V. Ratna Reddy *, Sanjit Kumar Rout *, T. Chiranjeevi * and S.S.P. Sharma **

Transcription

1 ARTICLE Performance and Factors Influencing the Impact of Watershed Development Programme in Rajasthan V. Ratna Reddy *, Sanjit Kumar Rout *, T. Chiranjeevi * and S.S.P. Sharma ** Ind. Jn. of Agri.Econ. Vol.67, No.1, Jan.-March 2012 I INTRODUCTION Watershed development is among the flagship programmes of rural development that assist in rural poverty alleviation, particularly in the more marginal semi-arid, rainfed areas. These areas house a large share of the poor, food insecure and vulnerable populations in the country. Moreover, as productivity growth in the more favoured green revolution areas is already showing signs of slowing down or stagnation (Pingali and Rosegrant, 2001), future growth in agricultural production and food security is likely to depend on improving the productivity in the semi-arid rainfed areas (Fan and Hazell, 2000). Watershed development (WSD) as a technology and its management as a philosophy has gained the attention of both social and natural scientists. Research studies undertaken in the 1990s and early 2000s to examine the socio-economic impacts of the watershed technology have endorsed the programme in terms of costs and benefits (Deshpande and Reddy, 1990, Singh et al., 1993, Ninan and Lakshmikantamma, 1994, Singh et al., 1995, Nalatawadmath et al., 1997, Joshi and Bantilan 1997, Reddy, 2000, Kolavalli and Kerr, 2002; Reddy et. al., 2004, Reddy et al., 2010). These studies not only vindicated the economic viability of WSD but also underlined that it is among the most important options for the development of rainfed agriculture in India. In recognition of the socio-economic and bio-physical benefits, India has one of the largest micro-watershed development (WSD) programmes in the world. More than US$4 billion were spent by the central government alone since the beginning of the 8th Plan (1992). About Rs crores is being spent annually through various projects supported by the government, NGOs and bi-lateral funds. The allocations are *Livelihoods and Natural Resource Management Institute, Hyderabad. and **Professor and Head, Centre for Water and Land Resources (CWLR), National Institute of Rural Development (NIRD), Hyderabad , respectively. This paper is part of a major study titled The Impact Assessment Study of Watershed Development Projects in Rajasthan carried out at the instance of National Institute of Rural Development (NIRD), under the Ministry of Rural Development (MoRD), Government of India. Thanks are due to the ministry for the financial support. Our thanks are due to the anonymous referee of the journal for useful comments on the earlier draft of the paper. However, the usual disclaimers apply.

2 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 117 being doubled (crossing Rs crores) during the 11th Plan period with enhanced per hectare investments. 1 The allocations towards WSD in the current annual budget are above Rs crores. However, the cost effectiveness of these allocations and the sustainability of the programme are widely questioned (Government of India, 2001). Several past reviews/studies have critically evaluated the key success factors required for effective watershed development but most of the studies were based on micro evidence from a few watersheds. There were no attempts to assess the performance of the programme on a wider scale for a state as a whole to examine the factors affecting the performance across the states. This is more so in the context of the participatory guidelines introduced during This paper, therefore, attempts to assess the impact of the WSD programmes after the introduction of the 1995 guidelines covering a large sample of watersheds in rainfed Rajasthan. The specific objectives include: (a) Assess the bio-physical, economic and institutional impacts of WSD, (b) Identify factors influencing the performance of watersheds, and (c) Provide policy inputs for improving the performance of WSD. This paper is organised in six sections including this section, which sets the objectives of the paper. The methodology adopted for the study is discussed in Section II. Section III presents the profile of sample districts and the status of watershed development in Rajasthan. The performance of sample watersheds are assessed in Section IV while Section V, which is the core of this paper, identifies the factors influencing the performance across sample watersheds. And the final section draws some policy conclusions. II METHODOLOGY The study is based on a sample of 110 watersheds spread over 15 districts and 25 blocks comprising watersheds implemented under three different schemes, i.e., 60 watersheds implemented under IWDP scheme, 15 under DPAP and 35 under DDP schemes (Table 1). The sampling design to select the districts, number of watersheds and year of sanction of the watershed projects to be covered was determined by the monitoring division, Ministry of Rural Development prior to the commencement of the fieldwork. Watershed Development Projects (WDPs) implemented under DPAP, DDP and IWDP schemes which are sanctioned between April 1, 1998 and March 31, 2002 by Ministry of Rural Development, Government of India were considered for the impact evaluation. The methodological approach adopted in the field involves a survey-based data collection exercise comprising close-ended questionnaires. Three independent sets of questionnaires were used to collect the data, which were developed by at the ministry level. All the three questionnaires were prepared to capture the change due to the advent of WSD in order to understand the impact of the programme in the light of

