Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin
Abstract Soil erosion is common and has a wide range of spatiotemporal variability. It is crucial in determining sediment output, which is essential for proper watershed management. In this research, we propose morphometric deterministic models (MDM) for prediction of sediment yield index using morp...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2022-05-01
|
| Series: | Applied Water Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s13201-022-01644-0 |
| _version_ | 1818210268083126272 |
|---|---|
| author | Sarita Gajbhiye Meshram Chandrashekhar Meshram Mohd Abul Hasan Muhammad Arshad Khan Saiful Islam |
| author_facet | Sarita Gajbhiye Meshram Chandrashekhar Meshram Mohd Abul Hasan Muhammad Arshad Khan Saiful Islam |
| author_sort | Sarita Gajbhiye Meshram |
| collection | DOAJ |
| description | Abstract Soil erosion is common and has a wide range of spatiotemporal variability. It is crucial in determining sediment output, which is essential for proper watershed management. In this research, we propose morphometric deterministic models (MDM) for prediction of sediment yield index using morphometric parameters of 49 watersheds from Upper Narmada Basin of Madhya Pradesh state, India. For this purpose, Shuttle Radar Topography Mission generated Digital Elevation Model was used to extract and analyze 12 morphometric parameters including linear, aerial, and relief parameters. Principle Component Analysis has been applied for the most effective parameter estimation. The linear and nonlinear MDM were discovered to be suitable for the field of sediment research due to the high value of R 2 (over 70%). The sediment yield forecasting is critical for taking the appropriate management measures in the watershed to reduce the sediment load in the reservoir and extend the life of the structure. |
| first_indexed | 2024-12-12T05:13:54Z |
| format | Article |
| id | doaj.art-6af9dc543cc746cb85d9e25369d6dd57 |
| institution | Directory Open Access Journal |
| issn | 2190-5487 2190-5495 |
| language | English |
| last_indexed | 2024-12-12T05:13:54Z |
| publishDate | 2022-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Applied Water Science |
| spelling | doaj.art-6af9dc543cc746cb85d9e25369d6dd572022-12-22T00:36:49ZengSpringerOpenApplied Water Science2190-54872190-54952022-05-0112711110.1007/s13201-022-01644-0Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada BasinSarita Gajbhiye Meshram0Chandrashekhar Meshram1Mohd Abul Hasan2Muhammad Arshad Khan3Saiful Islam4Water Resources and Applied Mathematics Research LabDepartment of Mathematics, Jaywanti Haksar Government P. G. College, Chhindwara UniversityCivil Engineering Department, College of Engineering, King Khalid UniversityDepartment of Chemical Engineering, College of Engineering, King Khalid UniversityCivil Engineering Department, College of Engineering, King Khalid UniversityAbstract Soil erosion is common and has a wide range of spatiotemporal variability. It is crucial in determining sediment output, which is essential for proper watershed management. In this research, we propose morphometric deterministic models (MDM) for prediction of sediment yield index using morphometric parameters of 49 watersheds from Upper Narmada Basin of Madhya Pradesh state, India. For this purpose, Shuttle Radar Topography Mission generated Digital Elevation Model was used to extract and analyze 12 morphometric parameters including linear, aerial, and relief parameters. Principle Component Analysis has been applied for the most effective parameter estimation. The linear and nonlinear MDM were discovered to be suitable for the field of sediment research due to the high value of R 2 (over 70%). The sediment yield forecasting is critical for taking the appropriate management measures in the watershed to reduce the sediment load in the reservoir and extend the life of the structure.https://doi.org/10.1007/s13201-022-01644-0Unguaged watershedsMorphological parametersSediment yield indexPCA |
| spellingShingle | Sarita Gajbhiye Meshram Chandrashekhar Meshram Mohd Abul Hasan Muhammad Arshad Khan Saiful Islam Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin Applied Water Science Unguaged watersheds Morphological parameters Sediment yield index PCA |
| title | Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin |
| title_full | Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin |
| title_fullStr | Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin |
| title_full_unstemmed | Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin |
| title_short | Morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper Narmada Basin |
| title_sort | morphometric deterministic model for prediction of sediment yield index for selected watersheds in upper narmada basin |
| topic | Unguaged watersheds Morphological parameters Sediment yield index PCA |
| url | https://doi.org/10.1007/s13201-022-01644-0 |
| work_keys_str_mv | AT saritagajbhiyemeshram morphometricdeterministicmodelforpredictionofsedimentyieldindexforselectedwatershedsinuppernarmadabasin AT chandrashekharmeshram morphometricdeterministicmodelforpredictionofsedimentyieldindexforselectedwatershedsinuppernarmadabasin AT mohdabulhasan morphometricdeterministicmodelforpredictionofsedimentyieldindexforselectedwatershedsinuppernarmadabasin AT muhammadarshadkhan morphometricdeterministicmodelforpredictionofsedimentyieldindexforselectedwatershedsinuppernarmadabasin AT saifulislam morphometricdeterministicmodelforpredictionofsedimentyieldindexforselectedwatershedsinuppernarmadabasin |