Rainwater conservation and soil erosion prevention are vital for the economic and financial sustainability of dry land agriculture. An integrated watershed development programme is thus a means of achieving these goals. Presently, integrated watershed management is receiving worldwide recognition as an effective model for watershed planning. A watershed is considered the basic geographical unit for developing any plan by integrating various social, economic, and policy factors with modern science. Hence, it is an approach to develop the basic resources for sustainable life support. The present study was conducted to assess the impacts of the watershed development programme on the social and biophysical aspects in a micro-watershed area of Cooch Behar district, West Bengal, India. This study confirmed that the project had positive effects that strengthened the socio-personal and economic characteristics of the farmers and improved the biophysical environment of the farms. The soil and water conservation efforts have increased the total cultivable area as well as improved the irrigation and drainage facilities in the micro-watershed units, thereby increasing the acreage and productivity of crops.

Introduction

Rain-fed agriculture occupies 80% of total agriculture lands and contributes 58% to the world's food basket (Raju et al., 2008). Because of the increase in the global population, water for food production is becoming an increasingly scarce resource, and this situation is further aggravated by climate change (Molden et al., 2007). The rain-fed areas are hotspots for poverty, malnutrition, food insecurity, severe land degradation, water insecurity, and poor social and institutional infrastructure (Rockstrom et al., 2007; Wani et al., 2007). Therefore, the watershed development programme is considered an effective tool for addressing many of these problems. It is recognised as the potential engine for agriculture growth and development in fragile and marginal rain-fed areas (Joshi et al., 2005; Wani et al., 2008).

In India, the watershed programme was designed to conserve water, soil, forests, and pasturelands in a harmonising manner (Rao et al., 2006; Palanisami et al., 2008; Ramappa et al., 2008). It is a multidisciplinary approach (Rao et al., 2006) to enhance farm income by increasing crop yield and to generate employment by using altering cropping patterns (Jain, 2008; Palanisami & Suresh Kumar, 2009). The watershed development project aimed to improve the peoples' involvement through the development of grass-root institutions. These institutions develop peoples' interaction, build cooperation (Ghosh et al., 2004), and encourage group activities. In their study, Rao et al. (2006) noted that identifying the linkage between the biophysical and social factors influences the success of the programme.

Realising the importance of the watershed programme, the Cooch Behar district in West Bengal implemented six micro-watershed projects during the XIth five-year plan (2007–08 to 2011–12) under the National Watershed Development Project in Rain-fed Areas (NWDPRA). Rangamati is one among these six implemented micro-watershed units. The major problems encountered there are as follows:

  • soil erosion (sheet erosion, rill erosion, gully erosion, and stream bank erosion);

  • high rainfall causing frequent floods and deposition of sand in cultivable areas, thereby making it uncultivable;

  • excessive run-off of downpour resulting in low crop production and productivity;

  • water stagnation in low-lying areas causing poor yield of crops;

  • lack of irrigation facilities;

  • acidic soil deficient in vital micronutrients, such as zinc, boron, and molybdenum.

Simultaneously, a lack of awareness regarding improved technology and modern agriculture has caused poor social and economic conditions in the communities of watershed units.

The project at Rangamati was implemented on 1 April 2007 against the backdrop of all these problems, to emphasise the following aspects:

  • plot making by installing graded and field banks;

  • gully plugging by using vegetative and mechanical measures;

  • construction and re-excavation of drainage channels;

  • building barrier and periphery bunds to improve water holding capacity and prevent stream bank erosion;

  • excavation and re-excavation of water harvesting structures and farm ponds to conserve maximum rainwater or downpour;

  • construction of wells in the project area to meet the water requirement for plants, animals, and human beings;

  • sand reclamation by constructing different types of bunds.

Moreover, the project aimed to demonstrate modern integrated farming systems to increase production as well as productivity. The project was completed on 31 March 2012.

With this background, the present study was undertaken to assess the impacts of the project on social and biophysical spheres, particularly after its completion (study period August 2013 to March 2014).