3 118 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS adaptation to 1995 guidelines. Three questionnaires, viz., (i) Rapid Reconnaissance Survey (RRS) Schedule; (ii) Village Profile (VP) schedule and (iii) Field Survey (FS) Schedule, were canvassed at different levels. Scheme (1) TABLE 1. DISTRIBUTION OF SAMPLE WATERSHEDS ACROSS SCHEMES AND DISTRICTS BY SIZE CLASSES District (2) No of blocks covered (3) No of watersheds covered (4) Year of sanction (5) SMF (per cent) (6) Sample HHs taken LMF (per cent) (7) Total (Nos) (8) IWDP Ajmer Baran Dausa Dholpur Jaipur Rajasamand Sirohi Tonk Udaipur Bundi Total DPAP Sawai Madhopur Tonk Udaipur Total DDP Barmer Bikaner Jaisalmer Jalore Rajasamand Total Overall The Rapid Reconnaissance Survey was targeted at understanding the impacts of WSD at the aggregate level involving the implementing agencies, village communities, and other key stakeholders. Village profile schedule is used to capture the profile of the village with the help of village officers, local leaders, other key informants, etc. Field Survey Schedule is targeted at the household level. The main purpose is to assess the impacts of WSD at the household level pertaining to different indicators. The schedule is prepared in such a way that it captures the changes, positive and negative or neutral impacts. About 40 sample households from each watershed were interviewed using the field survey schedule. These sample households are divided between Small and Marginal Farmers (SMF) and Large and medium Farmers (LMF) using probability proportionate sampling. Thus a total of 4448 households were covered across 110 watersheds in 15 sample districts, of which 65 per cent are SMF and 35 per cent are LMF. The composition of the sample varied across districts and schemes due to the prevailing agrarian structure. The IWDP and DPAP districts have roughly 3:1 ratio of

4 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 119 SMF: LMF while DDP districts have almost 1:1 ratio (Table 1). Field visits for data collection were carried out during August-October Household level data were collected mainly under three broad categories, viz., bio-physical, economic and institutional. Some of the important indicators include soil conservation works, water harvesting structure works, maintenance of CPRs, etc., under the bio-physical factors; employment generation, diversification in agriculture, income, standard of living, etc.; under the economic category and education of children, healthcare, participation in user groups, etc. under the institutional factors. Each assessment indicator has been assigned a pre-determined score as per its importance in its overall impact on the watershed development. All the scores, so distributed total up to 100. Scores are assigned in a descending order so that higher level of impacts gets higher scores than lower level impacts. For analytical purposes as well as to assess the performance of the watershed development programme, all the assessment indicators for which data were collected through rapid and household level surveys were categorised into three broad impact categories, namely, bio-physical impact, economic impact and institutional impact. Separate analysis was carried out for assessing the impact at the district level considering district as one assessment unit. To determine the performance level with respect to the assessment unit, maximum achievable scores and actual scores were calculated for each indicator. Maximum achievable score was calculated by multiplying the maximum score that could be assigned to each indicator with the total number of respondents associated. Actual score was calculated by multiplying the actual score given by the respondents to an indicator with the number of respondents giving the particular score. After calculating the maximum achievable scores and actual scores for every indicator belonging to the three broad categories (i.e., bio-physical, economic and institutional), the performance level of each assessment unit (i.e., district, group and scheme) was derived by taking the ratio of the sum of the actual scores of all the underlying indicators to the sum of the maximum achievable scores of those indicators and the resultant number is subsequently converted/standardised in percentage values in order to facilitate comparison across groups. The performance level of all the assessment units with respect to each individual assessment indicator is also determined following the same method; by taking the ratio of actual scores of that assessment indicator to the maximum achievable scores for that indicator for a particular assessment unit of watershed, which is subsequently converted/ standardised in percentage terms, so that comparison can be made. III PROFILE OF RAJASTHAN The state of Rajasthan is situated in the north western part of India between 23 o 3' and 30 o 12' North latitudes, and 69 o 30' to 78 o 17' East longitudes. Rajasthan occupies

5 120 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS the western most part of India and shares International boundary with Pakistan in the west. The adjoining States are Punjab and Haryana in the North, Uttar Pradesh in the Northeast, Madhya Pradesh in the Southeast, and Gujarat in the Southwest. With its geographical area of 3,42,239 sq. km, accounting for per cent of all India, Rajasthan is the largest state in the country in terms of area and also the one with the highest proportion of land occupied by desert. For administrative purpose the State is divided into 7 divisions, 33 districts, 188 sub-divisions, 241 tehsils and 237 development blocks (Panchayat Samitis). With 9,188 Village Panchayats the state has inhabited and 1600 un-inhabited villages. The climate of the State is the driest in the country, which varies from semi-arid to arid. The climate is characterised by low rainfall with erratic distribution, extremes of diurnal and annual temperatures, low humidity and high wind velocity. The arid climate has marked variations in diurnal and seasonal ranges of temperature, characteristic of warm-dry continental climates. On an average winter temperatures range from 8 to 28 C (46 to 82 F) and summer temperatures range from 25 to 46 C (77 to 115 F). May and June are the hottest months, while January is the coldest month. The rainfall of the State is not only meager but also varies significantly from year to year, quite frequently leading to droughts. The distribution of annual rainfall is also uneven and decreases from southeast to northwest. The average rainfall ranges from 480 mm to 750 mm being as low as 150 mm in arid region and 1000 mm in the south-eastern plateau, most of which falls from July through September during the monsoon season. The physiography of Rajasthan is the product of harsh climatic conditions resulting in erosion and denudation over time. On the basis of climatic conditions and agricultural produce, Rajasthan has been divided into nine agro-climatic zones, each one having special characteristics of its own. WSD in Rajasthan WSD is being implemented in Rajasthan under three different schemes, namely, Drought Prone Area Programme (DPAP), Integrated Wasteland Development Programme (IWDP) and Desert Development Programme (DDP). These schemes are mostly location-specific. In order to combat the frequent recurrence of droughts in the state, DPAP was introduced during the year 1975, as a centrally sponsored scheme with a matching state share of 50:50 and adopted the watershed approach in While DPAP concentrates on non-arable lands, drainage lines for in-situ soil and moisture conservation, agro-forestry, pasture development, horticulture and alternate land use were its main components. The basic objective of the programme is to minimise the adverse effects of drought on the production of crops and livestock and productivity of land, water and human resources thereby ultimately leading to drought proofing of the areas. The programme aims at promoting the overall economic development and improving the socio-economic condition of the resource

