Adapting a hazards risk model to water scarcity in rural india aurangabad case study

Adapting a Hazards-Risk Model to Water Scarcity in Rural India-Aurangabad Case Study by Paige MidstokkeSubmitted to the Institute for Data, Systems, and Society and the Department of Civ

Adapting a Hazards-Risk Model to Water Scarcity in Rural

India-Aurangabad Case Study

by

Paige K Midstokke B.A Political Economy

University of California, Berkeley 2013

Submitted to the Institute for Data, Systems, and Society and the Department of Civil and

Environmental Engineering in Partial Fulfillment of the Requirements for the Degree of

Master of Science in Technology and Policy

and Master of Science in Civil and Environmental Engineering AR

February 2018

All rights reserved.

Signature of Author:

Certified by:

$ iCertified by:

December 8, 2017

James L Wescoat Jr Aga Khan Professor, Department of Architecture Department of Urban Studies and Planning

Thesis Supervisor

Accepted by:

//I

Dennis McLaughlin H.M King Bhumibol Professor of Water Resources Management Department of Civil and Environmental Engineering, Thesis Reader

Signature redacted

Munther Dahleh

William A Coolidge Professor, Electrical Engineering and Computer Science

Director, Institute for Data Systems and Society

Accepted by: _Signature redacted

Professor of Civil and Environmental Engineering

Chair, Graduate Program Committee

Thank you.

Some pages in the original document contain text that runs off the edge of the page.

p.93

Adapting a Hazards-Risk Model to Water Scarcity in Rural

India-Aurangabad Case Study

by

Paige MidstokkeSubmitted to the Institute for Data, Systems, and Society and the Department of Civil and

Environmental Engineering on December 8, 2017 in Partial Fulfillment of the Requirements for

the Degree of Master of Science in Technology and Policy and Master of Science in Civil and

Environmental Engineering

Abstract

The objective of this project is to improve the responsiveness of District Planning to rural waterscarcity in India Through engagements with the Groundwater Survey Development Agency, andMaharashtra State Government Water Supply and Sanitation Department, we selected

Aurangabad District to conduct field visits and develop a model that can spatially represent risk

of villages to water scarcity Within Aurangabad District, Vaijapur block was selected as a casestudy due to its drought effects and high water tanker usage in the past five years

This thesis develops a disaster risk metric for water scarcity, using an analysis of potential

hazards, socioeconomic vulnerability, and policy responses to assign a "disaster risk score" toeach village Risk is seen as a function of hazard, vulnerability, and government capacity, so allthree factors of risk are addressed Villages are assigned a risk score in Vaijapur block of

Aurangabad District By providing a risk score a season in advance of drought, planners are able

to select an alternative capacity measures rather than the quickest tanker option

The aim of this research is to assist district governments in Maharashtra state in predicting,between one season to two years in advance, the risk of villages to drinking water scarcity inorder to respond before incurring a drinking water crisis Secondly, this model is used to

prioritize infrastructure projects over the coming two years in order to best use limited financialresources to alleviate the burden of water scarcity at the village level This research could

ultimately be integrated into the existing state website for statewide planning and allocation ofresources

Thesis Supervisor: James L Wescoat Jr

Title: Aga Khan Professor of the Department of Architecture

2

This thesis is a product of months of fieldwork, and the hard work, financial support, and

mentorship of many people My departmental support at Civil and Environmental Engineering,

and my home department Technology and Policy Program were incredibly supportive of myacademic goals and thesis research Barbara DeLaBarre and Dr Kenneth Oye were particularlyhelpful in their advice on framing the problem, and incorporating the methods of policy andengineering into a single, cohesive thesis

I would like to thank my advisor, Dr James Wescoat, for introducing me to field research and

proper methods for conducting academic research with integrity You have provided guidancethat has allowed me to understand the depth of analysis required to understand a problem beforeattempting a solution Thank you for supporting my interests in drought research, in

incorporating environmental engineering, and in developing a proper framework This workcould also not have been possible without our community partners in India, including MurthyJonnalagadda, consultant to the World Bank in Mumbai Our partners in Aurangabad, includingthe Zilla Parishad and Groundwater Surveys Development Agency, were also incredibly helpful

in providing data, coordinating meetings and village visits, and providing expert guidance on thewater scarcity dynamics in the region

The MIT Tata Center, supported by the Tata Trust, provided financial and academic support without which this project could not be possible I would also like to thank Michael Bono and

Chintan Vaishnav for their advice on designing metrics for risk and the different forms of

sensors available to measure water levels I would like to thank Riddhi Shah for her exceptional

GIS mapping skills and her work on this project, including making a trip out to Aurangabad for

surveying the Zilla Parishad in Marathi

I would also like to thank Dennis McLaughlin for his guidance as my engineering thesis advisor,

and his mentorship for developing the system identification and PCA models.

Finally, I would like to thank my family and Jeremy Elster for their support in my research, my

travel, and my graduate education Their compassion and support allowed me to dive deeply into

my research, and to commit to developing myself as a hydrologist and policy analyst

3

1.2.1 Government Criteria for Drought and Water Scarcity 9

1.3 Literature review of Methods for Managing Water Scarcity in India 12

1.4.1 Gaps in Current Water Scarcity Planning and Management 20

4

2.6 Policy and Regulations for Water Scarcity 34

5

1 Results in R for Regression Model: Social Vulnerability 79

2 Images of 19 Variables in Social Vulnerability Index, Created by Riddhi Shah 80

Figure 4.1 Principle Component Results: Cumulative Variance Explained 93

Figure 4.2 The Scaling applied to each variable in PCA 94

Figure 4.3 Mapping of Cumulative Variance Explained by first 10 PCs 95

Figure 4.4 Mapping of Principal Component 1 and Principal Component 2 95

Figure 4.6 Distribution of Ten Principal Components and Summation 98

Figure 4.8 Map of Vulnerability Score: Principal Component Based 100

Figure 4.9 Percentage Variables in Second PCA Analysis 101

Figure 4.10 Variance Reduction in Second Principal Component Analysis 102

Figure 4.11 Map of PCA for Percentage Variables: 10 Principal Components Score 103

Figure 4.12 Map of PCA for Percentage Variables: 8 Principal Components Score 103

6 Reference Table of Risk Score and Components for 16 Observation Well Villages 106

7 Format for Water Security Plan Household Survey, provided by GSDA Aurangabad 107

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Chapter 1: Introduction

1.1 Problem Statement

Severe and sustained water scarcity, predominantly in the form of depleted rainfall, has limitedthe availability of groundwater resources, and thus drinking water, in Central Maharashtra.Aurangabad district, located in central Maharashtra, has a complex array of challenges in

managing water scarcity Aurangabad has a growing population, water-intensive industriesincluding soda and beer manufacturing, small farmers who rely on rainfall, and the district haslower rates of rainfall absorption to groundwater due to elevation changes and runoff

It is expected that regions with below average rainfall will have declining groundwater levels A

newer challenge for districts is managing areas that are receiving the expected amount of rainfallbut at a higher intensity for a shorter period of time, meaning there is higher runoff and lesswater is absorbed into the ground Additionally, there are variable rates of withdrawal which lead

to variation in regional groundwater depletion Below, Figure 1.1.1 shows pockets of

groundwater depletion throughout the district of Aurangabad, in part because below average

rainfall, (i.e > 10% less than average rainfall) is experienced in the south.

