A Geospatial analysis towards achieving water security - case study of

Thesis submitted in partial fulfillment of the requirements for the degree of

Master of Science by Research in Computer Science and Engineering

by

Rahul Kumar Rai 200902048 [email protected]

Lab for Spatial Informatics International Institute of Information Technology Hyderabad - 500 032, February 2017 Copyright c Rahul Kumar Rai, 2017 All Rights Reserved Scanned by CamScanner

Acknowledgments

I would like to express my special appreciation and thanks to my advisor Dr. K. S. Rajan you have been a tremendous mentor for me. I will always be indebted to him for teaching me the basics of research. Your passion for work always motivate me. I would like to thank you for encouraging my research. I would also like to thank my family members for their support. I would also like to thank Shikha, Anshul, Kuldeep, Mukul, Chetan and Sachin for motivating me and supporting me during the course of my thesis.

v Abstract

Water security, simplistically defined as the capability of a society to ensure that its demands for water are met, is an important aspect which governs not only the well being of individuals in the present, but also acts as a deciding factor for the future prospects and expansion plans of any urban sprawl. The city of Hyderabad is rapidly expanding, resulting in a drastic increase in the population of the metropolis. It is estimated that with this rate of urban growth, the current municipal water distribution system would not be able to fulfil the demands efficiently of the city. Water problem has became the key obstacle for the sustainable development of any city and same goes with Hyderabad. Though the city has a large amount of water bodies within its perimeter , most of them are not being utilized for water distribution. Instead, water is being pumped in the city from rivers far-off. However, the initial and operational cost of such long-distance water projects in terms of resources and energy consumption is several times higher than that of local distribution system. Thus, though this model is fulfilling the current demands of the city, it is not sustainable and cannot be scaled up while maintaining profitability. The solution to this problem needs to rely upon local water bodies in the city. Because of its undulating geography and rocky soil, Hyderabad has a large number of lakes within its vicinity. Several of these are natural, and an equally significant number of reservoirs are man-made. These reservoirs were built with the primary intent of harnessing surface run-off water for local use. However, with rapid urbanization, they succumbed to pollution and encroachment, because of which they are not being utilized currently for supplying water to the city. If these water bodies are included in the citys main water supply, it may prove to be an efficient solution for the cities water issues. The approach described above is more of a proposal, verification of which needs comparative anal- ysis of the citys overall water consumption and the volume of water that can be drawn from the lakes. This poses a major obstacle in verification of the approach described. Calculation of water volume for any irregular shaped water body is a complicated and laborious task. As the circle of study expands from a small locality to a city, state or a country, existing methods to calculate the water volume tend to become highly expensive and thus non scalable. Therefore, a need arises to devise a simpler, yet highly efficient method which can be generically applied to any geographical area for analysing water volume of lakes. The objective of this thesis is to devise a system that relies on local water bodies for supplying water to the city, and in the process propose efficient ways to calculate water volume of any irregularly-shaped water body. In this study, a novel system has been proposed which would utilize local water bodies

vi vii for water distribution in the city. It also presents an efficient approach using open source geospatial technologies (GDAL/OGR library) to determine the volume of water in irregularly shaped lakes with embankment. The approach uses spatial vector data for boundaries, vector data for embankments, and depth data to calculate the amount of water present in any given lake. Algorithms for water volume calculation were written as python modules, leveraging the capabilities offered by the programming language and open source GIS library - the OGR/GDAL library. Calcula- tions for water volume of lakes gave results with considerable accuracy. The error percentage in water volume was found to be mainly dependent on the size of the lake under consideration. It was noticed that for medium-sized lakes with capacity between 50 Mcft. and 70 Mcft, the error percentage was 6.5% and for larger lakes with capacity between 2800 Mcft. to 3500 Mcft, the error percentage was 7.51%. The error percentage was also found to be dependent on the granularity of the grid which was used to model the surface of lake. When applied to all the lakes in Hyderabad, the algorithms gave a gross 9 TMC of water which could be used for supplying to the city. Population data for the city was also gathered from official sources and using the per-capita water consumption of the city, total water demands of the city were estimated. When the water consumption was compared against the volume available for supply, it was found that 67% of the population can be supplied water from local water bodies. This number, though fairly decent, can be improved if the lakes are deepened. By manipulating the embankment depths of lakes used for calculation, this scenario was simulated and it was observed that with increased embankment depths, the water storage capacity of lakes increased to an extent that they could easily meet the demands of 80% of the citys population. This study targets only quantitative analysis of water for distribution to the city. Qualitative analysis of water has been out of the scope of the problem definition and the related research work. This observation leads to the conclusion of this thesis on a note that local water bodies can be reliable sources of water, providing an efficient means to solve the water issues being faced by the city, and ensuring that water security is not compromised. Contents

Chapter Page

1 Introduction ...... 1 1.1 Research Questions ...... 4 1.2 Research Objectives ...... 4 1.3 Role of GIS ...... 4

2 Related Work And Literature Review ...... 6 2.1 Water Availability: World Wide Comparison ...... 6 2.2 Cities and Water Security ...... 6 2.3 Method for Estimating volume of water bodies ...... 9 2.3.1 The direct method ...... 9 2.3.2 Indirect method ...... 10

3 Study Area ...... 12 3.1 Hyderabad City ...... 12 3.1.1 Geology and Hydrology ...... 14 3.1.2 Climate ...... 14 3.2 Divisions of HMWSSB ...... 15 3.3 Water Supply Model ...... 15

4 Spatial Analysis of water bodies in Hyderabad ...... 20 4.1 Water Volume Estimation ...... 20 4.2 Methodology ...... 21 4.2.1 Data Collection and manipulation ...... 21 4.2.1.1 GIS Data ...... 21 4.2.2 Modelling of the lake into simpler shapes ...... 22 4.2.3 Volume calculation of lakes ...... 25 4.2.4 Use of GDAL/OGR and QGIS ...... 25 4.3 Comparison of Results ...... 29 4.4 Analysis of volume-calculation ...... 29 4.5 Application of Water Volume Estimation Algorithm on Hyderabad ...... 30

5 Water security of Hyderabad ...... 36 5.1 Water Security - Definition ...... 36 5.2 Population Distribution of Hyderabad Division wise ...... 36 5.3 Division wise Water supply ...... 39

viii CONTENTS ix

5.4 Can including local Water bodies in existing Water supply system improve Water secu- rity?...... 40 5.4.1 Lake Replenishment ...... 47 5.5 Timeline Study of Hyderabad ...... 48 5.6 Proposed solution toward improved Water Security: Depth Enhancement of lakes . . . 51

6 Conclusions ...... 56

7 Future Work ...... 58

Bibliography ...... 60 List of Figures

Figure Page

2.1 Per capita water availability across the world (2014) ...... 7

3.1 Study Area: Hyderabad, India (2014) ...... 13 3.2 Distribution of water bodies in Hyderabad (number of water bodies in specific area) . . 16 3.3 O&M Divisions of Hyderabad (Year: 2014) ...... 17 3.4 1991 ...... 18

4.1 Toposheet sample information for Mir Alam Cheruvu ...... 22 4.2 Generation of embankment data from point, arc and polygon vector data. The embank- ment points are determined by finding points on the polygon which are nearest to the corresponding points on the arc. (Lake Name: Mir Alam Cheruvu) ...... 23 4.3 Grid Superimposition on lake polygon. First the lake embankment is extrapolated to form a representative straight-line embankment. The grid is then imposed on the lake surface by aligning one of it’s edges with the emabnkment...... 24 4.4 Overview of Volume Estimation ...... 26 4.5 Logic flow of algorithm ...... 28 4.6 Variation of error percentage with block size. Note that for large sized lakes, the varia- tion is negligible as compared to the variation seen in case of medium sized lakes. . . 30 4.7 Distribution of lakes in Hyderabad. (2014) ...... 32 4.8 Division wise water availability. This data assumes only local water bodies as sources. 34 4.9 Division wise water availability. This data includes water from local reservoirs, and ...... 35

5.1 Division wise population distribution (bar chart) 2011 ...... 38 5.2 Division wise population distribution (map) ...... 39 5.3 Percentage of population targeted by considering only local water bodies...... 41 5.4 Water distribution for 16th Division and 15th Division using only local water bodies . . 42 5.5 Water distribution for 9th Division and 12th Division using only local water bodies . . 43 5.6 Water distribution for 1st Division and 10th Division using only local water bodies . . 44 5.7 Percentage of population targeted by considering local water bodies, Himayat Sagar and Osman Sagar...... 45 5.8 Percentage of population targeted by considering Current supply (all rivers) and also including local water bodies...... 46 5.9 Month-wise distribution of rainfall in Hyderabad ...... 47 5.10 2001 ...... 49

x LIST OF FIGURES xi

5.11 Timeline study of divisions based on water availability ...... 50 5.12 Percent of population served (Division wise, Based on 2011 census data) by local water bodies after applying depth enhancement ...... 51 5.13 Percent of population served (Division wise) by local water bodies after applying depth enhancement and including supply from Himayat Sagar and Osman Sagar lakes (Based on 2011 census data) ...... 52 5.14 Comparison of divisions after Depth enhancement-1 ...... 54 5.15 Comparison of divisions after Depth enhancement-2 ...... 55 List of Tables

Table Page

3.1 Details of major water bodies in the city ...... 16

4.1 Distribution of lakes across Hyderabad, based on the size range. The table also shows the total volume of water in all lakes of a given size range...... 32 4.2 Total water volume available in each division for consumption in Hyderabad...... 33

5.1 Details of O&M divisions. The table shows wards constituting eah division, and the population of each division...... 37 5.2 Details of water connections, frequency of water supply, and total water supplied in each division...... 40

xii Abbreviations

O&M : Operational and Management Division • MGD : Million Gallon Per Day • TMC : Thousand Million Cubic feet • LPCD : Litres per Capita per Day • GDAL : Geospatial Data Abstraction Library • MLD : Million Liters Per Day •

xiii Chapter 1

Introduction

Water security is defined as “The capacity of a population to safeguard sustainable access to adequate quantities of acceptable quality water for sustaining livelihoods, human well-being, and socio-economic development, for ensuring protection against water-borne pollution and water-related disasters, and for preserving ecosystems in a climate of peace and political stability” [1]. It is an abstract entity which can be represented as the sum-total of water resources, water environment and water disasters pertaining to a particular region. Not only does it imply inhabitability and survival conditions, but also possesses the several natural, social, economic and cultural attributes. The World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF) have estimated that currently, up to 1.1 billion of the world’s population does not have access to safe potable water. In regions of such acute water scarcity, water security has been regarded as a major reason for the spread of diseases, food shortages, water disputes, the stagnation of animal husbandry and agriculture [2].

