Theme-III-3-Web based groundwater information system for farmers & policy makers of Amritsar and Jalandhar districts (Punjab).

Abstract

Old Amritsar is one of the intensive agriculture districts of Punjab, supplying food grains to the entire country. It covers about 5000 sq Km and drained by two perennial rivers Ravi and Beas. It is composed of the recent deposits of Indo-Gangetic flood plains, which consist of alluvial sand, clay and loam. Majority of the soils are loamy or sandy loam consisting of a soil crust of varying depth. Groundwater depletion, water quality deterioration and water logging problems are the major concerns. Over the last four decades over-exploitation has been taking place through deeper tube wells and dug wells for extensive irrigation all over the central Punjab. Groundwater levels and groundwater quality being monitored since June 2007. Depth to Groundwater levels has been observed to have increased from 7.26 to 19.53m in the year 2007 to 8 to 23.23m in the during 2009. Groundwater has been depleting on an average 40 to 50cm/year. As regards groundwater quality High Nitrate and Heptachlor, Heptachlorepoxide—B, Aldrin, Diledrin, and GammaChlordane Pesticide concentrations have been detected in Groundwater. In some pockets high concentration of heavy metals has also been detected. High salinity and sodicity of the soils have led to decrease in agricultural productivity and increase in water logging. There is an urgent need for practising Sustainable Agriculture and improving groundwater resource management. For efficient management of the resource and to support taking related decisions, a web-based decision support system (DSS) has been developed based on standards from Open Geo-spatial Consortium (OGC). Information on aquifer susceptibility and suitability of groundwater for agriculture as well as for drinking purposes have been made accessible to the stakeholders. It helps download hydrogeological feature data and maps using Web Feature Service (WFS) and Web Map Service (WMS) specifications respectively. A faster updation of the feature data is feasible using the WFS from a field-based remote system. The framework developed in the research could be used to empower local people and local governments in sustainably managing soil and groundwater resources for Sustainable Agriculture.