Machine learning maps Mumbai’s flood zones with terrain and rainfall data
A machine learning framework combining satellite radar, optical, elevation and rainfall data mapped flood inundation across Mumbai, with hydrologic predictors ...
A machine learning framework combining satellite radar, optical, elevation and rainfall data mapped flood inundation across Mumbai, with hydrologic predictors ...
A GIS and Google Earth Engine framework classified Zimbabwe's groundwater potential nationwide and tested it against nearly 10,000 borehole records.
A retrospective ecological study of Ugandan cholera hotspot districts from 2012 to 2022 found that each 100 mm increase in ...
A 24-year validation against 95 Ethiopian rain gauges shows CHIRPS_v3, CHIRPS_v2 and IMERG are the most reliable satellite rainfall products, ...
A comprehensive evaluation of four satellite rainfall products against 34 ground stations in Zambia reveals that RFEv2 excels at daily ...
A 45-year analysis of northern Togo finds stable rainfall but significant warming that is quietly intensifying moisture deficits across one ...
A benchmark of deep learning and tree-based models shows that one-month drought early warning is achievable in Morocco's Atlas mountains, ...
A new satellite-based study combining MODIS, SMAP and CHIRPS data shows that drought affected more than 65 percent of Guba ...
A five-step machine learning framework projects sharp, basin-specific declines and surprising gains in West African hydropower under future climate scenarios.
A new study tested five satellite and reanalysis rainfall products against 23 Egyptian rain gauges and used deep neural networks ...
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© 2025 Scienmag - Science Magazine