dry Optimal cropping pattern 100 % (no reduction) 2 80 % 3 70 % 4 Historical supplies 100 % 5 80 % 6 70 % 7 Flood Optimal cropping pattern 100 % 8 80 % 9 70 % 10 Historical supplies 100 % 11 80 % 12 70 % 13 Average Optimal cropping pattern 100 % 14 80 % 15 70 % 16 Historical supplies 100 % 17 80 % 18 70 %

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Figure 4-23 shows optimized irrigation releases form the Khadakwasala reservoir sysetm (operation of Khadakwasala, Warasgaon, Panchet and Temgher) for a dry year considering water supply factors of 100%, 80% and 70% respectively.

35.00

30.00

25.00 20.00 15.00 Opt. Irrigation Supply 10.00

Release MCM Hist. Irrigation Supply 5.00 - 1 3 5 7 9 11131517192123252729313335 10 Day Intertval

WS =100% D

40.00

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20.00 Opt. Irrigation Supply 10.00 Release MCM Hist. Irrigation Supply - 1 3 5 7 9 1113 15 17 19 21 2325 27 29 3133 35

10 Day interval

WS=80% D

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30.00

25.00 20.00 15.00 Opt. Irrigation Supply 10.00 Release MCM Hist. Irrigation Supply 5.00 - 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

10 Day Interval

Figure 4-23 Optimal irrigation release from the Khadakwasala complex for optimal cropping pattern (dry year: WS factors: 1 – 100%, 2- 80%, 3- 70%) WS = 70%

54 Final Report 54 Krishna & Bhima River Basins RTSF&ROS

The optimized irrigation release is for satisfyting the irrigation requirement of an optimum cropping pattern that will yield a maximum crop production benefit from the command area. It can be seen that an optimum operation of the reservoirs results into a much higher irrigation releases than compared with historical irrigation releases from the same reservoir. The intergated oprimization-simulation tool is incorporated in the river basin modelling system installed at BSD and the Control room, so that WRD can use for making decisions in the future operational planning of the reservoir system.

4.5 Integrated Operation of Reservoirs

The optimum operation systems developed for the major reservoirs are simulated in the MIKE BASIN model for the entire basin. Figure 4-24 shows the MIKE BASIN model developed in the two basins (Interim Report, March 2012). Figures 4-25 and 4-26 show the schematics of the integrated reservoir systems in the model.

Figure 4-24 The Krishna-Bhima MIKE BASIN Model

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Figure 4-25 Schematic of the Integrated Reservoir System of Bhima Basin

Figure 4-26 Schematic of the Integrated Reservoir System of Krishna Basin The following three typical years are considered for simulation of integrated operation: (1) 2001-02 as an average year, (2) 2003-04 as a dry year and (3) 2006-07 as Flood (wet) year. Two optimum irrigation release scenarios are used, which have been obtained from optimisation results discussed in the previous sections. (1) D1: Optimized irrigation release for satisfying the demand of optimum cropping pattern

56 Final Report 56 Krishna & Bhima River Basins RTSF&ROS

(2) D2: Optimized irrigation release based on Historical/Existing irrigation schedules The MIKE BASIN simulation results in Figure 4-27 and Figure 4-28 show that for both the average year (2001-02) and dry year (2003-04), if the irrigation demands have to be satisfied from the Pawana reservoir with minimising the irrigation deficits, the reservoir will have to be depleted more compared to historical operation which would result into larger irrigation deficits. For the Wet year (2006-07), however, there is not much difference between the optimal releases and historical releases as depicted in Figure 4-29.

615

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10/06/01 01/07/01 22/07/01 12/08/01 02/09/01 23/09/01 14/10/01 04/11/01 25/11/01 16/12/01 06/01/02 27/01/02 17/02/02 10/03/02 31/03/02 21/04/02 12/05/02

Water Level D1 Water Level D2 Historical Water Level

Figure 4-27 Historical Water Level Comparison of Pawana Reservoir with Water Levels after Optimized Releases (for Average Year 2001-02)

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Figure 4-28 Historical Water Level Comparison of Pawana Reservoir with Water Levels after Optimized Releases (for Dry Year 2003-04)

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615

610 605 600 595 Water Level (m) 590 585

Water Level D1 Water Level D2 Historical Level

Figure 4-29 Historical Water Level Comparison of Pawana Reservoir with Water Levels after Optimized Releases (for Wet Year 2006-07) Figure 4-30 shows the flow situation in the entire basin with optimized releases for irrigation while satisfying water supply and keeping the hydropower demands intact, for the wet year 2006-07. This type outputs from a combined optimization- simulation exercise will be quite useful for analysing the flow situation in the entire basin any time during the operation of the system. It is also possible to view the results animated for any given.

58 Final Report 58 Krishna & Bhima River Basins RTSF&ROS

Figure 4-30 Simulation Result for Optimized Releases for the integrated Krishna- Bhima Basin System, showing flows (m3/s) in river reaches

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4.6 Reservoir Operation Guidance System The reservoir guidance system is presented in the RTSF&ROS Model Development Report (October 2012) whereas, updated features are incorporated in the Reservoir Operation system and Communication Management System Report (November 2012). The system has been installed at the BSD and has been tested for reservoir operational scenarios. Trial operation in real time is expected to be carried out during the monsoon of 2013, when the real time data will be available from the RTDAS being implemented by WRD. The Reservoir Operation can be performed via the Reservoir Operation Module of the RTSF&ROS User Interface (Figure 4-31).

Figure 4-31 User Interface for the operational forecasting system and reservoir operation system The tool is used to show the conditions for each reservoir included in the model setup and it can also be used for scenario simulations. The page consists of a Grahical View, as shown in Figure 4-32 (water level left axis and inflow & outflow right axis), a Tabular View (timeseries of inflow, outflow and reservoir levels) and a Reservoir Overview on the bottom of the page. Figure 4-32 shows an example for the operation of the Warasgaon Reservoir. The graph shows a 3 days period (1 day before Time of forecast, indicated with a grey vertical line and the forecasting period of 2 days). From Figure 4-32 it appears that the inflow (red line) is higher than outflow (green line) until ‘2006-07-30 03:00’, when

60 Final Report 60 Krishna & Bhima River Basins RTSF&ROS

the outflow exceeds the inflow. The water level (blue line) increases, therefore in the first part of the simulation, while it decrease when the ouflow eceeds the inflow.

Figure 4-32 Example of Reservoir Operation Module (Warasgaon) 4.7 Scenario Management The scenario management tools allow the user to run the forecast model with different data and compare the results from scenario simulations with the original simulation. Simulation of scenarios is activated when running the operation system in an offline mode. After finishing a scenario simulation, the scenario results can be archived, which can be loaded later for further assessment. The scenario management tools also include facilities to disseminate the scenarios to the WEB Portal. The Reservoir Operation Scenario manager can be used for operating reservoirs with user defined releases, including those derived from optimization.