Water is the most abundant, naturally available substance on Earth. A vital resource for sustaining life, it occupies a humongous 71 percent of the Earth’s crust. However, only 2.53 percent of it is potable freshwater while the remainder is salt water. Also, out of the miniscule fraction of freshwater, two-thirds is frozen in glaciers and as permanent snow cover; only the remaining one third is available in the form of various freshwater sources. Asia, which is the world’s largest continent by area and houses more than half of the world’s population, has only one-third of the world’s water resources (UN World Water Development Report, 2000). Earlier, the benchmark for water consumption was 135-150 LPCD, but with the rise in standard of living, the numbers have spiked to nearly 200 LPCD. As a consequence, water is becoming more and more a scarce resource. The shrinkage of freshwater resources due to pollution makes things even worse [3]

In countries and regions of tension over water resources, water security has become a strategic issue. Not only does it relate to the survival and development of the residents, but also shows up as an important aspect which impacts national security and international relations. Sustainable development of urban population too requires strong measure to be taken on the front of water security. All these factors make it mandatory to conduct in-depth research of regional water security [4]

1 Because water scarcity has been a prevalent issue in many parts of the world since a long time, the affected countries and regional bodies have taken measures to combat the issue. Apart from improving the quality and quantity of water supply from traditional freshwater resources, some cities have also started using desalinated sea-water as a major resource. This strategy has proved to be a success in almost all the cases, barring a few exceptional cases. Israel, for example, implemented desalination systems and in a matter of a few year, transformed from a water-deficient nation to a nation with surplus water [5]. Such success stories often lure policy makers into adapting the same strategy, as it is, in their respective regions. However, there are a lot of geographical factors which make this strategy successful - the most important one being proximity to sea, hence making sea water available easily and in huge amounts. For areas which are farther from the sea, the cost of transporting sea-water to the inland desalination plants or transporting desalinated water from sea-based plants to interior cities acts as a major cost factor. This suppresses the advantages of desalination hugely, since logistics just don’t add up [6].

If one considers desalination as an option to solve the water scarcity in Hyderabad and surrounding regions, the same geographical factors would make it difficult for developing and operating a sustainable model. The city is at a distance of around 370 km from the nearest shore, which would mean huge trans- portation costs, not to forget the cost of building and operating the related transportation infrastructure like pipelines and pumps. Hence, desalination is not an efficient strategy to solve water scarcity issue in Hyderabad.

A look at the history of various civilizations across the world shows that they were conceived at the banks of large rivers. The importance of water in the inception, development and advancement of any civilization can be assessed from the fact that most big civilizations have flourished along the banks of perennial rivers which ensured ample availability of water throughout the year. But one need not go too much back in time to look for similar evidences. Analysing the map of any country, it can be easily sees that most big cities came up (or have been built) near important rivers. In places where rivers could not be relied upon for water supply, reservoirs were built to trap surface run-off water and ensure that the city gets ample amount of water to thrive. Hyderabad poses an example of the latter scenario. Situated in a comparatively dry area, the city has only one river - Musi - flowing through it, which too has become almost a seasonal one and cannot be relied upon for year-long water supply. However, the citys undulating geography and rocky terrain has made it possible to build artificially enforced and purely man-made reservoirs to trap rainwater. Along with several smaller lakes, two big reservoirs - Osman Sagar and Himayat Sagar - built on the river Musi, provide water to the city.

To take care of civil amenities in such a large city, several municipal bodies work in close coordina- tion with each other, of which two are prominent and require a mention at this point. The Greater Hyderabad Municipal Corporation(GHMC) is an urban planning agency that oversees general mu- nicipal management of Hyderabad. The Hyderabad Metropolitan Water Supply and Sewerage Board (HMWSSB) ensures proper water supply and sewage treatment. The HMWSSB has divided whole

2 of Hyderabad into 16 Operation and Management divisions (O&M) for managing water supply and sewerage treatment/disposal [7].

Providing water for households and industries is a challenging task when the city is a metropolis like Hyderabad. For this, the HMWSSB uses a water supply system which relies mainly on rivers outside the periphery of the city. Two big lakes in the city - Osman Sagar and Himayath Sagar - are also being used as sources of water but as more and more rivers are added to the system, dependency on these lakes has decreased. Though other than these two lakes, there are a lot of other water bodies within the city limits, they are not being harnessed for civil water supply due to ignorance by the board. Another reason for this is the fact that most of the above mentioned water bodies are facing civil neglect in the form of pollution and illegal encroachment. The 16 O&M divisions of Hyderabad have a total of 350 to 375 such water bodies, which includes small, medium and large ones. If a system relying on these water bodies for civil water supply is developed, it will be sustainable and cheap, hence also profitable. Not only will these local water bodies provide water for day-to-day consumption, they will also play a pivotal role in improving the ground-water level of the region. [8]

This study analyses data about population and lakes in the city, and based on this information esti- mates the feasibility and reliability of a model in which the population is entirely dependent on local water bodies for its water needs. An important feature of this study is that as it progresses, a framework of sorts is developed which can be generically applied to any city or region. As will be seen in the forthcoming sections, this study broadly needs data about lakes which needs to be fed into algorithms to calculate the water volume, which can be compared to the total water consumption of population in the target area. This leads to a generic template-based approach, wherein all that is needed is lake spatial data and population data for calculations and then derive the necessary inferences. Hence, approached followed in this study can be generically applied to other areas of water scarcity such as Bangalore in India. Bangalore, like Hyderabad, is situated in landlocked area, with no major river within close proximity. In the past few years, rapid unplanned urbanization and population explosion, coupled with massive migration from other states to the city have resulted in a drastic spike in water consumption of the city. This has led to an acute shortage of water and raised concerns about water security in the area. The recent tussle over sharing of Kaveri river water between Karnataka and Tamil-Nadu government poses an example of the socio-political tension that may arise when water security is compromised. In this case also, similar analysis considering local water bodies for urban supply can be conducted easily and the feasibility of this solution can be determined.

This study targets only quantitative analysis of water for distribution to the city. Qualitative analysis of water has been out of the scope of the problem definition and the related research work. It has been assumed that water which is output from the proposed system will be filtered using standard treatment procedures such as water treatment plants, before being supplied to the city. Thus, the research targets only to analyse the amount of water that can be supplied to the city, and assumes that the quality will be maintained by standard procedures already in place.

3 1.1 Research Questions

As we move forward, the following questions will be answered:

Is there enough availability of water resources in and around Hyderabad ? • What regions of city can be self supported by local water bodies to offset large long distance water • supply ?

Are existing water bodies sufficient to fulfil water demand ? • Can existing water bodies further supplemented to improve water security of the city ? •

1.2 Research Objectives

Objectives of this thesis based on case study of Hyderabad are as follows:

Propose a model for distribution of water from local water bodies around the year, and rank the • divisions with respect to self sustainability according to the above model

Calculate and analyse population distribution in all operational and management divisions of Hy- • derabad using Census data.

Propose a volume calculation method for irregular shaped water bodies with embankment using • spatial vector data. Also calculate the total volume of water available in all the local water bodies of Hyderabad.

1.3 Role of GIS

Hyderabad has been dependent upon nearby rivers for its water supply since several decades. With the increase in the citys periphery and population, water demands also shot up persistently. However, to match up to this steep increase in water demand, only curative measures were taken as and when needed. These measures mainly included increasing the amount of water withdrawn from the rivers and reservoirs. Whenever the demands of the city would shoot up, administration would start pumping out more water from the existing long distance sources by adding additional pipelines. If it was felt that water from the rivers currently used for supply is falling short, another river would be included in the system. The inclusion of for the citys water supply is an example of this strategy. Thus, the issue of high load in this case was solved by horizontally scaling the system. This measure, though effective for a few years, would put enormous pressure on the rivers. When the city was being built, it was decided that the large number of lakes and reservoirs present in the city would be able to provide water to the city. But with the passage of time, the contribution of these

4 lakes towards the citys water supply gradually decreased until they virtually ceased to be a part of the system and were replaced by river-based water supply projects. Any increase in the demand of water was met by pumping out more water from these rivers. No proactive measure has yet been taken to solve this issue without putting additional burden on the rivers. Those lakes and reservoirs which were essential to the citys water supply have not been analysed for the feasibility of including them back into the citys water supply. One reason for the absence of any detailed study on the lakes of Hyderabad and their capacity is the sheer size and complexity of the study. The total number of water bodies in Hyderabad are around 350 to 375, and to calculate the volume of water in these, some standard and accurate yet efficient method is needed. Manually calculating volume of water of any irregularly shaped water-body is a complicated job, and needs a lot of equipments. Since it is costly in terms of manpower, logistics and time as a resource, the manual method is inefficient when implemented on a large scale. GIS encompasses a wide range of techniques and methodologies which use high-end information technology and automation systems to provide information of high quality and value with lesser dataset than manual techniques [9]. GIS solutions have the advantage of being highly scalable and universally applicable. A solution devised for one geographic area can be easily applied to any other area and quality results can be expected. To solve the above issue, we have used GIS techniques to calculate the capacity of water bodies using spatial data. Through requests to The Survey of India, we procured the required data. Most of this data was already in the required Shapefile format; however, for some of the lakes we were provided toposheets which were manually converted into Shapefile format. The shapefile format is a popular geospatial vector data format for geographic information system (GIS) software and libraries. We used OGR library which is a part of Geospatial Data Abstraction Library (GDAL) source tree. GDAL is a translator library for raster and vector geospatial data formats that is released under an X/MIT style Open Source license by the Open Source Geospatial Foundation (OSGeo) [10] . We used GIS for mainly spatial analysis and visualisation of data.