6 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 121 poor and disadvantaged sections inhabiting the programme areas through creation, widening and equitable distribution of resource base and increased employment opportunities. The objectives of the programme are being addressed in general by taking up development works through watershed approach for land development, water resource development and afforestation/pasture development. IWDP was introduced during 1991 with 100 per cent central assistance. IWDP included silvi-culture and soil and moisture conservation in lands under government or community or private control as its predominant activity, without any regard for the complete micro-watershed principle or with people s participation. IWDP was transferred to the Department of Land Resources along with the NWDB in July From 1 April 1995, the scheme is being implemented on a watershed basis under the common Guidelines for Watershed Development. The Programme is expected to promote employment generation in the rural areas besides enhancing people s participation at all stages in the development of wastelands- leading to sustainable development and equitable sharing of the benefits. The main objective of the IWDP are (1) to promote the overall economic development and improvement of the socioeconomic conditions of rural poor of the programme areas through optimum utilisation of resources, (2) generation of employment and (3) augmentation of other income generating activities. Further, it also aimed at encouraging restoration of ecological balance in the village through simple, easy and affordable technological and sustained community action (people s participation). All these result in overall upliftment of the poor and disadvantaged sections of the community. The major activities taken up under the programme are: soil and moisture conservation measures like terracing, bunding, trenching, vegetative barriers, etc.; planting and sowing of multipurpose trees, shrubs, grasses, legumes and pasture land development; encouraging natural regeneration in the programme areas; promotion of agro-forestry and horticulture; wood substitution and fuel-wood conservation measures; measures needed to disseminate technology such as training, extension and creation of greater degree of awareness among the participants are encouraged through people's participation, especially women. The Desert Development Programme (DDP) was started in the hot desert areas of Rajasthan in In hot sandy desert areas, sand dune stabilisation through shelterbelt plantations were given greater weightage. The programme was reviewed in by a Technical Committee headed by Prof. C.H. Hanumantha Rao and it was observed that the main reason for below satisfactory results was that area development was not taken up on watershed basis and the involvement of the local people was virtually non-existent, both in planning and execution of the programme. Besides inadequacy of funds, non-availability of trained personnel and taking up of too many activities, which were neither properly integrated nor necessarily related to the objectives of the programme, were identified as the contributory factors towards reducing the impact of the programme. Based on the recommendations of the Committee, new blocks/districts were included under the programme along with

7 122 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS comprehensive Guidelines for Watershed Development were issued in 1994 and made applicable to the area development programme with effect from Subsequently, Rajasthan has distinct problems because of large tracts of hot arid (sandy) areas. In view of the problem of sand dune stabilisation in ten districts of this State, special projects are under implementation under DDP since for combating desertification by way of shelterbelt plantation, sand dune fixation and afforestation. These ten districts are Barmer, Bikaner, Churu, Jaisalmer, Jalore, Jhunjhunu, Jodhpur, Nagaur, Pali and Sikar. The programme has been conceived as a long term measure for restoration of ecological balance by conserving, developing and harnessing land, water, livestock and human resources. It seeks to promote the economic development of the village community and improve the economic conditions of the resource poor and disadvantaged sections of the society in the rural areas. The major objectives of the programme include: (i) to mitigate the adverse effects of desertification and adverse climatic conditions on crops, human and livestock population and combating desertification; (ii) to restore ecological balance by harnessing, conserving and developing natural resources, i.e., land, water, vegetative cover and raising land productivity; (iii) to implement developmental works through the watershed approach, for land development, water resources development and afforestation/ pasture development. There are not many large scale studies assessing the impact of WSD programme in Rajasthan, especially after the 1994 guidelines. In 2002 a comprehensive study was conducted to assess the impact of WSD programme covering 462 watersheds in 25 districts (Taylor, 2002). The study covered the watersheds that were sanctioned between 1992 and 1998 and did not cover the watersheds completed under the 1994 guidelines. This study revealed that watershed development has enhanced the overall productivity of land; water table has gone up and there has been an increase in the livestock of various categories (except bullocks) in the project areas. The study also indicated that green vegetative cover, irrigation, crop yields, etc., have also improved in the state. Another study of 91 DDP watersheds implemented between 2002 and 2005 in four districts of Rajasthan revealed that WSD investments enhance land productivity through strengthening of the natural resource base, viz., soil and water resources, especially in rainfed conditions. However, the present level of impacts is rather limited and needs to be enhanced further (Reddy et. al., 2011). On the other hand, micro studies in Rajasthan have observed that social capital and institutions play an important role in enhancing the benefits from developmental programmes (Krishna, 2001) in general and watershed development in particular (Badal et al., 2006).

