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Nikam, Sandip
- Geomorphic Response Runoff Model for Prediction of June Monthly Runoff from Small Watersheds
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1 Agricultural Engineering Department, College of Agriculture, DHULE (M.S.), IN
2 College of Agricultural Engineering, Maldad, AHMEDNAGAR (M.S.), IN
1 Agricultural Engineering Department, College of Agriculture, DHULE (M.S.), IN
2 College of Agricultural Engineering, Maldad, AHMEDNAGAR (M.S.), IN
Source
International Journal of Agricultural Engineering, Vol 9, No 1 (2016), Pagination: 27-31Abstract
Quantitative assessment of runoff is needed for proper management of land and water resources especially for optimum agriculture production. This requires comprehensive knowledge of the various hydrological phenomena occurring in the catchment. All the watersheds cannot be gauged, as it would be costly and time consuming. Therefore, the indirect method of runoff quantification has to be resorted. The geomorphic parameters are quite useful as they reflect all the causative factors of the runoff. In the present study ten watersheds from Tapi catchment, Maharashtra, India were selected for development of geomorphic response models for prediction of June monthly runoff. Twelve geomorphic parameters were selected for development of model out of which two parameters, Sa and Rb are screened out in the principal component analysis. Remaining ten parameters are grouped into three physically significant components. The data sets were used to regress the runoff factor, R/√A , on three independent parameters (one each from already established components and rainfall factor, P/√A . It is observed that percentage deviation ranged from 0.3 to 7.0 using monthly runoff model for June. Therefore, developed runoff can be conveniently used for prediction of June month runoff from unguaged watersheds of the basin having similar physiographic conditions.Keywords
Geomorphic Response Model, Geomorphological Parameters, Runoff, Sediment Production Rate, PCA.References
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- Assessment of Groundwater Quality in Jaisamand Catchment for Drinking Purpose Using Geographical Information System
Abstract Views :310 |
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Authors
Affiliations
1 College of Technology and Engineering, Maharana Pratap University of Agricultural Technology, Udaipur (Rajasthan), IN
2 Agriculture College, Dhule (M.S.), IN
1 College of Technology and Engineering, Maharana Pratap University of Agricultural Technology, Udaipur (Rajasthan), IN
2 Agriculture College, Dhule (M.S.), IN
Source
International Journal of Agricultural Engineering, Vol 10, No 1 (2017), Pagination: 43-50Abstract
The present study focuses on a GIS-based assessment and characterization of groundwater quality using pre monsoon and post monsoon groundwater quality data. Spatio-temporal variations of water quality parameters in the study area were analysed by using GIS techniques. Maximum area of Jaisamand catchment showed the drinking water quality within permissible limit. EC somewhat extent within permissible limit during pre monsoon period. Sulphate content also exceeded from permissible limit some extent in pre monsoon period but in post monsoon period it was within permissible range. The maximum total dissolved solids were found in western site of study area during pre monsoon period whereas in post monsoon period maximum area showed total dissolved solids within permissible range.Keywords
Water Quality, GIS, Assessment, Spatio-Temporal.References
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- Geomorphic Modelling for Small Watersheds using Principal Component Analysis
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Authors
Affiliations
1 Department of Agricultural Engineerng, College of Agriculture (MPKV), Dhule (M.S.), IN
1 Department of Agricultural Engineerng, College of Agriculture (MPKV), Dhule (M.S.), IN
Source
International Journal of Agricultural Engineering, Vol 13, No 1 (2020), Pagination: 62-66Abstract
Principal Component Analysis was carried out for grouping the different parameters into the Principal Components. To understand the behaviour of all the parameters pertaining to study areas, and to reduce the dimensionality of database, the data pertaining to twelve parameters of ten small watersheds were submitted for Principal Component Analysis. The method of components analysis, then, involves the rotation in the total variable space - an orthogonal or uncorrelated transformation wherein each of the n original variables is describable, in terms of the n new principal components. An important feature of the new components is that they account, in turn, for a maximum amount of variance of the variables. Analysis extracted three components as a Principal Components with 10 parameters, accounting for a total variance of 97.256 per cent. The first component is highly correlated with Re, Rc, Sb and Lbw accounting for 68.52 per cent variance. Second component is strongly correlated with RN accounting for 18.60 per cent variance and Third with Sc, accounting for 10.13 per cent variance. Finally, these extracted 10 parameters were used for modeling for prediction of sediment yield and runoff from selected small watersheds of Tapi basin, Maharashtra, India.Keywords
Principal Component Analysis, Geomorphological Parameters, Morphometric Model, Small WatershedsReferences
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