5 Chapter 2

Related Work And Literature Review

2.1 Water Availability: World Wide Comparison

More than one in every six people in the world are water stressed, meaning that they do not have access to potable water. Those that are water stressed make up 1.1 billion people in the world and are living in developing countries. According to the Falkenmark Water Stress Indicator [11], a country or region is said to experience ”water stress” when annual water supplies drop below 1,700 cubic metres per person per year. At levels between 1,700 and 1,000 cubic meters per person per year, periodic or limited water shortages can be expected. When a country is below 1,000 cubic meters per person per year, the country then faces water scarcity. In 2006, about 700 million people in 43 countries were living below the 1,700 cubic metres per person threshold. Water stress is ever intensifying in regions such as India, China, and Sub-Saharan Africa, which contains the largest number of water stressed countries of any region with almost one fourth of the population living in a water stressed country. The world’s most water stressed region is the Middle East with averages of 1,200 cubic metres of water per person. In China, more than 538 million people are living in a water-stressed region. Much of the water stressed population currently live in river basins where the usage of water resources greatly exceed the renewal of the water source. In India, the availability of surface water in the years 1991 and 2001 were 2309 cubic meter and 1902 cubic meter. However, it has been projected that per capita surface water availability is likely to be reduced to 1401 cubic meters and 1191 cubic meters by the years 2025 and 2050, respectively. The Per capita water availability in the year 2010 was 1588 cubic meters against 5200 cubic meters of the year 1951 in the country [12]. Figure 2.1 explains worldwide water availability on per person per day basis.

2.2 Cities and Water Security

The issue of water scarcity as a result of rapid urbanization has been prevalent across a large number of cities. Most of these cities are situated in developing nations. With the increase in population, the water-stress levels in cities has been rising to alarming levels. Data collected from across the world have

6 Figure 2.1 Per capita water availability across the world (2014)

given deep insights on the severity of the issue. In some places, the Litre Per Capita per Day (LPCD) has halved, which essentially means that only half of the water needed is being supplied. Reducing water levels in natural sources not only affect the day-to-day economy of the region, but also have an impact on the socio-political scenario. For example, dispute over the Rhine and Danube river waters in Europe have led to international conflicts in the area. The dispute between Karnataka and Tamil Nadu over Cauvery waters is also a raging political topic which has even led to riots in the states [13]. To solve these issues, various strategies have been adopted by administrative bodies. Some have resorted to limiting the amount of water to be supplied, while the other, more successful ones have deployed new means to generate fresh water for supply such as desalination and recycling.

Water used in industrial and domestic sectors follows a linear usage chain. Fresh water is taken as resource input for consumption, used as needed, and is then disposed off as used water in the form of sewage or industrial discharge. Though this linear chain meets the requirements of industries and households, it eventually transforms water from fresh to waste. This process can be improved drastically if instead of a linear flow, a circular flow of water is introduced. Water which exits the system in the form of industrial or household waste can be treated, purified and fed back to the system in the form of fresh water. This process is popularly termed as recycling of water - a widely used practice which is very often propagated by environmentalists to limit the amount of water that goes waste in day-to-day processes. Though recycling may not fully eliminate water wastage, it does limit it to a very small fraction, thus

7 optimising the usage of water and ensuring fresh water availability. Apart from implementing reuse and recycle strategies, some cities have also started using desalinated sea-water as a major resource.

Each city has its own characteristic geography, hydrology, geology and water-usage patterns. Hence the solution to water issues is different for different cities. Several cities have implemented measures in-line with their conditions and achieved appreciable results. One such example is that of Singapore.

Singapore is a global city and a sovereign state located in Southeast Asia. Spread across a main island and several small islets covering close to 700 square kms of area, it is a global hub for commerce, finance and transportation. The city-state had been dependent on mainland Malaysia to the north for several of its commercial and natural resources needs, especially water. The states water bodies were too polluted to be acting as major water resources, and hence for a large period of time, Singapore used to get water from Malaysia as a part of two treaties signed during the British colonial rule. However, periods of drought in Malaysia combined with other political factors made it imperative that an in-house solution be devised to remove the dependency on Malaysia and to make Singapore self-sustained in terms of water supply. After consistent and diligent efforts, the city-state was finally successful in fulfilling the demands of water by the nation, and even supply surplus water to Malaysia. Implementation of water conservation and management techniques helped Singapore make a miraculous transition from a water- deficient state to the water-hub of Southeast Asia [14].

To manage the logistics of water supply and demand, Singapore devised a four-point programme focussed at improving the existing supply infrastructure, and creating new sources of water [15]. The first and the most crucial point was rainwater and watershed management. Singapore already had several water bodies which were highly polluted and didnt have enough water perennially to act as permanent water resources. The officials realised the potential of local water bodies and devised systems to harness rainwater effectively to fill these water bodies. Rivers and reservoirs were cleaned up, dug deeper, and catchment area of these water bodies was improved to ensure that maximum possible amount of rainwater reaches them and can be stored for future use. Infrastructure such as drains and pipelines was created in urban areas to segregate sewage from running rainwater, so as to prevent rainwater running- off unmanaged into drains and sea. All these measures ensured that the local water bodies are used to their full potential as reservoirs, and rainwater is accumulated to the maximum extent possible. As a result of these efforts, it is estimated that Singapore now conserves two-thirds of the rainwater falling within its territory, which is a remarkable feat in itself. This step proved to be a major contributing factor in making Singapore self-sufficient in terms of water supply.Apart from this, other techniques such as recycling of drainage and desalination of sea-water were also deployed. These however are very-specific to the area and (as will be explained in upcoming sections) not profitable in all scenarios. Still in the case of Singapore this approach had profound impact.

The case of Singapore is an excellent example of how local water bodies can be utilised for water supply, while keeping the cost low and logistics light.

8 2.3 Method for Estimating volume of water bodies

Inclusion of local water bodies into mainstream water supply requires analysis of their capacities as a prerequisite. Knowledge of water volumes in the lakes to be considered as water sources gives a better understanding of the feasibility of the solution, and the extent to which these water bodies can be depended upon for water supply. Calculation of water volume in lakes is an important step in the process. Its significance rises from the fact that it provides the data needed for feasibility analysis. However, this is not a straightforward task. Its complexity arises from the fact that reservoirs, like any other geographical feature, are irregularly shaped and cannot be easily modelled as any regular shaped container or a collection of such containers. Researchers around the world have spent a lot of time struggling with this issue and come up with two major techniques that can be applied to get the volume of any irregular shaped reservoir. They can be tagged as direct and indirect methods. The direct method uses contour information of the lake to determine the volume. If the contour information of any lake is available, the problem of water calculation can be approached by slicing the lake into slabs demarcated by contour lines. The area enclosed by each contour can be calculated easily, and this multiplied by the height between the current and next successive contour gives the volume of that particular slab. The total volume of the lake can then be arrived upon as an integral sum of the volumes of all such slabs. This method is very useful since it simplifies the process of water volume estimation by modelling the lake into simpler slabs. However, this method has a drawback - it relies heavily on availability of contour data of the lake. Though it might seem a trivial task to get the contour information of lake, it definitely cannot be taken for granted. Many small reservoirs are designed without carrying out a full topographical survey of the area, which leads to unavailability of the lakes contour data. In such cases, the storage volume is estimated from the reservoir width, the throwback, and maximum impounded water depth [16].

2.3.1 The direct method

The direct method can be deployed by representing the slabs as two kinds of shapes. Each approach results in a different formula, as described below.

The Mid Area Method assume the slabs to be simple cross-sections, thereby using the formula •

n A + A C = i i+1 dh (2.1) 2 Xi=1 ✓ ◆ Where C is Reservoir capacity, Ai is the Surface area at contour interval i, Ai+1 is the Surface area at the next contour level above contour level, i. This method is more suitable where the contour interval, dh, is small (equation 2.1).

The prismoidal method assumes the slabs to be prisms, thereby calculating the volume of lake as • Prismoidal method formula (equation 2.2)

9 n Ai + pAiAi+1 + Ai+1 C = dh (2.2) 3 i=1 ⇥ ⇤ X ⇢ Where C, A and dh are as previously defined.

Apart from these two, there are other formulae used which are based on simpler dimensions • obtained from quick survey.

C = K K D W T (2.3) 1 ⇤ 2 ⇤ ⇤ ⇤

Where K1 is a constant, K2 is another constant related to the shape of the valley cross section, D is the maximum water depth, W is the width of water surface at the dam at the spillway crest level, and T is the throwback at the spillway crest level [16]. Throwback is defined as the distance from the dam wall along the reservoir axis usually to the point where river enters (equation 2.3).

(D W T ) C = ⇤ ⇤ (2.4) 6 Where D, W and T represent the same quantities (equation 2.4). This is a special case of the 1 previous formula where the constants multiply to 6 [17] . This formula models the lake as a pyramid with the dam wall as pyramid base.

(A D) C = ⇤ (2.5) 3 Where A is the surface area of the lake at full capacity (equation 2.5). This formula also models the lake as a pyramid, though with the lake surface area as the pyramid base. The three methods described above have varying degrees of accuracy. With a some fine tuning of constants (Nelson and Fowler relationships), the first method gives 10-15 percent under-predicted volume at its best. The other two give better results than the first one, with the third one being the most accurate (equation 2.5). However, since the approaches discusses above are based on quick surveys, they cannot be relied upon much. For reliable results, it is recommended to use the first two equations.

2.3.2 Indirect method

The need of alternative, indirect methods for water volume estimation of lakes stemmed from the complexity of the equations involved in direct methods. In many cases, it may not be possible to obtain the dimensions required for the formulae. Indirect methods mainly use just the surface area of the lake to estimate its volume. A power-relationship between surface area and volume is formulated which estimated the water volume of the lake. Several studies have been conducted on this model in African

10 countries like Zimbabwe, Botswana and Ghana. While the one in Botswana used topographical maps to find the surface area of lakes, the one in Ghana used GIS for this purpose. The all the studies gave similar power-relationships between the area of lake and water volume, which can be generically described as in equation 2.6.