8 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 123 IV PERFORMANCE OF WSD The present assessment of WSD performance differs widely with the earlier assessments, as the earlier assessments were often based on either cost-benefit ratios or economic impacts. The nature and method of the present assessment deviates from the earlier ones in two ways. First, the beneficiaries were asked to assess the WSD performance in a close ended format by asking them to choose one of the answers, while the earlier assessments mostly used the deductive methods of collecting actual changes that have taken place due to the WSD programme through adopting before or after/with or without methods of assessment. Second, the beneficiaries were asked to provide a score based on the performance of the particular indicator. The sum of score for all the indicators is 100. The overall score a household accords would be based on the households own experience. This is also different from the earlier assessments where evaluators take an object view of the WSD success based on the performance of various indicators. Often these indicators are excessively biased in favour of economic impacts or indicators. In the present case all the important indicators are included. The scores accorded at the household level for each watershed for the three components and the overall score are examined in order to assess the WSD performance at the watershed level. The performance of WSD in terms of economic impacts received lowest score with an average score of 31. Across the watersheds the score ranges between 17 and 51. Of the 110 watersheds 39 watersheds fall in the range of above average performance (Table 2). While eight districts got above average scores seven got below average scores. Most of the below average districts are from low rainfall arid regions. If we consider 40 as the threshold level score for a fair level of performance only 16 sample watersheds fall in this category. That is only 15 per cent of the watersheds showed fair level of performance. And only 3 sample watersheds scored 50 or above. On the other hand, in the case of bio-physical or environmental and social impacts 57 and 62 watersheds respectively have shown above average performance. Some of the watersheds have scored as high as 70 per cent and above in both the cases. Above average performance is recorded in 10 of the 15 sample districts. Though the below average performing five districts are not the same, they are mostly from the arid districts. Therefore, the low performing watersheds are mostly from the low rainfall arid districts. But, there are watersheds that got above average score even from these districts (see Appendix 1). This indicates that the reasons for better performance go beyond natural or climatic factors. The average overall score is 40, which is the threshold level, and 35 per cent of the sample watersheds are above this score. The set of districts housing the watersheds above and below the average score are more are less same as that of other components.

9 124 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS Impacts (1) No. of sample watersheds above average (2) TABLE 2. PERFORMANCE OF WATERSHEDS IN RAJASTHAN Main districts (3) Environment 57 Baran, Dausa, Jaipur, SMPur, Dholpur, Bundi, Tonk, Ajmer, Sirohi and Udaipur Economic 39 Baran, Dausa, Jaipur, SMPur, Dholpur, Bundi, Tonk, Ajmer Institutional/ Social 62 Baran, Dausa, Jaipur, SMPur, Rajsamand, Dholpur, Bundi, Tonk, Ajmer and Udaipur Overall 42 Baran, Dausa, Jaipur, SMPur, Dholpur, Bundi, Tonk, Ajmer No. of sample watersheds below average (4) 53 Main districts (5) Rajasamand, Jaisalmer, Jalore, Barmer, Bikaner 71 Rajasamand, Jaisalmer, Jalore, Barmer, Bikaner, Sirohi and Udaipur 48 Bikaner, Jalore, Jaisalmer, Barmer, Sirohi 68 Rajasmand, Bikaner, Jalore, Jaisalmer, Barmer, Sirohi, Udaipur Average score (6) Range (7) CV (8) Note: Main districts are those where a majority of the watersheds are in the category. CV= Coefficient of Variation. The literature on the impact of WSD in general indicates only about 20 per cent success rate, whatever be the measure of success. The recent meta analysis observed that 35 per cent of the watersheds perform above average level (Joshi et al., 2005). The present assessment also provides a similar picture of the impact. To assess the success rate we assume that a score of 40 and above at the household level indicate a fairly satisfactory performance of the WSD. This appears reasonable given the harsh climatic conditions of Rajasthan. At this level 43 per cent of the sample watersheds have performed well as far as the overall performance is concerned. In terms of economic impacts only 15 per cent of the watersheds performed well as against 68 per cent in the case of bio-physical and 96 per cent in the case of social impacts. This brings out two important aspects: (i) better performance of bio-physical or environmental and institutional impacts are not translated into economic impacts. This could be due to the climatic conditions in most parts of the state. (ii) given the emphasis on participatory aspects in the 1994 guidelines the performance of watersheds in terms of institutional or social impacts appears commendable. It may

