Artificial Intelligence in Hydrology: Advancements in Soil, Water Resource Management, and Sustainable Development

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2250 - 2250

Published: March 5, 2025

Hydrology relates to many complex challenges due climate variability, limited resources, and especially, increased demands on sustainable management of water soil. Conventional approaches often cannot respond the integrated complexity continuous change inherent in system; hence, researchers have explored advanced data-driven solutions. This review paper revisits how artificial intelligence (AI) is dramatically changing most important facets hydrological research, including soil land surface modeling, streamflow, groundwater forecasting, quality assessment, remote sensing applications resources. In AI techniques could further enhance accuracy texture analysis, moisture estimation, erosion prediction for better management. Advanced models also be used as a tool forecast streamflow levels, therefore providing valuable lead times flood preparedness resource planning transboundary basins. quality, AI-driven methods improve contamination risk enable detection anomalies, track pollutants assist treatment processes regulatory practices. combined with open new perspectives monitoring resources at spatial scale, from forecasting storage variations. paper’s synthesis emphasizes AI’s immense potential hydrology; it covers latest advances future prospects field ensure

Language: Английский

DiffusionAAE: Enhancing hyperspectral image classification with conditional diffusion model and Adversarial Autoencoder

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103118 - 103118

Published: April 1, 2025

Language: Английский