V = K1 (AK2) (2.6) ⇤ Where V is the volume of lake, A is the surface area, and K1 and K2 are constants which were arrived upon on a case-by case basis, depending on the climatic conditions, geography of the region, and the method used to find the surface area of the lake (surveys/topo map/GIS). A power relationship between capacity of the reservoir and its surface area measured from topo- graphical maps was obtained from Meigh [18] as:

V =7.381 (A1.251) (2.7) ⇤ Where capacity is in thousand m3 and area in hectares (ha) The direct methods are quite laborious and time consuming hence the use of indirect methods.

11 Chapter 3

Study Area

3.1 Hyderabad City

Hyderabad is located in the northern part of Deccan plateau. It has an undulating geography marred by residual hills and rocks. The land is mostly hard and rocky. River Musi flows in the southern part of the city, and criss-crosses the otherwise hard plateau with a thin stripe of plain land made up of soft alluvial soil. The river enters the city from the west, where its flow is trapped in the form of Osman Sagar and Himayat Sagar- two large man-made reservoirs which act as major water sources for the city. The city can be roughly divided into two major regions - Hyderabad and . The Hyderabad Urban agglomeration (HUA) is composed of the Municipal Corporation of Hyderabad, Secunderabad Cantonment, and 10 surrounding municipal areas. is a major water body which has played a pivotal role in the history of the city. Geographically it separates Hyderabad from Secunderabad. Till late 90s, the extent of the city was limited to Banjara hills towards the west, Hussain Sagar towards the North, and AfzalGunj towards the South. However, with the advent of IT companies, the city expanded and the surrounding villages of Madhapur, Kondapur, Gachibowli and Shamshabad also came under the umbrella of Municipal Corporation of Hyderabad. These areas witnessed a flashy transformation from being demure villages to bubbling economic centres and plush, densely populated residential areas [19]. However, this put an enormous amount of pressure on the natural resources, particularly water. There are several big cities in India which are rapidly advancing in terms of urban sprawl and popu- lation. Most of these cities are located near major rivers or water reservoirs, which ensure ample water supply to these cities in spite of their rapid urbanization and industrialization. Hyderabad, on the other hand, is located in a dry area with no major rivers in close vicinity of the city. Though the city is rapidly expanding, absence of a dependable water resource leads to water scarcity in the city. This poses a critical challenge which needs smart and efficient strategies for resolution. Hence this study targets Hy- derabad, its water consumption pattern, and the possible solutions which can be implemented to solve the citys water crisis.

12 Figure 3.1 Study Area: Hyderabad, India (2014)

13 3.1.1 Geology and Hydrology

Hyderabad is located in the northern part of Deccan plateau, which is a comparatively dry area and doesnt have as many water bodies and rivers as compared to the plains in the north. The nearest river is Musi, which is a seasonal one and doesnt feature in the list of important rivers of India due to its relatively smaller basin. Hence since centuries, the city has been dependent on lakes and reservoirs to meet its needs for water. This was the primary reason for construction of two great reservoirs - Osman Sagar and Himayat Sagar - near the city to act as primary water sources for the city. These two lakes, along with several other smaller lakes have contributed to keep the surface and groundwater profile of the city sufficient for sustenance. However as the city is growing, and with urbanization happening, there has been an onset of water crisis in the city. This city is mainly dependent on lakes and reservoirs. Some water bodies are independent while others are interconnected. Ponds connected in series can be considered to be interconnected if they interact hydraulically. However, from a hydraulic modelling standpoint, ponds may be connected in series without being considered interconnected. If the downstream pond affects the hydraulic behavior of the outlet structure for the upstream pond, then the ponds are considered interconnected otherwise, they are independent [20]. Hyderabad once had 500-odd lakes that supplied drinking water to the twin cities of Hyderabad and Secunderabad. This number has now come down in the range of 350 to 375 (Figure-3.2) because most of the lakes have either become sewage dumps or have been encroached upon, urbanization also played a major role in intensifying the situation [21] [22]. This is alarming because if a lake gets polluted, it also pollutes the lakes interconnected to it. Hence a lot of other lakes which have till now been cleaner, are on high risk of getting polluted as a result of interconnection with other polluted lakes. Same goes for the lakes which suffer loss in catchment and total reservoir area due to encroachment. If such a lake is interconnected to another lake and supplies water to it through the interconnection, the existence of the other lake is also threatened since its primary source is depleted. The reverse situation also is highly undesirable. When a lake downstream perishes, the water in lake present upstream cannot drain anywhere else. This leads to lake overflow and flooding of surrounding areas, and the channels created in-situ to divert the overflowing water affect the vegetation and landscape. Hence the decline in number of lakes essentially becomes a chain reaction wherein all the interconnected lakes perish over time.

3.1.2 Climate

Being located on a plateau with land-locked features and absence of any major water body makes Hy- derabad witness a tropical wet and dry climate, usually bordering into a hot semi-arid climate. Summers are hot and humid, with April to June being the hottest period where temperature crosses 40 degrees celsius. The city receives rainfall from the SouthWest monsoon during July-September. Rainfall also occasionally occurs during the months of December-January. The balance between rainfall and temper- atures has been an intricate one, maintaining the water profile of the city to a borderline arid region. In the past few years however, this balance has been skewing towards more hot and arid type of climate,

14 with summers getting hotter year by year, and rainfall decreasing. This makes it difficult for the lakes in the city to get replenish themselves, and maintain groundwater levels.

3.2 Divisions of HMWSSB

Hyderabad is the fourth most populous city of India with area of 680 square km and expanding. To take care of civil amenities in such a large city, several municipal bodies work in close coordination with each other, of which two are prominent and require a mention at this point. The Greater Hy- derabad Municipal Corporation(GHMC) is an urban planning agency that oversees general municipal management of Hyderabad. Water Supply and Sewerage (HMWSSB), which was es- tablished in 1989, is an autonomous body that looks after water supply and sewage disposal systems of the metropolitan area of Hyderabad. The HMWSSB has divided whole of Hyderabad into 16 Operation and Management divisions (O&M) for managing water supply and sewerage treatment/disposal. Two O&M divisions from 16 are for bulk water supply for non-residential purpose. Hence this study shows detail only about 14 O&M divisions. Figure-3.3 shows geographical information about all the relevant O&M divisions. Since water distribution in Hyderabad is organized division-wise, spatial analysis of water bodies had to be done per division so that the feasibility of using local water bodies for water supply can be assessed for each division. For this purpose, division demarcation plan was procured as images from HMWSSB, which were georeferenced to produce the corresponding spatial vector data in form of ESRI Shapefiles.

3.3 Water Supply Model

Currently Hyderabad has a hybrid model of water distribution, where it is dependent on two big reservoirs - Osman Sagar and Himayat Sagar, along with rivers Krishna and Godavari for water supply. Geographical analysis of the region shows that the rivers are at considerable distance from the city (table-3.2), more than what would be considered optimal for transporting water. Early designers and developers knew this shortcoming of the city, and had accordingly built a system of reservoirs within the city to facilitate collection of rainwater and ensure that the water demands of the city are met. Apart from the small to medium sized lakes within the city, two large reservoirs (Osman Sagar and Himayat Sagar) were also built on the river Musi. This system reliably supplied water to the city for a long time, till the end of 20th century. At this point of time, the lakes had shrinked, become polluted and become less reliable for water supply. This, combined with the outburst in population made it necessary to seek other sources of water. Hence rivers such as Godavari and Krishna were included in the citys water supply. Table 3.1 shows detailed information about the above mentioned water bodies -including their proximity to the city, their potential capacity and their usage metrics.

15 Figure 3.2 Distribution of water bodies in Hyderabad (number of water bodies in specific area)

Water Body Source River Distance from city Capacity In- Capacity Normal (km) stalled(MGD) Storage Drawls (Mgd) (TMC) Osman Sagar Musi 15 (Gravity) 25 3.9 4 Himayat Esi 9.6(Gravity) 15 2.967 9 Sagar Manjira Manjira 58(Pumping/ Grav- 45 1.5 30 ity) Singur Manjira 80(Pumping/ Grav- 75 29.917 31 ity) Krishna Krishna 116(Pumping/ Grav- 180 180 Phase-I & II ity) Krishna Krishna 116(Pumping/ Grav- 90 1.5 45 Phase-III ity) Godavari Godavari 260(Pumping/ Grav- 86 20.175 86 ity) Total 516 385

Table 3.1 Details of major water bodies in the city

16 Figure 3.3 O&M Divisions of Hyderabad (Year: 2014)

17 Figure-3.4 is showing the dependency of various O&M divisions of the city on local water bodies, in the year 1991. The numbers represent the percentage of population that could be served using water from local water bodies including osman sagar and himayat sagar lakes.

Figure 3.4 1991

As can be seen in the map, almost all the percentages are more than 100, which means that even though the city was dependent only on local water bodies for water supply, there was sufficient water for day-to-day usage, and surplus water on top of that. However, due to population outburst, combined with illegal encroachment and ignorance by local administration, the dependency on these lakes decreased and as a countermeasure, rivers were included in the citys water supply. Though this step solved the issue of water scarcity for the time being, it cannot be applied as a sustainable solution to the citys water problems for various reasons. First, the rivers under consideration are seasonal ones, whose flow is highly dependent on the rainfall received during any given year. In the case of scant rainfall, drought-like conditions appear which paralyses the water supply to the city. Second, since the river has its own basin and dependent population, sharing of water leads to contention and disputes. These factors make the current model unsustainable and calls for implementation of new, sustainable models of water supply. To keep pace with population and economic growth, the city of Hyderabad, India,

18 will need to identify and develop new supply sources almost continually. Increasing population growth rate, declining surface water resources, overexploitation of groundwater, deterioration of ground water quality and poor sewage treatment are the major water-related issues in Hyderabad [23].