Figure 1.1.1 Groundwater Depletion in 2015 Compared to Last 5 Year Average

LI I I

The population of Aurangabad district, as of 2011 census, was 3,695,928 Of that population, 62.47% or 2,308,846 people live in rural villages (GOI, 2011) The high proportion of rural

communities makes water management extremely decentralized and challenging Aurangabad ispositioned in the arid Marathwada region of central India, and its district, along with surroundingdistricts, face difficult decisions in deciding which villages receive aid in times of drought, whattypes of aid they receive, and in anticipating rural village water needs In the current scarcityplanning process, money is set aside each year to be used in one of seven responses, and villagescan apply for assistance once they are receiving less than 40 liters per capita per day (LPCD) In

2016, for example, 80 tankers were sent on 2-3 trips per day for three months to villages, costing

the district over $3,000,000 USD (ZP Aurangabad, 2016) This is the most-costly of the seven

responses a district can make, but it requires the least amount of advanced planning or

anticipation

1.1.1 Problems Being Addressed

Of the vast challenges faced by a drought-prone arid rural region, there are three systemic

problems which should be addressed First, drought planning is currently reactionary rather thananticipatory; second, drought responses are spatially fragmented and thus inefficiently deployed,and third, drought planning is done in the short-term In order to improve resiliency in the

Maharashtra, it is crucial to address these three concerns

This thesis delves into the plans for how to make district planning proactive, increase

intervention efficiency by visualizing spatial patterns of risk, and design a tool for multi-year drought assessment by means of an adapted hazards risk model.

By improving our understanding of the risks and vulnerabilities rural villages face, the water

scarcity planning process can become more proactive and less reactionary, giving districts theability to respond with longer term solutions than the provision of tankers An integrated

regression model of groundwater prospect data, census data, rainfall data, and observation welldata is used to assign a hazard score to villages in specific monsoon scenarios, giving districtsinsight into which villages require intervention before the peak dry season This model of riskassessment will be incorporated into the planning process as a decision support tool that canprovide a ranking of water scarcity risks in the presence of different conditions, such as depletedrainfall

1.2 Defining Water Scarcity

Drought and water scarcity are often used interchangeably when discussing a depletion in thesupply of water to households, agriculture, or industry As this study is focused on the state ofMaharashtra, it is crucial to understand these terms as they exist in policy and practice in India aswell as specifically in Maharashtra

8

1.2.1 Government Criteria for Drought and Water Scarcity

The Indian Meteorological Department (IMD), a federal agency, has historically classified

drought as a rainfall deficiency which deviates from a long-term average Drought has beenclassified as normal if it deviates 25% or less from the long-term average, moderate drought if

50% or less, and severe drought if it deviates more than 50% from the long-term average (IMD,

2016) These classifications are typically given when a month, season, or year is atypical from

the historical long-term average for rainfall This understanding of drought does not considerhourly intensity of rainfall, groundwater absorption, or other forms of water scarcity such asincreased consumption Below is a map of rainfall variation in Aurangabad District, using IMDdata

Figure 1.2.1 The 2015 Isohyetal Map of Rainfall Variation in Aurangabad

ISOHYTAL MAP OF AURANGABAD

The Government of India has defined drinking water scarcity as an amount of liters per capitaper day received in the smallest administrative unit, the village Water Scarcity was a village

9

receiving less than forty liters per capita per day (LPCD), which increased to fifty-five LPCD in

2017.

Figure 1.2.2 District 2015 Water Scarcity Map - January to March

MAP SHOWING SCARCITY AREA - DISTRICT AURANGABAD

Jan to March 2015

Legend

TALUKA BOUNDARY Villages

In addition to agriculture and meteorological drought, it is commonly accepted that there are

socio-economic drought, hydrological drought, and ecological drought (UNL, 2016) While these

definitions for drought are defined at the national level, the state of Maharashtra is given theauthority to write policy for managing both drought and scarcity Currently, Maharashtra has

certain protections for groundwater when it is considered "overexploited" As defined by the

Groundwater Survey and Development Agency of Maharashtra, any watershed that is withdrawn

in a single year over 70% is considered overexploited This label triggers certain groundwater

withdrawal restrictions within the state, and also directs GSDA's attention to villages who rely

on groundwater from overexploited aquifers

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1.2.2 Broader Criteria for Water Scarcity

Seasonal drinking water scarcity in India is strictly defined as persons receiving less than 55

LPCD for drinking and living for a given season This standard was introduced in the 2012-2017

XII 5- year plan by the National Rural Drinking Water Programme (NRDWP) of India, in order

for a habitation or village to be considered "fully covered" (NRDWP, 2016) While LPCD is

measured annually, it often fluctuates during the year, giving rise to seasonal water scarcity.Seasonal water scarcity is seen as temporary, and has historically been alleviated when the

monsoon season arrives, but Aurangabad has experienced villages with as many as 9 months of water scarcity for up to 5 years in a row, a historic high for water scarcity magnitude and

longevity (AAP, 2015-16) For the purposes of this study, it is important to add complexity to

this definition to ensure that we understand the root causes and risk of water scarcity WaterScarcity will be defined as the deficiency of drinking water supplies leading to a lack of waterfor normal and specific needs, leading to health risks, diminished livelihoods and socioeconomic

vulnerability (UNL, 2016) Rainfall may remain unchanged, but water scarcity may occur in groundwater, surface water, or elsewhere as it is the supply of water that is insufficient to meet

demand

The ultimate goal of this study is to consider not only rainfall, but other causes of water scarcity,

and factors which lead a Gram Panchayat vulnerable to water scarcity By having a broader

understanding of the causes of water scarcity, one can foresee regional vulnerabilities in advance

of a crisis This is particularly useful for government responses and interventions

1.2.3 Intersection of Drought and Water Scarcity

We have discussed four of the five types of drought: (1) meteorological being the most referred

to, then (2) hydrologic, (3) agricultural drought, (4) socio-economic, and (5) ecological drought.

These types of drought are seen as forms of a diminished water supply, and all are forms of

water scarcity Water Scarcity can also occur without the supply being diminished by

environmental factors or drought Ecological drought, while outside the scope of this research,addresses the impacts of drought on multiple ecosystems such forests, vegetation, and livestock

(USGS, 2016) Ecological drought is a crucial element in considering the impacts of drought on

the environment and on farmers or irrigated land

This study looks at Water Scarcity under agricultural, socio-economic and hydrologic droughtconditions, meaning there is a diminished water supply Consumption patterns at the individual

household are relatively low, with the highest rural households consuming around 100 LPCD and peri-urban consuming around 135 LPCD (AAP, 2014-15) The government standard for

urban is 135, the standard for peri-urban is 70 LPCD, and the rural standard is now 55 LPCD

(GOI, 2017) For most rural households, consumption rates are much closer to 40-55 LPCD,

11

meaning policy targeting a decrease in household consumption would greatly affect livelihoods.The experience of Water Scarcity in times of hydrological and meteorological drought, meaningsubsurface and surface water supplies are insufficient for normal household activities is lifethreatening This form of water scarcity will be identified, and Gram Panchayats' vulnerability tothis form of water scarcity will be visually displayed for district governments to make policydecisions.

