Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets
Water-related soil erosion is a major environmental concern for catchments with barren topography in arid and semi-arid regions. With the growing interest in irrigation infrastructure development in arid regions, the current study investigates the runoff and sediment yield for the Gomal River catchm...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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MDPI
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/119637 |
| _version_ | 1855519755685855232 |
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| author | Ijaz, M. A. Ashraf, M. Hamid, S. Niaz, Y. Waqas, M. M. Tariq, M. A. U. R. Saifullah, M. Bhatti, Muhammad Tousif Tahir, A. A. Ikram, K. Shafeeque, M. Ng, A.W.M. |
| author_browse | Ashraf, M. Bhatti, Muhammad Tousif Hamid, S. Ijaz, M. A. Ikram, K. Ng, A.W.M. Niaz, Y. Saifullah, M. Shafeeque, M. Tahir, A. A. Tariq, M. A. U. R. Waqas, M. M. |
| author_facet | Ijaz, M. A. Ashraf, M. Hamid, S. Niaz, Y. Waqas, M. M. Tariq, M. A. U. R. Saifullah, M. Bhatti, Muhammad Tousif Tahir, A. A. Ikram, K. Shafeeque, M. Ng, A.W.M. |
| author_sort | Ijaz, M. A. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Water-related soil erosion is a major environmental concern for catchments with barren topography in arid and semi-arid regions. With the growing interest in irrigation infrastructure development in arid regions, the current study investigates the runoff and sediment yield for the Gomal River catchment, Pakistan. Data from a precipitation gauge and gridded products (i.e., GPCC, CFSR, and TRMM) were used as input for the SWAT model to simulate runoff and sediment yield. TRMM shows a good agreement with the data of the precipitation gauge (˜1%) during the study period, i.e., 2004–2009. However, model simulations show that the GPCC data predicts runoff better than the other gridded precipitation datasets. Similarly, sediment yield predicted with the GPCC precipitation data was in good agreement with the computed one at the gauging site (only 3% overestimated) for the study period. Moreover, GPCC overestimated the sediment yield during some years despite the underestimation of flows from the catchment. The relationship of sediment yields predicted at the sub-basin level using the gauge and GPCC precipitation datasets revealed a good correlation (R2 = 0.65) and helped identify locations for precipitation gauging sites in the catchment area. The results at the sub-basin level showed that the sub-basin located downstream of the dam site contributes three (3) times more sediment yield (i.e., 4.1%) at the barrage than its corresponding area. The findings of the study show the potential usefulness of the GPCC precipitation data for the computation of sediment yield and its spatial distribution over data-scarce catchments. The computations of sediment yield at a spatial scale provide valuable information for deciding watershed management strategies at the sub-basin level. |
| format | Journal Article |
| id | CGSpace119637 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | CGSpace1196372025-12-08T10:29:22Z Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets Ijaz, M. A. Ashraf, M. Hamid, S. Niaz, Y. Waqas, M. M. Tariq, M. A. U. R. Saifullah, M. Bhatti, Muhammad Tousif Tahir, A. A. Ikram, K. Shafeeque, M. Ng, A.W.M. sediment yield forecasting river basins catchment areas precipitation datasets hydrological modelling watershed management dams runoff sediment load soil erosion soil types land use rain semiarid zones spatial distribution biochemistry Water-related soil erosion is a major environmental concern for catchments with barren topography in arid and semi-arid regions. With the growing interest in irrigation infrastructure development in arid regions, the current study investigates the runoff and sediment yield for the Gomal River catchment, Pakistan. Data from a precipitation gauge and gridded products (i.e., GPCC, CFSR, and TRMM) were used as input for the SWAT model to simulate runoff and sediment yield. TRMM shows a good agreement with the data of the precipitation gauge (˜1%) during the study period, i.e., 2004–2009. However, model simulations show that the GPCC data predicts runoff better than the other gridded precipitation datasets. Similarly, sediment yield predicted with the GPCC precipitation data was in good agreement with the computed one at the gauging site (only 3% overestimated) for the study period. Moreover, GPCC overestimated the sediment yield during some years despite the underestimation of flows from the catchment. The relationship of sediment yields predicted at the sub-basin level using the gauge and GPCC precipitation datasets revealed a good correlation (R2 = 0.65) and helped identify locations for precipitation gauging sites in the catchment area. The results at the sub-basin level showed that the sub-basin located downstream of the dam site contributes three (3) times more sediment yield (i.e., 4.1%) at the barrage than its corresponding area. The findings of the study show the potential usefulness of the GPCC precipitation data for the computation of sediment yield and its spatial distribution over data-scarce catchments. The computations of sediment yield at a spatial scale provide valuable information for deciding watershed management strategies at the sub-basin level. 2022-05-05 2022-05-23T20:44:06Z 2022-05-23T20:44:06Z Journal Article https://hdl.handle.net/10568/119637 en Open Access MDPI Ijaz, M. A.; Ashraf, M.; Hamid, S.; Niaz, Y.; Waqas, M. M.; Tariq, M. A. U. R.; Saifullah, M.; Bhatti, Muhammad Tousif; Tahir, A. A.; Ikram, K.; Shafeeque, M.; Ng, A. W. M. 2022. Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets. Water, 14(9):1480. (Special issue: Innovate Approaches to Sustainable Water Resource Management under Population Growth, Lifestyle Improvements, and Climate Change) [doi: https://doi.org/10.3390/w14091480] |
| spellingShingle | sediment yield forecasting river basins catchment areas precipitation datasets hydrological modelling watershed management dams runoff sediment load soil erosion soil types land use rain semiarid zones spatial distribution biochemistry Ijaz, M. A. Ashraf, M. Hamid, S. Niaz, Y. Waqas, M. M. Tariq, M. A. U. R. Saifullah, M. Bhatti, Muhammad Tousif Tahir, A. A. Ikram, K. Shafeeque, M. Ng, A.W.M. Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title | Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title_full | Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title_fullStr | Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title_full_unstemmed | Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title_short | Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets |
| title_sort | prediction of sediment yield in a data scarce river catchment at the sub basin scale using gridded precipitation datasets |
| topic | sediment yield forecasting river basins catchment areas precipitation datasets hydrological modelling watershed management dams runoff sediment load soil erosion soil types land use rain semiarid zones spatial distribution biochemistry |
| url | https://hdl.handle.net/10568/119637 |
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