Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China
Water yield (WY) is a critical indicator of water availability, playing a significant role in sustaining ecosystem stability. Understanding the factors influencing water yield is crucial for effective regional water resource management and the long-term sustainability of ecosystems. However, the dyn...
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Elsevier
2025-09-01
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| Schriftenreihe: | Ecological Indicators |
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| author | Bo Guo Hui Yang Chunyu Zhu Ying Guo Yuhan Zhao Jiansheng Cao Yanjun Shen |
| author_facet | Bo Guo Hui Yang Chunyu Zhu Ying Guo Yuhan Zhao Jiansheng Cao Yanjun Shen |
| author_sort | Bo Guo |
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| description | Water yield (WY) is a critical indicator of water availability, playing a significant role in sustaining ecosystem stability. Understanding the factors influencing water yield is crucial for effective regional water resource management and the long-term sustainability of ecosystems. However, the dynamics of water yield and the driving mechanisms in the Taihang Mountain Region (TMR), particularly the influence of extreme precipitation, remain insufficiently understood. In this study, we employed the InVEST model to analyze water yield dynamics across the TMR. We introduced an analytical framework that integrates detrending analysis with scenario-based simulation to investigate the contributions of climate change (CC) and land use and land cover change (LUCC) to water yield. Furthermore, we applied the optimal parameters-based geographical detector (OPGD) to examine the influence of precipitation characteristics on water yield. We found that water yield in the TMR exhibited a decreasing trend of −0.66 mm/yr from 1990 to 2020. Significant spatial heterogeneity was observed in water yield changes, with notable decreases predominantly distributed in the eastern slope of the TMR. CC and LUCC contributed 86.46 % and 13.54 % to water yield variation, respectively. Our findings revealed that changes in water yield in the TMR are strongly influenced by precipitation patterns, with precipitation trends and extreme precipitation serving as the primary drivers. Notably, in areas experiencing significant water yield decline, precipitation intensity plays a more dominant role than precipitation trends. Afforestation areas exhibited a significantly higher decline in water yield than non-afforestation regions from 1990 to 2020. These findings provide valuable insights for guiding afforestation projects in TMR. |
| format | Article |
| id | doaj-art-13dcfb3c876f438f89ead05fdc2f7fd1 |
| institution | Matheson Library |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-13dcfb3c876f438f89ead05fdc2f7fd12025-07-23T05:23:48ZengElsevierEcological Indicators1470-160X2025-09-01178113923Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, ChinaBo Guo0Hui Yang1Chunyu Zhu2Ying Guo3Yuhan Zhao4Jiansheng Cao5Yanjun Shen6Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, ChinaKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, ChinaKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, ChinaKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China; University of Chinese Academy of Sciences, Beijing 100049, China; Corresponding authors at: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China.Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China; University of Chinese Academy of Sciences, Beijing 100049, China; Corresponding authors at: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China.Water yield (WY) is a critical indicator of water availability, playing a significant role in sustaining ecosystem stability. Understanding the factors influencing water yield is crucial for effective regional water resource management and the long-term sustainability of ecosystems. However, the dynamics of water yield and the driving mechanisms in the Taihang Mountain Region (TMR), particularly the influence of extreme precipitation, remain insufficiently understood. In this study, we employed the InVEST model to analyze water yield dynamics across the TMR. We introduced an analytical framework that integrates detrending analysis with scenario-based simulation to investigate the contributions of climate change (CC) and land use and land cover change (LUCC) to water yield. Furthermore, we applied the optimal parameters-based geographical detector (OPGD) to examine the influence of precipitation characteristics on water yield. We found that water yield in the TMR exhibited a decreasing trend of −0.66 mm/yr from 1990 to 2020. Significant spatial heterogeneity was observed in water yield changes, with notable decreases predominantly distributed in the eastern slope of the TMR. CC and LUCC contributed 86.46 % and 13.54 % to water yield variation, respectively. Our findings revealed that changes in water yield in the TMR are strongly influenced by precipitation patterns, with precipitation trends and extreme precipitation serving as the primary drivers. Notably, in areas experiencing significant water yield decline, precipitation intensity plays a more dominant role than precipitation trends. Afforestation areas exhibited a significantly higher decline in water yield than non-afforestation regions from 1990 to 2020. These findings provide valuable insights for guiding afforestation projects in TMR.http://www.sciencedirect.com/science/article/pii/S1470160X25008532Taihang Mountain RegionWater yieldOptimal parameters-based geographical detector (OPGD)Extreme precipitation |
| spellingShingle | Bo Guo Hui Yang Chunyu Zhu Ying Guo Yuhan Zhao Jiansheng Cao Yanjun Shen Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China Ecological Indicators Taihang Mountain Region Water yield Optimal parameters-based geographical detector (OPGD) Extreme precipitation |
| title | Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China |
| title_full | Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China |
| title_fullStr | Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China |
| title_full_unstemmed | Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China |
| title_short | Evaluating dynamics of water yield and its driving forces in the Taihang Mountain Region, China |
| title_sort | evaluating dynamics of water yield and its driving forces in the taihang mountain region china |
| topic | Taihang Mountain Region Water yield Optimal parameters-based geographical detector (OPGD) Extreme precipitation |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25008532 |
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