Materials and methods

In India, most watershed projects are implemented with the twin objectives of soil and water conservation and improving the livelihoods of impoverished people in rural areas (Sharma & Scott, 2005), including development at socio-personal levels. Therefore, research was conducted to evaluate the changes in these aspects.

Geographical location and profile of the study area

Rangamati micro-watershed [Soil and Land Use Survey of India (SLUSI) Micro-watershed Code: 3A1C6-r] is situated in Mathabhanga-II block in the catchment basin of the Mansai (Jaldhaka) river (Figure 1). The geographical location of this watershed is 26 °26′28′′ N to 26 °29′21′′ N latitude and 89 °11′17′′ E to 89 °13′47′′ E longitude. The total geographical area of the micro-watershed is 842.995 ha with 640 ha as the effective project area. Human settlements, roads, a river, playgrounds, and narrow perennial and seasonal rivulets and water streams occupy the remaining 202.995 ha.
Fig. 1.

Satellite map of Rangamati micro-watershed (Courtesy: www.coochbehar.nic.in; www.embassyindia.es and Google Maps).

Fig. 1.

Satellite map of Rangamati micro-watershed (Courtesy: www.coochbehar.nic.in; www.embassyindia.es and Google Maps).

The soil of the watershed is acidic in nature and formed by alluvial deposits carried by the strong currents and occasional floods due to heavy rainfall in the Himalayan foothills. The texture of the deposit is friable loam to sandy loam, with a depth ranging from 2.0 to 2.5 m. The soil has a low nitrogen level, moderate levels of potassium and phosphorus, and extremely low levels of zinc, boron, calcium, magnesium, sulphur, and molybdenum.

The study area has a moderate climate characterised by heavy rainfall during the monsoon. The summer season is from April to May. April is the hottest month with a mean temperature of 32.5 °C. The winter season starts from late November and continues until the end of February. January is the coldest month with temperature ranging from 10.4 °C to 24.1 °C. The weather is humid except in the period from February to May. The average annual rainfall is 3,300 mm, spread over an average of 95 rainy days.

Villages and respondents under study

Only three villages, namely Rangamati [Jurisdiction List (JL) No.74], Ramthenga (JL No.64), and Mukuldanga (JL No.61), fall under this micro-watershed, consisting of 805, 1,394, and 852 families, respectively. A group of families was registered with Water User Groups (WUGs) and self-help groups (SHGs) as beneficiaries of the project. Among these beneficiaries, 60 farms (20 from each village) were randomly selected as study units. Respondents were in the middle-age group (average age 42 years), with low–medium education level (up to 6th to 8th standard), and marginal land holdings (0.49 ha on average).

Approach of the study

The study was undertaken as an impact study, and changes were assessed on the biophysical and socio-economic levels. A before–after study design was planned and information was collected using a pre-tested structured interview schedule. Data from the pre- and post-project period were collected through a preliminary survey of available records of the selected beneficiary households. Reports of the Soil Conservation Officer of the block and district were also consulted. Opinion data were used for analysis wherever ready physical values were not available for reference.

Selection of impact variables

Watershed development projects directly affect biophysical aspects, including changes in arable (suitable for cultivation) land, improvement in irrigation and drainage, and improvement in soil and moisture conservation, which increase the production and productivity of crops and, thereby, enhance the livelihood status of the beneficiaries. Personal characteristics like media exposure, organisational participation, and outside exposure are also influenced by the project activities. All these changes may directly or indirectly affect sanitation and drinking water facilities, occupational diversity, and household income. Changes in all the listed variables were assessed in the study.

Measurement of variables

The present study relied on physical as well as opinion variables for impact assessment. The opinion variables were measured using a Likert scale following Likert (1932). The operational definitions and their measurement procedures are presented hereunder.

Organisational participation is the extent of participation in grass-root organisations (SHGs and WUGs) as ‘member’, ‘office bearer’, and ‘leader’ with corresponding scores of 1, 2, and 3, respectively.

