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Working Paper 205
SUSTAINABLE LIVELIHOOD
SECURITY INDEX IN GUJARAT: A
DISTRICT-LEVEL ILLUSTRATION
Pramod K. Singh and B.N. Hiremath
The purpose of the Working Paper Series (WPS) is to provide an
opportunity to IRMA faculty, visiting fellows, and students to sound out
their ideas and research work before publication and to get feedback
and comments from their peer group. Therefore, a working paper is to be
considered as a pre-publication document of the Institute.
Institute of Rural Management Anand
Post Box No. 60, Anand, Gujarat (India)
Phones: (02692) 260181, 260186, 260246, 260391, 261502
Fax: 02692-260188 Email: [email protected]
Website: www.irma.ac.in
March 2008
SUSTAINABLE LIVELIHOOD SECURITY INDEX IN
GUJARAT: A DISTRICT-LEVEL ILLUSTRATION
Pramod K. Singh1 and B.N. Hiremath
2
Abstract
The paper reviews the existing indicators of development and positions them
within the environmental, economic, and social dimensions of sustainable
development. The paper finds that the sustainable livelihood security index
(SLSI), based on its simplicity and flexibility, is one of the most
comprehensive yet simple indices for measuring long-term livelihood
security in rural areas, as it can function as an educational as well as a policy
tool for promoting a holistic perspective among planners, administrators, and
development workers. It presents empirical evidence of SLSI at the district
level in Gujarat. In order to select suitable parameters of the component
indices of SLSI, the paper presents a broad-ranging account of the ecological
and socio-economic profile of Gujarat state. District-level SLSI in Gujarat not
only identifies the general priorities but also the nature and types of policies to
be pursued in each district to enhance its sustainable livelihood security status.
1 Assistant Professor, Institute of Rural Management, Anand 388 001, Gujarat, India, Email:
[email protected]. 2 Professor, Institute of Rural Management, Anand 388 001, Gujarat, India, Email:
1
SUSTAINABLE LIVELIHOOD SECURITY INDEX IN GUJARAT: A DISTRICT-LEVEL ILLUSTRATION
1.0 INTRODUCTION
Gujarat1, located in western India, is one among several federal states in the
Union of India. It was formed in 1960 as a separate state. Over the last 47
years, it has emerged as a leading industrialised state in the country.
However, Gujarat has relatively poor and unevenly distributed natural
resources, which have been mismanaged over time. It has almost stagnant
long-term growth in agriculture and wide regional disparities (Hirway 2002;
Hirway and Terhal 2002). Though the incidence of poverty in the state is
much lower (16.75 per cent in 2004–05) as compared to all India (28.27 per
cent in 2004–05), it is significant enough, as this implies that almost every
sixth person in the state is living in poverty. Gujarat lags behind in several
dimensions of human development, particularly in female literacy, enrolment
and retention of children in school, infant mortality rate, and calorie intake.
The state has suffered heavy ecological damage as a result of industrialisation
and urbanisation.
The level of development in Gujarat is not uniform in terms of spatial
distribution and across sectors. The tribal districts of the state are lagging
behind in socio-economic terms; these districts have low food grain
productivity, low milk productivity, higher level of poverty, and low female
literacy. Gujarat needs to adopt an employment-intensive and environment-
friendly development plan for broad-based development, which could help
the state to achieve sustainable development. However, different parts of the
state require different kinds of development interventions. The sustainable
livelihood security index (SLSI), which facilitates consensus among different
partisan groups like economists, environmentalists, and egalitarians by
balancing their mutual concerns, could provide guidelines for achieving
sustainable development.
In the remainder of the paper, we will discuss the concepts of sustainable
development and sustainable livelihood security. We will present an
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overview of the existing development indicators. An analytical framework
and methodology of SLSI, which was developed by the MS Swaminathan
Research Foundation (MSSRF) (1993), will be presented in the subsequent
section. Before presenting empirical evidence of SLSI at the district level in
Gujarat, we will review the ecological and socio-economic status of the state.
Finally, we will construct SLSI at the district level in Gujarat and conclude
the paper.
2.0 CONCEPT OF SUSTAINABLE DEVELOPMENT (SD)
Since the publication of the Brundtland Report (1987), there have been
innumerable debates on sustainable development (SD). In 1983, the United
Nations convened the World Commission on Environment and Development
(WCED), also known as the Brundland Commission, after the name of its
chairman, Gro Harlem Brundtland. The commission was created to address
growing concern ‗about the accelerating deterioration of the human
environment and natural resources and the consequences of that deterioration
for economic and social development‘. The Brundtland Report defines
sustainable development as ―the development that meets the needs of the
present without compromising the ability of future generations to meet their
own needs‖ (WCED 1987:8). This definition explicitly mentions a trade-off
between two interests: those of the present generation and those of the future
generations. This is a conflict arising out of the recognition that growth in
material well-being has implications for the environment.
SD is a process in which the exploitation of resources, the direction of
investments, the orientation of technological development, and the nature of
institutional changes are all made consistent with the demands of future as
well as present needs. The basic premise of SD is a symbiotic relationship
between the human race and the natural systems, and compatibility between
ecology, economy, and equity.
Thus, SD calls for the integration of ecological, social, and economic (ESE)
objectives. Serageldin and Steer (1994) summarised these objectives in the
so-called ESE triangle (see Figure-1). A similar view was also expressed by
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Barbier (1987) and Daly (1992). The ESE triangle, or some variant of it, is
increasingly being used in debates about SD.
Economic objectives
*Growth
*Equity
*Efficiency
Social objectives Ecological objectives *Empwerment *Ecosystem integrity
*Participation *Carrying capacity
*Social mobility *Biodiversity
*Social cohesion *Global issues
*Institutional development
Figure-1:
Objectives of Environmentally Sustainable Development
(Source: Serageldin and Steer 1994)
The World Resources 1992–93 document, brought out by WRI–UNEP–
UNDP (1992:4–8), argued that sustainability has four critically interacting
dimensions of SD: environmental dimension, economic dimension, human
dimension, and technological dimension. However, the ESE triangle is
consistent with the above four dimensions in a given technological paradigm
proposed by World Resources 1992–93 when the technological dimension is
determined on the basis of a given technological regime (Saleth 1993a).
Another dimension could be awareness of and access to information about
the above three dimensions. However, for the sake of simplicity we may
ignore this dimension too.
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Thus, as a development paradigm, SD represents the confluence of three
conflicting development paradigms namely, deep-ecology, free-market
economics, and egalitarian ideology. Ecological integrity, economic
efficiency, equity with social justice, resource conservation and endogenous
choices are the basic preconditions to sustainable development.
3.0 CONCEPT OF SUSTAINABLE LIVELIHOOD SECURITY (SLS)
According to the Oxford Reference Dictionary, livelihood denotes ‗a means of
obtaining the necessities of life‘ and security means ―the state of being or
feeling secure‘. The concept of sustainable livelihood security (SLS) has a much
more generic meaning, encompassing most of the current concerns and policy
requirements pertaining to SD. Chambers (1986) has defined sustainable
livelihood as a ‗level of wealth and of stocks and flows of food and cash which
provide for physical and social well-being and security against becoming
poorer‘. Swaminathan (1991a and 1991b) has defined SLS as livelihood options
that are ecologically secure, economically efficient, and socially equitable in
order to underscore three aspects: ecology, economics, and equity. Chambers
and Conway (1992) have proposed the concept of rural livelihood security
(RLS) while focusing on three aspects: capability, equity, and sustainability.
Since the concept implies the protection or assurance of the means of livelihood
for the masses not only at the present time but also in the future, it reflects
equally the concern for both the intergenerational equity underlined by the
Brundtland Report (1987:8) as well as the intra-generational equity emphasised
by Swaminathan (1991b). In this respect, Barbier (1987) has argued that SD
should balance the livelihood requirements of the poor at the present time with
those of future generations.
The concept of SLS has both macro- and micro-level implications. The macro-
level prescriptions for ensuring SLS include stabilising population, reducing
migration, preventing core exploitation, and supporting long-term sustainable
resource management. At the micro and local levels, the critical ingredients of
SLS are ‗adequate stocks and flows of food and cash to meet basic needs‘ and
‗access to resources, income, and assets to offset shocks‘ (McCracken and
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Pretty 1988:14). While it is possible to manage population growth and
migration mainly through economic development and resource management,
social exploitation can be minimised only through greater equity in income
distribution, asset ownership, and access to natural and technological resources.
At the same time, ecological security needs to be ensured for the sustenance of
economic growth.
Since SLS aims to provide the means for meeting the basic needs of humans, it
is more sustainable as a policy tool than as a strategy aimed at the mere
provision of basic needs per se. Ensuring SLS by enabling people to meet their
own needs will lead to reduced pressure on the environment, which, in turn,
means that it will be possible for more people to meet their livelihood needs in
the future (Chambers 1986). A livelihood is sustainable, according to
Chambers and Conway (1992), when it ‗can cope with and recover from the
stress and shocks, maintain its capability and assets, and provide sustainable
livelihood opportunities for the next generation‘. Unfortunately, not all
households are equal in their ability to cope with stress and repeated shocks.
Poor people balance competing needs for asset preservation, income
generation, and present and future food supplies in complex ways (Maxwell
and Smith 1992). People may go hungry up to a point to meet other
objectives, such as preserving seeds for planting, cultivating their own fields,
or avoiding the sale of animals. However, all these factors cannot be captured
when an analysis is undertaken at the district level.
4.0 INDICATORS OF DEVELOPMENT: AN OVERVIEW
The development paradigms, welfare goals, and resource and technological
conditions prevalent at a given point in time explain, by and large, the
emergence and relevance of any particular set of welfare indicators (Saleth
and Swaminathan 1993). In the post-war years, when economic growth was
considered the panacea for all economic and social ills, human welfare was
measured mainly in economic terms as indicated by the gross domestic
product (GDP). But when economic growth failed to advance social
development, the focus shifted to social and human development indicators
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(ibid.). But now an ever-expanding population, increasing consumerism, and
overexploitation of natural resources has resulted in a population–resource
imbalance, which has acquired global dimensions and has led to ecological
imbalances. Hence, today, the SD paradigm has been broadened to
encompass ecological, economic, and equity concerns, necessitating an
entirely new set of welfare indicators that transcend disciplinary boundaries.