4.7.1 Reservoir operation scenarios The reservoir operation module can be used to specify user defined releases from the reservoirs to test alternative reservoir operations and releases of water from the reservoirs. As an example, a user defined release of 500 m3/s has been specified for a period of 12 hours for the Warasgaon reservoir as shown in Figure 3-33. To run this scenario the changes made are saved and a new simulation is started with the user defined release.

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In Figure 4-33, the figure to the left shows the specification of user defined releases (dark green bar), while the figure to the right shows the result of the scenario simulation (light green curve, calculated spilling).

Figure 4-33 Example of reservoir operation scenario (Warasgaon) After pressing the refresh button it is possible to inspect the effect of changes on the downstream stations. Figure 4-34 shows a comparison of the water level in the Khadakwasla reservoir (blue curve: original, black curve: with user defined release).

Figure 4-34 Viewing results of reservoir operation scenarios

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5 COMMUNICATION AND INFORMATION MANAGEMENT SYSTEM 5.1 Flow/Flood Warning Reports and Dissemination A variety of flow/flood warning reports and messages are proposed to be disseminated to concerned authority, organisation and communities. Also a variety of dissemination mechanisms are developed.

5.1.1 RTSF&ROS Website A website of the RTSF&ROS project has been developed (Figure 5-1). The Website may be hosted in a commercial server or at the mail server provided at the Operational Control Room. However, for efficiency of access, it is recommended that Operational Control Room should have the facility of high speed internet connection. The pages are divided into the following standard views:  Home: The Home Page shows the overall view and contents of the Website

 About Us: The About Us Page provides information linked to WRD offices and the Basin Simulation Division and the Operation Control Room.

 RTSF&ROS Project: This Page provides a brief about the RTSF&ROS Project, its objectives and outputs

 Alerts and Warnings: This Page provides current warnings and alerts for quick look, which are updated every day (or whenever decided by the authority)

 Contact Us: This Page presents the contact details of responsible officals of WRD, BSD and the Operational Control Room

 Feedback: This Page guides the users of the Website to share their views or provide feedback to the information produced via their E-mail. The E-mail is received to a dedicated E-mail address, which may be changed by WRD during actual implementation.

The Contents of the Website may be viewed by browsing the following Pages:

 The Knowledge Base Page: It provides a brief description of the Krishna-Bhima knowledge Base. It also has a provision of remote login for authorized user, which may be implemented by WRD later.  The Modelling System Page: This page provides a brief description of the modeling tools used in the RTSF&ROS, with reference and links to the provider of the modeling software.  The Krishna-Bhima Online Page: This is the key portal on which all the on-line information is available for dissemination. The information includes rainfall, discharge, water levels and reservoir situation for current and for the forecast period, currently set as 72

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hours. The On-line Page is designed as a standalone Web Portal, which may be hosted in a separate server.  Reports and Maps Page: This Page provides access to all the reports and maps, especially flood maps, which may be historical, current or forecasts produced by the mode. The reports are uploaded by the administrator as decided by WRD authority. The updated maps are also uploaded by the administrator whenever desired by the authority.  Important links: This Page guides the user to Web links (Websites), which are relevant to weather forecasting (national and international resources centers), and other relevant Government sites. Hidden to unauthorized users is a Page for the Web administrator or an authorized official at the Operational Control Room. The features of Web administration are:  Admin Login Page: The administrator can login to the Website with an authorized password. This allows the administrator to upload and update Reports/Maps and Alerts/Warnings in the Website.  Admin forms for updates of Alerts & Warnings: These forms are used by the administrator for day-to-day uploading and updating the Alerts and Warnings. During a severe flood situation, the alerts and warnings may be updated more frequently based on real time data and/or the results of the flood forecasting model.

Figure 5-1 RTSF&ROS Website Once the RTSF&ROS system is in trail operation from June 2013, the usefulness of the Website may further be carried out by WRD and refinement, if any, may be 64 Final Report 64 Krishna & Bhima River Basins RTSF&ROS

done easily. Training has been given to BSD officers on the use and updating of the Website, so that they are fully familiar with all the day-to-day updating features.

5.1.2 Communication WEB Portal All results from the forecast simulations are presented on a WEB Portal. The WEB display of station status takes place via Google Maps, with all Google Map facilities like zooming to street level and provision to show data on satellite images, road maps and on terrain maps. From the Google Map it is possible to watch station status at preselected time steps and to select a graphical view of a selected time series clicking on the map. The WEB Page has provision for display of four different data types: discharge, water level, precipitation and data from reservoir (water levels, inflow and outflow)

The web portal will be a part of the overall information communication management system. Two different sizes of WEB portals have been developed:

WEB Page for PC: The PC version (large screen) includes provision for viewing all the four different data types described above. Figure 5-2 shows an example of results presented on Google Map. Each station is coloured according to the actual flood status, for example:

Light blue: Below normal level Dark blue: Above normal level Yellow: Warning level Red: Alert Level

The alert levels have been developed from analysing historical data and based on ground conditions.

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Figure 5-2 The Krishna-Bhima WEB Portal (PC version) for status and forecast Figure 5-3 shows the results presented in a WEB Bulletin for the forecasted discharges along the rivers and inflow forecasts to reservoirs.

66 Final Report 66 Krishna & Bhima River Basins RTSF&ROS

Figure 5-3 WEB Bulletin showing flow forecasts

WEB Page for Mobile Devices: A compressed WEB portal has been prepared for dissemination of results to mobile devices. The display can be used for iPhone/iPad/Android or other devices supporting pixel resolutions from 320x480 up to 640x640 pixels. The mobile WEB Page has provision for selecting three different data types (discharge, reservoirs and rainfall). The upper part of the WEB Page shows the station status presented on Google Maps (including the normal Google

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Maps features like zooming and selection of different maps). The lower part of the WEB page shows selected graph (when clicking on the map), where it is possible to zoom in and out and to see the data at selected time steps in a tabular view.

Figure 5-4 shows examples of forecast results in a Mobile WEB Page for the Krishna-Bhima system. The three displays refer to discharge, reservoirs and rainfall.

Figure 5-4 Example from the Mobile WEB Page: left- discharge time series, middle- reservoirs, right- rainfall

5.1.3 Flood Warning Reports/Messages Table 5.1 shows a category of warning messages for dissemination through a specific medium.

Table 5.1 Dissemination of flood warning

Message Message Message dissemination to Message generation category dissemination by

1 SMS alerts List of mobile phone numbers Automatically of selected WRD officials, generated for the day Maharashtra State Government and time of forecast officials, Divisional update from the Commissioner, District RTSF&ROS system Collectors, district disaster as soon as the forecast management nodal officers reaches the specified (RDC),and any other 68 Final Report 68 Krishna & Bhima River Basins RTSF&ROS

individuals as decided by warning level. WRD. (the list can be updated by the operator of the Specific warning RTSF&ROS for current and messages can also be future use). entered by the operator (Figure 5.18)

2 E-mail List of WRD and other Automatically Government officials, relevant generated for the day organisations, NGOs, central, and time of forecast state and local level disaster update from the management agencies, any RTSF&ROS system other interested as soon as the forecast individuals/organisations who reaches the specified request flood warning warning level. information via the feedback system implemented in the Specific warning RTSF&ROS website. messages can also be entered by the operator (Figure 5.18)

3 Fax List of high level state The daily flood Government offices warning report (Mantralaya, Mumbai, WRD prepared by the duty offices) or district / officer is printed and subdivisional offices where E- faxed. mail service is not readily available.