10 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 125 be noted that the traditional institutional mechanisms existing in the state would have enhanced the impacts. The better performance of institutional and bio-physical impacts could ensure the sustainability of the limited economic impacts. Figure 1. Variations and Trends in the Performance of Different Components Across Watersheds Figure 2a. Regression Plot of the Economic and Environmental Scores Figure 2b. Regression Plot of the Economic and Social scores Linear Regression Environmental Score Economic Score Economic Score = * EnvironmentalScore R-Square = 0.48 Linear Regression Social Score Economic Score Economic Score = * SocialScore R-Square = 0.32

11 126 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS Environmental Score Environmental Score = * SocialScore R-Square = Social Score Linear Regression Figure 2c. Regression Plot of the Environment and Social Scores Our analysis also brings out clearly that these three components move together in most of the cases (Figure 1). They are also found to be interlinked as reflected in the regression plots (Figures 2a to 2c). All the three components are positively correlated. The regression coefficient between economic and bio-physical as well as economic and institutional components are of the same magnitude (0.44 and 0.43) and significant. And the regression coefficient between institutional and bio-physical components is high at 0.80 and statistically significant indicating a much stronger association between these two. Despite the significant linkages, economic impacts are quite subdued. There is need for converting the bio-physical and institutional impacts into economic impacts. For this one has to understand the factors that determine the economic impacts as well as other impacts. For, the impacts are not the same across watersheds of different agro-climatic zones or districts. This aspect is taken up in the next section. V FACTORS INFLUENCING WSD PERFORMANCE The variations in the performance across watersheds clearly provided a case for examining the factors influencing the level of impact across watersheds. While differential impacts are observed for the three components, the reasons are not clear why higher level of social and environmental impacts failed to translate into economic impacts? What could be the possible inter-relationships between biophysical, institutional and economic impacts? Is the performance of the WSD really linked to the scheme under which it is implemented? In order to answer some of these queries, an attempt is made in this section to analyse watershed level information. For this purpose, data are drawn from primary as well as secondary sources. Primary information has been drawn from rapid survey, village and household surveys. Secondary sources include census data and published documents at the village/block/ district level.

12 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 127 For the purpose of examining the factors determining the variations in the performance of WSD across sample watersheds, multiple regression analysis was adopted using number of indicators that could influence the performance. The basic specification is as follows: WSDP it = f(ts it, RF it, VS(HH) it, VS(GA) it, %AI it,wd it, LSD it, AEDU it, APHSC it, AMRK it, APWS it, FCBO it, AFM it, CWDF it, PIAL it, %CPR it,%frst it,) + u it Where, WSDP dt TS it = WSD performance, i.e., scores as assigned by the sample households in the four components, viz., bio-physical, economic, institutional and over all in watershed i at time t. = Type of scheme under which the watershed was implemented, i.e., IWDP, DPAP and DDP. RF it = Normal rainfall in millimetres (at the district where the watershed is located). VS (HH) it = Watershed village size in terms of number of households. VS (GA) it = Watershed village size in terms of geographical area. %AI it WD it LSDit AEDU it APHC it AMRK it APWS it FCBO it FM it CWDF it PIAL it %CPR it %FRST it U it = Per cent area irrigated from all the sources of the watershed village. = Well density (number of functioning wells per unit of land) = Livestock Density (livestock in standardised units - TLU per unit of land or population) = Access to education (school standard in the village). = Access to primary health centre in terms of distance from the village = Access to market (distance in km between the WSD village and market place). = Access to protected water supply. = Functioning of community based organisations. = Frequency of meetings. = Contribution to watershed development fund. = Linkages between the project implementing agency/the line department and the watershed institutions. = per cent of area under common pool resources. = per cent of area under forests. = Error term. While variables or factors included in the specification are based on theoretical expectations, the list of variables is not comprehensive due to lack of accurate data. The performance of a watershed is influenced to a large extent by the bio-physical

13 128 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS condition of the resources and to the extent the users rely on them for their livelihoods. While variables like normal rainfall and per cent area irrigated from all sources reflect the condition of the resources, the level of dependency on the resources is captured through variables like, number of functioning wells per unit of geographical area (WD), livestock population per unit of geographical area/and per human population (LSD), per cent area under common pool resources and forests. On the other hand, important variables like watershed catchment area, water holding capacity and number of wells recharged are not included in the specification due to lack of data. Variables concerning access to education (AEDU), health care facilities (APHC) and protected water supply (APWS) in a watershed were included in the analysis to reflect the human capital and basic amenities development in the watersheds. Watersheds endowed with better human capital in terms of education and health of the households are expected to have performed better, as human capital is observed to influence agriculture productivity positively (Tilak, 2002). And access to protected water supply is expected to enhance human capital through reduction in health risks (Reddy and Kullappa, 2008). Similarly, watersheds having better market accessibility are expected to perform better as it may lead to commercialisation of the agriculture and thus, provide more incentive for investment in agriculture. The study has used access to market (AMRK) as a proxy for the connection of the village to the market. Institutional factors have come to be viewed as extremely important in shaping access to natural resources and therefore very important in influencing watershed performances. In this analysis, several variables (FCBO, FM, CWDF and PIAL) are included to take into consideration the different aspects of institutions. These variables are viewed as indicators of the extent to which institutional enforcement is actually present in a watershed, and expect them to have positive relationships with watershed performance. In Rajasthan a typical watershed covers more than one village due to the small size of the village in terms of number of households and area. Number of households in the village is synonymous with the number of households dependent on watersheds. The independent variables are selected based on the theoretical considerations and the availability of data at the watershed level. The variables are drawn mainly from different sources like Rapid Reconnaissance Survey, village survey, household survey, secondary sources like census, departmental records, etc. An exhaustive list of indicators covering bio-physical, economic and institutional factors that are likely to influence the performance was prepared. The selected variables from the exhaustive list and their hypothetical/theoretical or expected impacts on the performance indicators along with their measurement are presented briefly in Table 3 to save space in presenting detailed hypotheses.