Here, we evaluate a set of development indicators; the list is not exhaustive
but illustrative and suggestive.
4.1 Economic and Social Indicators
Gross domestic product (GDP) is often described as the most important
measure of economic development. GDP measures the net value addition in
the primary, secondary, and tertiary sectors at factor cost plus consumption of
fixed capital and net indirect taxes. Since GDP does not refer to, or take into
account, the quality of human life and the status of environmental assets, it is
increasingly being discarded as a measure of welfare.
The disenchantment with GDP-related measures has led to the emergence of
‗poverty indices‘, based on the income level corresponding to the cost of a
‗commodity basket‘ considered essential for maintaining a reasonable standard
of living (Saleth and Swaminathan 1993). Along similar lines, Morris (1979)
has proposed the physical quality of life index (PQLI) as a measure of the
physical well-being of people. PQLI has three components: infant mortality, life
expectancy, and basic literacy. The empirical evaluation of PQLI for 150
countries revealed an interesting fact—that all the low GDP countries do not
have low PQLI and all the high GDP countries do not have high PQLI (Saleth
and Swaminathan 1993). Although PQLI captures the social and equity
dimensions ignored by the GDP indicator, it fails to account for both the
economic and ecological dimensions.
The human development index (HDI) developed by UNDP is similar in spirit
and methodology to PQLI. Since 1990, HDI has been reported annually as part
of the human development report of UNDP. It consists of three equally
weighted sub-indices, which are aggregated by an arithmetic mean: life
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expectancy index, education index (decomposed into an adult literacy index and
a gross enrolment ratio index), and a gross national product (GNP) index
(UNDP 2005). It has the following three components: longevity, literacy, and
purchasing power adjusted per capita real GDP (UNDP 1990 and 1992). The
two composite indices (PQLI and HDI) reach a common conclusion, that is,
economic growth is a necessary but not a sufficient condition for human and
social development. They also share a common drawback—that of ignoring the
ever crucial environmental concerns.
4.2 Physical and Ecological Indicators
The physical concept of net primary productivity (NPP) is often considered the
ecological counterpart of the economic measure of GDP. Gross primary
productivity (GPP) is the total amount of energy assimilated by the primary
producers per unit of time; NPP equals GPP minus respiratory loss (Rajvaida
and Markandey 2004; Odum 1975).
Ecological footprint (EF) provides a quantitative assessment of the
biologically productive area required to produce the necessary resources
(food, energy, and materials) and to absorb the wastes produced by a given
population (Rees and Wackernagel 1996). EF is based on the quantitative
land and water requirements for sustaining a (national) living standard into
infinity, thereby assuming certain efficiency improvements (Rees and
Wackernagel 1997, quoted in Bohringer and Patrick 2007). The EF report
reveals that humans are using over 20 per cent more natural resources each
year than can be regenerated (Bohringer and Patrick 2007). This figure is
growing every year (ibid.). EF measures only the size and not the location of
the footprint, and hence is not the right measure for assessing the natural
resource sustainability and livelihood security of a country or a state. The
consequent livelihood problems of the poor in a country are the result of
overexploitation of resources, which is something that is not apparent in the
EF concept. Removal of vegetative cover due to overgrazing, depletion of
soil fertility due to high yields, or disruption of watersheds and water
availability, non-availability of forest foods and free fuelwood due to
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commercial felling of forests, and so on come under this category. Hence, we
cannot use the EF method to assess sustainability, which is the integration of
ecological, economic, and social objectives.
The environmental sustainability index (EStI) is a composite index targeting
environmental, socio-economic, and institutional indicators as a means of
assessing sustainability. The core components of EStI are: environmental
systems, reducing stresses, reducing human vulnerability, social and
institutional capacity, and global stewardship (World Economic Forum et al.
2002). The EStI score quantifies the likelihood that a country will be able to
preserve valuable environmental resources effectively over a period of
several decades (Esty et al. 2005:23). EStI incorporates 20 indicators, each of
which combines two to eight variables, for a total of 68 underlying datasets.
EStI is highly data intensive.
The living planet index (LPI), a global biodiversity indicator, was developed
by WWF (1998). It measures trends in a sample of more than 2,000
specimens drawn from more than 1,100 species of vertebrates in terrestrial,
freshwater, and seawater ecosystems.
The environmental performance index (EPI) focuses on current on-the-
ground outcomes across a core set of environmental issues tracked through
six policy categories for which all governments are being held accountable
(Esty et al. 2006:9). It addresses the need for a gauge for policy performance
in reducing environmental stresses on human health and in promoting
ecosystem vitality and sound natural resource management.
The environmental vulnerability index (EVI) consists of 32 indicators of
hazards, eight indicators of resistance, and 10 indicators of damage
measurement (SOPAC 2005:7). EVI is also highly data intensive. Maximum
sustainable yield (MSY) ensures physical optimality by maintaining a
constant and optimally renewable stock (Daly 1990).
The Food and Agriculture Organisation (FAO) has evaluated the carrying
capacity of 117 countries in terms of their maximum food-producing
capabilities (FAO 1984). Under the concept of carrying capacity (CCC), the
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maximum population (of human and other life forms) that can be supported
by the resource base is measured (ibid.).
In the pressure–state–response (PSR) model, developed by the Organisation of
Economic Cooperation and Development (OECD), pressure and the state are
focused mainly on the physical and ecological aspects, while the response
indicators are related to policy responses to various stress–state conditions
(OECD 1991). The excessive ecological focus of the PSR indicators, including
the policy-response indicators, has led the PSR approach to fall into the
exclusive zone of ecology.
In addition to their contextual nature, the most severe limitation common to
most of the physical and/or ecological indicators is that they are essentially
deep-ecology based, and hence do not take into account economic and equity
concerns.
4.3 Indicators Focused on the Ecology–Equity Interface
Saleth (1990) has developed the relative measure of sustainability (RMS),
which explicitly considers the issue of intergenerational trade-offs, a kind of
bargaining between the present and future generations, which is implicit in the
Brundtland Report.
Toman and Crosson (1991) have proposed the concept of the safe minimum
standard (SMS) for intergenerational resource management and conservation.
SMS identifies the boundary where market-based approaches should end and
where moral and ethical imperatives should begin for guiding resource
management decisions. SMS is not an indicator but only an approach to an
indictor. Despite their economic moorings, the main driving forces behind both
RMS and SMS are moral and ethical imperatives. Even their concern with
equity is only partial, as their focus on intergenerational equity is only at the
cost of intra-generational equity.
The well-being index (WI) is a composite index evaluating human and
ecosystem well-being. WI is based on the belief that assessing the
combination of these two elements offers insight into how close a country is
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to becoming sustainable. WI is an equally weighted average of the human
well-being index (HWI) and the ecosystem well-being index (EWI). Both
consist of five dimensions; the former comprises health and population,
household and national wealth, knowledge and culture, community, and
equity; the latter consists of land, water, air, species and genes, and resource
use (Prescott-Allen 2001).
This category of indices lacks the ability to address the issues of economic
development, which limits their wider acceptability.
4.4 Indicators Focused on the Ecology–Economics Interface
Benefit-cost analysis (BCA) has often been used as an indicator of economic
viability and ecological feasibility of individual projects (Ray 1984). In addition
to the practical problems in evaluating environmental effects within a market
framework, there are also ethical issues involved in the choice of both the
planning horizon and the discount rate in the BCA exercise.
Natural resource accounting (NRA) is a measure of the creation or depletion of
environmental capital into GDP (Repetto and Magrath 1988). As natural
resources provide several use values and non-use values for human welfare and
for the sustainability of all species, NRA measures the sum of use values and
non-use values, which constitute the total values (Kadekodi 2001).
Genuine savings index (GSI) defines the level of reinvestment from resource
rents that are reinvested to ensure that the (societal) capital stock will never
decline (Hamilton et al. 1997). The societal capital stock consists of produced
capital, human capital (knowledge, skills, etc.), and natural capital (resources,
etc.). All the values are monetised, and aggregation is achieved by simple
addition to construct GSI. Here, a lot of subjectivity is involved in monetising
human capital.
Environmentally adjusted net domestic product (EDP) has been developed
within the scope of the System of Integrated Environmental and Economic
Accounting, United Nations Environmental Programme, 2000, and the
United Nations, European Commission, International Monetary Fund,
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Organisation for Economic Cooperation and Development, and the World
Bank (UN et al. 2003). Hanley (2000) distinguished three different versions
of the EDP, which are: (i) EDP-I, which subtracts depreciation of natural
resources caused by their extraction from the net national income (NNI); (ii)
EDP-II, which subtracts from NNI the costs necessary for reaching the same
state of the environment at the end of the period as that which existed at the
beginning of the period; and (iii) EDP-III, which subtracts the costs of
environmental pressure and destruction (calculated by willingness-to-pay
methods). Here also, all values are monetised, and aggregation is achieved by
simple addition.
Environmental impact assessment (EIA) identifies, predicts, evaluates, and
mitigates the biophysical, social, and other relevant effects of development
proposals. EIA is a more focused version of BCA, with a relatively sharper
focus on environmental impacts than on economic concerns (US National
Environmental Policy Act 1969, quoted in Glasson and Chadwick 1994).
This category of indices lacks the ability to address distributional issues, which
limits their wider acceptability. However, BCA could be modified to
accommodate equity parameters.
4.5 Indicators Focused on the Ecology–Economics–Equity Interface
Under the SD paradigm, the scope of human welfare has been broadened
enough to encompass ecological, economic, and equity concerns, necessitating
an entirely new set of welfare indicators that can transcend disciplinary
boundaries (Saleth 1993a). Some of the indicators under this category are
described below.
The city development index (CDI), proposed by the United Nations Centre for
Human Settlements (HABITAT), consists of five sub-indices: (i) an
infrastructure index, which builds on four (equally weighted) indicators as a
percentage of households that are connected to clean water, canalisation,
electricity, and a telephone network (without mobiles); (ii) a twofold (equally
weighted) waste index, which is composed of the percentage of untreated
sewage in total wastewater and the percentage of disposal of solid waste in
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total solid wastes; (iii) a twofold (diversely weighted) health index, which
considers life expectancy and the infant mortality rate; (iv) a twofold (equally
weighted) education index, which is calculated by adding the percentage of
the literacy rate and the combined enrolment rate; and (v) a city product
index, which is based on the logarithmic value of a city‘s GDP (Bohringer
and Jochem 2007). CDI, as the name suggests, is an important indicator for
measuring the SD level of a city, and is not appropriate for use in a rural
setting.