4 Courier Senior officials of WRD and Daily, weekly, Mantralaya Mumbai monthly, seasonal (annual) flood outlook reports to be produced by BSD and delivered .

5 Website Public All the information as described above will be available in the RTSF&ROS website with relevant links

Figure 5-5 shows the dissemination tool from the RTSF&ROS User Interface, in which a number of mobile phones and E-mail addresses can be entered, updated and saved. The warning and alert message can then be sent to the specified list by pressing the “send” button. The message provides the WEB link for detailed forecasts and waning information.

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Figure 5-5 Sample Warning Message for SMS alert and E-mail Figures 5-6 and 5-7 show sample flood warning report formats for dissemination.

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Figure 5-6 Flow/flood warning report format (Krishna)

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Figure 5-7 Flow/flood warning report format (Bhima)

72 Final Report 72 Krishna & Bhima River Basins RTSF & ROS

6 CAPACITY BUILDING 6.1 Introduction The goal of Capacity building is to ensure that by the end of the project WRD has a self sustaining team operating and maintaining the Real Time Streamflow Forecast and Reservoir Operation System (RTSF&ROS), with a strong internal structure, and links to external organisations with whom WRD can share experience, impart to and draw on external knowledge. As a process of needs analysis, a review of the existing organisations and institutional arrangement and training requirement was made in the Inception Report (December 2011). 6.2 Trainings Conducted Under the project regular and intensive training activity was taken up right from the beginning of the project covering various subjects. The trainings were conducted by International and National experts in their respective field of expertise.

Geographic Information System (GIS) along with use of remote sensing data has emerged as a powerful tool for handling spatial and non-spatial geo-referenced data for preparation and visualization of inputs and outputs, and for integrating with hydrological and hydrodynamic models. To understand the capabilities of remote sensing and GIS, trainings on Remote sensing & GIS and its application to water resources were organised.

As the basics of hydrological and hydraulic and modelling approach in these fields are immensely important to this project, the trainings on introduction to modelling, Open Channel Hydraulics, Hydrology, Rainfall-runoff modelling and River Basin modelling were conducted.

No model is useful without the good data sets and no data set is used efficiently without the relevant model. The input data sets for the modelling cover range of data including time series data of hydrological and climatic parameters, topographical data including the river cross sections, GIS data sets, the data related to all hydraulic structures, the users, their demands etc. The good part of training period was devoted to make these data sets ready for the modelling. This also included the training on Global Positioning System with field exercises.

Emphasis was also given on hands-on-training, including exercises on MIKE 11 and MIKEBASIN packages which form the backbone of the project. MIKE 11 is a user friendly, fully dynamic, dimensional modelling tool for the detailed analysis, design, management and operation of both simple and complex river systems. MIKE 11 is used in the project for short term forecasting. Hence continued sessions of MIKE 11 trainings were conducted. MIKEBASIN is a river basin modelling tool, which is used for the optimal water allocation for planning as well as long term forecasting. Exposure was given to officers on MIKEBASIN software. An introduction was also given to optimisation tools in the short term and long term forecasting.

The Knowledge Base System (KBS) is developed and installed to store the spatial and non-spatial data sets including historical and real time data as well as the Final Report 73 RTSF & ROS Krishna and Bhima River Basins

simulation results from models. The KBS provides many tools to analyse the time series and GIS data. The officers are given training on Knowledge Base System (KBS).

The ultimate aim of the project is to run the forecasting system in operational mode to generate the advance warnings and alerts. The user friendly forecasting system developed in RTSF&ROS is capable of running in an on-line mode and also in an off-line mode to generate different scenarios. The officers are trained to run the forecasting system, which they did on a trial basis during the monsoon period of 2012.

Appendix A provides a detailed list of trainings conducted during the project. In addition to these training activities, three presentations on Flood Forecasting as well as the on forecasting using RTSF&ROS for Krishna & Bhima basins were given to the Officers of HP and MERI at Nashik.

6.3 International Study Tours

As per the conditions of contract DHI had organized international study tours in Europe and USA for senior officers as a part of capacity building programme. The aim of the study tour was to give exposure to the officials and to observe the operational inflow forecasting & decision support in these countries. A group of 4 Senior Officials visited Europe during 3-10 June, 2012 and another group of 5 officials visited USA during 14-25 June, 2012. Summary reports of the two study tours as prepared by the WRD teams are given below.

6.3.1 Study tour to Europe The Water Resources Department nominated five officers for this study tour to Europe to visit Denmark, Austria & Germany, which included Shri. Ekanath B. Patil, Principal Secretary (WR) Water Resources Department, Mantralaya, Mumbai; Shri. H. T. Mendhegiri, Chief Engineer (WR) & Joint Secretary,Water Resources Department, Mantralaya, Mumbai; Shri. C. A. Birajdar, Chief Engineer (SP), Water Resources Department, Pune; Dr. P. K. Pawar, Executive Engineer, Hydro-meteorological Data Processing Division, Nashik and Shri. J. M. Shaikh, Executive Engineer, Irrigation Project Division, Nagpur. However, Shri. Ekanath B. Patil, Principal Secretary (WR), could not participate in the study as his presence was required in an urgent and important Government work in Mantralaya, Mumbai. Mr. Gregers Jorgensen, Web based Modeller & Forecasting Expert of DHI, Denmark coordinated the study tour in Europe. Ms Silvia Matz, Team Leader, Forecast System, DHI WASY, Germany provided support as a resource person for the tour. The visit to DHI Head office, Horsholm, Copenhagen, Denmark was organized on 4th June 2012. Dr. Jacob Host Madsen, Director, Dr. Kim Wium Olesen, Head of Water Resources Department and Mr. Gregers Jorgensen were available for conducting the study visit to DHI. Worldwide applications of state-of-the-art modelling systems for water resources & flood management including flood mapping, flood, forecasting, modelling & web based water resources information management were presented. A visit to hydraulic laboratory & test facilities 74 Final Report Krishna & Bhima River Basins RTSF & ROS

including a physical model for coastal area erosion of East of American coast was organised. The radar system to forecast rainfall for Copenhagen city installed at DHI was also shown to the visitors. The officials left for Vienna, Austria on 5th June, 2012 and a tour to visit Danube river complex was arranged. Officials observed the measures taken to avoid flooding the city by constructing a parallel river stream/channel to divert flood water due to snow melt, which is also used for navigation purpose. The participants visited International Forecasting Center, Graz, Austria on 6th June, 2012. Mr. Schatzl Robest from hydrological forecasting unit of Department of Steiermark Schee Loudesre Giesnug, welcomed the team & explained the forecasting system. An automated river forecasting system is working in three different basins in Styria, namely Mur, Raab & Enns rivers. The forecasting system is based on MIKE 11, similar to the system being implemented in Krishna & Bhima river basins in Maharashtra. Field visit to “Kainach Lieboch” station on a tributary of Mur was taken up to observe real time data collection.