Outside contact is the extent of visits undertaken to the state headquarters, district headquarters, sub-division town, or nearest town in a specified period. The sum of the number of visits comprises the score.

Mass and personal media exposure is the frequency of communication with mass media and interpersonal channels of information in a specified period. The sum of the frequency is the score.

Occupational diversity is the variety of occupations (including agriculture, animal husbandry, and fishery) found in a family. The total number of occupations constitutes the score.

Housing, drinking water, and sanitation facilities indicate the quality of available facilities. The scale used for housing consisted of ‘bamboo house’, ‘tin house’, ‘wood house’, and ‘brick house’, corresponding to scores of 1, 2, 3, and 4, respectively. The drinking water facility scale consisted of access to ‘open surface water’, ‘dug well’, ‘shallow tube well’, ‘deep tube well or pipeline’, corresponding to scores of 1, 2, 3, and 4, respectively. The sanitation scale consisted of access to ‘scientific sanitation with safety tank’, ‘ring sanitation’, and ‘open field’, corresponding to scores of 2, 1, and 0, respectively.

Farm-level biophysical changes were measured as highly improved (HI), improved (I), no change (NC), deteriorated (D), and highly deteriorated (HD), corresponding to the scores 2, 1, 0, −1, and −2, respectively. The mean score (MS) was calculated for comparison by using the following formula: 
formula
where,
  • fi = frequency of the ith change category (frequency under HI, MI, …)

  • wi = scale value of change category 2,1, …)

  • n = number of change categories considered (here 5)

  • N = number of respondents (here 60)

Adoption levels of watershed and crop production technology were measured through the following indices.

Adoption Quotient (AQ): A composite index derived from the modification of original formula developed by Chattopadhyay (1963). It is calculated as follows: 
formula

where,

  • ni = number of adopters of ith technology for a crop

  • N = total number of farmers

  • T = total number of technologies considered

Knowledge-Adoption Quotient (KAQ): An index calculated from a combined score on knowledge and adoption of a technology and calculated as follows: 
formula

The score obtained for a technology was achieved by a three-point scale [do not know = 0, know but not adopted = 1, adopted = 2].

Results and discussion

The impacts of the programme were assessed using a before–after study design and the findings are presented systematically hereunder.

Changes in socio-economic aspects

Socio-personal levels

Socio-personal characteristics are crucial factors of human behaviour towards an action (Mischel et al., 1989; Mischel & Ayduk, 2004). Watershed project activities, including group formation, training, and leadership development, have influenced socio-personal characteristics of the people positively. From Table 1, the pre-project levels of organisational participation (score value = 0.13), outside contact (score value = 6.57), personal media contact (score value = 3.03), drinking water facilities (score value = 2.37), and sanitation (score value = 1.00) improved significantly to the respective post-project scores of 0.45, 9.25, 7.23, 2.90 and 1.28. All the differences in scores are significant at p < 0.01 and p < 0.05 levels. The Rangamati Watershed Project led to the formation of five SHGs and 22 WUGs [Source: unpublished project document, Rangamati Watershed, Cooch Behar], which increased the organisational participation of the members. Regular training (inside and outside the project area) and organisational meetings under the project improved socio-personal characteristics significantly. Drinking water facilities and the development of sanitation were inset in the objectives of watershed development projects.

Table 1.

Change in socio-economic and personal variables.

Respondents' characteristics Scale of measurement Pre-Project Post-Project t-value 
Organisational participation Score3 0.13 0.45 2.95** 
Outside contact Score1 6.57 9.25 5.49** 
Mass media exposure Score2 1.3 1.45 NS 
Personal media contact Score4 3.03 7.23 7.26** 
Occupational diversity Number of occupations found in family 1.37 1.38 NS 
Drinking water Score5 2.37 2.9 4.96** 
Housing condition Score6 6.01 NS 
Sanitation Score7 1.28 2.32* 
Respondents' characteristics Scale of measurement Pre-Project Post-Project t-value 
Organisational participation Score3 0.13 0.45 2.95** 
Outside contact Score1 6.57 9.25 5.49** 
Mass media exposure Score2 1.3 1.45 NS 
Personal media contact Score4 3.03 7.23 7.26** 
Occupational diversity Number of occupations found in family 1.37 1.38 NS 
Drinking water Score5 2.37 2.9 4.96** 
Housing condition Score6 6.01 NS 
Sanitation Score7 1.28 2.32* 

NS, Non-significant.