The index of sustainable economic welfare (ISEW) has been developed by
Cobb (1989) to integrate environmental and social externalities in national
welfare accounting. With some modifications to the original accounting
method (Cobb and Cobb 1994), ISEW has been relabelled as the genuine
progress indicator (GPI) (Cobb et al. 1995). ISEW is a comprehensive index,
which not only explains the average consumption and its distribution across
social groups but also the long-term deterioration in environmental assets (Daly
and Cobb 1989). As for the calculation of ISEW and GPI, both indices begin
not with GDP as their base but with the extraction from the national accounts
of the transactions deemed directly relevant to human well-being (Cobb et al.
1995, quoted in Lawn 2003). Further adjustments are made to account for the
many benefits and costs of economic activity that GDP ignores. Accordingly,
ISEW and GPI include a number of social and environmental benefits and
costs that invariably escape market valuation. Here also, all the values are
monetised. Box-1 presents a list of the typical items used in the calculation of
ISEW and GPI.
Sustainable net benefit index (SNBI) is similar to ISEW and GPI. It mainly
differs in the explanation of the rationale for an alternative index and the
presentation of the items used in its calculation. The items, which are similar
to those listed in Box-1 (Lawn and Sanders 1999), are sorted into separate
‗benefit‘ and ‗cost‘ accounts. The total of the cost account is subtracted from
the benefit account to obtain the SNBI.
Sustainable livelihood security index (SLSI), originally proposed by
Swaminathan (1991b) and empirically illustrated later by Saleth and
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Swaminathan (1993), is also an attempt towards formulating a comprehensive
indicator to reflect the ecology–economic–equity interface of SD. The
conceptual and methodological bases as well as the information efficiency and
flexibility of SLSI have been treated in detail in Section 5.
Although the indices in this category (CDI, ISEW/GPI, SNBI, and SLSI) are
composite indicators, combining information on ecological, economic, and
equity aspects within a unifying framework, they differ in terms of their
methodological basis and information content. CDI, as the name suggests, is
not applicable to a rural setting. While ISEW, GPI, and SNBI are temporal
indicators, SLSI is essentially a cross-sectional measure that is useful in
evaluating the relative sustainability status of a given set
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Box-1:
Items Used for Calculating the GPI of the USA from 1950 to 1995
Personal consumption expenditure (+)
Index of distributional inequality (+/-)
Weighted personal consumption expenditure
Cost of consumer durables (-)
Services yielded by consumer durables (+)
Services yielded by roads and highways (+)
Services provided by volunteer work (+)
Services provided by non-paid household work (+)
Cost of noise pollution (-)
Cost of commuting (-)
Cost of crime (-)
Cost of underemployment (-)
Cost of lost leisure time (-)
Cost of household pollution abatement (-)
Cost of vehicle accidents (-)
Cost of family breakdown (-)
Net capital investment (+/-)
Net foreign lending/borrowing (+/-)
Cost of loss of farmland (-)
Cost of resource depletion (-)
Cost of ozone depletion (-)
Cost of air pollution (-)
Cost of water pollution (-)
Cost of long-term environmental damage (-)
Cost of loss of wetlands (-)
Cost of loss of old-growth forests (-)
(+) stands for positive item
(-) stands for negative item
(+/-) stands for item that may be either positive or negative
Total is calculated as sum of all positive and negative values.
Source: Lawn and Sander 1999 (quoted in Lawn 2003).
15
of entities (households, villages, districts, ecosystems, regions, nations, etc.).
Consequently, SLSI requires only a minimum amount of easily available
ecological, economic, and equity information. Furthermore, the cross-
sectional character, simplicity, and information efficiency of SLSI make the
index easily replicable and suitable for generalisation across various
evaluation levels.
The diagrammatic representation of the position of existing indicators of
sustainable development is presented in Figure-2. A critical evaluation of the
indicators developed to date reveals that the major snag in indicator-
development activities is not the scarcity of approaches or methodologies but
the absence or inadequacy of crucial environmental and ecological
information (Saleth and Swaminathan 1993). SLSI has the potential to
function as a context-independent generic tool for evaluating SD concerns at
various interrelated levels—households in a village context, villages in a
district context, districts in a state context, uses or practices in a
resource/ecosystem context, projects/technologies in a policy option context,
regions in a national context, and nations in a global context.
5.0 SUSTAINABLE LIVELIHOOD SECURITY INDEX (SLSI):
ANALYTICAL FRAMEWORK AND METHODOLOGY
The utility and replicability of a given index or measure depends primarily on
its simplicity and flexibility, not on its complexity and rigidity. As discussed in
Section 2, SD focuses on three mutually dependent dimensions of ecological,
economic, and social objectives. Hence, the three basic conditions crucial for
SD are ecological security, economic efficiency, and social equity
(Swaminathan 1991a). The operational measure proposed by Swaminathan
(1991b quoted in MSSRF 1993) to check whether the necessary conditions
essential for the attainment of sustainable livelihood security (SLS) are
present in a given region or ecosystem is known as the sustainable livelihood
security index (SLSI), which again has the following three interacting
components:
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GDP Gross Domestic Product
PQLI Physical Quality of Life Index
HDI Human Development Index
NPP Net Primary Productivity
EF Ecological Footprint
EStI Environmental Sustainability Index
LPI Living Planet Index
EPI Environmental Performance Index
EVI Environmental Vulnerability Index
MSY Maximum Sustainable Yield
PSR Pressure-State-Response model
CCC Concept of carrying capacity
RMS Relative Measure of Sustainability
SMS Safe Minimum Standard
WI Well Being Index
BCA Benefit-Cost Analysis
NRA Natural Resource Accounting
GSI Genuine Savings Index
EDP Environmental Adjusted Domestic Product
EIA Environmental Impact Assessment
CDI City Development Index
ISEW Index of Sustainable Economic Welfare
SNBI Sustainable Net Benefit Index
SLSI Sustainable Livelihood Security Index
Figure-2:
Positioning Existing Indicators of Sustainable Development
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i. Ecological security represented by variables such as forest cover, soil
and water quality parameters, air pollution, groundwater depletion, etc.
ii. Economic efficiency represented by variables such as land productivity,
labour productivity, marketable surplus, input–output ratio, etc.
iii. Social equity represented by variables such as distribution of land, asset
and income, people above poverty line, female literacy, etc.
To operationalise the concept of SLS within the context of SD, Saleth and
Swaminathan (1993) propounded the following propositions:
Given the dynamic nature of SD, it needs to be relative rather than absolute
both in time and space as well as against any scientifically determined
norms or standards;
Since SD is contextual, what is sustainable in a given region or ecosystem
need not necessarily be sustainable in another region or ecosystem; hence
there cannot be a unique recipe for achieving SLS everywhere; and
SD is a hierarchical and interrelated process, as the sustainability
requirements of households, resources, ecosystems, regions, nations, and
ultimately, the planet itself are critically interlinked.
The MS Swaminathan Research Foundation (MSSRF) developed SLSI for
the 15 agro-climatic regions of India (MSSRF 1993; Saleth 1993a; Saleth and
Swaminathan 1993). MSSRF (1993) and Saleth and Swaminathan (1993)
(both referring to the same study) selected the following indicators. They
selected forest cover and net sown area as ecological indicators; land
productivity and area under cereals as economic indicators; and people above
poverty line and female literacy as equity indicators. Saleth (1993b)
developed the agricultural sustainability status of the agro-climatic sub-zones
of India by selecting forest cover, per capita utilisable groundwater potential,
and population density as ecological indicators; land productivity, labour
productivity, and per capita cereal output as economic indicators; and people
above poverty line, female literacy, and current groundwater use as a
percentage of its ultimate potential as equity indicators.
MSSRF (1993) listed the following factors for developing SLSI:
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The index needs to be composite so as to take stock not only of the conflicts
between the three aspects of sustainability but also of the intrinsic synergy
among them;
It should be simple, flexible, and information-efficient;
It should be easy to construct and understand by policy makers, local-level
administrators, and, more importantly, by rural families; and
It should be a tool both for policy making as well as for public education.
Utilising the three-dimensional conception of SD, Saleth and Swaminathan
(1993) described the procedure for developing SLSI as a relative approach
underlying the PQLI–HDI methodology in a generic context, which is
presented below:
Let SLSIij be the index for the ith component of SLSI related to the jth entity
(households in a village context, projects or technologies in a policy-option
context, uses or practices in a resource/ecosystem context, regions in a national
context, and nations in a global context) and let Xij be the value of the variable
representing the ith component of SLSI related to the j
th entity. Then the index
for the ith component of SLSI of the j
th entity can be calculated as follows:
Xij - min Xij j (i = 1,2,..,I) [1] SLSIij = ──────── (j = 1,2,..,J) max Xij - min Xij j j
Notice that the numerator in [1] measures the extent by which the jth entity did
better in the ith component of SLSI as compared to the entity showing the worst
performance in that component, and the denominator indicates the range (i.e.
the difference between the maximum and the minimum values of the variable
representing a given component), which is a simple statistical measure of total
variation present in the variable representing the ith component of SLSI. The
denominator, in fact, serves as a scale by which the extent of the better
performance of the jth entity in the i
th component is evaluated. Having calculated
the SLSIij for all the components (i = 1, 2, . . . , I) and all the sample entities (j =
1, 2, . . . , J), the composite index, which measures the overall performance of a
19
given entity (SLSIj), can be calculated as a weighted average of all the
component indices [SLSIij (i = 1, 2, . . . , I)]. That is:
I Σ aij SLSIij i=1 SLSIj = ─────── (j = 1,2,..,J) [2] I
The aij in [2] denotes the weight assigned to the ith component of SLSI of the j
th
entity and has the property that: a1j + . . . + aIj = 1. If aij is identical for all i and j
and is equal to 1, it means that an unrealistic system of equal weights is being
assumed.
In view of our three-dimensional conception of SD and hence SLS, SLSI
will have three component indices, i.e. the ecological security index (ESI),
the economic efficiency index (EEI), and the social equity index (SEI). Each
of the three component indices of SLSI can be based on one or more
variable(s) reflecting the state of affairs in a given dimension. When there are
two or more variables to represent a given component of SLSI, the index for
that component can be formed again by taking either the simple or the
weighted average of the individual indices of the representative variables.