Figure 6-1 WRD officials at the Hydrological Unit, Ljubljana Visit to the Flood Forecasting Department ARSO (Meteorological Office), Ljubljana in Slovenia was organised on 7th June, 2012 where the flood forecasting upgrade for the Slovenian rivers Sava & Soca was presented. ARSO (Meteorological Office of Slovenia) in cooperation with DHI, Denmark, has developed “FLOOD WATCH”, a user friendly decision support system for flood forecasting. Field visit to river gauge station on Sava river near Ljubljana city was arranged to study the setup of a new automatic telemetric network and measurement techniques. The officials visited Munich, Germany on 8th June, 2012. Miss. Silvia Matz, made presentation on flow forecasting system for hydro-power projects & river water quality in Germany. Forecast model E-Watch developed for forecast in DACH areas in Germany was explained. It was initially developed for flood forecast &

Final Report 75 RTSF & ROS Krishna and Bhima River Basins

now is being used for energy forecast. During the afternoon session, a visit to Danube river system was organised after which, the study tour programme was completed

6.3.2 Study tour to USA The study tour to USA (14 – 25 June 2012) was organized by DHI as a part of the capacity building activities of the Project with an objective to obtain an overview of latest technologies real time streamflow forecasting, acquire a sound understanding of state-of-the-art solutions to water resources management, and specifically to multi-purpose reservoir management. The officers namely Mr. D.D.Bhide, Director General, MERI, Nashik, Mr. H.K. Gosavi, Chief Engineer, Planning and Hydrology, Nashik, Mr. R.B.Ghote Chief Engineer & Chief Administrator (CADA), Aurangabad, Mr. R.N.Thakare, Superintending Engineer, Vigilance Unit, Nagpur and Mr. D.A.Bagade, Executive Engineer, Basin Simulation Division, Pune were nominated by Government of Maharashtra, Water Resources Department, Mantralaya. On request of DHI the tour was assisted and conducted by Mr. Carter Borden, Senior Hydrologist, University of Idaho, Boise, Idaho, USA, who acted as the resource person and tour director. After arriving San Fancisco on 14th June, the team moved to Sacramento, the capital city of California State for a halt and discussed the study tour program with tour organiser. On June 15, the team went to the Bay Delta Tour sponsored by California Department of Water Resources. For this Bay Delta tour, team was accompanied by Mr. Micheal Miller of California Department of Water Resources and Martina Koller, Staff Environmental Scientist, Delta Science Program. The Delta of the Sacramento and San Joaquin Rivers is California’s unique and valuable resource and an integral part of California’s water system. It receives runoff from over 40% of State’s land area and is the major collection point for water that serves more than 25 million people, two-thirds of State’s population. Agricultural, urban, industrial, environmental, and recreational interest have a vital stake in the Delta and have a complex inter relationships. The Delta provides habitat for many species of fish, birds, mammals, and plants.

Photographs of Bay Delta Tour California State

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Daily Decision of river releases, Trinity diversions, delta exports and San Luis Operations is based on process which accounts data evaluated (delta water quality, delta outflow, river flow, river temperatures, Energy, fishery status and storage targets) in coordination with Department of Water Resources, Corps of Engineers, National Weather Service, Fish and Wildlife, Department of Fish and Game, National Marine Fisheries, Western Area Power Administration and local agencies. Non controllable factors like forced outages, air temperatures, emergency operations, tides, winds, precipitation etc. Overview of California state water project: Office of the State Engineer established with appointment of William Hammond Hall in 1878. California state water project is the largest state-built and operated multipurpose water and power system in USA. The 701 miles of canals and pipelines provide drinking water for 25 million people and irrigation for 750000 acres of farmland. The SWP (State Water Project) also provides power generation; recreation, flood protection, and helps in maintain delta water quality. The SWP includes 770 ft high, Oroville dam and one of main source of hydropower. Number of storage facilities are 34. Total reservoir storage is 7.2 cubic kilometres. Prominent projects are California aqueduct with canal 33.5 m width, 10 m deep and capacity 13100 cfs, construction of delta pumping facilities, south bay facilities, Edmonton pumping plant having highest lift per volume in the world with single lift of 1926 feet and volume of 4480 cfs. On 16th June, the team saw San Francisco Bay-Delta Model at Bridge way Sausalito, CA. Mrs. Linda Holm, Park Ranger gave in brief discussed the critical issues of Bay-Delta. It is a three dimensional model of the San Francisco Bay and Sacramento/San Joaquin Delta. It was built in 1957 by the U.S. Army Corps of Engineers as a scientific tool to test the impact of proposed changes to the Bay and related waterways. It helps in interpreting the critical missions of the Corps in environment, navigation, and flood control throughout the watershed. The simulated tidal action and currents in the Bay Model change every few minutes and can create a 24-hour tidal cycle in 14.9 minutes. The team studied the model in detail. On June 18th, the team visited the Real Time Data Acquisition System of Oroville- Wyandotte Irrigation District Watershed Data Centre and Bubbler System at Sly Creek Reservoir. Mr. Mark Heggli, World Bank Consultant and an Instrumentation specialist guided the team. The system of twenty five telemetry hydro meteorological stations is installed in the valley. The different equipments like receiver, antenna, servers, workstations etc were installed at real time data centre. It was possible to observe the data of nearly 1000 stations of the continent. The details were discussed in detail and then team proceeded to visit Bubbler System at Sly Creek Reservoir. The Sly Creek reservoir mainly produces hydroelectricity. The bubbler system was installed on the left flank of the reservoir. Small gauge house building was built to accommodate bubbler system with data logger. The equipment were installed in 2010 and were working satisfactorily. System measures Reservoir water level at an interval of an hour and transmits this data to the data centre. Team members also had a fruitful interaction on INSAT, VSAT mode of transmission, instrumentation with the instrumentation specialist.