1Number of visits to the state headquarters, district headquarters, sub-division town and nearest town in a month.

2Frequency of communication with mass media and interpersonal channels of information in a specified period.

3,4The scale composed of ‘no member’, ‘member’, ‘office bearer’ and ‘leader’, with corresponding scores of 0, 1, 2, and 3, respectively.

5Source of drinking water is ‘open surface water’, ‘dug well’, ‘shallow tube well’, ‘deep tube well/pipeline’ with 1, 2, 3, and 4 scores, respectively.

6House made of ‘bamboo’, ‘tin’, ‘wood’ and ‘pucca’ with corresponding scores of 1, 2, 3, and 4, respectively.

7The scale composed of ‘no sanitation’, ‘ring (soft wall)’, ‘ring (hard wall)’ and ‘sanitary’ with corresponding scores of 0, 1, 2, and 3, respectively.

*p < 0.05, **p < 0.01.

However, mass media exposure, occupational diversity, and housing conditions did not exhibit any change over pre-project levels. Access to mass media technology and scope to diversify occupation and economic activities were otherwise limited in the project area, which may have hindered the improvement of these personal characteristics.

Changes in cropping pattern and per capita cropped area and productivity

Household surveys as well as an analysis of project reports revealed that only jute as an autumn crop (locally called pre-kharif crops: crops harvested between August and September) and local variety paddy as a winter crop (locally called kharif crop: crops harvested between November and January) were cultivated in medium land (land with optimum water retention capacity for cultivation; no water logging or stress) (Table 2). Vegetables from June–July to September–October and tobacco from September–October to January–February were grown in very small areas of the upland. In pockets of low-lying areas, summer paddy was cultivated (locally called boro: the season starts between January and February and ends between April and May or extends to June. Photo-insensitive rice varieties are most suitable for this season). The cropping intensity (the ratio between gross cropped area and net cropped area multiplied by 100) was 190% on average. Successful completion of the project improved the situation. Acreage under crops, particularly those that required more water, was intensified (e.g. maize, potato, and vegetables) (see Table 3). Per capita acreage under crops increased from 53.13% to 92.45% compared with pre-project acreage. Paired t-test results for all crops were significant at p < 0.01 level. As a result, the cropping intensity increased to 270%. Successful implementation of the watershed development project adopted different community and individual water conservation measures, such as construction of water harvesting and conservation structures, excavation and renovation of farm ponds, and open wells. This improved availability of water in individual farms in the dry season and intensified crop cultivation in the micro-watershed.

Table 2.

Change in cropping pattern.

Land
topography 
Crop season
 
Pre-Project
 
Post-Project
 
Pre-kharif Kharif Summer/Rabi Pre-kharif Kharif Summer/Rabi 
Upland Jute Aman paddy/Veg Tobacco Jute Maize Veg Aman paddy/Veg Potato Mustard Wheat 
Medium land Jute Aman paddy Tobacco Jute Maize Veg Aman paddy Potato Veg Boro Wheat 
Low land Jute Aman paddy Boro Jute Aman paddy Boro 
Land
topography 
Crop season
 
Pre-Project
 
Post-Project
 
Pre-kharif Kharif Summer/Rabi Pre-kharif Kharif Summer/Rabi 
Upland Jute Aman paddy/Veg Tobacco Jute Maize Veg Aman paddy/Veg Potato Mustard Wheat 
Medium land Jute Aman paddy Tobacco Jute Maize Veg Aman paddy Potato Veg Boro Wheat 
Low land Jute Aman paddy Boro Jute Aman paddy Boro 

Aman (winter) paddy; Boro (summer) paddy.