19 Chapter 4

Spatial Analysis of water bodies in Hyderabad

4.1 Water Volume Estimation

Prior knowledge of water volume is a prerequisite for calculating retention time of a lake. Lake reten- tion time helps in calculating the number of people and the number of days water can be supplied using the given lake; and this data can be very helpful in predicting the future estimate of water availability in any specific region [24]. One of the most accurate methods for water-volume calculation is to use a planimeter to trace the shoreline contour of a lake. This hand-held instrument is designed for measuring the area of a shape as drawn on a two-dimensional plane [25]. Digital tablets or computer scanners can also be used to trace or scan a bathymetric map image; this method is however not popular. The shape of lake between two consecutive contours is modelled as the frustum of a cone. Its volume is then estimated by applying the appropriate formula, and the total volume of lake is determined as the sum of the volumes of individual slices [26] [27]. A major shortcoming of the above method is that it requires complete bathymetric survey to generate contour maps from which the area of depth contours is calculated. This involves considerable manual effort, which is redundant. Calculation of water volume for any irregular shaped water body is a complicated and laborious task. As the circle of study expands from a small locality to a city, state or a country, existing methods to calculate the water volume tend to become highly expensive and thus non scalable. Therefore, a need arises to devise a simpler, yet highly efficient method which can be generically applied to any geographical area for analysing water volume of lakes. GDAL is an open-source library which encompasses a wide range of techniques and methodologies using high-end information technology and automation systems to provide information of high quality and value with lesser dataset than manual techniques. This section presents a novel approach using open source geospatial technologies (GDAL/OGR library) to determine the volume of water in irregularly shaped lakes with embankment. The approach uses spatial vector data for boundaries, spatial vector data for embankments, and depth data to calculate the amount of water present in any given lake. In this study, the above mentioned approach has been described with details of information and implementation. As

20 a follow up, results have been tabulated and compared to the results obtained from manual methods and the overall accuracy and feasibility of the new approach has been discussed.

4.2 Methodology

4.2.1 Data Collection and manipulation

4.2.1.1 GIS Data

A geodatabase is a database that is in some way referenced to locations on the Earth. Coupled with this data is usually data known as attribute data. Attribute data is generally defined as additional information which can be tied to spatial data. Thus GIS data can be separated into two categories: spatially referenced data which is represented by spatial vector and raster forms (including imagery) and attribute tables which is represented in tabular format. Within the spatial referenced data group, the GIS data can be further classified into two different types: vector and raster. Most GIS software applications mainly focus on the usage and manipulation of vector geodatabases with added components to work with raster-based geodatabases. Vector data is split into three types: polygon, line (or arc) and point data [28]. The proposed method to calculate water-volume requires three kinds of vector data sets -

Boundaries of water bodies as polygon : Polygons are used to represent areas such as the boundary • of a city, lake, or forest. Polygon features are two dimensional and therefore can be used to measure the area and perimeter of a geographic feature. Polygon features are most commonly distinguished using either a thematic mapping symbology (color schemes), patterns, or in the case of numeric gradation, a color gradation scheme could be used. We collected polygon data for boundaries of all the lakes of Hyderabad city and the surrounding area. This is an essential data which we used to calculate water-volume of lakes.

Embankment of water bodies as linestring. Line (or arc) data is used to represent linear features. • Common examples would be rivers, trails, and streets. Line features only have one dimension and therefore can only be used to measure length. Line features have a starting and ending point. Common examples would be road centerlines and hydrology. We collected Line or arc data for embankment of lakes. An embankment refers to the artificial or natural barrier which stops the flow of water, thus creating the reservoir. A lake is usually assumed to be the deepest along its embankment. For embankments which are straight, line data was collected and for embankments which are in the form of an arc, arc data was collected.

Depth of embankment as point data. Point data is most commonly used to represent non-adjacent • features and discrete data points. Points have zero dimensions, therefore one can measure neither length or area with this dataset. Examples would be schools and points of interest. Point features

21 are also used to represent abstract points. For instance, point locations could represent city lo- cations or place names. We collected point data which had depth detail of all the embankments. We used this annotation data to get the depth details of embankments, and after doing geopro- cessing to match the embankment using nearest neighbor method, we stored this depth detail with embankments as one of the attributes.

Figure 4.1 Toposheet sample information for Mir Alam Cheruvu

Required data for this study was obtained from Survey of India. The vector data was collected as Shapefiles in ESRI format, which is a popular geospatial vector data format for GIS systems. After processing the collected vector data through geoprocessing and removing topological errors, two shape- files were created [29]. The first shapefile contained lake boundaries and second shapefile contained embankment as a linestring superimposed on top of lake-boundary polygon, with depth of embankment as one of the attribute of this second shapefile (Figure-4.2).

4.2.2 Modelling of the lake into simpler shapes

In order to model the lake as an integral sum of simpler cuboids, the lake surface was first modelled as a 2-d surface on which lay a grid of blocks of size nXn square meters on top (as shown in Figure 4.3). The actual embankment was extrapolated as a straight line extending from one end of the embankment to the other, and the grid was aligned to this fictitious line as a reference boundary. In the forthcoming section we will discuss about the appropriate value of n based on lake’s size.

22 Figure 4.2 Generation of embankment data from point, arc and polygon vector data. The embankment points are determined by finding points on the polygon which are nearest to the corresponding points on the arc. (Lake Name: Mir Alam Cheruvu)

23 Figure 4.3 Grid Superimposition on lake polygon. First the lake embankment is extrapolated to form a representative straight-line embankment. The grid is then imposed on the lake surface by aligning one of it’s edges with the emabnkment.

24 4.2.3 Volume calculation of lakes

Given that the lake is modelled as numerous cuboids fitted together, water volume estimation of the lake corresponds to finding the volume of each such cuboid and summing all such volumes obtained. For this purpose, the length, width and height of each cuboid needs to be determined. Since the lake surface has been superimposed by a grid, each grid square acts as the top of cuboid which gives us the length and width of each cuboid as a constant. The only unknown variable now, is the height of cuboid. Since the depth of the lake along the embankment is known, linear interpolation can be applied to calculate the depth at any point at some known distance from the embankment. For this, an imaginary line is drawn perpendicular to the embankment, which reaches out to the farthest point on the lake, and the length of this line is calculated. Given the depth of lake at embankment is known, and assuming the depth at the farthest point is zero, linear interpolation can be applied to calculate the depth at any point on this line. Hence the volume of a cuboid can be calculated as

V = n n D (4.1) c ⇤ ⇤ c where

De dc Dc = ⇤ (4.2) dmax 3 where Vc is volume of any cuboid in m ; n is edge length of block; Dc is average depth at selected cuboid in meter; De is maximum available depth on embankments; dc is euclidian distance between cuboid and embankment; dmax is euclidian disatance between embankment and farthest point on lake from embankment. The total volume of lake is summation of volumes of all cuboids. The whole process from scratch is shown in Figure-4.4. Total volume as

n Vt = Vi (4.3) Xi=0 3 th where Vt is total volume of lake in m ; n is total number of cuboids; Vi is volume of i cuboid.

4.2.4 Use of GDAL/OGR and QGIS

The GDAL/OGR library has been used for all the geoprocessing required for carrying out this study. There are a various of Python packages and extensions which have a number of tools for programming and manipulating the Geospatial Data. The package which has been used is known as Geospatial Data Abstraction Library (GDAL). It is used for manipulating geospatial raster data, and has an additional library names OGR for manipulating geospatial vector data. This study used OGR as the data was in geospatial vector format [30] [31]. Figure-4 depicts the flowchart used for calculations. Below are some of the functions which were used for geoprocessing.

The ‘ESRI Shapefile’ driver to open the shapefiles. This driver can be used to open the shapefile • data, and from shapefile data the layers can be opened using GetLayerByIndex() function.

25 Figure 4.4 Overview of Volume Estimation

26 The ResetReading() API to iterate multiple times over all the features in a layer. To get geometry • from any feature the GetGeometryRef() method was used on the target feature.

The Distance() function for calculating the euclidean distance between any two geometries. • The Intersection() function to generate a new geometry which is the region of intersection of • the two geometries operated upon. Additionally, the Intersects() method was used to test if two geometries intersect.

The Crosses() function to test if any given geometry crosses the geometry passed as an argument • to this function.

The Within() function to test if any given geometry object is within the passed geometry. • The Overlaps() function to test if any given geometry and the geometry passed to the method • overlap, that is, their intersection has a non-zero area.

The Equals() function to check if two geometries are equivalent. • The Centroid() function to compute the geometry’s centroid.The centroid location was applied to • the passed in point object of OGR type. The centroid may not be necessarily within the geometry.

The Area() function to calculate area of any polygon or closed ring. • The DeleteFeature() method to delete any specific feature from shapefile. This greatly helped • in optimizing the run time because cuboid objects were deleted after processing, thereby reducing the resource consumption and improving time complexity for next run.

The Destroy() function to optimize memory utilization for machine on which the program was • run. It helped destroy all the features and shapefiles after usage.

Apart from these methods, a set of methods from the OGR library were used to manipulate the existing shapefiles attribute and geometries, and also to create new shapefile. Quantum GIS is an open source Geographic Information System that supports most geospatial vector and raster file types and database formats. It was used for all the visualization purpose and also for digitization of few lakes and boundaries of O&M divisions, their analysis and various map generation. Apart from this vector data classification module of QGIS is also used in this study. Classifying vector data allows you to assign different symbols to features (different objects in the same layer), depending on their attributes. To create a map, one has to style the GIS data and present it in a form that is visually informative. There are a large number of options available in QGIS to apply different types of symbology to the underlying data. In this study Graduated symbology type is used in the Style dialog. Graduated symbology type allows you to break down the data in a column in unique classes and choose a different style for each of the classes. There are 5 modes available for classification of classes. Equal Interval, Quantile, Natural Breaks (Jenks), Standard Deviation and Pretty Breaks. These modes use

27 Figure 4.5 Logic flow of algorithm

28 different statistical algorithms to break down the data into separate classes. We used Natural Breaks as mode for classification of data [32].