Figure 1.2.2 Groundwater Depletion Heat Map of Aurangabad District comparing 2015 levels to average of the previous 5 year levels

>3 M Depletion

Source: GSDA Aurangabad, 2015

Methods for understanding the impacts, effects, and causes of drought have evolved over time inboth academic and political fields It is important to assess this evolving notion of drought, andthe related fields of natural hazards and risk, in order to assess the best way to incorporate datainto anticipating risk of drought for villages in India

1.3 Literature review of Methods for Managing Water Scarcity in India

Issues pertaining to the management of water supply and demand in India have been documentedfor centuries In order to understand the historical context for water scarcity in Rural India, wefirst examine the historical distinction between drought and scarcity to understand their

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differences This literature review also outlines the array of modeling methods for basaltic

fractured watersheds, as it defines the geomorphologic challenge and will provide insight intomethods used to understand groundwater fluctuations Finally, the literature review will

reference the current field of water scarcity planning as the starting point for this research

1.3.1 Literature Review Abstract

My research entails the development of a water scarcity decision support tool for the state of

Maharashtra to identify Gram Panchayats (multi-village administrative units) most vulnerable towater scarcity In order to develop such a tool, it is crucial to first explore the concepts of waterscarcity and drought to best understand how the notion of each term shapes the reasons for itsperpetuation For India, a long history of farming has made water for irrigation a central focus inthe livelihood of the nation, but now even drinking water and industrial water face scarcity Thisreview addresses literature on the history of drought and water scarcity in India, as well as the

history of how to measure, model, predict and remediate water scarcity A mixture of academic

articles, government literature, books, and doctoral theses are referenced in order to develop arobust catalog of water scarcity resources

1.3.2 Historical Water Scarcity

The notion of water scarcity and drought has evolved over history and geographic boundaries InIndia, drought becomes well documented in the early 1 9 th century as the cause of famine, and

drought management was defined in terms of famine relief (Arnold, 1993) Famine relief came

most commonly in the forms of irrigation works, where the baseline goal was for every farmer toreceive enough water for their crops so that communities had enough food to subsist (Arnold,

1993) This form of drought management is now called "deficit irrigation"- irrigation which

provides enough water for crops to survive, but no more This led to lower crop yields in India,

as the goal of drought management was to provide farmer subsistence (Burgher) These survivalgoals for drought management were prevalent during British colonial rule, when farmland wasvast and there was opportunity for higher revenues with higher crop yields Drought managementbecame drought mitigation, as the British diverted more surface water flows to irrigation toensure a cash flow from Indian exports such as shampoo and cotton (Peckham) The concept ofdrinking water scarcity brought with it health implications in 1 9 th century India, as the British

sought to curb contagion of disease by encouraging social hygiene, which involved regular

bathing and handwashing (Peckham)

Since Indian independence, the Indian Meteorological Department (IMD) has defined drought aswhen annual rainfall for a region falls below 75% of expected rainfall IMD has historicallycategorized drought into three categories, hydrological drought, meteorological drought, andagricultural drought Their monsoon forecasts predict rainfall deficits and declare "drought

years" in the three drought categories In January 2016, India Meteorological Department

13

decided to replace the nomenclature of drought with "more precise" language (Vasudeva, 2016) Instead, the word drought is now being replaced by "deficit".

The Groundwater Survey Development Agency (GSDA), operating in Pune, Maharashtra,

operates as a state-level agency and measures water scarcity based on the percentage of

groundwater withdrawn from a watershed or aquifer GSDA deems a watershed "overexploited" when a community extracts 70% or more of its watershed in a given year, leading to longer-term depletion issues and dropping of the water table (GSDA, 2015) The term "overexploited" is used to indicate extreme groundwater scarcity While the GSDA does not govern surface waters

or canals, it does work closely with drinking water municipalities as groundwater is the dominantsource for drinking water in Rural Maharashtra

The Government of India defines water scarcity in India for households as a function of waterreceived Any household receiving less than 40 liters per capita per day (LPCD) is experiencing

water scarcity The State Government of India has a new target of 55 LPCD by 2017 for rural India, meaning a home is water scarce in 2017 if each person has access to less than 55 LPCD (NRDWP, 2015).

Water Scarcity in Maharashtra is currently attributed to a lack of rainfall catchment and

groundwater availability in basins across the state, as described by engineer and Maharashtrian water storage expert, M.M Dighe (2003) Dighe attributes scarcity to the increasing population

and increasing demand for water in rural Maharashtra, accounting for the numerous bore wellscompeting for, and depleting, the water table Dighe's water scarcity entails a lack of sufficient

drinking water for households to live comfortably on a daily basis, and it is threatened by a lack

of dams, groundwater recharge, and overall catchment of the sporadic rainfall Maharashtra

receives Water Scarcity has evolved to become something that is understood based off its

categorization, causing it to be fragmented into more and more types of categories from

hydrological to socioeconomic and meteorological Similarly, the field of hydrology is

continuing to expand drought and water scarcity to a problem of not only precipitation changes,but also human demands and climate change as culprits and social vulnerability as a side effect.These changes in academic understanding of water scarcity shape the conceptual frameworkthrough which one addresses scarcity

1.3.3 Water Scarcity Frameworks

Now that we have addressed the evolving historical notions of water scarcity, we are able todefine conceptual frameworks for thinking about and categorizing water scarcity Timing isimportant in the creation of a conceptual framework for water scarcity In India, drinking water

scarcity is deemed as receiving less than 40 LPCD (NRDWP, 2015) regardless of for how long,

although government intervention usually requires an expectation of three months of future waterscarcity

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To provide contrast, water scarcity in the United States is not deemed severe unless it persists

more than two years, whereas drought that spans 6 months or more in India is seen as severe From 1855-63, the West Coast of the United States experienced extreme prolonged drought due

to La Nina, the counterpart to El Niio, where sea temperatures drop and trade winds are

incredibly harsh in the Pacific (Cole) In this time, and even now, U.S drought lasting more than

2 years is regarded as prolonged and intense (Cole) The El Niflo and La Nifia were seen as

cyclical, causing water scarcity and drought in the Pacific to be viewed as cyclical changes(Cole) In India, the annual monsoon season is seen as the cyclical 'reversal' of water scarcity

Sinha in a survey of 900 years of monsoon precipitation shows the increased variability in total

accumulated precipitation each year and variability in the intensity of rainfall in order to show

that sustained drought is likely to become a more common occurrence (Sinha 2007).

With a fixed amount of rainfall, conceptual frameworks have shifted to understanding not onlythe supply, but ways to model and curb demand for industrial, household, and agricultural wateruse Malin Falkenmark is a leading expert on not only the effects of human demand on scarcity,but the concentrated negative effects on low-income, rural and minority populations Falkenmarkclaims that water scarcity is the key strain on water security, and thus on socioeconomic

development (Falkenmark, 1997) Falkenmark, along with colleagues, addresses the concept of demand-driven water scarcity, how it can be measured by use-to-availability, and postulates the proper reserve amounts as a percentage of total water supply (Falkenmark and Lindh, 1976).

Demand-driven water scarcity was coined as "water stress" in 2011 to identify the human andnon-human consumption of water as a stress on the overall water system (Kummu and Varis,

2011) The United Nations formally set the mark for high water stress as 40% withdrawal in a

"Comprehensive Assessment of the Freshwater Resources of the World" (UN, 1997), but this

has been expanded by Falkenmark in developing nations to 70% withdrawal as the point of

overexploitation, where a basin should be closed until recharge has occurred (Falkenmark,

2003).