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Photographs of Visit to Bubbler System installation at Sly Creek Reservoir On June 19, the team visited the Napa County Flood Control and Water Conservation District. The Napa county flood control authority welcomed the delegation and had a presentation explaining history of Napa Flooding, funding problems for flood control works, peoples participation, flood/river training works. Rick Thomasser, Julie Blue Lucida, P.E. Flood Project Manager and Lindsey of California Water Resources Department participated in the discussion. The Napa river runs some 89 km from Mount St. Helena to San Pablo Bay and drains a watershed of 1100 Sq Km. The average annual flow of the Napa river is about 37 cumecs through the populated centre of the city of Napa. During a 100 year flood, the flow increases to an estimated 1200 cumecs to 1300 cumecs. Napa valley is inundated on regular basis for thousands of years. The river is prone to seasonal flooding from November through April month. Some 21 serious floods have been recorded from 1862 to till date. The most serious recent floods occurred in 2005, 1997, 1995 and 1986. The federal government first authorised the preliminary examination and survey in 1934. In 1944 recommended channel improvement and construction of dam on Conn Creek. In 1948 water conservation reservoir namely Lake Hennessy was created by building a dam on Conn Creek. This dam did not solve the problem. In 1995, Corps offered a plan; enlarging the river channel and constraining the river within that channel. In 1997, living river design was adopted. Work on the Napa creek portion started in Nov 2010. This portion of the project was undertaken to control potential flooding in an area along Napa Creek between Jefferson street and the Napa river in downtown Napa. Removal of existing vehicle bridges, installations of new channels and reshaping of the creeks bank are the main activities. Team had a walkthrough for observing the flood control works. Team visited Vineyards in the Napa valley and also visited University of Berkley. On June 21, after arriving New York, the team travelled to visit Robert Moses Niagara Hydroelectric Power Station in Lewiston, New York near Niagara fall. The place is about 650 miles away from New York. On June 22, they observed the Niagara Hydroelectric Power Station. The Hydroelectric Power Plant diverts water from Niagara river above Niagara falls and returns the water into the lower portion of the river near lake Ontario. It utilizes 13 generators at an installed capacity of 2525 megawatts (MW). In 1957 the United States congress approved the project and construction began. The New York Power Authority created a man-made 7.7 Sq. Km, 83 Million Cubic meter upper reservoir which stores water for day time use through a tunnel from a point upstream on the Niagara river. The opposite boundary of this fore bay is another dam. This dam is part of the 240 MW Lewiston Pump generating plant which houses 12 electrically powered pumps that can move 78 Final Report Krishna & Bhima River Basins RTSF & ROS

water to another higher storage reservoir behind this second dam. At night a substantial fraction 2300 cubic meter/second of the water in the Niagara river to the lower reservoir by two 210 m tunnels. The normal flow of water volume flowing over the Horseshoe falls is approximately 100000 cubic feet per second. Peak flow over Horseshoe falls recorded by Ontario Hydro has been 225000 cubic feet per second. By International agreement Canadians draw 56500 cubic feet per second & Americans draw 32500 cubic feet per second of water. Electricity generated in the Moses plant is used to power the pumps to push water into the reservoir behind the Lewiston dam. The water is pumped at night because demand for electricity is much lower than during the day. When electricity demand is high, water is released from the upper reservoir through generators in the Lewiston dam. The same water flows into the lower reservoir, where it falls again through the turbine of Moses plant. This arrangement is called pumped storage hydroelectricity.

6.3.3 International training (Proposed) It is proposed to organise a one-week training by international experts to about 16 technical officers of WRD to enhance concepts and skills on modelling, forecasting and operation of water resources systems. The training is planned to be held in Pune in November 2013 DHI has contacted the Asian Institute of Technology (AIT) in Bangkok Thailand for conducting the proposed training. The Geoinformatics Center (GIC) - http://www.geoinfo.ait.ac.th/ of AIT has expertise in conducting such training. GIC has also developed expertise in advanced GIS and satellite based technologies in assessing flood and drought risk in many countries and has conducted training courses for Government agencies of many countries in Asia. AIT (www.ait.asia) is an intergovernmental organisation, which is also supported by the Government of India and is an international academic institute of high reputation. Therefore, the consultant strongly recommends to WRD to avail the expertise and experience of AIT so that its technical officers get an opportunity to learn the state-of-the art technology related to RTSF & ROS. The following training modules: 1. Advance GIS and satellite data processing tools and techniques for flood and drought mapping and risk assessment 2. Advance hydrology and hydraulic modelling 3. Disaster management: concepts and practices 4. Flood management concepts, flood modelling, forecasting, warning and dissemination

6.4 Workshops As part of capacity building and engaging WRD and other stakeholders in the project development, a total of five workshops were conducted. The workshops were organized by WRD and were facilitated by experts of the consultants. Among the workshops listed below, the final workshop was conducted on 3rd October 2013 in which the Final Report was presented. Also presented was the plan to implement the 24-month technical support period (March 2013 – February 2015).

Final Report 79 RTSF & ROS Krishna and Bhima River Basins

Table 5.4 List of Workshops Sl. Workshop Date Activities No. 1 Inception 7 December Presentation of Inception Report, Workshop 2011 stakeholder consultation, further needs assessment, feedback on approach & methodology and on capacity building plan. 2 Interim 27 March Presentation of Interim Report, Workshop 2012 feedback on the modelling systems developed. Presentation of draft knowledge base system, initial demos of the models and forecasting and reservoir operation system. 3 Workshop 11 October Presentation of the modelling system, on flow 2012 comments & discussion on the system, and flood including the forecasting formats and flood forecasting mapping, suggestions to incorporate into the final version of the forecasting system.

Presentation of the Draft Reservoir Operation Guidance system and Draft communication management system, including web portal.

4 Workshop 7 May 2013 Presentation of the Final Reservoir reservoir Operation Guidance system including operation optimization system and and communication management system, Informatio including web portal. n communic Presentation of Draft Final Report, ation feedback/comments/suggestions, system and Draft Final evaluation of project achievement, Report finalisation of technical support for the next two years of system operation discussion on work plan for the support period.

5 Final 3 October Presentation of the complete project Workshop 2013 (including RTDAS) by WRD, presentation of the Final Report, Implementation Plan for Support Period and recommendations for sustainability of the RTSF&ROS.

80 Final Report Krishna & Bhima River Basins RTSF & ROS

6.5 Strategy for Sustainability of RTSF&ROS 6.5.1 Institutional Strengthening The Basin Simulation Division (BSD) at Pune was established in 2007 after recommendations of the Wadnere Committee for Real Time Streamflow and Flood Forecasting. BSD is headed by an Executive Engineer supported by administrative staff. At present there are four Assistant Engineers (Grade –I) and six Assistant Engineers (Grade-II). The six Assistant Engineers (Grade-II) are also assigned to sub-divisions in Shirur, Kohlapur, Sangli, Stara, Solapur and Pune.

The organisational aspects of the RTSF& ROS are of paramount importance for the sustainability of the established systems. It is important to foster an environment through training and participation in which WRD staff take ownership of the system. To sustain this it is critical to establish simple and well thought work processes ensuring optimal use of the capabilities of the modelling systems. The BSD is, therefore, considered as the key division of WRD in implementing the project and develop into a sustainable organisation in operating, maintaining and updating the modelling systems developed under the RTSF& ROS project. Therefore, based on the requirements for operationalizing the RTSF&ROS developed in the project in a sustainable way, an institutional development plan is focussed at BSD.