4.3 Comparison of Results

For calculation purpose, the surface area of a given lake was analysed by superimposing a grid of blocks of size nXn square meters on top. Since the lakes were found to be irregular in shape, the block size was varied case-by-case to efficiently cover the lake surface. This exercise was carried out for lakes of all sizes - ranging from the big ones like Himayat Sagar to smaller, local ones. In this section, lakes with capacity between 50 Mcft. and 70 Mcft were classified as medium sized, while the ones with capacity between 2800 Mcft. to 3500 Mcft were classified as large sized. The block sides were varied in the range of 5 meter to 40 meter. It was observed that with change in block size, there is no fixed trend in the error percentage; the variation instead depends on the size of lake under consideration. The variation in error percentage however does not itself vary significantly with change in block size within the tested range. Figure-4.6 shows the relationship between the error percentage (calculated volume relative to the actual volume) and the block edge for sample lakes of two contrasting sizes - a big one (represented by purple dots) and a small one (represented by blue dots). For the larger lake, the best results are observed when the block side is 25 meter, and for the medium one the best results come for a block side of 10 meter. The mean percentage of error observed is 6.5 percent for medium size lakes and 7.51 percent for larger lakes. So far the lakes which have been considered for the study have been man made lakes which have a well-defined embankment as a reference point for all modelling and calculations. Though the concepts used to derive this method generically apply to both natural and man-made lakes, it cannot be directly applied to natural lakes since their structure is different from that of man made lakes. Most natural lakes do not have a well-defined embankment; rather they have the maximum depth somewhere in the middle with the depth gradually decreasing towards the periphery. In this case, the proposed method can be modified by taking the mean depth as the reference depth, the centroid of lake as the reference point and then calculating the depth at any given point by means of linear extrapolation.

4.4 Analysis of volume-calculation

The proposed approach for calculating water-volume is very efficient and reliable since it gives highly accurate results with a limited amount of data. One of the limitations of this method is the reliability of data depicting the depth of lake at embankment. For this study, data was received from Survey of India (SOI) which is the national survey and mapping organisation of India - the leader in providing user focused, cost effective, reliable and quality geospatial data. Hence this data can be considered fairly accurate and reliable. However, data collection can be automated and improved by the use of GIS for this task. Similar work has been done in Europe, where GIS was used to calculate the mean depth of lake using DEM data with regression equations [33].

29 Figure 4.6 Variation of error percentage with block size. Note that for large sized lakes, the variation is negligible as compared to the variation seen in case of medium sized lakes.

Hence the loose end for this approach is linear interpolation of local depth using maximum depth at embankment, and with the help of any additional data providing more insights into the geography of the lake and the contour pattern, the results of this method can be improved drastically. The use of GIS makes this approach simple and effective as it involves limited resources, yet is highly effective. As compared to hemispherical or conic methods, the proposed method is far more realistic and estimated volume from this method is closer to actual values.

4.5 Application of Water Volume Estimation Algorithm on Hyderabad

Providing water for households and industries is a challenging task when the city is a metropolis like Hyderabad. For this, the HMWSSB uses a water supply system which relies mainly on rivers outside the periphery of the city. Two big lakes in the city - Osman Sagar and Himayath Sagar - had played an equally prominent role as sources of water for the city. However, as more and more rivers were added to the system, dependency on these lakes gradually decreased to a minute percentage. Though other than these two lakes, there are a lot of other water bodies within the city limits, they are not being harnessed for civil water supply. One prominent reason for this is the fact that most of the above mentioned water bodies are facing civil neglect in the form of pollution and illegal encroachment, which has made the civil administration rule out these lakes as possible sources of water. The 16 O&M divisions of

30 Hyderabad have a total of 350 such water bodies, which includes small, medium and large ones. If a system relying on these water bodies for civil water supply is developed, it will be sustainable and cheap, hence also profitable. Not only will these local water bodies provide water for day-to-day consumption, they will also play a pivotal role in improving the ground-water level of the region. For analysing such a system, it would be imperative to find out the water profile of the city. Since the HMWSSB provisions and manages water supply in the city through O&M divisions, it would make better sense to conduct any analysis on water supply also for each division separately. If the total water volume of lakes in a division can be obtained, it can be equated with the total water consumption of that division and the dependency on lake water for each division can be determined. Hence calculation of water volume becomes an important step in analysing the feasibility of the water distribution system described above. As already mentioned, application of traditional methods to estimate water volume of lakes is cumbersome and would require a lot of resources, effort and time to be applied for each and every lake in any division. This is where the technique to calculate water volume using GIS (described above) can come handy and would prove very useful because of its low-weight and accuracy. Estimated value of water-volume of all the small and medium lakes in Hyderabad is calculated using the above discussed algorithm. Figure-4.7 shows all the lakes of City Hyderabad. From the data, it was found that out of 680 km2 of total residential area of Hyderabad, only 22.5 km2 is comprised of water bodies, which is 3.33 percent of residential area. This is a very low ratio which is just sufficient to maintain the water profile of the region. Though this conclusion is based on figures which have been calculated without considering the two biggest lakes - Himayat Sagar and Osman Sagar which have areas of 21 km2 and 20 km2 respectively. If these lakes are also taken into consideration, this number increases to 9.33 percent. The Tables-4.1 illustrates data about lakes categorised on basis of their area. For each category, the total number of lakes and the total volume of those lakes has been tabulated. It should be taken into consideration here that only data from small and medium lakes has been tabulated here. These are the ones which are not used for water supply. If we include Himayat Sagar and Osman sagar as well (which are currently supplying water to the city), the numbers change towards a more positive and optimistic data. Based on the calculations, the total volume comes out to be 23,412 millon gallon, which is 3.2 TMC. But to preserve aquatic life in water bodies, the amount of water present in a lake at any given time should not be below than 35 to 40 percent of its total capacity. This puts a cap on the extent of water that can be drawn from lakes to a maximum of 60 to 65 percent. So we can use up to 1.92 TMC of water from all the lakes of Hyderabad combined. As discussed in the earlier section on water-volume calculation, these results have on an average 7 percent error. So the average water supply will vary from 1.79 TMC to 2.05 TMC. For further analysis, we have taken this number to be 2 TMC. As mentioned earlier, these numbers have been arrived upon without considering the two biggest lakes in the city - Osman Sagar and Himayat Sagar, since they are already being used for water supply and near to city hence including these two gives a full idea of how the proposed system can work as a standalone component in the citys

31 Figure 4.7 Distribution of lakes in Hyderabad. (2014)

Lakes Area Range (acres) Count of Lakes Total Volume (Million Gallon) 0 to 1 51 71 1 to 3 118 447 3 to 6 62 583 6 to 15 69 1521 15 to 50 53 4808 50 to 100 11 5059 100 to 150 8 3554 300 to 400 3 7369 Total 375 23412

Table 4.1 Distribution of lakes across Hyderabad, based on the size range. The table also shows the total volume of water in all lakes of a given size range.

32 Division Number Total Water Available Lo- Total Water Available In- Percentage cal Lakes(million gallon) cluding Big Lakes(million gallon) 1 1833 5741 9 2 309 6273 9 3 233 4199 6 4 11 2796 4 5 33 3845 5 6 193 4190 6 7 39 3109 5 9 2802 7418 11 10 2249 7447 11 12 2416 7359 11 13 810 4125 6 14 1266 4393 7 15 1286 3255 5 16 1416 3115 5 Total 14896 67265 100 Percent

Table 4.2 Total water volume available in each division for consumption in Hyderabad. water supply system. Including these two lakes, the water volume increases by 7 TMC, thereby raising the number to 9 TMC. Considering these two lakes into our system also inflates other kinds of numbers, presenting a more positive outlook on the system. The Table-4.2 shows the total water available for consumption purpose in each division, basically in our study lakes are classified as local lakes and big reservoirs so 2nd column of the tables shows water availability in each division considering local lakes and 3rd column shows total water available including both the big lakes of city, Osman Sagar and Himayat Sagar. Figure-4.8 and Figure-4.9 shows the same data on an outline map of Hyderabad. As can be observed in Figure-4.8, the divisions which are interior to the city have very less percentage of water, and the number tends to zero for three out of five such divisions in the 0-4 percent bracket. This is due to the fact that the lakes in these regions have already dried up due to to pressure of population, leading to encroachment, pollution and sewage disposal. However, considering the bigger lakes into picture, the percentage goes up significantly. Thus the total water volume from smaller local lakes and the bigger lakes comes out to be a satisfactory number as shown in Figure-4.9.

33 Figure 4.8 Division wise water availability. This data assumes only local water bodies as sources.

34 Figure 4.9 Division wise water availability. This data includes water from local reservoirs, Himayat Sagar and Osman Sagar.

35 Chapter 5

Water security of Hyderabad

5.1 Water Security - Definition

Water security is defined as the capacity of a population to safeguard sustainable access to adequate quantities of acceptable quality water for sustaining livelihoods, human well-being, and socio-economic development, for ensuring protection against water-borne pollution and water-related disasters, and for preserving ecosystems in a climate of peace and political stability. (UN-Water, 2013) Water security encapsulates complex and interconnected challenges and highlights waters centrality for achieving a larger sense of security, sustainability, development and human well-being. Many factors contribute to water security, ranging from biophysical to infrastructural, institutional, political, social and financial many of which lie outside the water realm. In this respect, water security lies at the centre of many security areas, each of which is intricately linked to water. Addressing this goal therefore requires interdisciplinary collaboration across sectors, communities and political borders, so that the competition or potential conflicts. The post-2015 process must incorporate a goal and related targets for achieving water security, as this will address multiple priority development areas under consideration: conflict and fragility; environmental sustainability; growth and employment; health, hunger, food and nutrition; inequities; energy; and of course, water. It is safe to state that investment in water security is a long- term pay-off for human development and economic growth, with immediate visible short-term gains. (by UN-water report)

5.2 Population Distribution of Hyderabad Division wise

Since the water distribution for Hyderabad is managed in divisions, it was imperative to conduct the study too on division level. This meant doing all the analyses and calculations per division. There were two major players involved in carrying out the analysis for each division - total water-volume of lakes which would be acting as the source of water, and resident population which would be acting as the consumer. The equation and balancing of these numbers would determine how much population of a division can depend on the lakes.