Within drinking water scarcity, it is broadly accepted that there are two forms: demand-driven

water scarcity and population/supply driven water scarcity (Lankford, 2013) Supply driven

water scarcity is the result of a lack of sufficient water, including rainfall, surface water,

groundwater, and treated oceanic water

The University of Nebraska, Lincoln provides detailed conceptual frameworks for water scarcityand drought through their Institute of Agriculture and Natural Resources This institution, whichspecializes in drought studies, identifies that drought is a "deficiency of rainfall over an

extended period of time, generally at least one season", where the meaning of deficiency varies

widely by geography Donald A Wilhite provides a method for differentiating drought from

other water crises such as scarcity through a conceptual framework (Wilhite, 2005), while A.F.

Loon uses observation-modeling to distinguish drought from water scarcity (Loon, 2013).

15

The Government of India's Ministry of Water Resources establishes three categories of drought,each measured differently The Government of India concretely measures and defines

meteorological, hydrological, and agricultural drought (Ministry of Water Resources, 2013).

These definitions are used to classify a village or administrative unit in India as 'water scarce',which in turn signals government remediation processes

1.3.4 Water Scarcity Indices

There are water scarcity and drought indicators or indices, used to identify the relative risk orvulnerability of a region, watershed, or community to an imbalance in water access The WaterPoverty Index is a new, holistic look at the aggregate of many indices and is designed for

identifying the vulnerability of a community to risk by aggregating watershed, country, and

regional indices (Sullivan, 2002)

The Palmer Drought Severity Index and Crop Moisture Index were the leading indices for

drought measures in the 1950's-2000's Both gave a relative measure of moistness based ontemperature and precipitation to estimate the amount of evaporation or evapotranspiration, and

were best suited for those reliant on irrigation or groundwater (Palmer, 1965) The Standard

Precipitation Index, a less complex index to calculate, was developed in 1993 as an alternative to

the Palmer Index to measure the standard deviations away from mean precipitation in a regionand provides early warning of drought (NASA.gov)

1.3.5 Impacts on the Rural

Drought impacts on rural communities, particularly in India, differ widely from drought impacts

on the urban The University of Yamanashi, Japan explored the impacts drought have on

Maharashtra, a state with a large rural and farming population and a state that produces 15% of

India's gross domestic product (Ichikawa et al, 2014) This study found that the depletion ofwater resources in rural Maharashtra had high impacts on agriculture and food security for thestate as a whole They point out that the 2012 drought in India caused the nation's gross domestic

product to decrease by 0.5% The study also shows the varying degree of water quality among

private water tankers, and the cumbersome process involved with retrieving water out of a

depleted well

There are also large questions of livelihood and gender inequality during rural drought in India,

addressed by Krishna in an exploration of community resource management (Krishna, 2004).

Krishna addresses the dangers of women retrieving water late at night, the inability to attendschool, and how rural industries rely more heavily on water, and thus does their livelihood

drought iessons over time, in a study by Dr Gopalakrishnan in order to illustrate that poverty and environmental degradation are likely effects of drought (1993).

International studies on rural drought in arid regions on impacts of the family, the farm, genderequity, education, and livelihoods are found on Tanzania (Krishna, 2004), Nepal (Merz et al,

2003), Australia (Bettini et al, 2013), Brazil (Garcia-Torres et al, 2003), and Canada (Sanyal,

2015).

1.3.6 Modeling Scarcity in India

There are a variety of hydrological modeling methods relevant to water scarcity, as well as somemore general climatic, natural disaster related modeling and general vulnerability modelingmethods Although it deals with geohazards, a relevant survey of modeling techniques includesPradham's "Terrigenous Mass Movements", which explores methods for modeling and mappingvulnerability to natural disaster These methods include risk mapping, "data modeling,

topography, geology, geomorphology, remote sensing, artificial neural networks, binomialregression, fuzzy logic, spatial statistics and analysis, and scientific visualization" (Pradham et

al, 2012)

Remote sensing of bore wells has become a successful way to monitor water levels and water

management, though it has limitations in hardrock terrain (Rao, 2003) Remote sensing has also

been found effective for measuring evapotranspiration of crops, and is well suited for rural, aridIndia, as was found in a 2001 study (Srinivas 2001) Remote sensing data have also been

successfully incorporated into GIS for mapping of water resources by the International

Astronautical Congress (Jeyaram et al, 2006).

Demand modeling of water using non-spatial modeling, such as system dynamics modeling, has

been demonstrated by the Massachusetts Institute of Technology in a 2011 study on Singapore (Welling, 2011) Methods for multi-variable econometric regression for water demand and prediction based on population and environmental factors are analyzed by the Institute for Water Management in Dresden, Germany (Koegst et al, 2008).

Maharashtra faces unique challenges in modeling its groundwater due to the nature of basaltic

fractured hard rock A notable study on the formation of basaltic aquifers in India was conducted

to address the complexities of the structures to be modeled Measuring potentialities for

groundwater in basaltic hardrock in India is a method that allows for error and interquartileranges Kriging, a geostatistical method used in the Oil and Gas industry is also used in somegroundwater models when one can assume uniformity of the soil or rock underneath the surface

(Khan et al, 2016) An alternative method for randomizing water levels across an unmapped

aquifer is Monte Carlo simulation, which requires large amounts of data for the strata types and

depths below all observation wells (Khan et al, 2016) The most commonly used method today

for modeling groundwater in hard rock is still the pumping test, which is an empirical method

17

that requires pumping all of the water out of an irrigation well and measuring recovery rates(Shah, 2012).

Service delivery models for drinking water in India are analyzed in a study by the Naandi

Foundation (Kumar et al, 2014) Modeling monsoon rainfall variability using national Indiandata has been completed in a 2014 study (Ranade et al, 2014) Drought characterization,

modeling future predictions of drought, and modeling change and down-scaling are all addressed

in a 2015 study of international drought modeling and mitigation (Senaut, 2015).

1.3.7 The Modem Field of Planning: Drought and Scarcity

In March 2016, U.S President Obama released a Federal Action Plan for Long Term Drought

Resilience, which included a memorandum, action plans, progress reports, and a tracking of

actions taken' The US Bureau of Reclamation is offering WaterSMART grants for funding

small, on the ground projects as well as large scale energy efficient and water conservationprojects and planning improvements for drought2 This shift towards increased research in the

drought planning field has been gradual, as can be seen in Figure 1.3.7.1, showing the number of English-written books referencing Drought Planning, peaking in 1990 and again after 2008.

Figure 1.3.7.1 Drought Planning references in English books

(cM n hNi1sifar fOcus 9&ftPWaodfoaactcw=8%*N*)

Source: Google Ngram Viewer, 2017

This trend helps to narrow the scope of drought planning to its relative inception in the 1970's,

its peak in the 1990's, and the current field as it stood in the 2008 time frame.

We are seeing the most data-intensive forms of drought planning research in academic

dissertations and theses, with modeling, prediction, and decision support systems designed, such

I https://www.whitehouse.gov/campaign/drought-in-america

2 http://www.usbr.gov/watersmart/grants.html

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as a recent Texas A&M dissertation that integrates risk, two new multivariate indices, and a

decision support tool (Deepthi, 2014)

The University of Nebraska, Lincoln has a leading center on drought planning (UNL, 2016).

