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• W4224015977 abstract "Identifying and mapping of potential groundwater-dependent ecosystems (pGDEs) are pivotal to well understanding of the interaction between groundwater and ecosystem as well as rational allocation of regional water resources. As the largest tributary of the Yellow River with complex landscape types, the Weihe River basin is an essential region for both water and sediment management in the Yellow River basin. However, either the distribution of pGDEs or the role of groundwater in ecosystems of the Weihe River basin has been largely unexplored. In this study, focused on the Weihe River basin, the framework for identifying and mapping of pGDEs was suggested to perform hierarchical grade based on the coupling of NDVI classification method and Groundwater-dependent Ecosystem Mapping (GEM) method. Moreover, the identification and mapping of pGDEs were validated based on statistical analyses among Normalized Difference Vegetation Index (NDVI), water table depth (WTD), previous month’s precipitation (Ppm), evapotranspiration (ET), and precipitation (P). The spatial patterns of pGDEs obtained from mapping are generally consistent with those from validation, and the differences of pGDEs in the Weihe River distributed largely. The pGDEs group of “Likely” and “Very Likely” accounted for 22.5% of the basin, and mainly distributed in Ziwuling Mountains, Qinling Mountains, Liupan Mountains, and Huanglong Mountains, and the “Neutral” group was scattered in the loess area of the northwestern basin, accounting for 13%. The finding of this study promotes the development of the GDEs identification and provides references for water and ecosystem regulation and protection of the Weihe River basin as well as other similar basins." @default.
• W4224015977 created "2022-04-19" @default.
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• W4224015977 date "2022-06-01" @default.
• W4224015977 modified "2023-10-14" @default.
• W4224015977 title "Identifying and mapping potential groundwater-dependent ecosystems for a semi-arid and semi-humid area in the Weihe River, China" @default.
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• W4224015977 doi "https://doi.org/10.1016/j.jhydrol.2022.127789" @default.
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