Background

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A View of WYC Canal

Approximately 80% of water resource of the country is used in irrigated agriculture and canals contribute to approximately 50% to the total irrigated area. In spite of massive investment in the irrigation sector of the country, land and water productivity in canal commands remains low due to poor canal supply management and inefficient on-farm water management practices. This could further degrade due to poor maintenance of canals, ongoing secondary soil salinization and waterlogging, degradation of groundwater quality, diversion of canal water to other user sectors, farmers’ limited capacity to afford risks, etc. This deterioration in crop productivity would lead to socio-economic unrest and conflicts in rural societies living in canal commands. In order to enhance productivity and to reduce conflicts in farming society, management of land and water resources in canal commands requires  to apply an holistic approach to understand spatial variability of resources in different reaches of a canal in the terms of water availability and crop water demands  and other bio-physical constraints during crop growing seasons. Besides, socio-economic information of farmers needs to be coupled to develop best management practices (BMPs) for canal reach specific problem under various constraints to enhance water productivity. The state-of-the-art geo-information technology including satellite remote sensing, differential GPS based field survey and GIS will be employed for assessing and monitoring land and water productivity at field and command scale as conventional techniques 

for assessing productivity in canal commands are time consuming and costly. Multidate remotely sensed data along with ground truth information will be used in GIS for productivity gap analysis leading to identification and delineation of homogenous areas of different productivity levels in various segments of a canal command. The PRA survey will be employed for collection of socio-economic data of farmers living in the command. Thus, there is a scope to upscale canal reach technology to command scale in order to improve land and water productivity in irrigated areas, particularly in areas of low productivity leading to substantial increase in productivity at the command level. The low productivity areas in different segments of the canal command could be analysed to delineate homogenous areas under various resource constraints and socio-economic conditions of farmers to work out suitable strategies and management option scenarios for enhancing land and water productivity.

In the past, a few decision support systems (DSS) for canal water supply management in the country were developed on the basis of non-spatial bio-physical resource data. Since land and water management processes in a command vary considerably in space and time, these DSS could not generate realistic scenarios in space for developing alternate management plans. Of late, development of GIS based DSS, widely known as spatial DSS (SDSS) for canal water management have been attempted for research purpose on the basis of command resource data, but these could not deliver practical management options due to lack of socio-economic information of stakeholders for optimizing the productivity. There is a need to develop SDSS for canal commands for generating realistic BMPs in space and time under various resource and production constraints for enhancing productivity. In this sub-project under the NAIP, GIS based DSS for the Western Yamuna canal (WYC) command in Haryana will be developed as a model by integrating bio-physical resources and socio-economic data of the command within DSS framework to generate BMPs for enhancing productivity of the canal command in irrigated saline environment including deficit canal water supply, poor soil and water quality and waterlogging conditions. The developed SDSS will be validated, fine-tuned and implemented in the canal command for diversifying the options in SDSS. Computer program and new knowledge on SDSS would be transferred effectively to stakeholders through sensitisation and capacity building trainings, field demonstrations and interactive workshops so as to enable them to apply SDSS to arrive at right decision with BMP. The sub-project is multidisciplinary in nature and in consortium mode for utilising expertises of participating institutions with unique built-in features of modelling and stakeholder servicing to infuse confidence for growing more food with less water and with poor quality soil and water resources.