The current framework for rural drought planning in the United States consists of a balance sheetwhere supply and demand are calculated, with water quality compromised supplies are

subtracted from the total supply A target is set for the amount of water in reserves, and when

supply falls below a certain level actions are triggered

The current framework for water scarcity in India consists of a bottom-up "signal" for scarcity,and then a top-down response Water scarcity is experienced at the village level, paperwork issubmitted to a Block Development Officer (BDO), and then either the BDO or District

determines the type of response, if any, to be provided to the village This process is timely anddoes not provide Districts any insight to plan for future water scarcity The process is designedfor rural villages who receive less than 40 LPCD, for which it receives applicants during threequarters of the year Applications are not received during monsoon season The governmentenlists one of seven approved responses to remediate the drinking water, ranging from short tolong-term solutions and vary in cost The policy responses are listed in the table below

Figure 1.3.27.2 Policy Responses to Water Scarcity Applications in Maharashtra

1 Provide Shallow Trenches in Riverbed

2 Deepening and Desilting of Wells

3 Acquisition of Private Wells

4 Providing Water by Tanker/Bullock Cart

5 Special Repairs of Piped Water Supply Schemes

6 Provide a Tubewell

7 Provide Temporary Piped Water Supply

IIT Bombay, IIT Roorkee and a variety of other institutions in Maharashtra, Gujarat, and

Uttarakhand India have produced sophisticated research on predictive techniques for watermanagement, aquifer mapping, applications of sensor technology to water supply estimation ofsurface and groundwater, and techniques for curbing agricultural and household consumption ofwater in villages There is a lack of integration of socio-economic vulnerability with

hydrogeological vulnerability

1.3.8 Literature Review Conclusion

This literature review provides historical context for water scarcity research in India, as well asthe general shift in the field of water management to conceptualize, model, and respond to waterscarcity While the concept of water scarcity is not new to rural Maharashtra, a region heavily

19

reliant on irrigation, we are entering a new era of sustained drought that current literature doesnot adequately address The policy and practical responses to higher severity drought and longer-term water scarcity require a multi-year planning process and a new suite of planned responses.

In Maharashtra, the water scheme investment plans, called "Annual Action Plans" occur on anannual basis, and serve as systematic planning processes for water scheme construction andalteration in rural Maharashtra These plans are not compared year to year, and long-term

solutions are often unable to be reached due to the need for quick solutions to drinking waterscarcity While water tanker use is widely discouraged as a long-term fix, government fundinglimits the response to scarcity-prone villages to one action at a time This means, provide atanker for instant relief and assume the monsoon season will relieve this need, or construct ormend sources for water withdrawal

Water scarcity, in the form of depleted rainfall, or scarcity due to water stress is increasinglyhard to predict as rural Maharashtra is covered in publically dug wells, as well as non-sanctionedprivately dug wells for human consumption and irrigation The lack of proper community

management at the aquifer and sub-basin levels often leads to a scurry in newly prolonged dryseasons for groundwater

This research on water scarcity planning in Aurangabad will augment existing practices formanagement of a scarce resource for drinking water, while introducing new concepts regardingthe modeling of vulnerability to water scarcity, and the suite of policy responses available toeach block (Taluka) There is a striking parallel between natural disaster modeling and droughtmodeling, making it a natural connection to design a drought model with the existing naturaldisaster modeling methods already established

1.4 Research Questions and Objectives

The primary research question is how can the district planning process for water scarcity beimproved with a numeric model to identify drought risk? This research question is further broken

down into two lines of thinking: how can the data being collected by the district and state

agencies be used to anticipate future drought risks, and how can data models be integrated intothe current planning process

The objectives of this research are to make the planning process more proactive, to understandhow a variety of factors, including rainfall, affect groundwater levels, and to provide a decisionsupport tool that can be used for scenario-based modeling of Gram Panchayats groundwaterlevels

1.4.1 Gaps in Current Water Scarcity Planning and Management

As is referenced in the Literature Review, there is a lack of sophisticated data integration incurrent water scarcity frameworks as it can be cumbersome and up-front costs are high Muchemphasis is put on predicting rainfall, but not on how that variability disproportionately affects

20

Gram Panchayats There is also a lack of conjunctive groundwater and surface water

management, as in India different state agencies control the two sources of water, politicizing thepossibility of conjunctive management

1.4.2 Connection of Data Sources to Planning Process

The District Governments of Pune and Aurangabad, as well as the Groundwater Survey andDevelopment Agency of Maharashtra have expressed an interest in using their existing datasources to the planning process Our partnership began with a statistical analysis of AnnualAction Plan data from 2014-2015 to notice trends in the types of projects, forms of scarcity, andcharacteristics of villages being selected for water scarcity remediation measures These data,along with Groundwater Prospect Map data, a century of rainfall data, Observation Well data,

the Integrated Management Information System (IMIS) repository, and Government of India

Census data from 2011 have been cleaned, combined, and analyzed for trends, relationships andstatistical significance in advance of the model creation This process was done as an initial step

to understand how projects have been selected, and the types, timing and recurrence of waterscarcity in Aurangabad District as well as Pune District Initial reports were presented in person

in Maharashtra in January 2015 and August 2016 to ensure applicability of research and

feasibility of integration with existing planning processes

1.4.3 Expanding the Range of Choice

Aurangabad district is aware of the sustained drought and the changing nature of monsoon

seasons Their fractured basaltic hardrock makes it difficult for geologists and hydrologists topredict exactly where water sits and where rainfall recharges the land without aquifer maps,

which are being mandated by the federal government but have not been completed in

Aurangabad Many regions of Aurangabad experience water scarcity at some point in the span of

a calendar year, but the timing, cause and severity have become seemingly unpredictable

By developing a model to help assess the risk of groundwater scarcity in Gram Panchayats,

districts are able to react to the problem earlier, and possibly differently than if they had less time

to react This expands the range of choices and policy responses a district can employ The latescientist, hydrologist and professor Gilbert F.White studied how in disaster preparedness andresponse planning, when a government can consider the full range of choices they are less bias to

pick one over another (White, 1986) Ultimately, this would improve the management process of water scarcity planning in India by limiting a bias towards the quickest solution.

1.4.4 Summary of Research

Chapters two through four will outline the conditions of our study's location , how the risk scorewas calculated, and how the results of this research could be introduced to the existing annual

21

District Water Security Plan Methods tried but not ultimately used for the risk score are located

in the appendix

Chapter 2: Aurangabad District Case Study

The federal government, referred to as the Government of India (GOI), mandates general rules

such as national limitations on well-depths (60 meters) and minimums for drinking water (55

LPCD by 2017), but it recognizes that states develop regulations for consumption and

distribution of groundwater and surface water (GOI, 2011) Indian States govern most aspects of

water, including drinking water and irrigation water This allows for tailored policies to distinctgeographies, but also creates challenges regarding coordination of interstate rivers, canals andwatersheds The state of Maharashtra, shown in Figure 2.0.1, spans the coastline, desert, andmountains adding many layers of complexity to state-level water management

Figure 2.0.1 Maharashtra State Highlighted in India Map

Source: GSDA Mumbai, 2017

The state of Maharashtra is the focal point of this research project The following is a briefexplanation of the social and environmental landscape of the state Maharashtra is a state withextremely high literacy rates relative to the country, and home to two large cities; Mumbai and

Pune In terms of area, the state is predominantly agrarian, and is comprised of 70% basaltic

hardrock and associated black cotton soils The state has 114,200,000 people according to the

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2011 national census, and its cities and peri-urban regions are expected to increase in population

(Hui, 2017).