6.5.2 Proposed Setup and Functions of BSD The Basin Simulation Division will be responsible to maintain all the data and models developed in the present project. Regular updating of the models including timely validation as new data becomes available will also be the responsibility of BSD. The operational control room will be central operations room for BSD. Therefore, BSD will perform the following functions:  Operation and maintenance of the Real Time Data Acquisition System  Management of the central Database  Meteorological analysis and forecast  Hydrologic and hydraulic analyses of the basin  Update of the hydrologic and hydrodynamic models  Operation and maintenance of real time forecasting systems (inflow and flood)  Operation and maintenance of the reservoir operation guidance system  Communication and information dissemination These functions should be performed by the assistant engineering staff with one executive engineer as the manager of BSD. The engineering staff will take turns to manage the operational control room. Additional staff might be required to man the operational control room round the clock during critical situations. In addition to the existing assistant engineers, it is recommended to employ two more staff at BSD: 1) Meteorologist or a hydrologist with experience and training in interpreting meteorological information, 2) ICT Expert. The proposed hydrologist/meteorologist should have a postgraduate degree in hydrology/meteorology/climatology with Final Report 81 RTSF & ROS Krishna and Bhima River Basins

expertise in rainfall forecasting and satellite data applications in meteorology. The ICT expert should have a graduate degree in computer science/engineering with expertise in information communication, web design and updates. It is proposed to organise BSD into the following sub-divisions/sections. Also shown in Figure 6-3 is the proposed Organogram. No. Sub-div/Section Functions Responsible Officer Other staff 1 Operational Operation of the Assistant Engineer (Gr-I) Assistant Eng. Control Room forecast and (Gr-II), reservoir operation Meteorologist, guidance system. ICT Expert, Office Assistant 2 Meteorological Management of Hydrologist/Meteorologist forecast meteorological data, Analysis of meteorological conditions of the basins, Compilation of rainfall forecasts. 3 Database Acquisition of Assistant Engineer (Gr-I) 2 Assistant hydro-met, river, Engineers reservoir, GIS and (Gr-II) satellite data and database maintenance 4 Modelling Maintain and Assistant Engineer (Gr-I) 4 Assistant update of all Engineer (Gr- models including II) DSS and reservoir operation system 5 Information Communication of ICT expert Management forecasts, reservoir operation guidance system, dissemination of flood forecasts, web page management and updates.

82 Final Report Krishna & Bhima River Basins RTSF & ROS

Figure 6-2 Proposed Organogram of BSD

6.5.3 Operational Control Room The Operational Control Room is located at the 1st floor of Sinchan Bhawan, Pune together with the RTDAS Data Centre. The control room will be linked to the BSD at the 4th floor with LAN. Both the BSD and the Control Room will have dedicated broadband internet connectivity. The communication between BSD and the Control Room should preferably be via intranet in addition to the general purpose internet for links with all stakeholders. It is expected that all important reservoir operation offices and related decision making offices in Pune, Nashik, Mumbai and other districts have broadband Internet connectivity so that communications to and from the control room is efficient and transparent. It is expected that the Operational Control Room and hence the staff will be active beyond the monsoon season. Water resources monitoring will be required for droughts as well as for optimal management of the river basins.

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7 ACTIVITIES FOR SUPPORT PERIOD 7.1 Introduction As stipulated in the Contract, a two-year technical support will commence after completing the tasks assigned in the consultancy project. The Technical Support period is from 17 February 2013 to 16 March 2015. Activities in the two year Technical Support period will be directed towards ensuring the RTSF-ROS continues as a relevant and robust system for water resources and flood management in the Krishna-Bhima Basin. The main activities to be carried out in the technical support period are:  Software Updates: DHI will provide free updates of the modelling software, and the RTSF&ROS user interface according to new releases and new developments.

 Help Desk and Hotline Support: A hotline support will be permanently established as a help desk support at DHI Denmark, with remote access to the system in the Operational Control Room in Pune. The operational staff and other related officials of WRD will also be able to contact the DHI experts via E-mail, skype or telephone to resolve any software and operational problem related to the developed system. Thus a technical problem may be solved in an interactive way. During the technical support, as stipulated in the TOR, the consultant shall provide full and effective response to queries within 2 working days and on-site visit to address issues that cannot be resolved through remote assistance within 2 weeks of a request.

 Operational Support: DHI will provide required support to the concerned officials responsible for the operation of the RTSF&ROS. This support has been more intensive during the initial period before the BSD staff gain full confidence in operating the system. It should, however, be noted that the consultants will not operate the system. They will only be available when the BSD staff requires expert support to resolve certain issues. In addition to the above, an intensive support has been provided by the consultant during the monsoon period of 2013 to test RTSF&ROS and it was successfully live-tested and made operational on a trial basis during the monsoon of 2013.

 Support in Model Updating: The hydrological and hydrodynamic models used in the RTSF&ROS may require updating if new information becomes available. The Consultants will provide support to the modelling staff of BSD in updating the models. The updates may be in the form of adding new cross sections, new structures, testing with new date or events and recalibration.

 Training: As stipulated in the TOR, DHI will conduct four training courses for concerned staff. The details of the training courses are provided in the following sections. 7.2 Support to be Provided

Table 7.1 presents detailed activities during quarter (3 months) of the proposed support to be provided during the two-year technical support period.

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Table 7.1 Description of activities during the support period (March 2013 – Feb 2015) Period Support activities Outcome Qtr-1: Monitoring of installation of RTSF&ROS ready to be March-May 2013 RTDAS and quality assured data operationalized on a trial flow to the Data Centre. basis during the monsoon Support BSD staff in self learning of 2013 and practice in modelling. Quarterly Report -1. Establish hotline and help desk support at DHI Denmark. Software update with new release, compatibility checks. Qtr-2: Final test of link between RTDAS Real time data from June-Aug 2103 data and the RTSF&ROS database. RTDAS provided First Training Course successfully as input to the RTSF&ROS Updating of model for input of available real time data from BSD Staff capable of RTDAS operating the RTSF&ROS Trial Operation of RTSF&ROS RTSF&ROS operating on a trial basis with forecasts issued for internal evaluation by WRD Quarterly Report -2. Qtr-3: Operation of RTSF&ROS during Successful trial operation Sept-Nov. 2013 September 2013. of RTSF&ROS, forecasts Evaluation of performance of evaluated by WRD, forecasts by RTSF&ROS models fine-tuned with one-season’s real time Recalibration (fine tuning) of data. models if required, with the real time data of June-Sept 2013. Quarterly Report -3 Qtr-4: Model updates with new data, if Updated models Dec.2013–Feb. available Quarterly Report -4 2014 Second Training Course Qtr-5: Ensure complete linkage between RTSF ready for operation March-May 2014 RTDAS data and RTSF&ROS during the monsoon of database 2014 Software updates with new releases Quarterly Report -5 and compatibility checks. Qtr-6: Operation of RTS&ROS RTSF&ROS being June-Aug 2014 Issue of Forecasts (to be decided by operated regularly, forecasts issued WRD), regular updating of Website

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Third Training Course Quarterly Report -6 Qtr-3: Continue forecasting up to Sept – Regular forecast issued Sept-Nov. 2014 Oct if required Dissemination of flood Evaluation of forecast performance warning in consultation Obtain feedback from stakeholders with stakeholders and incorporate suggestions on Quarterly Report -7 dissemination of forecasts and warning Fourth training course

Qtr-4: Model updates, if new data Successful completion of Dec 2014 – Feb. available the Support period 2015 Prepare annual flood report Quarterly Report -8

Quarterly reports will be submitted, which will contain type of issues, number of requests and resolved, and any major issues that needs attention, any update required, and trainings offered with number of participants. Quarterly invoices in equal instalments will be submitted to account for the remaining 15% of the contract value.