14 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 129 TABLE 3. MEASUREMENT AND EXPECTED/ HYPOTHESIZED SIGNS OF THE SELECTED VARIABLES Theoretical or Expected Impacts Variable (1) Measurement (2) ECO (3) BIOPHY (4) INST (5) OVAL (6) TS Dummy (IWDP=1; DPAP=2 and DDP= 3) -ve -ve -ve -ve RF Normal rainfall in mm +ve +ve -ve +ve VS (HH) Number of households -ve -ve -ve -ve VS (GA) Geographical area -ve +ve -ve -ve %AI Percentage of area irrigated +ve +ve -ve +ve WD Number of functioning wells per unit of geographical area +ve +ve +ve +ve LSD Livestock population per unit of geographical area/and +/-ve +/-ve +/-ve +/-ve per human population AEDU School standard +ve +ve +ve +ve APHC Distance in range of KM -ve -ve -ve -ve AMRK Distance in KM -ve -ve -ve -ve APWS Dummy (Yes=1 and No=0) +ve +ve +ve +ve FCBO Dummy (1= Formed but not functional; 2= Partially +ve +ve +ve +ve functional; 3= fully functional) FM Dummy (0= No regular conduct of meeting; 1= Regular +ve +ve +ve +ve conduct of meetings CWDF Dummy (0= No; 1= Yes) +ve +ve +ve +ve PIAL Dummy (1= linkage ended with the watershed; 2= +ve +ve +ve +ve Continuing) % CPR Percentage of geographical area -ve -/+ve -/+ve -/+ve %FRST Percentage of geographical area +ve +ve -/+ve -/+ve Note: ECO= Economic Score; BIOPHY= Bio-physical or Environmental Score; INST= Institutional or Social Score; OVAL= Overall Score. All these variables were tried in different combinations and permutations. But, some of the variables, though important, did not find place in the specifications due to various reasons like multicollinearity, non-significance and also the absence of variation. For instance, maintenance of CPRs is highly correlated with contribution to WDF; nomination of leaders is the main practice in all the watersheds and no elections were observed for electing the watershed associations and committee office bearers. And variables like size of watershed, social audit, sharing of benefits, maintenance of records, number of tanks, per cent of SC/ST households, etc., did not turn out significant and hence dropped from the analysis. Some of the variables were measured in two ways, viz., size of the village was measured in terms of area and population and livestock density was measured in relation to population and area. Here population of the village is the beneficiary population. Linear regressions applying Ordinary Least Squares (OLS) were estimated by regressing the dependent variables (WSDP) against the selected independent variables (SPSS package). Regressions were run on cross sectional data covering 110 sample watersheds. Various permutations and combinations of independent variables were used to arrive at the best fits. Multi-colinearity between the independent variables was checked using the Variance Inflation Factor (VIF) statistic. Multi-colinearity is not a serious problem as long as VIF value is below 2.

15 130 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS The best fit specification was selected for the purpose of final analysis for each dependent variable. While the descriptive statistics of the selected indicators are presented in Appendix 2, the estimates of the selected specifications are presented in Table 4. TABLE 4. REGRESSION ESTIMATES OF SELECTED SPECIFICATIONS Dependent/ Independent Economic score Bio-physical score Institutional score Overall score Variable (1) Coefficient (2) VIF (3) Coefficient (4) VIF (5) Coefficient (6) VIF (7) Coefficient (8) VIF (9) Constant 2.66* * * * - (5.2) (2.8) (7.1) (9.3) TS RF 0.02* * * ** 1.5 (5.9) (6.76) (4.0) (1.7) VS (HH) ** (0.60) (2.1) VS (GA) * (2.49) %AI * * * 1.7 (1.04) (3.29) (2.37) (3.26) % CPR -0.09* (3.06) (1.12) % FRST (1.4) WD 18.8* *** 1.4 (2.9) (1.63) (0.52) (1.63) LSD (0.56) (0.45) AEDU -0.76* (2.6) (1.52) (1.55) AMRK (0.39) (0.57) (1.03) APWS 2.95** (2.12) (1.32) (1.23) APHC (1.18) FCBO 2.38** *** * 1.8 (1.89) (1.9) (6.1) FM 2.88*** *** 2.0 (1.7) (1.7) CWDF 6.48* ** * 1.9 (3.95) (2.12) (7.3) PIAL 5.46* * * * 1.1 (2.45) (2.8) (3.9) (5.3) R Square R Bar Squ N Note: Figures in parentheses indicate t values. *;** and *** indicate level of significance at 1, 5 and 10 per cent level, respectively.