Source: Unpublished report of Soil Conservation Office, Cooch Behar.

Table 3.

Change in acreage and productivity of cultivated crops after watershed project.

N = 60
 
Crops Average per capita acreage (ha)
 
Productivity of crops (MTha−1)
 
Before After Percentage increase t-value Before After Percentage increase t-value 
Aus paddy 0.14 0.24 69.16 12.89** 1.51 1.65 9.27 NS 
Aman paddy 2.00 2.31 15.50 NS 
Boro paddy 2.39 3.01 25.94 2.51* 
Jute 0.08 0.13 53.13 5.87** 2.21 3.11 40.72 8.43** 
Maize 0.10 0.16 63.64 9.68** 2.19 2.50 14.16 2.10* 
Brinjal 0.11 0.21 87.06 10.57** 4.50 4.99 10.89 NS 
Potato 0.06 0.10 65.96 7.04** 14.11 16.48 16.80 3.01** 
Chilli 0.05 0.09 65.85 4.35** 9.01 9.69 7.55 2.22* 
Cabbage 0.07 0.13 92.45 5.70** 4.51 5.22 15.74 NS 
N = 60
 
Crops Average per capita acreage (ha)
 
Productivity of crops (MTha−1)
 
Before After Percentage increase t-value Before After Percentage increase t-value 
Aus paddy 0.14 0.24 69.16 12.89** 1.51 1.65 9.27 NS 
Aman paddy 2.00 2.31 15.50 NS 
Boro paddy 2.39 3.01 25.94 2.51* 
Jute 0.08 0.13 53.13 5.87** 2.21 3.11 40.72 8.43** 
Maize 0.10 0.16 63.64 9.68** 2.19 2.50 14.16 2.10* 
Brinjal 0.11 0.21 87.06 10.57** 4.50 4.99 10.89 NS 
Potato 0.06 0.10 65.96 7.04** 14.11 16.48 16.80 3.01** 
Chilli 0.05 0.09 65.85 4.35** 9.01 9.69 7.55 2.22* 
Cabbage 0.07 0.13 92.45 5.70** 4.51 5.22 15.74 NS 

Aus (autumn) paddy; Aman (winter) paddy; Boro (summer) paddy.

NS, Non-significant.

*p < 0.05, **p < 0.01.

Source: Primary survey.

The results revealed that productivity of most of the crops increased significantly (Table 3) due to the implementation of watershed projects in the study area. The highest percentage increase in productivity was recorded in jute (40.72%) followed by summer paddy (25.94%). Retting of jute improved considerably because of the increased level of water in farm ponds. Higher productivity was recorded for crops, such as potato, boro paddy, or maize, that require more water (with an increase of 16.80%, 25.94%, and 14.16%, respectively). Furthermore, the productivity of chilli also significantly improved after the adoption of watershed technologies. Mondal et al. (2013), Pathak et al. (2013) and Kulshrestha et al. (2015) have also recorded similar results with respect to impacts observed in their study.

Changes in adoption of crop production technology

Adoption level is one of the determinants of enhanced production, which invariably shows a positive effect on the livelihood status of the concerned population. Table 4 depicts the level of adoption of the crop production technologies assessed using the AQ. The adoption level increased significantly at p < 0.01 in the case of brinjal (AQ changed from 0.32 to 0.42), cabbage (AQ changed from 0.24 to 0.41), jute (AQ changed from 0.28 to 0.45), maize (AQ changed from 0.28 to 0.66), and potato (AQ changed from 0.68 to 0.73) compared with the pre-project adoption levels. Although the post-project adoption levels of crop production technology in chilli and rice were higher when compared with the pre-project levels, the difference was not statistically significant.

Table 4.

Adoption scenario of crop production technology (percentage of respondents).