7.3 Training Plan during the Support Period The following trainings will be provided to about 10 WRD officials.

Training Duration/ Subject Topics to be covered No. dates

1 1 week Operation of KBS Refresher course on June 2013 and RTSF&ROS modelling, knowledge base system and on the operation of the RTSF&ROS using real time data from RTDAS, interpretation of results, use of the communication Web Portal, updating of Website.

2 1 week Hydrological and Refresher on hydrological January 2014 Hydrodynamic and hydrodynamic modelling modelling, model calibration, model updating

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3 1 week Operation of the Full operation of the June 2014 RTSF&ROS, RTSF&ROS, updating trouble shooting system configuration, reservoir operation scenario management, optimization, error logging and trouble shooting, help desk coordination, generation of flow and flood forecast products and dissemination of warning messages.

4 1 week Reporting, Flood Advance topics on January 2015 forecast and dissemination of flood warning warnings based on dissemination stakeholders’ feedback, reservoir operation guidance, maintenance and updating of the RTSF&ROS.

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8 REFERENCES

/1/ Contract, RTDSS: HP II/MAHA (SW)/2/2011, INDIA: HYDROLOGY PROJECT PHASE –II, (Loan No: 4749-IN), Consultancy services for implementation of a Real Time Streamflow Forecasting and Reservoir Operation System for the Krishna and Bhima River basins in Maharashtra, 2011.

/2/ Technical Offer, Loan No: 4749-IN, RFP No. : HP II/MAHA (SW)/2, Consultancy services for implementation of a Real Time Streamflow Forecasting and Reservoir Operation System for the Krishna and Bhima River basins in Maharashtra, 2011.

/3/ Request for Proposal, RFP: HP II/MAHA (SW)/2/, INDIA: HYDROLOGY PROJECT PHASE –II, (Loan No: 4749-IN), Consultancy services for implementation of a Real Time Streamflow Forecasting and Reservoir Operation System for the Krishna and Bhima River basins in Maharashtra, 2011.

/4/ DHI (India) Water & Environment, Monthly Progress Report-1, RTSF& ROS, September 2011.

/5/ DHI (India) Water & Environment, Monthly Progress Report-2, RTSF& ROS, October 2011.

/6/ Government of Maharashtra, Water Resources Department, Report on precise determination of reservoir releases during emergency situation in the State by Technical Committee. May 2007.

/7/ Bidding documents for Procurement of Goods and Related Services for Supply, Installation, Testing, Commissioning and Maintenance of Real Time Data Acquisition System for the Krishna and Bhima River Basins in Maharashtra, ICB No: HP II / MAHA (SW) / 1, India: Hydrology Project Phase-II, (Loan: 4749-IN), Chief Engineer, Hydrology Project, Government of Maharashtra, 2011.

/8/ National Institute of Hydrology / DHI. Development of Decision Support System for Integrated Water Resources Development and Management, Inception Report, DSS (Planning) Project, Hydrology Project-II, 2009.

/9/ Water Resources Department, Government of Maharashtra. Documents of various Reservoirs.

/10/ National Institute of Hydrology (NIH), Development of Decision Support System for Integrated Water Resources Development and Management, Interim Report, DHI, June 2011.

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/11/ Bhakra Beas Management Board, Real Time Decision Support System for Operational Management of BBMB Reservoirs. DSS Software Development Specifications. DHI. October 2009.

/12/ Government of Maharashtra, Irrigation Department, Dam Safety manual Chapter 2, Identification of causes of failures in Dams and their appurtenant structure, 1995.

/13/ Government of Maharashtra, Irrigation Department, Dam Safety manual Chapter 7, Flood forecasting, reservoir operation and Gate Operation,1984.

/14/ Government of Maharashtra, Irrigation Department, Dam Safety manual Chapter 8, Preparedness for Dealing with emergency situations on dams, 1984. /15/ Government of Maharashtra, Irrigation Department, Dams in Maharashtra, 2000. /16/ Maharashtra Water and Irrigation Commission Report, 1999.

/17/ Raghunath, H.M. Hydrology: Principles, Analysis, Design. New Age Publishers, 2006.

/18/ World Meteorological Organisation (WMO), Guide to Meteorological Instruments & Methodology of Observations (6th edition) WMO-No. 8, 1996. /19/ DHI (India) Water & Environment, Interim Report RTSF& ROS, March 2012. /20/ DHI (India) Water & Environment, Knowledge Base System Documentation, June 2012. /21/ DHI (India) Water & Environment, Knowledge Base System User Guide, June 2012. /22/ DHI (India) Water & Environment, RTSF&ROS Version 1, User Guide Draft, June 2012. /23/ DHI (India) Water & Environment, Installation Guide for KBS and RTSF&ROS modelling Packages /24/ DHI (India) Water & Environment, RTSF&ROS Version 2, User Guide, September 2012. /25/ DHI (India) Water & Environment, RTSF&ROS Model Development Report, September 2012. /26/ DHI (India) Water & Environment, Reservoir Operation System & Communication Management System, October 2012. /27/ HALL, W.A. and DRACUP, J.A. 1970. Water resources systems engineering. New York, McGraw-Hill. /28/ HILLIER, F.S. and LIEBERMAN, G.J. 1990. Introduction to operations research, 5th edn. New York, McGraw-Hill. /29/ WURBS, R.A. 1996. Modelling and analysis of reservoir system operations. Upper Saddle River, N.J., Prentice Hall

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/30/ REVELLE, C. 1999. Optimizing reservoir resources. New York, John Wiley /31/ Loucks, D.P., et.al. (2005). Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications. UNESCO PUBLISHING. /32/ DHI Water & Environment (2011), MIKE by DHI, AUTOCAT User Guide, 2001. /33/ Ngo, L.L. Madsen, H. & Rosbjerg, D. (2007), Simulation and Optimization modelling approach for operation of the Hoa Binh reservoir, Vietnam, Journal of Hydrology, 336, 269-281. /34/ Pedersen, C.B., Madsen, H., Skotner, C. (2007), Real-time optimization of dam releases using multiple objectives. Application to the Orange-Fish- Sundays River Basin, South Africa, 13th SANCIAHS Symposium, Cape Town, South Africa. /35/ Duan, Q., Sorooshian, S. and Gupta, V. (1992), Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resources Research, 28(4), 1015-1031. /36/ Madsen, H. (2003), Parameter Estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives, Advances in Water Resources, 26, 205-216. /37/ Madsen, H. & Vinter, B. (2006), Parameter optimisation in complex hydrodynamic and hydrological modelling systems using distributed computing, Proceedings of the 7th International Conference on Hydroinformatics (Eds. P. Gourbesville, J. Cunge, V. Guinot and S.Y. Liong), 4-8 September 2006, Nice, France, Vol. 4, 2489-2496. /38/ Madsen, H., Skotner, C. (2005), Adaptive state updating in real-time river flow forecasting - A combined filtering and error forecasting procedure, Journal of Hydrology, 308(1-4), 302 – 312.