16 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 131 The explanatory power of the selected specifications is quite good for three of the four components. The selected indicators explain about 70 per cent of the variations in the dependent variables of economic and bio-physical scores (Table 4). In fact, the selected indicators explain 86 per cent of the variations in the overall performance of the watersheds. In the case of institutional impacts the explanatory power is low at 40 per cent. Most of the independent variables have the expected signs or relationships with the dependent variables. One unique feature of all the specifications is that the social or institutional indicators have revealed a positive and significant impact on all the other components of watershed performance including the overall performance. These indicators include functioning of CBOs (FCBO), frequency of meetings (FM), contribution to watershed development fund (CWDF) and the linkages of project implementing agency/line department with the watershed institutions (PIAL). 2 This re-emphasises the importance of the participatory institutions in the WSD, which was at the core of the 1994 watershed guidelines. This is despite the better performance of WSD in social/institutional component when compared to economic and bio-physical components. On the other hand, type of scheme (TS), which differentiates the IWDP, DPAP and DDP watersheds, did not turn out significant in any of the specifications. The variable had to be dropped in some specifications where it turned out significant due to multicollinearity problem. At the same time its inclusion reduced the explanatory power of the specification. Though the performance of various indicators among these three schemes differ significantly (Reddy et al., 2010) at the aggregate level, the type of scheme did not explain variations when the other factors are controlled. For, it could be either irrigation or rainfall that explains the variations better rather than the scheme. In what follows we discuss the factors influencing each component. Economic Impact: Not many factors turned out significant in explaining the economic performance of WSD. As mentioned earlier the economic performance has received lowest scores when compared to other components. The proportion of area under irrigation turned out to be significant with a positive sign. This indicates that economic impacts are better in the watersheds where irrigation is available. In other words watersheds perform better in the better endowed regions, i.e., medium rainfall regions when compared to arid regions with very low rainfall. For, WSD is not taken up in the high rainfall and high irrigation regions. Access to protected water supply (APWS) also turned out significant with a negative sign. Theoretically APWS is expected to have a positive sign, as protected water supply is more common in the better endowed regions. But in case protected water supply is competing with irrigation then it could have negative impact on the economic performance of WSD. In Rajasthan multi village drinking water schemes provide water from bore wells located at one point. This may adversely affect the availability of groundwater in the surrounding areas, given the extreme water scarce situation in the arid parts of the state in particular.

17 132 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS The three institutional factors (i) functioning of CBOs; (ii) contribution to watershed development fund (CWDF) and (iii) linkage of PIA/line departments with watershed institutions have revealed a positive and significant impact on the economic performance of the WSD. These three factors are critical for maintaining the watershed structures. For, the active or functioning of CBOs ensure fund generation. Funds can be effectively used for the maintenance of structures with the help or support of the department. Moreover linkages with the line departments can provide technical support in crop, livestock development, etc. Of these three factors CWDF and PIAL the larger influence on the economic impacts. Therefore, economic impacts can be enhanced by strengthening the institutional indicators. On the other hand, the impact of irrigation is not only low but also difficult to enhance it in the given climatic conditions. Bio-Physical or Environmental Impact: The number of variables turned out significant in explaining the variations in the performance of bio-physical impact. Rainfall (RF) and area irrigated (%AI) have a significant and positive impact indicating bio-physical or environmental impacts are more pronounced in high rainfall and irrigated regions. These impacts are in the expected lines. This is obviously due to the conducive natural conditions, as the improvements in vegetation cover, availability of fodder or fuel would be difficult in harsh climatic conditions of arid regions. Watershed development cannot be a perfect substitute for these natural conditions. However, environmental impacts of watershed development could be enhanced with institutional arrangements like functioning CBOs (FCBO), regular meetings of watershed committees (FM), contribution to development fund (CWDF) and the linkage between the implementing agency and the line department (PIAL). Of these variables, WD, CWDF and PIAL have greater influence on environmental impacts. Social Impact: In the case of social impacts the goodness of fit is not as robust as other impacts. Not only the explanatory power of the specification is low but also only a few variables turned out significant. Size of the village in terms of population (VS-HH) has a negative influence on social impact. This follows Olsan s (1965) classic theory of size and collective action, where he argues that collective action would be successful in small groups rather than in bigger groups. On the other hand, geographical area (VS-GA), rainfall (RF) and irrigation (%AI) revealed a positive and significant impact. This indicates that institutional or social impacts are stronger in better endowed regions or watersheds, though it is generally believed that social capital is stronger in backward regions. This could be due to the inter linkages between institutional, economic and bio-physical impacts. While size of the population is deterrent, size of the area appears to have positive impact on institutional score. As in the case of economic and environmental impacts, PIAL has

