Blending GIS and RS Technologies with Mathematical Tools for Agricultural Pollution Assessment
Water! As correctly said is the life for all living things. It is the most precious resource on this earth, which is, under threat of overuse and pollution. Water pollution is of great concern to everybody since it shows direct impact on human health. Two broad categories of water pollution vis-à-vis point and non-point are expanding enormously in terms of time and space. Agriculture is one of the main activities contributing to non-point Source Pollution (NPS) of water bodies in India as well as over the globe. In this context, a mathematical modeling study coupled with Remote Sensing (RS) Analysis and Geographic Information System (GIS) mapping was attempted for Nagpur District of Maharashtra State in India. Satellite image of IRS-P6 LISS III data was classified using supervised classification algorithm to map major landuse classes in the study area. The numerical data on type of crop grown, area under each crop, cropping pattern, nutrient requirement of crop, fertilizer used, soil type and rainfall was obtained from secondary sources. Mathematical computations were done for total amount of fertilizer N:P:K applied in two cropping seasons viz. Kharif (from June to November) and Rabi (from December to May). Considering the overall fate of nitrogen fertilizer as reported to be 30 to 70% -removed in harvested crop, 5 to 10%-leaching loss, 10 to 30% -gaseous loss, and 10 to 40%-incorporated into soil organic matter; the nutrient remaining in the soil were estimated. The NPS loading from agricultural land which is available for wash off and gets transported with runoff were estimated by simulating the monthly lodographs in terms of N and P. Runoff estimation was landuse-specific and only runoff generated from agricultural land was considered for load estimation. Results indicated that out of thirteen tehsils (small administrative units), maximum runoff was generated from Narkher tehsil and the nutrient removal was 22.6% N and 59.2% P. GIS-mapping of buffer zone of 2km distance around each water body and overlaying of slope map was performed to identify the water resources that are likely to receive pollution load vis-à-vis environmental threat. The remaining load which would accumulate onto the land or drainage was categorized as environmental burden. The estimated environmental burden and environmental threat can form basis in formulation of guidelines for structural and non-structural Best Management Practices (BMPs) for water pollution control within the administrative boundary.
agricultural pollution nutrients GIS RS mathematical modelling.
Aabha SARGAONKAR
Environmental Systems Design and Modelling Division,National Environmental Engineering Research Institute Nehru Marg,Nagpur,India–440 020
国际会议
2009 International Symposium on Environmental Science and Technology(2009环境科学与技术国际会议)
上海
英文
1215-1221
2009-06-02（万方平台首次上网日期，不代表论文的发表时间）