Groundwater storage downscaling and regional water resource analysis based on an attention-enhanced RF model
Source abstract
Abstract
This study develops an “Attention Mechanism + Random Forest” model integrating GRACE/GRACE-FO, GLDAS, and ERA5-Land data to downscale GWSA resolution from 0.25° to 0.1° in Jiangsu Province. The downscaled data effectively captures local groundwater variations, showing strong agreement with original observations (R² = 0.95). Results reveal an overall GWSA increase of 4.824 mm/yr with distinct spatial heterogeneity: southern regions (e.g., Suzhou) show significant increases (up to 25.754 mm/yr) while northern areas (e.g., Lianyungang) experience declines (as low as −7.063 mm/yr). The GWSA centroid has shifted toward Changzhou-Taizhou, with seasonal variations primarily driven by precipitation (weight 0.32) and evapotranspiration. Analysis of heritage sites indicates pronounced fluctuations in lake-wetland areas compared to stable forest regions. This research provides crucial support for refined groundwater monitoring and sustainable management.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Soil Moisture and Remote Sensing · Groundwater flow and contamination studies · Hydrology and Watershed Management Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (47)
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