The choice of the candidate variables to represent the different components of
SLSI is influenced inter alia by their relevance and capacity to represent a
given component, availability of data, and the level at which SLSI is
constructed.
6.0 EMPIRICAL ILLUSTRATION OF SLSI AT THE DISTRICT
LEVEL IN GUJARAT
In order to construct SLSI, one needs to select suitable parameters or
indicators. However, the choice of indicators should flow from the ecological
and socio-economic profile of the region. Hence, in this section, we discuss
the ecological and socio-economic profile of the state before describing the
method of constructing SLSI.
20
6.1 Ecological Status of Gujarat
The process of economic growth has had a very bad effect on the
environmental health of the state. In this sub-section, we review the
ecological degradation of Gujarat under two broad categories: problems of
land resources and problems of water resources.
6.1.1 Problems of Land Resources
Land degradation: While there is a clear distinction between soil and land
(the term land refers to an ecosystem comprising land, landscape, terrain,
vegetation, water, and climate), there is no clear distinction between the terms
land degradation and desertification (desertification refers to land degradation
in arid, semi-arid, and sub-humid areas due to anthropogenic activities)
(UNEP 2000, quoted in GEC 2005). In a strict sense, land degradation is a
process that lowers the productivity of the land when all other factors such as
technology, farming practices, and weather remain constant (GEC 2005).
Land degradation is a complex process, with multiple driving forces acting on
an environmental resource base that is severely strained due to the geo-
climatic peculiarities of a given region. Many interrelated factors, particularly
those of land and water management, are responsible for various forms of
land degradation. It is, however, very difficult to isolate the real causes that
drive productivity losses. Land degradation affects 41.5 per cent of Gujarat
(NBSS–LUP 1994). The major conditions that aggravate land degradation in
the state are soil erosion, soil salinity, degradation of forests and pasturelands,
mining activity, and dumping of hazardous and domestic wastes.
Soil erosion: Erosion of soil is caused by both water and wind. As per the
assessment of NBSS–LUP (1994), in Gujarat, a total of about 7.32 M ha is
affected by soil erosion. This is 42.6 per cent of the total reporting area
(TRA) of the state.
Soil salinity: Large areas of Gujarat have emerged from the sea in the recent
geological past, and are hence inherently saline. The Ranns of Kachchh are
remnants of the ancient seabed and still experience periodic inundation by the
sea (GEC 2005). Low-lying regions like Banni, Bhal, Ghed, and Khadapat
21
are no longer exposed to regular saline inundations but their soil still retains
marked saline characteristics. In addition, there are extensive saline mud-flats
in the coastal areas around the gulfs of Khambhat and Kachchh. As per the
NBSS-LUP (1994), an area of about 2.48 M ha in Gujarat is affected by
varying degrees of soil salinity. This is about 14.4 per cent of the total
reported area. About 1.5 M ha of these lands are slightly affected by salinity,
while the remaining 0.97 M ha are affected by moderate to higher levels of
salinity (EC greater than 4 ds-mn
). Improper soil and water management
practices—such as damming of rivers, disintegration of traditional water-
harvesting systems, faulty irrigation systems and practices, over-withdrawal
of groundwater, etc.—aggravate salinity problems in Gujarat.
Degradation of forests: Growing human population coupled with increased
grazing, firewood collection, reckless felling, and conversion of forest areas
for agricultural and other developmental purposes have certainly increased
the pressure on forests. In a state where the natural endowment is already
poor, ecological conditions have deteriorated even further as a result of the
loss of forest cover due to increasing demands for land, wood, and fodder and
extractive management practices, particularly until the 1980s (GEC 2005).
Degradation of pasturelands: The majority of grazing lands or pasturelands
in Gujarat is under the open access management regime. Thus, the issue of
pastureland degradation is a classic case of the ‗tragedy of the commons‘
(GEC 2005). Actually, this degradation needs to be seen as the large-scale
degradation of common grazing land. Over the years, several village-level
studies have indicated clearly that because of the cumulative effect of several
factors, these common grazing lands are being degraded rapidly, both in
terms of quantity and quality (Jodha 1986; Iyenger 1988). One major reason
for the shrinking of grazing lands is their conversion to other uses, either by
legal transfer or by illegal encroachment. While records of land transfers are
maintained at the village or taluka level, there are hardly any records of the
encroachment of these lands for cultivation purposes (GEC 2005). Another
important cause of pastureland degradation is the invasion of a woody
species, Prosopis juliflora. The Banni grassland in Kachchh district is the
22
most typical example of such degradation. Jadhav et al. (1992) reported an
alarming shrinkage of these grasslands at a rate of about 30 sq km per annum,
mainly due to the invasion of P. juliflora. The situation is more or less similar
in other pasturelands. SAC (2001) based on its mapping exercise reported
that an area of about 0.94 M ha is covered by this exotic species in the
Kachchh and Saurashtra regions of the state.
6.1.2 Problems of Water Resources
The problems of water resources in Gujarat constitute quantitative shortages
as well as qualitative deterioration. According to Falkenmark‘s indicator of
physical water scarcity, Gujarat is a water-stressed region, as the per capita
freshwater availability of 1,137 cubic metres in 2001 was far below the
prescribed 1,700 cubic metres per annum (GEC 2005). Total water use in the
state for all sectors is about 35 per cent of total freshwater availability, as
against the national average of 28 per cent. In a larger sense, the water-related
problems of Gujarat can be seen as originating mainly from the demands of
the agricultural, domestic, and industrial sectors. These sectors, in turn,
actually put pressure on the water resources of the state in the following
manner:
Overexploitation and appropriation of ground and surface water
Salinity ingress in coastal regions
Waterlogging and command area salinity
Increasing levels of fluorides, nitrates, and TDS (total dissolve solutes) in
groundwater
Overexploitation of water: In Gujarat, one of the most widespread problems
related to water is the overexploitation of groundwater and its depletion to
meet the demands of different sectors. In regions where rainfall is scanty and
erratic, groundwater remains the only source of sustenance during lean years
and hence becomes vulnerable to overexploitation. Since highly erratic
rainfall and successive droughts are the characteristics of the arid and semi-
arid regions of Gujarat, groundwater forms the only reliable source of water
for drinking, irrigation, and other needs. Overexploitation is emerging as a
23
major threat to the physical sustainability of groundwater systems, and
consequently leads to many environmental problems (Moench 1995; Shah
1997; IRMA–UNICEF 2001; Kumar et al. 2001). Problems related to
overexploitation occur when large-scale exploitation of aquifers results in
major declines in groundwater levels, deterioration in groundwater quality,
scarcity of drinking water, increase in pumping costs, intrusion of seawater,
subsidence of land, changes in surface drainage patterns, etc. (Custodio
2000). Therefore, assessing groundwater overexploitation involves several
complex considerations in terms of physical sustainability and its socio-
economic impact.
The Gujarat Water Resource Development Corporation (GWRDC) monitors
the groundwater situation in the state. It classifies districts and talukas as
white or safe, grey or semi-critical, dark or critical and overexploited,
depending on the level of groundwater development (i.e. level of extraction).
This is defined as the ratio of net annual withdrawal (draft) to total utilisable
recharge. The criterion of calculating the level of groundwater development
has been changing from time to time. In the present study, we have employed
the 1984 criterion. If in a taluka or district, the net annual draft of
groundwater is more than 100 per cent of the utilisable recharge, then it is
said to be overexploited; if it is 85–100 per cent, then it is said to be dark; if it
is 65–85 per cent, it is said to be grey; and if it is less than 65 per cent, it is
said to be white. According to the 2002 estimates of GWRDC, in five
districts (Ahmedabad, Banaskantha, Gandhinagar, Mahesana, and Patan) out
of the total number of 25 districts, the gross annual withdrawals exceed the
utilisable groundwater recharge, and hence they are said to be overexploited
districts. There are two dark and six grey districts. In the remaining 12
districts, the gross withdrawal is below 65 per cent of the utilisable annual
recharge, i.e. they are white. The categories described in the present paper
may differ from the ones officially reported by GWRDC due to the
multiplicity of criteria. However, both are derived from the same raw data.
Salinity ingression in coastal regions: Salinity ingression is evidence of the
problems caused by the disruption of the natural hydrological balance
24
between freshwater and seawater in coastal areas. The problem occurs
because of many reasons: inundation of coastal depressions by tidal water
entering through coastal creeks; inherent salinity of groundwater in marine
gaj formations (i.e. layers of tertiary clay and limestone), which form a major
aquifer in the coastal tract; intrusion of seawater into freshwater aquifers due
to the reversal of the groundwater gradient resulting from excessive pumping
from coastal aquifers; irrigation with saline water; and salt-laden winds (GEC
2005). While seawater ingress is a major problem in the entire coastal belt of
Gujarat, the entire coastline of Saurashtra with its several creeks forms the
main front of salinity ingress. Tidal water enters the coastal plains up to a
distance of 2–6 kilometres because of topographical depressions. On the
other hand, the coastal alluvial tract (consisting of recent alluvium) is also
highly prone to intrusion due to its highly permeable nature. The groundwater
in these formations is brackish, and the system for groundwater extraction is
poorly developed.
Waterlogging and command area salinity: Surface inundation and rise in the
water table are the two forms of waterlogging in irrigation command areas.
The resulting increase in salinity is the major negative environmental
consequence of those canal irrigation schemes that have inadequate
provisions for drainage management. Without proper drainage management,
the groundwater level rises due to excessive seepage and percolation.
Overuse of irrigation water has been identified as one of the major causes of
waterlogging-induced salinity in the Ukai–Kakrapar irrigation projects
(Khandelwal et al. 1996). Similar is the case with the Mahi-Kadana irrigation
project (Patel and Bhrambhatt 1991). The problem of waterlogging affects
crops when the water table rises up to the root zone of crops (generally 1.5 to
3 metres). Salts tend to be deposited in the soil as water evaporates in
waterlogged areas where the water contains high levels of dissolved salts.