N = 60
 
Crops Area Improved technologies considered
 
AQ χ2-value 
Improved variety Organic nutrient Fertiliser Plant protection 
Brinjal Pre-Project 6.67 40.00 40.00 40.00 0.32 26.92 (p < 0.01) 
Post-Project 38.33 43.33 43.33 43.33 0.42 
Cabbage Pre-Project 6.67 30.00 30.00 30.00 0.24 35.95 (p < 0.001) 
Post-Project 38.33 41.67 41.67 41.67 0.41 
Chilli Pre-Project 6.67 20.00 20.00 20.00 0.17 5.08 (p > 0.16) 
Post-Project 15.00 18.33 18.33 18.33 0.18 
Jute Pre-Project 0.00 20.00 46.67 46.67 0.28 36.43(p < 0.001) 
Post-Project 1.67 31.67 73.33 73.33 0.45 
Maize Pre-Project 13.33 33.33 33.33 33.33 0.28 89.49 (p < 0.001) 
Post-Project 63.33 66.67 66.67 66.67 0.66 
Potato Pre-Project 3.33 90.00 90.00 90.00 0.68 76.53 (p < 0.001) 
Post-Project 71.67 73.33 73.33 73.33 0.73 
Rice Pre-Project 80.00 100.00 100.00 100.00 0.80 1.48 (p > 0.68) 
Post-Project 91.67 100.00 100.00 100.00 0.98 
Overall Adoption Quotient: Pre-Project = 0.40; Post-Project = 0.55(Wilcoxon t = 3.5; p > 0.07) 
N = 60
 
Crops Area Improved technologies considered
 
AQ χ2-value 
Improved variety Organic nutrient Fertiliser Plant protection 
Brinjal Pre-Project 6.67 40.00 40.00 40.00 0.32 26.92 (p < 0.01) 
Post-Project 38.33 43.33 43.33 43.33 0.42 
Cabbage Pre-Project 6.67 30.00 30.00 30.00 0.24 35.95 (p < 0.001) 
Post-Project 38.33 41.67 41.67 41.67 0.41 
Chilli Pre-Project 6.67 20.00 20.00 20.00 0.17 5.08 (p > 0.16) 
Post-Project 15.00 18.33 18.33 18.33 0.18 
Jute Pre-Project 0.00 20.00 46.67 46.67 0.28 36.43(p < 0.001) 
Post-Project 1.67 31.67 73.33 73.33 0.45 
Maize Pre-Project 13.33 33.33 33.33 33.33 0.28 89.49 (p < 0.001) 
Post-Project 63.33 66.67 66.67 66.67 0.66 
Potato Pre-Project 3.33 90.00 90.00 90.00 0.68 76.53 (p < 0.001) 
Post-Project 71.67 73.33 73.33 73.33 0.73 
Rice Pre-Project 80.00 100.00 100.00 100.00 0.80 1.48 (p > 0.68) 
Post-Project 91.67 100.00 100.00 100.00 0.98 
Overall Adoption Quotient: Pre-Project = 0.40; Post-Project = 0.55(Wilcoxon t = 3.5; p > 0.07) 

Source: Primary survey.

The overall AQ for crops increased from 0.40 in the pre-project period to 0.55 in the post-project period (significant at p < 0.02). The various training, demonstration, and subsidy programmes resulted in these benefits. They further contributed towards the development of socio-personal characteristics of the people (as in Table 1) and enabled them to become more receptive, which was manifested in the increased adoption levels of scientific crop management practices. The findings are consistent with those of Sadaqath & Devendrappa (2011).

Changes in biophysical aspects

Changes in land use, irrigation, and drainage pattern

Analysis of the project documents and reports obtained from the Water Conservation Officer, Cooch Behar indicated a noticeable change in the nature of farm lands (Figure 2). The status of land utilisation patterns and irrigation is assessed by respective micro-watershed projects from time to time using the information obtained from land use survey and satellite image analysis undertaken by central agencies. From Figure 2, clearly only 65% of the total land (416 of 640 ha) was arable before the implementation of the project. This percentage increased to 100% by implementation of land rejuvenation activities, including sand reclamation, raising earthen and stone bunds, gully plugging, creating vegetable barriers, and tree planting. An area of 7 ha was used for social forestry (also called community forestry), where community members have an open access to the forests and also share their finished products. Irrigated land, which constituted only 75 ha in the pre-project period, increased to 509 ha by installing various micro-irrigation systems (Figure 3). Both excessive drainage and drainage congestion were considerably reduced by the implementation of various water conservation measures and drainage structures. After implementation of the project, the area of land covered by well and moderately drained plots increased from 285 ha (44.53%) to 565 ha (88.28%) (Figure 4). These findings are consistent with the results of Palanisami et al. (2008) and Pathak et al. (2013).
Fig. 2.

