Stage-discharge sediment modelling using soft computing techniques and prioritization of sub-watersheds of Ghatshila watershed
| dc.contributor.advisor | Pravendra Kumar | |
| dc.contributor.author | Manish Kumar | |
| dc.date.accessioned | 2021-07-27T11:31:47Z | |
| dc.date.available | 2021-07-27T11:31:47Z | |
| dc.date.issued | 2021-02 | |
| dc.description.abstract | Soil and water resources conservation are primary aspect for sustainable development of agricultural production. In this study, soft computing techniques like artificial neural network (ANN), support vector machine (SVM), wavelet based artificial neural network (WANN), wavelet based support vector machine (WSVM) and multilinear regression (MLR) were used for stage-discharge-sediment modelling. The stage, discharge and suspended sediment concentration (SSC) data of 10 years duration (2004-2013) was used for prediction of present day SSC for three sites namely, Adityapur, Jamshedpur and Ghatshila sites of Ghatshila watershed. Gamma test was used to select the best input combination for the development of models. Multilayer perceptron was used for ANN and WANN techniques while linear and radial kernel function were used for SVM and WSVM techniques. The results showed that the WSVM-LF model was found to be the best among all developed models for Adityapur and Ghatshila site while SVM-RF model was found to be the best for Jamshedpur site. Further, prioritization of the sub-watershed based on principal component analysis (PCA) was carried out for Ghatshila watershed. The morphometric analysis of twenty five sub-watersheds of Ghatshila watershed was done based on information obtained from drainage map extracted using remote sensing data and GIS tool. Based on PCA, four principal components namely, texture ratio (T), drainage density (Dd), circulatory ratio (Rc) and stream frequency (Fs) were identified for prioritization. Based on compound factor, SW-15 sub-watershed assigned with rank 1 priority whereas SW-22 sub-watersheds was assigned with rank 25. Therefore, SW-15 sub-watershed can be treated with suitable conservation measures. | en_US |
| dc.identifier.uri | https://krishikosh.egranth.ac.in/handle/1/5810170931 | |
| dc.keywords | discharge, sediments, models, software, computing, watersheds | en_US |
| dc.language.iso | English | en_US |
| dc.pages | 237 | en_US |
| dc.publisher | G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand) | en_US |
| dc.research.problem | Artificial Neural Networks | en_US |
| dc.sub | Soil and Water Conservation | en_US |
| dc.theme | Watershed Management | en_US |
| dc.these.type | Ph.D | en_US |
| dc.title | Stage-discharge sediment modelling using soft computing techniques and prioritization of sub-watersheds of Ghatshila watershed | en_US |
| dc.type | Thesis | en_US |