Increasing levels of fluorides, nitrates, and TDS in groundwater: The quality
of groundwater is monitored by the Gujarat Water Supply and Sewerage
Board (GWSSB) in all the districts of Gujarat through a survey of selected
villages. As per the standards of the World Health Organisation (WHO), the
25
permissible level of fluorides in potable water is 1.5 ppm. When the fluoride
content in groundwater exceeds 1.5 ppm or 1.5 mg per litre, the well water
becomes unsuitable for drinking. According to a survey conducted in 1995–
96 by the Government of Gujarat (1996), a total of 2,836 villages in the state
faced the problem of high fluorides in groundwater. High levels of fluorides
are mostly found in the deep confined aquifers of the alluvial parts of north
and central Gujarat. Fluoride contamination is a major problem in Saurashtra
and north Gujarat. Similar is the case with nitrate concentrations.
As per GWSSB sources, high levels of TDS and salinity in groundwater have
affected large parts of the state. High levels of TDS in groundwater, like high
fluoride levels, are found in the alluvial areas of north and central Gujarat.
The TDS content in groundwater is found to be higher in deeper aquifers. In
the groundwater discharge areas, high levels of TDS and salinity are
encountered in shallow aquifers as well. According to FAO standards, the
permissible level of TDS in water used for irrigating conventional crops is
1,500 ppm, with a maximum permissible level of 2,000 ppm. The permissible
level of TDS in water used for drinking is 500 ppm, with a maximum
permissible level of 1,000 ppm. Furthermore, a clear pattern is emerging with
respect to spatial variation in TDS. TDS increases towards the south-western
parts of Mehsana and the western parts of Banaskantha district. TDS in
groundwater is generally high in the alluvial belt. TDS in groundwater is
enormously high along the coastal belt of Saurashtra. This is mainly due to
coastal salinity, which is the result of several complex phenomena.
6.2 Socio-economic Status of Gujarat
Though Gujarat has less than 5 per cent of the national population, it has 6.56
per cent of GDP and about 11 per cent of the national industrial output
(Government of Gujarat 1997). The state economy, however, is peculiar in
some ways. On the one hand, it has a high per capita income, 35 per cent
higher than the all-India average (Rs 3,717 in 1996–97 as against Rs 2,761
for India, both at 1980–81 prices). However, this measure can not be
considered satisfactory because the primary sector, particularly agriculture,
26
has lagged far behind, with almost stagnant long-term growth, since the
1980s (Hirway 2002; Hirway and Terhal 2002).
Gujarat has succeeded in reducing the incidence of poverty to a considerable
extent, from 46.35 per cent in 1972–73 to 16.75 per cent in 2004–05. The
eastern belt, inhabited by tribal people, is the poorest in rural, urban, as well
as in total poverty. It seems that the tribal population is the poorest section in
the state. As far as urban poverty is concerned, the southern plains area,
which is considered to be ‗the golden corridor‘ of industries, is the least poor
region (Hirway 2002). However, the rural areas of this golden corridor are
also very poor. In other words, industrial development has helped the urban
population, but not so much the rural population of this region.
Since health and education are two important components of human
development, we will examine the performance of Gujarat in these two
sectors. Many health and equity indicators are shown in Table-1. Life
expectancy at birth (LEB) and infant mortality rate (IMR) are two reliable
indicators of the health of a population. Gujarat ranks low in both these
indicators. Although LEB and IMR in Gujarat are slightly higher than the
national average, the state nevertheless has a long way to go before it can
achieve the level of Kerala (Table-1).
The rural population in Gujarat has an alarmingly low level of calorie intake,
which is much lower than the national average (Table-1). Over 23 per cent of
rural households do not have access to safe drinking water (Table-1).
Anaemia among children (below 3 years) and among women (15–49 years) is
almost equivalent to that of the national average. As per the Planning
Commission‘s annual plan 2005–06, 874 rural habitations are partially
covered and 56 habitations are not covered under the drinking water supply
network in Gujarat (Planning Commission 2006). The literacy rate of Gujarat
is 58.53 per cent, which is much lower than that of Kerala (90.2 per cent).
The gross enrolment ratio in Gujarat is higher than the national average.
However, the state has a long way to go before it can achieve the level of
Himachal Pradesh (Table-2). Gujarat must accomplish much more before it
27
can attain the levels of the best-performing states in India in all of these
health and equity parameters.
6.3 Construction of SLSI at the District Level in Gujarat
Given the evaluation context, the selection of suitable variables, and the
collection of data, there are three steps involved in the construction of SLSI: (i)
identification of three scales, one each for the evaluation of ecological security,
economic efficiency, and social equity; (ii) calculation of three indices, i.e. ESI,
EEI, and SEI, for each entity; and (iii) derivation of the overall SLSI related to
each entity by combining the three indices.
Table-1: Health and Equity Status of Gujarat
(Except LBE, IMR and ECPR, all figures are in percentage)
Parameters Year Gujarat India Best
Values
Best Perfor-
ming State
Life expectancy at birth (LBE)a
Male 2001–06 63.1 64.1 71.7 Kerala
Female 2001–06 64.1 65.4 75 Kerala
Infant mortality rate (IMR)b
Male 2005 52 56 14 Kerala
Female 2005 55 61 15 Kerala
Total 2005 54 58 14 Kerala
Effective couple protection rate
(ECPR)c 2000 52.8 46.2 65.5 Punjab
Deficient calorie intake in rural areasd
Household consuming <1890
kcal 1997 20.4 13.4 6.3 Punjab
Household consuming <2400
kcal 1997 53.7 42.0 27.6 Punjab
Underweight and anaemia
Underweight children under 3
years of age 2005–06 47.4 45.9 28.8 Kerala
Anaemic children under 3 years
of age 2005–06 80.1 79.2 55.7 Kerala
Anaemic women 15-49 years of 2005–06 55.5 56.2 32.3 Kerala
28
age
Equity parameters
Rural household with safe
drinking waterf
2001 76.9 73.2 96.9 Punjab
Population below poverty lineg 1993–94 24.92 36.02 13.14 Punjab
Population below poverty lineh 2004–05 16.75 28.27 8.12 Punjab
Note: Best values are compared amongst major Indian states in terms of population and size. Some of
the smaller states and union territory are performing still better in many cases Sources:
a MHFW 2002 b MHFW 2005 c CSO 2001 d NIPCCD 2005 e Lok Sabha 2007 f Ministry of Finance 2006 g Planning Commission 2001 h Dev and Ravi 2007
Table-2: Educational Status of Gujarat
Parameters Year Gujara
t India
Best
Values
Best Performing
State
Literacy ratea
Male 2001 70.71 71.18 93.54 Kerala
Female 2001 45.75 46.58 86.79 Kerala
Total 2001 58.53 59.21 90.05 Kerala
Gross enrolment ratiob
Boys 2003–04 32.93 30.08 61.03 Himachal Pradesh
Girls 2003–04 22.18 21.79 55.07 Himachal Pradesh
Total 2003–04 27.84 26.22 58.12 Himachal Pradesh
Note: Best values are compared amongst major Indian states in terms of population and size.
Sources:
a Planning Commission 2001
b MHRD 2003
29
6.3.1 Rationale for Variable Selection
Based on ecological as well as socio-economic status, and the availability of
district-wise data, we have selected the following indicators for the
construction of SLSI:
Ecological security indicators: forest cover, water quality unaffected
habitations (i.e. habitations that are not affected by pollutants such as
fluorides, nitrates, and brackishness), and groundwater recharge
potential;
Economic efficiency indicators: total food grain yield, milk yield, and net
sown area;
Social equity indicators: percentage of population above poverty line,
female literacy, maternal survival rate, per capita food grain production,
and per capita milk production.
Sources of the raw data used for the construction of SLSI are shown in Table-
3. Forest areas play an important role in the sustenance of watersheds and
thereby in enhancing livelihoods. Both the economic and ecological functions
of forests help people in sustaining their
Table-3: Sources of Data Used for Constructing SLSI in Gujarat
Sr.
No. Data Type Year Source
1 Forest cover (%) 2001–02 FSI 2005 2 Water quality unaffec-ted
habitations (%) 2003 Gujarat Water Supply and Sewerage Board,
Government of Gujarat 3 Recharge potential (%)
(recharge to draft ratio) 2002 Gujarat Water Resource Development
Corporation (GWRDC) 4 Total food grain yield
(kg/ha) 2003–04 Directorate of Agriculture, Government of
Gujarat 5 Milk yield (kg/day) 2004–05 NDDB (National Dairy Development
Board) 6 Net sown area (%) 2003–04 Directorate of Agriculture, Government of
Gujarat 7 Above poverty line
(APL) population (%) NA Department of Rural Development,
Government of Gujarat 8 Female literacy rate 2001 Census of India (accessed through
http://www.indiastat.com on January 2, 2008)
9 Maternal survival rate NA Health Department, Government of
30
(1000 minus MMR) Gujarat 10 Per capita food grain
production (kg) – Rural population
2003–04 Directorate of Agriculture, Government of Gujarat
11 Per capita milk production (kg) – Rural population
2004–05 NDDB (National Dairy Development Board)
Note: Except Sr. 1 and 8, data have been collected directly from the sources.
livelihoods. Habitations that are not affected by pollutants such as fluorides,
nitrates, and brackishness ensure better health for the habitants and help
people in sustaining their livelihoods. Groundwater recharge potential, which
is the ratio of gross annual recharge to gross annual draft of groundwater,
thus can be understood as being the opposite of groundwater development. It
signifies that groundwater is available for future use. Recharge potential of
groundwater serves not only as an indicator of ecological security but also as
an indicator of intergenerational equity of the SD paradigm.
For evaluating the economic efficiency of the agricultural systems of districts,
the variable land productivity measure was selected. Total food grain yield,
which is the ratio of total food (cereals plus pulses) to the food grain area, is
essentially an efficiency parameter of food production. Similarly, milk yield,
which is the ratio of total milk production to the number of total milch
animals, is essentially an efficiency parameter of milk production. Food grain
yield and milk yield not only capture the physical performance of soil
productivity, biochemical technologies, and yield of milch animals but also the
potential for the overall food and nutritional security of the districts. Net sown
area represents the comparable agricultural land base for farm-based
production systems.
The percentage of the population above the poverty line is calculated as 100
minus the percentage of the population below the poverty line. It signifies
income, asset ownership, food consumption, employment, sanitation
facilities, house type, indebtedness, etc. It shows how equitably the resources
are distributed across the population. Female literacy captures not only
women‘s social and economic participation but also population stabilisation.