Change in land utilisation pattern. Data source: Unpublished report of Soil Conservation Office, Cooch Behar.

Fig. 2.

Change in land utilisation pattern. Data source: Unpublished report of Soil Conservation Office, Cooch Behar.

Fig. 3.

Change in micro-irrigation structures and their effective coverage and drainage conditions (STW, shallow tubewell; WHS, water harvesting structures). Data source: Unpublished report of Soil Conservation Office, Cooch Behar.

Fig. 3.

Change in micro-irrigation structures and their effective coverage and drainage conditions (STW, shallow tubewell; WHS, water harvesting structures). Data source: Unpublished report of Soil Conservation Office, Cooch Behar.

Fig. 4.

Change in drainage conditions. Source: Primary survey.

Fig. 4.

Change in drainage conditions. Source: Primary survey.

Changes in adoption of watershed technology

Table 5 indicates that roof rainwater harvesting was the most unexplored practice (100% of respondents were unaware of this technology even after implementation of the project), followed by gully plugging, vegetative barrier, stone bunds, deep tillage, and check dams. In the post-project period, although the farmers gained knowledge about watershed technology, they did not adopt any practice. The reasons cited were insufficient skill-based training facilities, requirement of funds, and rigid subsidy schemes. After the implementation of the project, few farmers adopted farm ponds, open wells, earthen bunds, and mulching technology as water conservation measures. Overall, the KAQs in the pre- and post-project periods did not differ statistically and thus have not been substantially affected by the adoption of these technologies. Contradictory effects were observed in the case of adoption of crop production technology and watershed technology (comparing Tables 4 and 5). Community mobilisation is believed to be a crucial factor affecting the adoption of watershed technology, but Rangamati watershed failed to gain impetus in this respect. Furthermore, the observation supports the findings of Kulshrestha et al. (2014).

Table 5.

Adoption scenario of water conservation technology (percentage of respondents).

N = 60
 
Water conservation technologies Area Don't know Know but not adopted Adopted KAQ 
Roof rainwater harvesting Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Farm ponds Pre-Project 0.00 100.00 0.00 0.50 
Post-Project 0.00 85.00 15.00 0.58 
Check dams Pre-Project 0.00 100.00 0.00 0.50 
Post-Project 0.00 100.00 0.00 0.50 
Open wells Pre-Project 16.67 83.33 0.00 0.42 
Post-Project 0.00 96.67 3.33 0.52 
Earthen bunds Pre-Project 83.33 16.67 0.00 0.08 
Post-Project 55.00 5.00 40.00 0.43 
Stone bunds Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 96.67 3.33 0.00 0.02 
Gully plugging Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Deep tillage Pre-Project 93.33 6.67 0.00 0.03 
Post-Project 93.33 6.67 0.00 0.03 
Deep furrows Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 100.00 0.00 0.00 0.00 
Vegetative barriers Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Mulching Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 90.00 6.67 3.33 0.07 
Drought-prone crop Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 98.33 1.67 0.00 0.01 
Overall KAQ: Pre-Project = 0.18; Post-Project = 0.13(Wilcoxon t = 2.0; p > 0.07) 
N = 60
 