36 Div Number Areas list in divisions Population 1 , Bahadurpura, Chandrayangutta, Misrigunj, 528906 Moghulpura, Pattargatti, Darulshila, Azampura, Hasannagar, Sultanshahi etc. 2 Malakpet, Yakutpura, Asmangadh, Moosarambagh, Santosh na- 807277 gar, Saidabad, Madannapet, Chanchalguda, Dabeerpura, Balapur, Aliabad, Gowlipura, Maisaram., etc. 3 Karwan, Vijayanagar colony, Masab tank, Humayun nagar, 536727 Mehdipatnam, Shaikpet, Kakatiya nagar, Tolichowki, Golconda, Karwan etc. 4 Goshamahal, Mangalhat, Jiyaguda, Allabanda, Boggulkunta, 376944 Gowliguda, Sultanbazaar, Red Hills, Hindi nagar, New MLA Qauarters etc. 5 Amerpet, Musheerabad, Narayanguda, Boats Club, Domalguda, 516002 Gandhinagar, Chilkalguda, Bholakpur, Azamabad, Vidyanagar, Adikmet, Chi kkadpally etc. 6 Jubilee Hills, Khairatabad, Banjara Hills, Tattikhana, Ameerpet, 540877 Erragadda, Somajiguda, S.R.Nagar etc 7 Sanathnagar, Boiguda, Marredpally, Padmarao nagar, 415629 Seethaphalmandi, Tarnaka, Lalapet, Mettuguda etc. 9 Kukatpally, Balanagar, Hashamathpet, Moosapet etc. 624764 10 LB Nagar, Saroomagar, Dilsukhnagar, Gaddiannaram, 703411 Vanasthalipuram, Autonagar, NTR nagar. 12 Qutubullapur, Chintal, Jeedimetla, Gajularamaram, Ja- 669050 gadgidgutta Shapoor nagar 13 Malkajgiri, Alwal, Father Balaiah nagar, Yapral. 448570 14 Uppal, Kapra, Sainikpuri, Ramanthapur, Hasibguda. 423312 15 Serlingampally, Madhapur, Gachibowli, Chandanagar, Ra- 266472 machandrapuram, Patancheru. 16 Rajendranagar, Budvel, Hyderguda. 229823 Total Population City of Hyderabad. 7087764

Table 5.1 Details of O&M divisions. The table shows wards constituting eah division, and the popula- tion of each division.

37 From Hyderabad Metropolitan Water Supply & Sewerage Board, the list of areas/wards covered for each operation and management division was procured. Table-5.1 shows areas covered for all division. Taking help of Primary Census Abstract data of 2011 census, we calculated population for each O&M Division. Primary Census Abstract (PCA) has population data on District, Subdistrict, Town/Village and ward level [34] . Since ward level details for each O&M Division were available in the PCA, aggregation of population data for each ward gave the population for each O&M division.

Table 5.1 shows the population of each O&M division in a crude format. For comparative analysis, the data needs to be visualized in a better, simpler way. For this purpose, the data has been represented as a bar chart in Figure-5.1. As can be seen from the graph, division numbers 2, 9, 10, 12 have the most population and hence pose critical test cases for the solution which will be proposed by this study.

Figure 5.1 Division wise population distribution (bar chart) 2011

Since the study attempts to compare the total water volume available in each division against the total volume of water used in that division, it would be insightful to visualize population distribution as a function of geography. Figure 5.2 shows the population of various O&M divisions on an outline map of Hyderabad, with divisions demarcated. Visualising population data in this manner can help provide primary insights on the feasibility of using local lakes as water sources. Figure-4.7 shows the distribution of lakes in the city on a similar outline map of Hyderabad. From the two figures depicting population density and lake distribution, one can figure out how much dependency on local water bodies can be leveraged.

38 5.3 Division wise Water supply

Figure 5.2 Division wise population distribution (map)

The Table-5.2 shows amount of water supplied by the HMWSSB in all 16 O&M divisions on a weekly basis. These numbers show that around 86 perent of the population is receiving water on alter- native days and 8 percent is receiving 3 time in a week. The total water supplied to city is around 308 MGD; Traditional method of distribution relies on Osman Sagar, Himayath Sagar and the rivers Krishna and Manjeera for water supply. This system has several overheads associated with it. For each of the water sources mentioned above, there is a considerable cost of infrastructure construction and maintenance associated. For the sake of simplicity, let us take three different projects - Himayat & Osman Sagar (on the river Musi), Singur Dam (on the river Manjeera) and the river Krishna. Of these, the two reservoirs on Musi are the closest to Hyderabad, followed by Singur Dam; and river Krishna is the farthest from the city. If the project costs involved in these three are compared, one will observe that as the distance of the project from the city increases, the cost involved with the project also increases. What is more intriguing here is the trend that is followed. For instance, the project cost of Krishna river project is three times that of Singur Dam and five times that of Osman & Himayat Sagar [8]. Hence it can be deduced that distance of water source from the targeted supply area is a major factor which increases the cost of the project manifold.

39 Supply Frequency O &M No of Present Avg. Supply ( No of Connections) Div. Conn. Qty Sup. Once Once Once Supply in a Alternate in MGD Daily in 3 in 4 in 5 days in a week(MG) 1 Day Days Days Days week I 49184 25.89 0 46351 2833 0 0 3.43 88.88 II 80842 48.93 0 80842 0 0 0 3.5 171.26 III 59188 23 0 59188 0 0 0 3.5 80.5 IV 42050 22.3 0 42050 0 0 0 3.5 78.05 V 68664 25.85 0 68664 0 0 0 3.5 90.48 VI 77452 41.45 0 77452 0 0 0 3.5 145.08 VII 59930 20.68 0 59930 0 0 0 3.5 72.38 IX 66322 18.34 0 66322 0 0 0 3.5 64.19 X 87900 22.2 0 79701 0 0 0 3.17 70.45 XII 53056 11.04 0 26056 12500 14500 0 2.75 30.33 XIII 52393 11 0 0 24890 15858 11645 1.95 21.44 XIV 48113 11.5 0 24613 23500 0 0 2.93 33.7 XV 33849 17.08 0 33849 0 0 0 3.5 59.78 XVI 19702 8.88 0 19702 0 0 0 3.5 31.08 Total 798645 308.14 0 684720 63723 30358 11645 1037.58

Table 5.2 Details of water connections, frequency of water supply, and total water supplied in each division.

The deduction made above is a major reason why this study proposes the use of local water bodies as the source of water for Hyderabad. Since these water bodies are within the periphery of the city, the overhead involved in terms of infrastructure and maintenance will be very less. It might not be necessary to fully rely only on local water bodies, but these can be used along with the existing system to make the existing system more robust, reliable and profitable.

5.4 Can including local Water bodies in existing Water supply system improve Water security ?

Proper understanding of the proposed solution requires analysis of water availability respective to population distribution of Hyderabad. The previous section discussed about the availability of water in Hyderabad. If the population factor is now included in this study, it will be possible to rank the divisions based on water security if divisions solely depend on local water bodies. According to the WHO, 150 liter per capita per day water is required by the city. All calculations have been done based on this number. Figure-5.3 depicts the extent of reliability of O&M divisions on local water bodies without including Osman sagar and Himayat sagar, two big reservoirs of the city. It can be observed that the divisions which are interior cant rely entirely on water bodies, since availability of lakes with good embankment depth and large capacity is more in outer divisions. Figure 5.3 shows graduated

40 Figure 5.3 Percentage of population targeted by considering only local water bodies.

classification of divisions based on percent of population covered by local water bodies. Total percentage of population served by local lakes only is 15 percent.

If we take this study to one more level and try to understand the water distribution in each divisions. Top 6 divisions distribution is shown in Figure-5.4,5.5 and 5.6.

The numbers arrived upon so far have been calculated assuming that only the water bodies local to a division can be used as water sources. However, one cannot neglect the impact of two biggest reservoirs - Osman Sagar and Himayat Sagar - on the citys water distribution system. Though these two lakes (reservoirs) are located outside the boundaries of the city; their sheer size, availability of water, and the mere fact that these are the biggest sources of water currently being used for the citys water supply make it necessary to redo the above analyses considering these two lakes as well into picture.

Figure 5.7 shows the population that can be served with local lakes and the two big reservoirs as sources. By comparing with Figure 5.3, it can be seen that the numbers increase to more optimistic and satisfactory levels, with the minimum dependency being 53 percent, meaning that in this scenario, at least half of any O&M division can rely on the lakes for water supply. If the total population of city is considered, 67 percent of the population can be served by all the lakes. And as shown in figure-5.8 if Hybrid water suplly is used, all the O&M divisions will have sufficeint water.

41 Figure 5.4 Water distribution for 16th Division and 15th Division using only local water bodies

42 Figure 5.5 Water distribution for 9th Division and 12th Division using only local water bodies

43 Figure 5.6 Water distribution for 1st Division and 10th Division using only local water bodies

44 Figure 5.7 Percentage of population targeted by considering local water bodies, Himayat Sagar and Osman Sagar.

45 Figure 5.8 Percentage of population targeted by considering Current supply (all rivers) and also includ- ing local water bodies.

46 Figure 5.9 Month-wise distribution of rainfall in Hyderabad

5.4.1 Lake Replenishment

The lakes considered for this study have been mostly formed by collecting rainwater except two big reservoirs, as they are partially dependent. There is no perennial or even seasonal stream of water which would act as the source for most of the lakes. Every year, these lakes depend on rainwater alone for replenishment. If the rainfall is scarce in any year, these lakes would tend to dry up. Since rainwater is the only source of water for these lakes, it is crucial to analyse the rainfall pattern in the city to evaluate whether these lakes will be replenished thoroughly on a yearly basis, so as to sustain the model described in this study. Hyderabad is blessed with a good amount of rainfall. It receives rain from the south-west summer monsoon between June and September, which comprises most of its mean annual rainfall. The city experiences semi-arid tropical climatic conditions. The average annual rainfall is 821 mm. The south-west monsoon contributes 74 percent of annual rainfall and north east monsoon contributes 14 percent. The temperatures reaches 45 C during summers and with the onset of monsoons in June, the temperature drops and varies between 26 C to 38 C. Lake water availability around the year can be maintained for supplying water efficiently. Total water consumption for each month is around 5 percent as total water consumption is 60 to 65 percent of total water from lake for 12 months. This 5 percent can be varied based on the total study of lake water availability around the year.