18 PERFORMANCE AND FACTORS INFLUENCING THE IMPACT OF WATERSHED DEVELOPMENT 133 a positive and significant impact on institutional impacts. In fact, PIAL has much stronger impact than any other variable on the institutional performance of WSD. Overall Impact: Selected indicators explain 86 per cent of the overall performance of watershed development in the sample watersheds. Seven variables turned out significant in explaining the variations and all of them are positively correlated with the overall performance of WSD. The indicators include rainfall (RF), irrigation (%AI), well density (WD), functioning of CBOs (FCBO), frequency of meetings (FM), contribution to the watershed development fund (CWDF) and the linkages of the implementing agency/line department and the watershed institutions (PIAL). This brings out clearly that the overall performance depends on natural endowments and institutional strengths of the communities. Stronger collective and participatory approach seems to hold the key for the overall success of the WSD. Though it may be argued that some threshold level of natural endowments like medium rainfall along with protective irrigation facilities are necessary for effective WSD impacts, institutional aspects seem to have much stronger influence on the performance. VI CONCLUSIONS The preceding analysis brings out that the performance of watersheds varies widely across as well as within the districts. The watershed wise analysis indicates that 43 per cent of the sample watersheds show overall performance above 40 per cent score. Substantial proportion of watersheds perform above the threshold level (40 per cent score) in terms of bio-physical (68 per cent) and institutional (96 per cent) impacts. This reflects the influence of the 1995 participatory guidelines that emphasised the strengthening of the WSD institutions. While the higher institutional impacts are reflected in the bio-physical impacts, they failed to translate into economic impacts in most of the cases. This could be due to adverse climatic conditions of Rajasthan. This is despite the strong linkages between the three components. The performance of WSD does seem to be constrained in the poor rainfall conditions. Hence, impact assessments need to keep this in view while dealing with low rainfall regions. Regression analysis carried out to examine the factors that influence economic as well as other components brings out the following aspects: Natural and participatory institutional aspects play an important role in determining the performance of WSD in Rajasthan. The analysis does not support the earlier conclusion that IWDP watersheds perform better than DPAP and DDP watersheds. The analysis suggests that impact of WSD is determined mainly by natural factors like rainfall and

19 134 INDIAN JOURNAL OF AGRICULTURAL ECONOMICS access to irrigation rather than the type of scheme. The scheme is a manifestation of natural factors. Participatory institutions like functioning of community based organisations, regular meetings of watershed institutions, contributions to watershed development fund and continued linkage with the line department are critical the success of WSD. Continuation of WSD institutions like watershed committee and watershed association even after the completion of the programme is essential for enhancing and sustaining the impacts. Contributing to and management of watershed development is another import element in ensuring sustained benefit flows through proper maintenance of watershed structures. And the continued support from the line department, which could be possible through maintaining the relationship between the watershed committees and the department, would help in continued technical support and sustained impacts of WSD. Received June Revision accepted January NOTES 1. The common watershed guidelines have enhanced the per hectare expenditure from the existing Rs to Rs Indicators like social audit and record keeping were also tried but dropped due to nonsignificance or multicolenearity. REFERENCES Badal P.S., Pramod Kumar and Geeta Bisaria (2006), Dimensions and Determinants of Peoples Participation in Watershed Development Programmes in Rajasthan Agricultural Economics Research Review, Vol. 19, No.1, January-June, pp Deshpande, R.S. and V. Ratna Reddy (1990), Social Dynamics and Farmer s Society: A Case Study of Pani- Panchayat, Indian Journal of Agricultural Economics, Vol. 45, No. 3, July-September. Fan, S. and P. Hazell (2000), Should Developing Countries Invest More in Less Favoured Areas? An Empirical Analysis of Rural India, Economic and Political Weekly, Vol.35, No.17, April 22-28, pp Government of India (2001), Approach Paper to the Tenth Five Year Plan ( ), Planning Commission, New Delhi, September. Joshi, P.K. and M.C.S. Bantilan (1997), Vertisol Watershed Research in the Semi-Arid Tropics: Directions for Impact Assessment, Artha Vijnana, Vol.39, No.3, September, pp Joshi,P.K., A.K. Jha, S.P. Wani, L. Joshi and R.L. Shiyani (2005), Meta-Analysis to Assess Impact of Watershed Programme and People s Participation, Comprehensive Assessment Research Report No.8, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Andhra Pradesh. Kolavalli, L.S. and J. Kerr (2002), "Mainstreaming Participatory Watershed Development", Economic and Political Weekly, Vol. 37, No.3, January 19, pp Krishna, A. (2001), Moving from Stock of Social Capital to Flow of Benefits: The Role of Agency, World Development, Vol. 29, No. 6, pp Nalatawadmath, S.K, M.S. Rama Mohan Rao and M. Padmaiah (1997), Joladarasi Model Watershed Development Program in Bellary District of Karnataka-A Diagnostic Evaluation, Journal of Rural Development, Vol.16, No.2, April-June.