/39/ Website: www.imd.gov.in /40/ Website: www.punefloodcontrol.com /41/ Website: [email protected] /42/ Website: www.ncmrwf.gov.in /43/ Website: www.ecmwf.int/products/forecasts/ /44/ Website: www.nrsc.gov.in /45/ Website: www.mahawrd.org /46/ Website: www.idrn.gov.in /47/ Website: www.ndma.gov.in /48/ Website: www.mdmu.maharashtra.gov.in /49/ Website: www.trmm.gsfc.nasa.gov /50/ Website: www.cgwb.gov.in /51/ Website: www.mahahp.org /52/ Website: www.isro.gov.in /53/ Website: www.trmm.gsfc.nasa.gov

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DOCUMENTATION

Following documents have been prepared and submitted to WRD as deliverables of the Project:

 INCEPTION REPORT  INTERIM REPORT  KNOWLEDGE BASE SYSTEM  USERGUIDE TO THE KNOWLEDGE ABSE SYSTEM  INSTALLATION GUIDE FOR THE KNOWLEDGE BASE SYSTEM  USERGUIDE (VERSION 1 AND 2) TO THE RTSF&ROS MODELLING SYSTEM  MODEL DEVELOPMENT REPORT  RESERVOIR OPERATION AND COMMUNICATION MANAGEMENT SYSTEM  TRAINING MATERIALS  WORKSHOP PROCEEDINGS  USER GUIDES OF THE MODELLING SYSTEMS  DRAFT FINAL REPORT  FINAL REPORT  FINAL REPORT Appendix: Results of Real time testing during the monsoon of 2013

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APPENDIX A: LIST OF TRAININGS CONDUCTED

N0 Duration Topic / Venue Trainers Participants / date contents 1 4 days Introduction to BSD Consultant Executive Engineer, Remote sensing staff (Dr. and 8 officers of 27-30 Sep. & GIS and Pandit) BSD (9 persons) 2011 application to water resources 2 1 day Introduction to RTSF&ROS Consultant Executive Engineer, modelling Consultant’s staff (Guna and 8 officers of 20 Oct. Project office, Paudyal, BSD (9 persons) 2011 Pune Finn Hansen) 3 3 days Hydraulics: RTSF&ROS Consultant 8 officers of Open Channels, Consultant’s staff (Guna BSD 22-24 Control Project office, Paudyal, Dec. Structures, Mike Pune Dr Pandit) 2011 Basin 4 1 days Hydraulics: RTSF&ROS Consultant 8 officers of Open Channels, Consultant’s staff (Finn BSD 27 Jan Control Project office, Hansen) 2012 Structures Pune 5 1 days Hydrology: RTSF&ROS Consultant Executive Concepts of Consultant’s staff (Dr Engineer, and 3 Feb rainfall runoff, Project office, Saso) 8 officers of 2012 met forecasts, Pune BSD (9 rainfall runoff persons) modelling using NAM 6 3 days GIS & RS : Use RTSF&ROS Consultant Executive of Spatial Data Consultant’s staff (Guna Engineer, and 28, Feb, and sources Project office, Paudyal, 8 officers of 1 Mar, 3 MIKE 11 : HD Dr Pandit , BSD (9 Mar Model Prashant) persons) 2012 MIKE Basin

7 5 days MIKE 11 : HD BSD Consultant BSD (9 Modelling and staff (Finn persons); HP 16-21 Result Hansen) (5 persons) = April 2012 Interpretation 14 8 2 days Introduction to BSD Consultant BSD (9 GPS (Including Field staff (Dr persons); HP 18-19 May Field Exercise) Pandit, (9 persons) 2012 Guna =18 Paudyal) 9 4 days Knowledge BSD Consultant BSD (9 staff persons); HP 18-21 Base System and the (Gregers, (3 persons)

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N0 Duration Topic / Venue Trainers Participants / date contents June. 2012 RTSF&ROS Anders (Forecasting Klinting, System) Guna Paudyal, Dr Pandit ) 10 1 Day Reservoir BSD Consultant BSD (9 Optimisation staff persons); HP (Claus (3 persons) Pedersen, Guna Paudyal, Dr Pandit ) 11 3 Days GIS & Remote BSD Consultant BSD (8 Sensing, staff (Dr. persons); HP 3-5 Dec, Refresher on Pandit) (4 persons); 2012 GIS and remote WRD 1 person sensing concepts, Applications of RS & GIS in Water Resources 12 1 Day Knowledge BSD Consultant BSD (8 Base System staff persons); HP 6 Dec, (KBS) (Kavita (4 persons); 2012 GIS, Time Patil, WRD 1 person Series Data Rucha Dakave) 13 1 Day Operation of BSD Consultant BSD (8 RTSF&ROS, staff (Dr. persons); HP 7 Dec, RTSF&ROS for Pandit) (4 persons); 2012 forecasting & WRD 1 person reservoir operation 14 2 Days River Basin BSD Consultant BSD (8 Modelling staff (Dr. persons); HP 11-12 (MIKE BASIN) Pandit, (4 persons); Dec, Basics of MIKE Kavita WRD 1 person 2012 Basin, Patil) components, development, Krishna - Bhima model simulations 15 1 Day Crop Water BSD Consultant BSD (8 Requirement staff (Dr. persons); HP 13 Dec, using Pandit) (4 persons); 2012 CROPWAT WRD 1 person 16 1 Day Rainfall-runoff BSD Consultant BSD (8 modelling staff persons); HP 14 (NAM) (Kavita (4 persons); Dec2012 Details of NAM Patil, WRD 1 person model, data Rucha inputs, Dakave) parameters,

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N0 Duration Topic / Venue Trainers Participants / date contents viewing results, calibration 17 4 Days River BSD Consultant BSD (8 Hydrodynamic staff (Guna persons); HP modelling, Paudyal, (4 persons); Details of Prashant WRD 1 person MIKE11 model, Kadam, setting up Rucha network, Cross- Dakave)) section, boundary, time series data, model updating, flood mapping, viewing and analysing results

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APPENDIX B: RESULTS OF RTSF&ROS USING REAL TIME DATA ACQUISITION SYSTEM

Separate Volume

Final Report 95