Water conservation technologies Area Don't know Know but not adopted Adopted KAQ 
Roof rainwater harvesting Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Farm ponds Pre-Project 0.00 100.00 0.00 0.50 
Post-Project 0.00 85.00 15.00 0.58 
Check dams Pre-Project 0.00 100.00 0.00 0.50 
Post-Project 0.00 100.00 0.00 0.50 
Open wells Pre-Project 16.67 83.33 0.00 0.42 
Post-Project 0.00 96.67 3.33 0.52 
Earthen bunds Pre-Project 83.33 16.67 0.00 0.08 
Post-Project 55.00 5.00 40.00 0.43 
Stone bunds Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 96.67 3.33 0.00 0.02 
Gully plugging Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Deep tillage Pre-Project 93.33 6.67 0.00 0.03 
Post-Project 93.33 6.67 0.00 0.03 
Deep furrows Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 100.00 0.00 0.00 0.00 
Vegetative barriers Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 100.00 0.00 0.00 0.00 
Mulching Pre-Project 96.67 3.33 0.00 0.02 
Post-Project 90.00 6.67 3.33 0.07 
Drought-prone crop Pre-Project 100.00 0.00 0.00 0.00 
Post-Project 98.33 1.67 0.00 0.01 
Overall KAQ: Pre-Project = 0.18; Post-Project = 0.13(Wilcoxon t = 2.0; p > 0.07) 

Source: Primary survey.

Farm level biophysical changes

Various community level and individual farm level measures have contributed in improving the biophysical conditions of the farm. The biophysical conditions were assessed indirectly by using opinion data of the farmers on different aspects. MSs were obtained to assess the degree of change observed in various aspects of farm conditions. An MS of 1 indicated the highest change, whereas 0 indicated NC. An MS with a negative value indicated deterioration in the biophysical conditions. From Table 6 we conclude that soil erosion in farms (MS = 0.725), availability of water in farm ponds (MS = 0.708), and availability of water in the dry seasons (MS = 0.675) improved considerably, whereas all other conditions showed marginal improvement. These changes in the farm level further altered the total cropping pattern and cropping intensity in that area. A similar result was recorded by Palanisami & Suresh Kumar (2009).

Table 6.

Changes in farm conditions (percentage of respondents).

N = 60
 
Changes occurred in HI Improved NC Deteriorated Highly deteriorated MS 
Soil erosion from farm 45.00 55.00 0.00 0.00 0.00 0.725 
Soil sedimentation in ditches and furrows 1.67 78.33 20.00 0.00 0.00 0.408 
Water availability in farm ponds 45.00 51.67 3.33 0.00 0.00 0.708 
Water availability in dry seasons 41.67 51.67 6.67 0.00 0.00 0.675 
Groundwater table 26.67 66.67 6.67 0.00 0.00 0.600 
Cultivation area in dry seasons 20.00 51.67 28.33 0.00 0.00 0.458 
N = 60
 
Changes occurred in HI Improved NC Deteriorated Highly deteriorated MS 
Soil erosion from farm 45.00 55.00 0.00 0.00 0.00 0.725 
Soil sedimentation in ditches and furrows 1.67 78.33 20.00 0.00 0.00 0.408 
Water availability in farm ponds 45.00 51.67 3.33 0.00 0.00 0.708 
Water availability in dry seasons 41.67 51.67 6.67 0.00 0.00 0.675 
Groundwater table 26.67 66.67 6.67 0.00 0.00 0.600 
Cultivation area in dry seasons 20.00 51.67 28.33 0.00 0.00 0.458 

Source: Primary survey.

Conclusion

Watershed management is a landscape-based practice for establishing improved natural resource management systems and to ensure better livelihoods and conservation of natural resources. Watershed development can ensure the development of households with increased production through the adoption of new technologies and expansion of cultivable areas. It demands increased labour and generates alternative employment opportunities for mainly poor and landless farmers. The present study confirmed all the above general trends. The introduction of the Rangamati watershed project improved the quantity and quality of cultivable land, enhanced adoption of crop production technology, and ensured the availability of water in the dry seasons and thus improved the productivity of crops. Furthermore, with the adoption of watershed technologies, the project also showed commendable achievements in providing micro-irrigation facilities and increasing the total arable land and forest areas, which were manifested as the biophysical characteristics of farms, thereby leading to sustainability in water and soil usage.

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