Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions
Study region: The Upper Blue Nile Basin in Ethiopia, characterized by its complex hydrological system, is the focus of this study. The basin includes 76 gauged watersheds, which were analyzed to estimate parameters for ungauged locations using regionalization techniques. Study focus: Regression-Base...
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Elsevier
2025-02-01
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| Series: | Journal of Hydrology: Regional Studies |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581824005123 |
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| author | Temesgen T. Mihret Fasikaw A. Zemale Abeyou W. Worqlul Ayenew D. Ayalew Nicola Fohrer |
| author_facet | Temesgen T. Mihret Fasikaw A. Zemale Abeyou W. Worqlul Ayenew D. Ayalew Nicola Fohrer |
| author_sort | Temesgen T. Mihret |
| collection | DOAJ |
| description | Study region: The Upper Blue Nile Basin in Ethiopia, characterized by its complex hydrological system, is the focus of this study. The basin includes 76 gauged watersheds, which were analyzed to estimate parameters for ungauged locations using regionalization techniques. Study focus: Regression-Based Approach (RBA), Physical Similarity Approach (PSA), and Spatial Proximity Approach (SPA), for estimating GR4J model parameters. A 25 km by 25 km fishnet-based grid was implemented to enable parameter prediction for ungauged watersheds. Principal Component Analysis (PCA) and k-means clustering were used to group gauged watersheds into three homogeneous clusters, with Beressa, Dedessa, and Gilgel Abay selected as pseudo-watersheds for validation. Model performance was evaluated using PBIAS, R², and NSE metrics. New hydrological insights for the region: The RBA outperformed PSA and SPA in parameter transfer, achieving R² values of 0.57, 0.79, and 0.67; PBIAS values of 7.3, −1.5, and 2.6; and NSE values of 0.58, 0.78, and 0.67 for Beressa, Dedessa, and Gilgel Abay, respectively. Incorporating grid-based parameter values further improved model performance, with NSE values of 0.81 for Dedessa, 0.63 for Beressa, and 0.61 for Gilgel Abay. These findings highlight the effectiveness of the grid-based regionalization approach for accurate streamflow prediction in ungauged watersheds within the Upper Blue Nile Basin. |
| format | Article |
| id | doaj-art-0fe8a963da354c7784b5191535704366 |
| institution | Kabale University |
| issn | 2214-5818 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-0fe8a963da354c7784b51915357043662025-01-22T05:42:16ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-02-0157102163Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regionsTemesgen T. Mihret0Fasikaw A. Zemale1Abeyou W. Worqlul2Ayenew D. Ayalew3Nicola Fohrer4Faculty of Civil and Water Resources Engineering, Bahir Dar University, Ethiopia; Department of Water Resources and Irrigation Engineering, Assosa University, Ethiopia; Corresponding author at: Faculty of Civil and Water Resources Engineering, Bahir Dar University, EthiopiaFaculty of Civil and Water Resources Engineering, Bahir Dar University, EthiopiaInternational Center for Agricultural Research in the Dry Areas (ICARDA), Tunis, TunisiaDepartment of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Kiel, GermanyDepartment of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Kiel, GermanyStudy region: The Upper Blue Nile Basin in Ethiopia, characterized by its complex hydrological system, is the focus of this study. The basin includes 76 gauged watersheds, which were analyzed to estimate parameters for ungauged locations using regionalization techniques. Study focus: Regression-Based Approach (RBA), Physical Similarity Approach (PSA), and Spatial Proximity Approach (SPA), for estimating GR4J model parameters. A 25 km by 25 km fishnet-based grid was implemented to enable parameter prediction for ungauged watersheds. Principal Component Analysis (PCA) and k-means clustering were used to group gauged watersheds into three homogeneous clusters, with Beressa, Dedessa, and Gilgel Abay selected as pseudo-watersheds for validation. Model performance was evaluated using PBIAS, R², and NSE metrics. New hydrological insights for the region: The RBA outperformed PSA and SPA in parameter transfer, achieving R² values of 0.57, 0.79, and 0.67; PBIAS values of 7.3, −1.5, and 2.6; and NSE values of 0.58, 0.78, and 0.67 for Beressa, Dedessa, and Gilgel Abay, respectively. Incorporating grid-based parameter values further improved model performance, with NSE values of 0.81 for Dedessa, 0.63 for Beressa, and 0.61 for Gilgel Abay. These findings highlight the effectiveness of the grid-based regionalization approach for accurate streamflow prediction in ungauged watersheds within the Upper Blue Nile Basin.http://www.sciencedirect.com/science/article/pii/S2214581824005123Upper Blue Nile River BasinHydrological modelingGR4JRegionalizationRegression equationUngauged watersheds |
| spellingShingle | Temesgen T. Mihret Fasikaw A. Zemale Abeyou W. Worqlul Ayenew D. Ayalew Nicola Fohrer Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions Journal of Hydrology: Regional Studies Upper Blue Nile River Basin Hydrological modeling GR4J Regionalization Regression equation Ungauged watersheds |
| title | Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions |
| title_full | Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions |
| title_fullStr | Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions |
| title_full_unstemmed | Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions |
| title_short | Unlocking watershed mysteries: Innovative regionalization of hydrological model parameters in data-scarce regions |
| title_sort | unlocking watershed mysteries innovative regionalization of hydrological model parameters in data scarce regions |
| topic | Upper Blue Nile River Basin Hydrological modeling GR4J Regionalization Regression equation Ungauged watersheds |
| url | http://www.sciencedirect.com/science/article/pii/S2214581824005123 |
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