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Non‐point source pollution estimation using a modified approach
Author(s) -
Jha Ramakar,
Ojha C. S. P.,
Bhatia K. K. S.
Publication year - 2007
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.6291
Subject(s) - nonpoint source pollution , environmental science , pollution , hydrology (agriculture) , sampling (signal processing) , drainage basin , point source pollution , digital elevation model , statistics , remote sensing , mathematics , geography , computer science , geology , cartography , ecology , geotechnical engineering , filter (signal processing) , computer vision , biology
Non‐point source (NPS) pollution from agricultural land is increasing exponentially in many countries of the world, including India. A modified approach based on the conservation of mass and reaction kinetics has been derived to estimate the inflow of non‐point source pollutants from a river reach. Two water quality variables, namely, nitrate (NO 3 ) and ortho ‐phosphate ( o ‐PO 4 ), which are main contributors as non‐point source pollution, were monitored at four locations of River Kali, western Uttar Pradesh, India, and used for calibration and validation of the model. Extensive water quality sampling was done with a total of 576 field data sets collected during the period from March 1999 to February 2000. Remote sensing and geographical information system (GIS) techniques were used to obtain land use/land cover of the region, digital elevation model (DEM), delineation of basin area contributing to non‐point source pollution at each sampling location and drainage map. The results obtained from a modified approach were compared with the existing mass‐balance equations and distributed modelling, and the performances of different equations were evaluated using error estimation viz. standard error, normal mean error, mean multiplicative error and correlation statistics. The developed model for the River Kali minimizes error estimates and improves correlation between observed and computed NPS loads. Copyright © 2007 John Wiley & Sons, Ltd.