Maternal survival rate, which is calculated as 1,000 minus the maternal
31
mortality rate, signifies the general health condition of the population. Per
capita food grain production and per capita milk production for the rural
population reveal how equitably the basic food items are distributed across
the rural population.
6.3.2 Procedure for the Construction of SLSI
The indices for all the representative variables with the exception of the forest
cover variable were calculated by a straightforward application of equation [1]
to the values of the selected indicators (see Table-4). The values of the indices
for the indicators are shown in Table-5. Since forest occurrence and growth is
governed by geophysical conditions, the ‗critical minimum‘ forest cover
essential for ensuring ecological security will vary depending upon the
geophysical condition of the district. For instance, FAO has suggested that the
critical minimum forest cover should be 20 per cent, 33.3 per cent, and 66.6 per
cent for the plains regions, plateau and hill regions, and mountainous regions
respectively (Government of India 1952). Whenever the actual forest cover is
greater than or equal to the
32
Table-4: Raw Data Used for the Calculation of SLSI in Gujarat
Ecological Security Indicators Economic Efficiency
Indicators Social Security Indicators
District Forest cover (%)
Water quality
unaffected habitations
(%)
Recharge potential
(%)
Total food grain yield
(kg/ha)
Milk yield (kg/ day)
Net sown area (%)
APL popu-lation (%)
Female literacy
rate
Maternal survival
rate
Food grain production per capita of rural
population (kg/yr)
Milk produc-tion per
capita of rural population
(kg/yr)
Ahmedabad 2 64 94 1,769 2.3 62.6 99 42 919 370 216
Amreli 3.2 67 150 1,665 2.8 73.3 93 42 941 105 202
Anand 1.9 68 184 1,911 2.8 60.7 94 40 801 266 235
Banaskantha 8.7 62 86 1,093 3.1 68 95 33 914 170 269
Bharuch 5.3 76 179 852 2.5 50.1 92 42 803 101 121
Bhavnagar 2.9 68 159 1,665 2.6 55.8 97 40 926 83 194
Dahod 16 76 165 950 1.3 18.9 79 40 802 197 127
Dangs 80.4 100 493 1,341 0.4 15.9 88 34 905 303 18
Gandhinagar 6.8 51 55 2,190 2.9 73.7 94 41 908 181 240
Jamnagar 2.6 62 173 1,480 2.7 42.7 94 41 925 102 207
Junagadh 19.4 57 142 2,939 2.8 59.7 96 41 954 228 193
Kaira 2.6 79 112 1,961 2.4 71.1 95 40 835 320 160
Kutch 5 60 152 717 2.3 9.9 95 38 933 124 306
Mahesana 2.8 52 67 1,592 4.1 79.3 98 41 915 126 434
Narmada 39 91 318 1,072 1.7 40.3 86 38 898 115 97
Navsari 14.2 96 215 2,002 3.3 66.9 94 44 947 130 151
Panchmahals 12.9 57 171 860 1.9 52.3 87 36 999 125 149
Patan 3 38 75 989 3.4 66.6 96 37 884 117 341
Porbandar 4.9 21 118 1,916 3.4 50.2 97 42 897 148 373
Rajkot 1.3 27 143 1,991 3 66.4 97 43 955 119 228
Sabarkantha 10.8 67 121 1,256 2.8 59.7 89 38 964 165 308
Surat 17.7 90 276 1,499 3 55.4 95 40 992 126 186
Surendranagar 1.6 52 157 1,322 2.5 65.7 95 38 950 137 194
Vadodara 8.1 73 148 1,075 2.1 67.5 95 41 866 130 146
33
Valsad 32.9 98 233 1,530 2.7 53.1 79 41 999 106 106
34
Table-5: Indices Values of the Sustainability Indicators
Ecological Indices Economic Indices Social Indices
District Forest
index
Water quality
index
Recharge potential
index
ESI
value
Food
grain
yield index
Milk yield
index
NSA
index
EEI
value
APL
index
Female literacy
index
Maternal survival
index
Per capita food
grain
production index
Per capita
milk
production index
SEI
value
Ahmedabad 0.04 0.54 0.09 0.22 0.48 0.53 0.76 0.59 1.00 0.82 0.60 1.00 0.48 0.78
Amreli 0.10 0.58 0.22 0.30 0.22 0.67 0.91 0.60 0.71 0.82 0.71 0.08 0.44 0.55
Anand 0.03 0.59 0.29 0.30 0.76 0.65 0.73 0.71 0.74 0.62 0.00 0.64 0.52 0.50
Banaskantha 0.40 0.52 0.07 0.33 0.27 0.75 0.84 0.62 0.79 0.00 0.57 0.30 0.60 0.45
Bharuch 0.21 0.70 0.28 0.40 0.27 0.57 0.58 0.47 0.66 0.80 0.01 0.06 0.25 0.36
Bhavnagar 0.08 0.60 0.24 0.31 0.37 0.61 0.66 0.55 0.92 0.59 0.63 0.00 0.42 0.51
Dahod 0.46 0.70 0.25 0.47 0.32 0.24 0.13 0.23 0.00 0.67 0.01 0.40 0.26 0.27
Dangs 1.00 1.00 1.00 1.00 0.23 0.00 0.09 0.11 0.46 0.16 0.53 0.77 0.00 0.38
Gandhinagar 0.29 0.39 0.00 0.23 0.44 0.67 0.92 0.68 0.78 0.68 0.54 0.34 0.53 0.58
Jamnagar 0.07 0.52 0.27 0.29 0.28 0.63 0.47 0.46 0.77 0.73 0.63 0.07 0.45 0.53
Junagadh 0.97 0.46 0.20 0.54 0.64 0.66 0.72 0.67 0.85 0.70 0.77 0.51 0.42 0.65
Kaira 0.07 0.73 0.13 0.31 0.40 0.55 0.88 0.61 0.82 0.59 0.17 0.82 0.34 0.55
Kutch 0.20 0.49 0.22 0.30 0.29 0.53 0.00 0.27 0.80 0.47 0.67 0.14 0.69 0.55
Mahesana 0.08 0.39 0.03 0.17 1.00 1.00 1.00 1.00 0.94 0.73 0.58 0.15 1.00 0.68
Narmada 1.00 0.89 0.60 0.83 0.30 0.35 0.44 0.36 0.33 0.45 0.49 0.11 0.19 0.32
Navsari 0.40 0.95 0.37 0.57 0.01 0.79 0.82 0.54 0.75 1.00 0.74 0.16 0.32 0.59
Panchmahals 0.62 0.45 0.26 0.45 0.30 0.43 0.61 0.44 0.41 0.27 1.00 0.15 0.32 0.43
Patan 0.09 0.22 0.05 0.12 0.30 0.83 0.82 0.65 0.85 0.40 0.42 0.12 0.78 0.51
Porbandar 0.19 0.00 0.14 0.11 0.23 0.83 0.58 0.55 0.91 0.77 0.48 0.23 0.85 0.65
Rajkot 0.00 0.08 0.20 0.10 0.16 0.72 0.81 0.57 0.91 0.86 0.78 0.12 0.51 0.64
Sabarkantha 0.51 0.59 0.15 0.42 0.43 0.67 0.72 0.60 0.52 0.50 0.82 0.29 0.70 0.57
Surat 0.88 0.88 0.50 0.75 0.22 0.72 0.66 0.53 0.81 0.66 0.96 0.15 0.40 0.60
Surendranagar 0.02 0.39 0.23 0.21 0.34 0.57 0.80 0.57 0.80 0.43 0.75 0.19 0.42 0.52
Vadodara 0.36 0.65 0.21 0.41 0.94 0.46 0.83 0.74 0.81 0.74 0.33 0.16 0.31 0.47
Valsad 0.99 0.97 0.41 0.79 0.31 0.63 0.62 0.52 0.00 0.74 1.00 0.08 0.21 0.41
35
critical minimum forest cover, the forest cover index will be one. Otherwise, the
index is based on the region-specific scale defined by the range.
The three component indices of SLSI, i.e. the ecological security index (ESI),
the economic efficiency index (EEI), and the social equity index (SEI), are
calculated by taking the equal weights of the indices of the respective
representative variables. In calculating these indices, we have assumed equal
weights. SLSI, which is a composite index, was calculated by taking the
arithmetic mean of its component indices following equation [2], since we
have no reason to believe that one component index on SLSI is more
important than the others.
All the indices were mapped using the ArcGIS 9.1 geographic information
system (GIS) software of ESRI. For purposes of analysis, the results were
categorised by quintile based on a relative sustainability ranking within each
indicator. Quintile is deemed to be an appropriate level of aggregation with
which to achieve the goal of discerning gross differences between the
variables.
While the SLSI methodology is simple and conceptually sound, it faces the
same problems often encountered in the construction of any composite index,
such as the choice of the component variables and the identification of
appropriate weights for its different components. Within the data constraints,
the variable choice becomes more of an art than a science. Naturally, the
SLSI constructed by two individuals with differential preferences will not be
the same, and this is also the case in the evaluation of sustainability. In this
sense, it is more appropriate to consider SLSI as an approach to a measure
rather than a measure in itself (Saleth and Swaminathan 1993). The most
serious limitation of the SLSI methodology is that it provides only a relative
rather than an absolute indicator. Thus, it helps only in establishing the
ranking among a given set of entities but does not say ‗how much‘ an entity
has performed compared to others. Hence, the policy-induced changes in the
SLS status could not be measured in any quantitative sense (ibid.).
36
6.3.3 Relative SLS Status of the Districts and their Policy Relevance
While SLSI gives the overall relative performance of a district in Gujarat, the
component indices (i.e. ESI, EEI, and SEI) indicate how a district fares in the
three dimensions of sustainability. SLSI and its component indices (ESI, EEI,
and SEI) at the district level are presented in Table-6 and Figure-3. The
ranking of districts in decreasing order of the values of SLSI and its
component indices is given in Table-7. The SLSI methodology identifies not
only the general priorities but also the nature and type of policies to be pursued
in each district in order to enhance its SLS status.
Dahod district has the lowest SLSI ranking because of its very low EEI and
SEI rankings. Hence, economic development and social development require
special attention in Dahod. Kutch district has an SLSI ranking second from
the bottom because of low EEI and ESI rankings, thus warranting special
attention for improving the economic and ecological status of the district.