Figure 2.0.2 Divisions of Maharashtra State

Source: Google Images, 2017

Figure 2.0.2 displays the six divisions of Maharashtra state, which each contain four to eightdistricts Maharashtra on its west side is home to the Konkan Division, known for high rainfall,lush terrain, and high salinity coastal soil due to its proximity to the ocean On one field visit to a

village in Raigad District, I sampled a glass of water collected from a rice field with a TDS of over 3000 This brackish water limits groundwater utilization, forcing rural communities to rely

heavily on the vast rainfall during monsoon seasons to carry them through the year Their soil isbest for rice and coconut crops While water scarcity is not an issue, storage capacity of rainfalland water quality are threats to their drinking water supply

The central part of Maharashtra state, the Aurangabad Division, is home to the Godavari basin,named after the Godavari river This area is a part of the Marathwada region, an arid to semi-aridregion with low rainfall in monsoon season and limited surface water Eight districts withinMaharashtra state rest within the Marathwada region, one of which is Aurangabad district Theentire Marathwada region is known for its proclivity to drought Aurangabad is the regionalheadquarters and will be the case study for this research

The varying geography and climate of Maharashtra state, as is seen in the contrast between theKonkan and Aurangabad divisions, makes water planning at the state level challenging This hasled the State of Maharashtra to empower its district governments to shape planning practices andstandards that encourage financial and water sustainability under the conditions unique to their

regions This study intends to enhance the existing planning practices at the district level by

identifying regional risk to drought and regional socio-economic vulnerabilities

Figure 2.0.3 Aurangabad District

Phulambri

Paithan

Source: GSDA Aurangabad, 2016

Aurangabad district, as seen in Figure 2.0.3, is comprised of nine blocks The district is the

headquarters for the Aurangabad Division of Maharashtra State, governing the arid and semi-aridMarathwada region Aurangabad District has a history of water innovation, with some structuresstill in operation from the 1600s

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Figure 2.0.4 Vaijapur Block with Drainage Points in Green

Source: Paige Midstokke, 2017 with GSDA data

A Block Development Officer (BDO) governs a block, also referred to as a "tehsil" or "taluka".

The BDO receives requests from villages and makes preliminary decisions or final decisions in

emergency situations, before the District government reviews these requests All Block

Development Officers are appointed for a set period, and their primary role is to oversee theGram Panchayats in their blocks and to communicate between Panchayats and the District When

a village requests assistance due to water shortages, Block Development Officers review the

completeness of the Village or Panchayat application before it is seen by the District, or if an

emergency, approve tankers to be sent directly to the requesting community

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2.0.5 Heat Map of LPCD in Vaijapur District

Source: Riddhi Shah, 2017

Figure 2.0.5 Displays the pattern of LPCD ranges across Vaijapur Block One can see that there

are 3-5 village clusters with red, or extremely low, LPCD meaning government mitigations could

occur at the cluster level rather than village level While Vaijapur has many high scarcity

villages, noted in red as less than 20 liters per capita per day, the district of Aurangabad has along history of managing low rainfall with high irrigation demand on water

2.1 Historical Water Context and Landscape

Aurangabad district has a history rich in water systems, as well as the famous Daulatabad Fort,

Bibi Ka Maqbara - a tomb made in the likes of the Taj Mahal Panchakki, and the Ajanta and

Ellora Caves Panchakki, a water mill, was built circa 1695 A.D and remains functional in

Aurangabad city This mill sits in front of a mosque with an oblong reservoir, and uses energyfrom a spring to run the flour mill This flour mill was used to serve visitors, pilgrims, and later

to feed an orphanage Water is fed to Panchakki from a well eight kilometers away, through anunderground conduit There water falls into the Panchakki cistern producing enough energy toturn the mill Prior to Panchakki, Aurangabad had a sophisticated water delivery system with its

26

earliest aqueduct built in 1612 upon the discovery of groundwater at the foot of mountains north

of Aurangabad city There has historically been a shortage of reservoirs, surface water, and rain

in Aurangabad making it necessary to deliver water from elsewhere This aqueduct served as the

basis of the Nahr (conduit) water system and supported a population of approximately 700,000 people By 1803, two more aqueducts were built by to support the increase in population and

water demand

As Aurangabad city's administrative boundaries expanded to Aurangabad district, covering over

10,000 square kilometers of land, the district continued to face challenges supplying sufficient

drinking water and irrigation water Observation wells are constructed to monitor the quality andquantity of groundwater as it is the primary source of drinking water for rural district residents.There are currently 141 observation wells in Aurangabad District, with the intent of expanding to

714 observation wells for their district's Groundwater Prospect Map by 2020 District officials select wells by mapping the district and marking the varying terrain Wells are selected across

the district to ensure that a variety of terrain and all varying climates within the district are

monitored GSDA, with the guidelines of the Ministry of Drinking Water and Sanitation's Rajiv

Gandhi National Drinking Water Mission Project, selects wells based on construction-type, with

priority given to bore wells as seen in Figure 2.1.1 below.

Figure 2.1.1 Preference of Well Selection for Observation by Ministry of Drinking Water and

Sanitation

Priority Number Well Type

1 Irrigation Bore/Tube Well

Vaijapur Tehsil has three observation wells, housing over 100 villages and 41,296 people

(Census, 2011) Vaijapur sits 514 meters above sea level, and is known as the "Gateway to Marathwada" for its 1 8 th century war-torn history under the Moghul Empire, followed by the

Marathas Vaijapur district has a rail connection with both Mumbai and Hyderabad, positioningitself to be a region of growth for those wishing to reside in the rural countryside and travel orwork in a metropolitan city Even with its connectivity to nearby cities, it remains an agriculturedominant tehsil

The Narangi River flows through Vaijapur district, with a Narangi-Vaijapur dam located

northwest of Vaijapur city This dam contains the Vaijapur reservoir, a reservoir used

exclusively for irrigation It was completed in 1998 and has a live storage capacity of 11.5

million cubic meters (India WRIS)

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2.2 Existing Planning Practices

District Governments within Maharashtra State deploy existing annual drinking water planningprocedures to budget for the upcoming year This process involves gathering quantitative data;but no goal setting, qualitative measurements, or multi-year objectives Planning for water isbased around the monsoon season, assuming that the post-monsoon season will require no watertankers or shortages due to the heavy rainfall accumulation

Planning practices include assessing a financial budget and selecting villages that will receiveassistance due to issues of water quality, failures of piped water supply schemes, or inability toreceive 55 LPCD from current water scheme(s) Some of these villages are identified by Block Development Officers, some self-nominate, and some are selected by District officials The

selection process for these villages into the Annual Action Plan for water varies between districts

in Maharashtra In some cases, it is desirable to select "low-hanging fruit" villages who are close

to 55 LPCD in order to report to the state a high success rate in village interventions In other

cases, districts choose to assist the most vulnerable and lowest LPCD receiving villages

