Journal of Geospatial Information Technology, Journal Year: 2024, Volume and Issue: 12(2), P. 103 - 124
Published: Sept. 1, 2024
Language: Английский
Journal of Geospatial Information Technology, Journal Year: 2024, Volume and Issue: 12(2), P. 103 - 124
Published: Sept. 1, 2024
Language: Английский
Published: Jan. 1, 2024
Language: Английский
Citations
0Arid Land Research and Management, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 28
Published: Aug. 22, 2024
The Tarim Basin is a typical hyper-arid area, 57% of which occupied by the Taklimakan desert. Because evapotranspiration (ET) key factor in determining water demand, accurate estimation ET critical for efficient management arid regions. In this study, spatiotemporal dynamics across from 2001 to 2020 were simulated based on revised Surface Energy Balance System (SEBS) algorithm, and impacts driving factors trends desert quantified. findings indicated that mean annual entire basin was slightly greater than (302 mm vs. 295 mm), although decreasing rate slower (−0.27 mm/year −0.50 mm/year). Strong increasing found croplands, whereas trends, accounted 56.5% basin, primarily concentrated central southern parts Correlation analysis revealed wind speed (WS) soil moisture (SM) dominant factors, with negative contribution more 35% positive 45%, respectively, trends. Compared ERA5-Land complementary relationship using extended triple collocation method, SEBS provided detailed information lower random error standard deviation. Our contribute understanding how impact regions provide reference management.
Language: Английский
Citations
0Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 175 - 202
Published: Dec. 6, 2024
Groundwater is a natural renewable resource vital for any life on Earth. management of emerging concern the conservation and protection this resource. With advent innovative technologies, managing such resources become easier to some extent. This chapter illustrates advanced their contribution, challenges future prospects sustainable groundwater. AI methods have widespread in decision-making recent years are accepted globally due cost-effectiveness, time-saving, efficient nature. AI-driven models provide precise analytical modelling, real-time monitoring, data integration groundwater management. Innovative can detect vulnerable regions that prone pollution depletion level draw attention scientists, local people policymakers prompt intervention.
Language: Английский
Citations
0Journal of Geospatial Information Technology, Journal Year: 2024, Volume and Issue: 12(2), P. 103 - 124
Published: Sept. 1, 2024
Language: Английский
Citations
0