Although Dangs district has the highest ESI ranking, it has the lowest
position in EEI and the 22nd
position in SEI, which essentially requires policy
intervention for both economic and social development in the district. In
Narmada district also, the ecological security is very high but the SEI and
EEI status rankings are low, thus requiring policy intervention to achieve
both economic and social development. Mehsana district has the highest
ranking in EEI but the 22nd
position in ESI. Similarly, Ahmedabad has the
highest ranking in SEI but the 20th
position in ESI. Hence, unless proper
ecological restoration in both Mehsana and Ahmedabad is initiated, the
livelihood security of these two districts will not be sustainable in the long
run. Although Surat district has the highest ranking in SLSI, it has the 17th
position in EEI. The poor performance of the eastern tribal talukas of Surat
district in the economic dimension is responsible for its lower EEI ranking.
37
Table-6: District-wise Ranking of the ESI, EEI, SEI and SLSI
District
ESI EEI SEI SLSI
ESI
value
ESI
rank
EEI
value
EEI
rank
SEI
value
SEI
rank
SLSI
value
SLSI
rank
Surat 0.75 4 0.53 17 0.6 6 0.63 1
Junagadh 0.54 6 0.67 5 0.65 3 0.62 3
Mahesana 0.17 22 1 1 0.68 2 0.62 2
Valsad 0.79 3 0.52 18 0.41 21 0.57 5
Navsari 0.57 5 0.54 16 0.59 7 0.57 4
Vadodara 0.41 10 0.74 2 0.47 18 0.54 6
Sabarkantha 0.42 9 0.6 9 0.57 9 0.53 8
Ahmedabad 0.22 20 0.59 11 0.78 1 0.53 7
Anand 0.3 15 0.71 3 0.5 17 0.51 9
Dangs 1 1 0.11 25 0.38 22 0.5 10
Narmada 0.83 2 0.36 22 0.32 24 0.5 11
Kaira 0.31 13 0.61 8 0.55 10 0.49 13
Gandhinagar 0.23 19 0.68 4 0.58 8 0.49 12
Amreli 0.3 16 0.6 10 0.55 11 0.48 14
Banaskantha 0.33 12 0.62 7 0.45 19 0.47 15
Bhavnagar 0.31 14 0.55 15 0.51 15 0.46 16
Panchmahals 0.45 8 0.44 21 0.43 20 0.44 18
Porbandar 0.11 24 0.55 14 0.65 4 0.44 17
Jamnagar 0.29 18 0.46 20 0.53 13 0.43 20
Surendranagar 0.21 21 0.57 13 0.52 14 0.43 21
Patan 0.12 23 0.65 6 0.51 16 0.43 22
Rajkot 0.1 25 0.57 12 0.64 5 0.43 19
Bharuch 0.4 11 0.47 19 0.36 23 0.41 23
Kutch 0.3 17 0.27 23 0.55 12 0.38 24
Dahod 0.47 7 0.23 24 0.27 25 0.32 25
38
Figure-3:
ESI, EEI, SEI and SLSI Maps of Gujarat
39
Table 7: Ranking of Districts in Decreasing Order of Various Indices
Rank ESI Ranking EEI Ranking SEI Ranking SLSI Ranking
1 Dangs Mahesana Ahmedabad Surat
2 Narmada Vadodara Mahesana Mahesana
3 Valsad Anand Junagadh Junagadh
4 Surat Gandhinagar Porbandar Navsari
5 Navsari Junagadh Rajkot Valsad
6 Junagadh Patan Surat Vadodara
7 Dahod Banaskantha Navsari Ahmedabad
8 Panchmahals Kaira Gandhinagar Sabarkantha
9 Sabarkantha Sabarkantha Sabarkantha Anand
10 Vadodara Amreli Kaira Dangs
11 Bharuch Ahmedabad Amreli Narmada
12 Banaskantha Surendranagar Kutch Gandhinagar
13 Kaira Rajkot Jamnagar Kaira
14 Bhavnagar Bhavnagar Surendranagar Amreli
15 Anand Porbandar Patan Banaskantha
16 Amreli Navsari Bhavnagar Bhavnagar
17 Kutch Surat Anand Porbandar
18 Jamnagar Valsad Vadodara Panchmahals
19 Gandhinagar Bharuch Banaskantha Rajkot
20 Ahmedabad Jamnagar Panchmahals Jamnagar
21 Surendranagar Panchmahals Valsad Surendranagar
22 Mahesana Narmada Dangs Patan
23 Patan Kutch Bharuch Bharuch
24 Porbandar Dahod Narmada Kutch
25 Rajkot Dangs Dahod Dahod
If we look at the regional pattern (Figure-3), the central part of Gujarat is
relatively good in terms of economic efficiency and social equity, but it has a
very poor ecological security status, warranting ecological restoration work in
40
this part of the state. The eastern tribal belt of Gujarat in general scores high
in ESI but very low in EEI and SEI. Hence, the tribal belt of the state requires
special intervention to bring about economic and social development. The
eastern periphery of Gujarat has 43 tribal talukas, accounting for 15 per cent
of the state‘s total population; this area lacks mainly in the economic and
equity dimensions. Further analysis of SLSI at the taluka level will bring out
such details more effectively.
7.0 CONCLUSIONS
SLSI could prove a powerful tool for verifying the necessary conditions for
sustainable development in a functional unit of development planning. As a
policy tool, SLSI identifies not only the districts requiring immediate
attention but also the specific thematic areas in which the efforts could be
focused to attain livelihood security. For instance, the Dangs district has the
highest ESI ranking, but it has the lowest position in EEI and the 22nd
position in SEI, requiring policy intervention for improving the EEI and SEI
status in the district. SLSI helps to focus on the conflicts and the potential
synergy between ecology, economics, and the equity dimensions of SD. SLSI
can also function as an educational and policy tool promoting a holistic
perspective among planners, administrators, and development workers.
Construction of SLSI using time series data could help in improving the
progress of different development interventions over a period of time aimed
at SD in general and at livelihood security in particular.
Acknowledgements
We thank the Sir Dorabji Tata Trust, Mumbai for providing funding support for the
study. Gujarat Water Supply and Sewerage Board, Gujarat Water Resource
Development Corporation, Directorate of Agriculture, Government of Gujarat,
Health Department, Government of Gujarat, Department of Rural Development,
Government of Gujarat, and National Dairy Development Board are duly
acknowledged for providing the necessary data for the study.
41
Endnotes
1 Gujarat is divided into 25 districts for administrative purposes, which are further
subdivided into 265 sub-districts (talukas). The human population of the districts
varies considerably. With an overall human population of over 50 million in
Gujarat, the average population of a district is around 2 million.
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Table 1:
Health and Equity Status of Gujarat
(Except LBE, IMR and ECPR, all figures are in percentage)
Parameters Year Gujarat India Best
values
Best
performing
state
Life expectancy at birth (LBE)a
Male 2001-06 63.1 64.1 71.7 Kerala
Female 2001-06 64.1 65.4 75 Kerala
Infant mortality rate (IMR)b
Male 2005 52 56 14 Kerala
Female 2005 55 61 15 Kerala
Total 2005 54 58 14 Kerala
Effective couple protection rate
(ECPR)c 2000 52.8 46.2 65.5 Punjab
Deficient calorie intake in rural areasd
Household consuming <1890
kcal 1997 20.4 13.4 6.3 Punjab
Household consuming <2400
kcal 1997 53.7 42.0 27.6 Punjab
Underweight and anemiae
Underweight children under 3
years of age 2005-06 47.4 45.9 28.8 Kerala
Anemic children under 3 years
of age 2005-06 80.1 79.2 55.7 Kerala
Anemic women 15-49 years of
age 2005-06 55.5 56.2 32.3 Kerala
Equity parameters
Rural household with safe
drinking waterf
2001 76.9 73.2 96.9 Punjab
Population below poverty lineg 1993-94 24.92 36.02 13.14 Punjab
Population below poverty lineh 2004-05 16.75 28.27 8.12 Punjab
Note: Best values are compared amongst major Indian states in terms of population and size. Some of
the smaller states and union territory are performing still better in many cases Sources: a MHFW , 2002 b MHFW , 2005 c CSO, 2001 d NIPCCD, 2005 e Lok Sabha, 2007 f Ministry of Finance, 2006 g Planning Commission, , 2001 h Dev and Ravi, 2007
38
Table 2: Educational Status of Gujarat
Parameters Year Gujara
t India
Best
values
Best performing
state
Literacy ratea
Male 2001 70.71 71.18 93.54 Kerala
Female 2001 45.75 46.58 86.79 Kerala
Total 2001 58.53 59.21 90.05 Kerala
Gross enrollment ratiob
Boys 2003-04 32.93 30.08 61.03 Himachal Pradesh
Girls 2003-04 22.18 21.79 55.07 Himachal Pradesh
Total 2003-04 27.84 26.22 58.12 Himachal Pradesh
Note: Best values are compared amongst major Indian states in terms of population and size.
Sources:
a Planning Commission 2001
b MHRD 2003
Table 3: Sources of Data used for Constructing SLSI in Gujarat
Sr.