Figure 2.2.1 Variables collected

Aurangabad District

on Villages selected for the District Annual Action Plan in

Column AAP Variables

36 Present Stage Scheme

37 Expected Month Completion

38 Excepted Year Completion

39 Implementing Agency

40 Proposed Subworks

41 Total Est Cost

42 GOI Share Cost

43 GOM Share Cost

44 Project Population

45 Number of Habitations in Scheme

46 Per Capita Cost

47 Funds Released to ZP

48 Gen Govt Fund Required

49 SC Govt Fund Required

50 ST Gov Fund Required

51 Total Govt Fund Required

Reasons of slipped back

( 1 Population migration,

2 Drying of source,

3 Water Quality affected, (The lab test

report should have to be got uploaded on

67 Approved by Collection Peri Urban

68 Present LPCD Peri Urban

69 Proposed LPCD Peri Urban

70 Scarcity Measures Taken

71 Cost for Scarcity Measures

72 Habitation in Directory?

73 DPR Prepared by GOI Guidelines

74 SC WQ Habitation Funds

75 ST WQ Habitation Funds

76 Gen WQ Hab Funds

77 Total WQ Hab Funds

78 GSDA Recommendation Taken

79 New Habitation Spillover

Figure 2.2.1 depicts the variables gathered and tracked within a single year for all villages in theAurangabad Annual Action Plan The Annual Action Plan consists of the villages selected forsome form of infrastructure assistance to improve their village or multi-village level water

scheme The Annual Action Plan tracks finances, water needs, socioeconomic data, and otherinformation listed in Figure 2.2.1 in order to keep track of their yearly projects

Each district submits its plan to the state, but these annual action plans are not combined or

analyzed at the state level Formatting of plans varies slightly by state, making combining reports

tedious, and state governments do not currently have personnel to analyze water infrastructureprojects across districts, or across years for a single district It is compelling for district

governments to use their historical data to make projections about future water planning

decisions to anticipate funding requests from the state

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2.3 Climatological Conditions

Aurangabad District, and thus Vaijapur Tehsil, reside within the semi-arid Marathwada Region

of India Climate is particularly dry outside of monsoon season, with an annual mean

temperature ranging from 17 to 33 degrees celsius, depending upon time of day and year The

climate of Vaijapur is a part of the steppe zone, as precipitation is anticipated to be slightly lessthan evapotranspiration annually As a steppe climate, Aurangabad receives slightly more rainthan a desert, but it is received in high intensity during the monsoon season, in some casesincreasing runoff and limiting recharge

2.3.1 Reported Rainfall (mm) for Aurangabad District from 1990 - 2015, source India

Source: Paige Midstokke, 2017

Figure 2.3.1 depicts the rainfall from 1990-2015 in Aurangabad, calculated as an average of four sites measured daily within Aurangabad district Rainfall for the district averages 710 mm annually, 595 mm or 83.8% of which are received during the monsoon season of June, July, August and September Using the total district average for rainfall from 2011-2016, Vaijapur district received 12.1% more rainfall than Aurangabad district with an average of 735 mm

compared with the district five year average of 634 mm

2.4 Hydrologic and Geologic Conditions

Aurangabad District is a part of the Deccan trap, a region entirely covered by basaltic lava This

lava is now fractured basaltic hard rock The typical strata consists of a vesicular basalt in upper

31

I

WA

&i

layers and massive basalt in lower layers This heterogeneous geology has made modelinggroundwater flow challenging, and aquifer mapping incredibly important In the absence ofdistrict wide aquifer maps in Aurangabad, the Groundwater Survey Development Agency useshydrographs and watershed delineations to estimate groundwater recharge and flow.

Figure 2.4.1 Hydrograph of Dahegaon Observation Well, Aurangabad District

PIAMoft on VMter La&W 7*W: Y z -0.00OMIX + 12.14t01

Source: Paige Midstokke, 2016 with GSDA data

Figure 2.4.2 Hydrograph of Kinhala Observation Well, Aurangabad District

E

I

I I

700 500 500 400

100

I ='ft*MirLvITrend W - - PouMortrLvfTrend

PRMonmoon biber i&W Tend: Y --0 01WE2X + 7.W7370

Post hAnmon Mbior ia w 7,,nd: Y --0.08M707X + 5 033

Source: Paige Midstokke, 2017 with GSDA data

Figure 2.4.1 and 2.4.2 provide two hydrographs for Gangapur block observation wells in

Aurangabad district These graphs show a strong correlation between groundwater levels andrain, but it is important to note that factors such as groundwater withdrawals, population fluxes,recharge zones, irrigation, and terrain elevation affect water levels as well

The fractures in the rock make the rocks productive for groundwater storage, but the decrease inthe number of days of rainfall and increase in runoff from high intensity rainfall have caused ashorter supply for infiltration into the groundwater supply

Figure 2.4.3 Vaijapur District map of irrigation (blue dots) and drainage (green lines)

Source: Paige Midstokke, 2017 with GSDA data

The figure of Vaijapur block above highlights major irrigated areas in purple Irrigation areasare seen in the south and eastern borders of the district, bordering Gangapur block in AurangabadDistrict to the east and Ahmednagar District to the south Green lines denote drainage networksand blue dots indicate village settlements Drainage networks are predominantly dendritic

33

Fractured basalt can have a porosity of 0.05, less than sand, to 0.50, greater than clay, making

drainage maps crucial for understanding the porosity of Vaijapur's geology (ANL, 2017).

The above figure also depicts, in green, the paths for drainage Vaijapur block consists

geomorphologically of a set of plains, with a set of low lying hills in the upper west corner TheGodavari river has tributaries which pass through Vaijapur block, providing some irrigationwater, a dam, and opportunities for some local groundwater recharge Vaijapur's soil is

composed primarily of black cotton soil, which is characteristic of the Deccan Trap basaltichardrock There is a string of softer rock across the southern edge of Vaijapur, where a large dam

is located

2.5 Socio-Economic Conditions

Aurangabad City, known as the "City of Gates" was founded in 1610 and has historic Muslim

architecture with a strong Muslim and Hindu presence While Aurangabad City has over onemillion residents and is the 5 th largest city in Maharashtra state, it remains somewhat rural withlivestock wandering freely and many unpaved roads Aurangabad district, which has primarilyrural villages, has two dominant ethnic groups: Marathi and Hyderabadi Muslim communities.Aurangabad houses a large pharmaceutical industry and two beverage companies - one soda andone beer company - who use water-intensive processes to produce their goods Maharashtra

Industrial Development Corporation (MIDC) has been acquiring village land to set up industrial estates since 1960, when Aurangabad and the rest of the Marathwada region joined Maharashtra state and fell under MIDC jurisdiction These industrial estates house auto companies such as Audi and Goodyear, oil companies such as MAN Diesel, textile companies and Johnson and

Johnson

The district as a whole is still predominantly rural by population and by land area Of over 1,300

villages in the district, only 45 have internet cafes or public access to internet (GOI, 2011).

71.97% of adults of in Aurangabad are literate (GOI, 2011) Villages range from a few

households, to 4095 households, making the ability of a village to organize and respond in times

of disaster extremely varied The size, income, location, and education of a village are likely toaffect not only their social vulnerability, but also their awareness of government resources andpolicy regulations

2.6 Policy and Regulations for Water Scarcity

Aurangabad district has a history of water governance due to its semi-arid climate and limitedrainfall supply Policy is set at the state level governing groundwater consumption as well as atthe national level regarding the depth of wells District policies aim to enforce the State's

Groundwater Management Act, to set procedures for applying for water supply assistance from

34

the government, and to set procedures for selecting villages to improve water supplies or

schemes though these aims are difficult to implement in practice

Aurangabad District, including Vaijapur block, experienced severe and sustained drought from

2010-2015 In 2016, most blocks received the total annual rainfall expected, but in a higher

intensity which led to runoff and lower groundwater infiltration rates

Figure 2.6.1 Policy Responses for Water Scarce Villages in Aurangabad District

Aurangabad Drought Response: Oct 15, 2016-July 31, 2016, source: GSDA

Aurangabad 8/11/2016

2.7 Case Study Synthesis

Aurangabad District is an ideal candidate for risk assessment due to its arid temperature, the ZillaParishad's willingness to collaborate, and its placement in the Marathwada region Within

Aurangabad district, the southern belt of three blocks are said to be most vulnerable to water

scarcity Of these, Vaijapur block is a special case, as it is located near a river but the primary source of drinking water for all of Vaijapur's villages is groundwater (NRWDP, 2016).