47 From the graph shown in Figure-5.9, it can be seen that Hyderabad receives an average of 821 mm of rainfall annually. Now, 1 mm rainfall on an area of 1 meter counts to

1 mm X 1 m2 =1Liter of water (5.1)

Which means that 1 mm of rainfall in an area of 1 km2 gives 1 million litres of water. Given that the total area of Hyderabad is 680 km2, this implies that an 820 mm average rainfall pours 19.7 TMC of water in Hyderabad, per year. This number is approximately 10 times than the figure of 2 TMC water that was arrived upon for consumption from the lakes. This essentially means that rainfall in the city should be sufficient to replenish the lakes. It also implies that by implementing techniques such as improving landscape, catchment area, watershed management and rainwater harvesting, a huge amount of rainwater which usually runs-off into nearby rivers can be actually trapped and stored either in the form of surface water in reservoirs, or as groundwater. This will improve the water-profile of the area to a great extent. The two biggest lakes in the city - Osman Sagar and Himayat Sagar, have river Musi and its tributaries as their main source of water. The catchment area of these two is also considerably large, with Himayat Sagar having an area of 500 sq miles and Osman Sagar having an area of 280 sq miles. The cumulative rainfall in the catchment area is sufficient to fill the reservoirs once in a year, and the river Musi keeps flowing in the trickling water from its source - the nearby Ananthagiri hills throughout the year, albeit in smaller volumes. This implies that ideally, the lakes should be having sufficient water at any time of the year. However, river Musi is the only major source of water for these lakes, and its flow depends on the rainfall pattern in its catchment area. Hence depending on the weather, the lakes are either fully replenished or partially replenished. In any case, consideration of these lakes into this study gives optimistic results.

5.5 Timeline Study of Hyderabad

The analysis done so far on the population distribution and corresponding dependency on lakes has taken the latest census data into account. If the same analysis is done using data spanning around two decades, interesting insights can be deduced about the water and population profile of the city, the pattern that has been followed, and the possible trends in water security that can be expected in future decades. A glance at the population data of the past decades shows that the since the population was less, the citys water distribution system was self sustainable. But as the population grew, the city too expanded and witnessed encroachment and negligence towards local water bodies, in order to cram residential and commercial buildings into whatever land was available in the city. This lead to a decrease in the total water volume which the citys lakes could store and provide. Though the population grew rapidly, the lakes became smaller and shallower, thereby decreasing their capability to act as reliable water sources for the population. Figure-3.4 and Figure-5.10 shows the dependency numbers for population data corresponding to the census of 1991 and 2001. It can be seen that all the percentages are greater than 100, implying that in

48 Figure 5.10 2001

49 Figure 5.11 Timeline study of divisions based on water availability that decade, not only were the local lakes sufficient to meet the needs of population, but had surplus amount of water available. In fact, in a few divisions, the water volume was double of what was needed for sustenance. This shows that the water profile of Hyderabad in those times had been very impressive. Figure 5.11 consolidates the trend over two decades of study, and provides insights on the changes in water availability patterns. For each year, the number of divisions where water availability was abundant, moderate and severe have been plotted. It can be seen that in 1991, all the divisions had abundance of water. In the ten years, some of the divisions fell short of water and came under the nearly sufficient category. However, in the next fifteen years, a large number of divisions faced acute shortage of water and came under the severe category. Currently, majority of the divisions fall under moderate and severe categories, and only a few of them fall under the nearly sufficient category. There is no division which can be said to be in the sufficient category. With the rapid and uncontrolled urbanization, these dependency numbers have reduced drastically. Though the percentages today are still optimistic, the sharp decline of dependency ratio by nearly 100 percent shows that there has been sheer neglect of water bodies under the hood of mandatory urban- ization. Population outburst is a phenomenon that cannot be avoided or blamed altogether, since the population inflation is not just because of local population, but is majorly contributed by the swarm of immigrants from other states which came to the city in early 20th century as a result of better job and life opportunities given by the IT and Pharma boom. However, the manner in which urbanization took place to house the companies and their employees is questionable. With the increase in population, the

50 lakes could have been curated and deepened, if not expanded, in order to increase their storage capabil- ity. Such measures could have helped in maintaining the water profile of the city despite the population outburst.

5.6 Proposed solution toward improved Water Security: Depth Enhance- ment of lakes

Figure 5.12 Percent of population served (Division wise, Based on 2011 census data) by local water bodies after applying depth enhancement

From the data collected, the average depth of embankments came to be 3.75 meters, which is very less as compared to the standard embankment depths. If the depth of these is increased, it will improve the water storage capacity, thus making them more reliable for water supply. To support the above

51 Figure 5.13 Percent of population served (Division wise) by local water bodies after applying depth enhancement and including supply from Himayat Sagar and Osman Sagar lakes (Based on 2011 census data)

52 hypothesis, calculations for water volume were done with the embankment depth inflated to 7 meters. The resultant water volumes were far more than the current water volume of lakes. Figure-5.12 shows the results obtained when the embankment depth of lakes is increased, and then calculations are done to get the water volume of lakes. As can be seen broadly, an increase in the embankment depth results in increase in water volume - the increased percentage ranging to maximum of 68%. The overall population which can be served solely using local water bodies also shot up from 67% to 80%. Thus it can be concluded that increasing the depth of embankment leads to a substantial increase in the water capacity, thus increasing the dependency on local water bodies. The increase in embankment depths wasnt a uniformly applied rule. The increment was done based on current depth of any lake. So for lakes with depth less than 5 meters, the depth was increased by 100 percent and for lakes with depth between 5 to 10 meters, the depth was increased by 50 percent. After this change, the calculated water volumes show that 7 divisions can be dependent on local water bodies by more than 30 percent and 2 divisions can be dependent more than 50 percent. If water supply from Osman Sagar and Himayat Sagar is also included, the numbers shoot up sharply. Figure 5.13 shows the percentage of population that can be served with this scheme per division. As shown in Figure-5.13, percent of population served by local water bodies after applying depth enhancement and including supply from Himayat Sagar and Osman sagar lake. To understand in depth about the distribution of water within each O&M Division, water was dis- tributed within circle. Figure-5.14 and Figure-5.15 show a comparative analysis on the area covered by lake water with current depth and increased depth. The figures are geographical outlines of particular O&M divisions. Each division can be seen having several mid and small sized lakes. To generate each figure, the whole division was divided into small grids, and the grid blocks sourrounding each lake were filled with green color. This was done only till the total water consumption of colored grids was less than the water volume of the lake. This generated a pattern of colored grids surrounding each lake, depicting the fraction of population which could be supplied water from lakes in that division. Hence, a greater area in green means larger percentage of population can be served. In Figure-5.14 and 5.15, the pictures on the left represent calculations done with normal embankment depth, and the ones on the right represent the calculations done for the same O&M divisions, with depth enhanced. As can be seen in the images, incresed depth lead to increase in water supply for 20 to 25 percent.

53 Figure 5.14 Comparison of divisions after Depth enhancement-1

54 Figure 5.15 Comparison of divisions after Depth enhancement-2

55 Chapter 6

Conclusions

Water security is an important parameter which decides the economic, political and social well-being of any society. It is also an indicator of level of sustainability of development and urbanization. In the past few years, Hyderabad has seen a rapid decline in water security - a phenomenon which demands quick action and efficient mitigation. This study proposes to leverage local water bodies as sources of water and incorporate them in the citys main water supply system. To back this solution, this study presents data on the water volume available in these lakes and the per capita consumption of water in the city. In the process of doing so, it also proposes a faster solution to calculate the water volume of any irregularly shaped water body by using GIS. This solution is found to give results with error percentages ranging from 6.5% for medium-sized lakes to 7.5% for large sized lakes. Moreover, the error percentage further depends upon the granularity of the grid which was used to model the surface of lake. This makes error reconciliation easier, thereby pointing out to the eventual accuracy of the proposed algorithm.

When applied to all the lakes in Hyderabad, the algorithm gives a gross 9 TMC of water which could be used for supplying to the city. Population data collected from official sources, along with information on per capita water consumption of the city show that the city needs around 13 TMC of water. This leads to the conclusion that in their current state, the lakes in Hyderabad can be used to supply water to 67% percent of the population. This is an important finding as it points out to the possibility of delegating almost two-thirds of water supply to local reservoirs- a step which will help lowering down the cost and logistics of water distribution system. These numbers give a holistic view of the problem and its solution. If these figures are broken down according to the O&M divisions in the city and then anal- ysed, a diverse and more realistic, accurate picture comes up. There are divisions where the dependency shoots up to 96%, and there are ones where it is 50%. Thus only local water cannot be relied upon as a standalone solution to the citys water needs. They can however be used in conjunction with the current system and act as a complementary to the rivers. Such a hybrid system would be highly effective and prove to be an important factor in making Hyderabad a world class city.

56 The amount of water that can be drawn from lakes can be further improved if the lakes are deep- ened and their catchment area is reclaimed. Extrapolation of lake embankment depths to simulate this scenario and using new depths to calculate lake water volume show that in such a situation, 80% of the population can be supplied water using local reservoir. These results lead to the conclusion that the proposed system for water distribution using local water bodies can prove to be an efficient solution to the citys water problems.

57 Chapter 7

Future Work

In its current scope, the study proposes a novel solution using local water bodies to supply water to the population in Hyderabad. It also proposes faster and efficient methods to calculate water volume of any irregularly shaped water body using GIS technology. The research work done till now can be further augmented in several directions to give a greater width and depth to the scope, research and results. The proposed future works for this study are as follows:

Feasibility and Profitability analysis: This involves doing a rigorous analysis of the project from • economics and feasibility point of view; covering detailed study of the logistics, operational cost and eventual profitability of the project.

Comparative study of the proposed system and any long-distance water distribution project: This • involves coming up with parameters to compare the proposed system and any other water dis- tribution system, and evaluating both systems on those parameters to check which one is more feasible. For instance, in the case of Hyderabad, there is an existing long-distance project where water is drawn from the Krishna and Godavari rivers. Hence the proposed system for Hyderabad can be compared to the Krishna-Godavari project for better understanding of the pros and cons, if any.

58 Related Publications

Rahul Kumar Rai, K.S. Rajan, Volume Calculation of Irregularly Shaped Water Bodies, page 30, • 2017, Free & Open Source Solutions for Geoinformatics-ASIA.

Rahul Kumar Rai, K. S. Rajan, Improved water security by preserving water bodies in Hyderabad, • In Process, 2017, Water Resources Management, http://www.wessex.ac.uk/conferences/2017/water- resources-management-2017

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