No. Data Type Year Source
1 Forest cover (%) 2001-02 FSI 2005 2 Water quality unaffected
habitations (%) 2003 Gujarat Water Supply and Sewerage
Board, Government of Gujarat 3 Recharge potential (%)
(recharge to draft ratio) 2002 Gujarat Water Resource Development
Corporation (GWRDC) 4 Total Food grain Yield (kg/ha) 2003-04 Directorate of Agriculture,
Government of Gujarat 5 Milk yield (kg/day) 2004-05 NDDB (National dairy Development
Board) 6 Net sown area (%) 2003-04 Directorate of Agriculture,
Government of Gujarat 7 Above poverty line (APL)
population (%) Department of Rural Development,
Government of Gujarat 8 Female literacy rate 2001 Census of India (accessed through
“http://www.indiastat.com on January 2, 2008”)
9 Maternal survival rate (1000 minus MMR)
Health Department, Government of Gujarat
10 Per capita food grain produc- tion (kg) - Rural pop
2003-04 Directorate of Agriculture, Government of Gujarat
11 Per capita milk production (kg) - Rural Pop
2004-05 NDDB (National dairy Development Board)
Note: Except Sr. 1 and 8, data is collected directly from the sources
39
Table 6: District-wise Ranking of the ESI, EEI, SEI and SLSI
District ESI EEI SEI SLSI
ESI
value
ESI
Rank
EEI
value
EEI
Rank
SEI
value
SEI
Rank
SLSI
value
SLSI
Rank
Surat 0.75 4 0.53 17 0.6 6 0.63 1
Junagadh 0.54 6 0.67 5 0.65 3 0.62 3
Mahesana 0.17 22 1 1 0.68 2 0.62 2
Valsad 0.79 3 0.52 18 0.41 21 0.57 5
Navsari 0.57 5 0.54 16 0.59 7 0.57 4
Vadodara 0.41 10 0.74 2 0.47 18 0.54 6
Sabarkantha 0.42 9 0.6 9 0.57 9 0.53 8
Ahmadabad 0.22 20 0.59 11 0.78 1 0.53 7
Anand 0.3 15 0.71 3 0.5 17 0.51 9
Dangs 1 1 0.11 25 0.38 22 0.5 10
Narmada 0.83 2 0.36 22 0.32 24 0.5 11
Kaira 0.31 13 0.61 8 0.55 10 0.49 13
Gandhinagar 0.23 19 0.68 4 0.58 8 0.49 12
Amreli 0.3 16 0.6 10 0.55 11 0.48 14
Banaskantha 0.33 12 0.62 7 0.45 19 0.47 15
Bhavnagar 0.31 14 0.55 15 0.51 15 0.46 16
Panchmahals 0.45 8 0.44 21 0.43 20 0.44 18
Porbandar 0.11 24 0.55 14 0.65 4 0.44 17
Jamnagar 0.29 18 0.46 20 0.53 13 0.43 20
Surendranagar 0.21 21 0.57 13 0.52 14 0.43 21
Patan 0.12 23 0.65 6 0.51 16 0.43 22
Rajkot 0.1 25 0.57 12 0.64 5 0.43 19
Bharuch 0.4 11 0.47 19 0.36 23 0.41 23
Kutch 0.3 17 0.27 23 0.55 12 0.38 24
Dahod 0.47 7 0.23 24 0.27 25 0.32 25
35
Table 7: Ranking of Districts in Decreasing Order of Various Indices
Rank ESI Ranking EEI Ranking SEI Ranking SLSI Ranking
1 Dangs Mahesana Ahmadabad Surat
2 Narmada Vadodara Mahesana Mahesana
3 Valsad Anand Junagadh Junagadh
4 Surat Gandhinagar Porbandar Navsari
5 Navsari Junagadh Rajkot Valsad
6 Junagadh Patan Surat Vadodara
7 Dahod Banaskantha Navsari Ahmadabad
8 Panchmahals Kaira Gandhinagar Sabarkantha
9 Sabarkantha Sabarkantha Sabarkantha Anand
10 Vadodara Amreli Kaira Dangs
11 Bharuch Ahmadabad Amreli Narmada
12 Banaskantha Surendranagar Kutch Gandhinagar
13 Kaira Rajkot Jamnagar Kaira
14 Bhavnagar Bhavnagar Surendranagar Amreli
15 Anand Porbandar Patan Banaskantha
16 Amreli Navsari Bhavnagar Bhavnagar
17 Kutch Surat Anand Porbandar
18 Jamnagar Valsad Vadodara Panchmahals
19 Gandhinagar Bharuch Banaskantha Rajkot
20 Ahmadabad Jamnagar Panchmahals Jamnagar
21 Surendranagar Panchmahals Valsad Surendranagar
22 Mahesana Narmada Dangs Patan
23 Patan Kutch Bharuch Bharuch
24 Porbandar Dahod Narmada Kutch
25 Rajkot Dangs Dahod Dahod
37
Table 4: Raw Data used for the Calculation of SLSI in Gujarat
Ecological Security Indicators Economic Efficiency
Indicators Social Security Indicators
District Forest cover (%)
Water quality
unaffected habitations
(%)
Recharge potential
(%)
Total food grain yield
(kg/ha)
Milk yield (kg/ day)
Net sown area (%)
APL popu-lation (%)
Female literacy
rate
Maternal survival
rate
Food grain production per capita of rural
population (kg/yr)
Milk produc-tion per
capita of rural population
(kg/yr)
Ahmadabad 2 64 94 1769 2.3 62.6 99 42 919 370 216
Amreli 3.2 67 150 1665 2.8 73.3 93 42 941 105 202
Anand 1.9 68 184 1911 2.8 60.7 94 40 801 266 235
Banaskantha 8.7 62 86 1093 3.1 68 95 33 914 170 269
Bharuch 5.3 76 179 852 2.5 50.1 92 42 803 101 121
Bhavnagar 2.9 68 159 1665 2.6 55.8 97 40 926 83 194
Dahod 16 76 165 950 1.3 18.9 79 40 802 197 127
Dangs 80.4 100 493 1341 0.4 15.9 88 34 905 303 18
Gandhinagar 6.8 51 55 2190 2.9 73.7 94 41 908 181 240
Jamnagar 2.6 62 173 1480 2.7 42.7 94 41 925 102 207
Junagadh 19.4 57 142 2939 2.8 59.7 96 41 954 228 193
Kaira 2.6 79 112 1961 2.4 71.1 95 40 835 320 160
Kutch 5 60 152 717 2.3 9.9 95 38 933 124 306
Mahesana 2.8 52 67 1592 4.1 79.3 98 41 915 126 434
Narmada 39 91 318 1072 1.7 40.3 86 38 898 115 97
Navsari 14.2 96 215 2002 3.3 66.9 94 44 947 130 151
Panchmahals 12.9 57 171 860 1.9 52.3 87 36 999 125 149
Patan 3 38 75 989 3.4 66.6 96 37 884 117 341
Porbandar 4.9 21 118 1916 3.4 50.2 97 42 897 148 373
Rajkot 1.3 27 143 1991 3 66.4 97 43 955 119 228
Sabarkantha 10.8 67 121 1256 2.8 59.7 89 38 964 165 308
Surat 17.7 90 276 1499 3 55.4 95 40 992 126 186
Surendranagar 1.6 52 157 1322 2.5 65.7 95 38 950 137 194
Vadodara 8.1 73 148 1075 2.1 67.5 95 41 866 130 146
Valsad 32.9 98 233 1530 2.7 53.1 79 41 999 106 106
38
Table 5: Indices Values of the Sustainability Indicators Ecological Indices Economic Indices Social indices
District Forest
index
Water quality
index
Recharge potential
index
ESI
value
Food
grain
yield index
Milk yield
index
NSA
index
EEI
value
APL
index
Female literacy
index
Maternal survival
index
Per capita food
grain
production index
Per capita
milk
produc- tion index
SEI
value
Ahmadabad 0.04 0.54 0.09 0.22 0.48 0.53 0.76 0.59 1.00 0.82 0.60 1.00 0.48 0.78
Amreli 0.10 0.58 0.22 0.30 0.22 0.67 0.91 0.60 0.71 0.82 0.71 0.08 0.44 0.55
Anand 0.03 0.59 0.29 0.30 0.76 0.65 0.73 0.71 0.74 0.62 0.00 0.64 0.52 0.50
Banaskantha 0.40 0.52 0.07 0.33 0.27 0.75 0.84 0.62 0.79 0.00 0.57 0.30 0.60 0.45
Bharuch 0.21 0.70 0.28 0.40 0.27 0.57 0.58 0.47 0.66 0.80 0.01 0.06 0.25 0.36
Bhavnagar 0.08 0.60 0.24 0.31 0.37 0.61 0.66 0.55 0.92 0.59 0.63 0.00 0.42 0.51
Dahod 0.46 0.70 0.25 0.47 0.32 0.24 0.13 0.23 0.00 0.67 0.01 0.40 0.26 0.27
Dangs 1.00 1.00 1.00 1.00 0.23 0.00 0.09 0.11 0.46 0.16 0.53 0.77 0.00 0.38
Gandhinagar 0.29 0.39 0.00 0.23 0.44 0.67 0.92 0.68 0.78 0.68 0.54 0.34 0.53 0.58
Jamnagar 0.07 0.52 0.27 0.29 0.28 0.63 0.47 0.46 0.77 0.73 0.63 0.07 0.45 0.53
Junagadh 0.97 0.46 0.20 0.54 0.64 0.66 0.72 0.67 0.85 0.70 0.77 0.51 0.42 0.65
Kaira 0.07 0.73 0.13 0.31 0.40 0.55 0.88 0.61 0.82 0.59 0.17 0.82 0.34 0.55
Kutch 0.20 0.49 0.22 0.30 0.29 0.53 0.00 0.27 0.80 0.47 0.67 0.14 0.69 0.55
Mahesana 0.08 0.39 0.03 0.17 1.00 1.00 1.00 1.00 0.94 0.73 0.58 0.15 1.00 0.68
Narmada 1.00 0.89 0.60 0.83 0.30 0.35 0.44 0.36 0.33 0.45 0.49 0.11 0.19 0.32
Navsari 0.40 0.95 0.37 0.57 0.01 0.79 0.82 0.54 0.75 1.00 0.74 0.16 0.32 0.59
Panchmahals 0.62 0.45 0.26 0.45 0.30 0.43 0.61 0.44 0.41 0.27 1.00 0.15 0.32 0.43
Patan 0.09 0.22 0.05 0.12 0.30 0.83 0.82 0.65 0.85 0.40 0.42 0.12 0.78 0.51
Porbandar 0.19 0.00 0.14 0.11 0.23 0.83 0.58 0.55 0.91 0.77 0.48 0.23 0.85 0.65
Rajkot 0.00 0.08 0.20 0.10 0.16 0.72 0.81 0.57 0.91 0.86 0.78 0.12 0.51 0.64
Sabarkantha 0.51 0.59 0.15 0.42 0.43 0.67 0.72 0.60 0.52 0.50 0.82 0.29 0.70 0.57
Surat 0.88 0.88 0.50 0.75 0.22 0.72 0.66 0.53 0.81 0.66 0.96 0.15 0.40 0.60
Surendranagar 0.02 0.39 0.23 0.21 0.34 0.57 0.80 0.57 0.80 0.43 0.75 0.19 0.42 0.52
Vadodara 0.36 0.65 0.21 0.41 0.94 0.46 0.83 0.74 0.81 0.74 0.33 0.16 0.31 0.47
Valsad 0.99 0.97 0.41 0.79 0.31 0.63 0.62 0.52 0.00 0.74 1.00 0.08 0.21 0.41