Additionally, Vaijapur's public transportation links it to three major cities, yet agriculture

remains the primary source of income for villages It will be increasingly important for Vaijapur

to manage its groundwater water demand as the district increases in population, and potentially

in industrialization due to its accessibility to major cities The proposed risk model presented inthe next chapter will assist district planners in assessing Vaijapur's village water scarcity risks as

caused by its physical hazards and by its socioeconomic conditions and infrastructure.

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Chapter 3: Risk Model Methodology

The model is developed in three parts, each of which represents an element of risk The threeparts, hazard, social vulnerability, and government capacity, are then multiplied together toproduce a risk score Each piece of the risk score helps to capture an element of risk, with theultimate goal of developing a meaningful risk score for District governments of Maharashtra.These three concepts: Hazard, Social Vulnerability and Capacity, together provide an

understanding of a village's risk to being affected by groundwater scarcity In order to develop a

risk score, we must first select variables, conduct initial statistics, and develop scores for each ofthe three segments of the risk model

3.1 Conceptual Framework

The premise of this model is two fold; (1) a village-level risk score can be derived from water

hazard and social vulnerability, and (2) this risk score can be used to anticipate future risk ofgroundwater scarcity, allowing for government intervention before the dry season occurs Figure

3.1.1 describes the components of the risk score.

Figure 3.1.1 Conceptual Framework for Risk Model

Source: Paige Midstokke, 2017

Figure 3.1.1 describes the construction of a risk score as a function of both hazard (drought) sensitivity and the social vulnerability of each village A hazard is a natural disaster in the form

of drinking water scarcity We estimate this using data on rainfall and water levels with a

systems identification model The hazard score is a function of the effect of inputs and

36

New,Tailored Responses

Water Tanker

withdrawals to groundwater on groundwater levels The social vulnerability score is an equationassessing the effect of socioeconomic variables on the ability of a village to respond to water

scarcity If you have a high water hazard score without ay social vulnerability (e.g., multiple

sources, water infrastructure, disposable income, etc), your risk score would in theory be zero

However, there is no such thing as zero vulnerability If you have high social vulnerability but

no likelihood of a hazard, your drought risk would also be zero If you had high hazard but low

capacity, you are better off than someone with high capacity as you are able to reach subsistencewithout a tanker The Village Risk Score is the comprehensive propensity of a village to needinggovernment assistance for water scarcity, and the score designed to be relative risk within asingle district The following sections describe the development of the hazard score, the

vulnerability score, and capacity efforts, which comprise the Village Risk Score in the villages ofVaijapur block

3.2 Hazard Score Development

The Hazard score captures the sensitivity of groundwater supply to changes in rainfall, by

controlling for withdrawals and temperature Aurangabad district has current and historical data

on water levels for 141 public observation wells in addition to location data for private wells In

Vaijapur block alone, there are sixteen public observation wells with data spanning 2009 to

2016 The purpose of the hazard score is to determine how closely these well levels fluctuate

with rainfall, as a means of understanding infiltration rates to aquifer storage and who is most atrisk to water scarcity in a low rainfall monsoon year This sensitivity analysis can assist districtgovernments in their understanding and preparation for the dry season, or in years with predictedlow monsoon seasons

The following description details the steps taken to develop the groundwater hazard score,

beginning with variable selection, variable calculation, assumptions, and preliminary statisticalmodeling before the final model is developed The hazard score is ultimately derived from asystems identification model, which is a powerful tool for relating time series inputs to timeseries outputs In this case, it helps explain how water levels are fluctuating over time as theresult of three time series inputs, which is elaborated in a later section of this chapter below

3.2.1 Variables and Sources

The Groundwater Survey and Development Agency (GSDA) of Aurangabad provided us with monthly groundwater levels for 141 observation wells between the years 1995-2000, and 2009-

2016 These data provide the distance from the ground level (terra) to the groundwater in meters

in each well, known as the static water level Rainfall data were provided by the India

37

Meteorological Department (IMD) in Pune, going back to 1916 We used the monthly

aggregated rainfall data to match the static water levels for time series analysis

I began the analysis by visualizing the time series fluctuations of rainfall and well levels for the

16 observation wells in Vaijapur District between 2009 and 2016 These fluctuations were placed

in the same time series to observe any similarities in trends as well as time lags between rainfall

and groundwater absorption After conducting exploratory analysis on rainfall and well levels, I

built a systems identification model in order to find a linear multivariable relationship betweentime series inputs of rainfall, temperature, and irrigation demand and the time series output ofwell levels The following sections depict the results of the exploratory analysis and systemsidentification models to ultimately derive a hazard score

3.2.2 Rainfall Statistics

Recharge is a function of the total volume of rainfall, infiltration, flow of surface water out of theland area, and evaporation/evapotranspiration The first step in estimating total recharge to

groundwater, indicated by an observation well, is to first understand rainfall The Indian

Meteorological Department (IMD) provided us with 100 years of monthly rainfall and daily rainfall for Aurangabad District, using an average of its 9 stations in the district This 100 year

time series was graphed and analyzed for its long-term average, its moving average, and its

cyclical trend I then took 66 years of rainfall (1950-2016) to look more specifically at rainfall

trends over time

38

Figure 3.2.2.1 Aurangabad Rainfall from 1950-2016

Source: Paige Midstokke, 2016

Figure 3.2.2.1 shows the decomposition of the rainfall time series data for 1950-2016 The top row contains the monthly data points recorded by IMD The second, third, and fourth rows depict the trend, seasonality, and estimated irregularity not explained by trend or seasonality If you

combine rows 2-4, they describe the fluctuations in our time series of rainfall The second row depicts seasonality, which shows us the monthly presence in variation What we see is that

seasonality was the "widest" or largest between 1950 and 1965, and smallest in the 1970's and in

the 2010O's This reduced seasonality in recent years means the month-to-month changes in rainfall are small, likely due to drought in the wet season The third row displays the general trend in the data at a monthly level, showing peaks and valleys in rainfall What we see is the

valleys are lowest in 1970 and in 2012, which we would expect due to the historical droughts The fourth row shows the remainder, or amount of data not explained by seasonality and trend.

This "remainder" appears most volatile in the late 1950's and 1980's-1990's This remainder is

less pronounced after 1992, possibly due to the decreased total rainfall and less out-of-cycle

rainfall in the 2000-2016 period.

We then focus our analysis of rainfall data on the months in which we have groundwater

measurements, from 2009-2016, to explore the relationship between rainfall and observation

well level We also have daily rainfall data collected during this period from IMD for

Aurangabad District The following graphs show the observed rainfall, as well as the expected

39