Symbolic Regression Captures Combined Flood Factors in Machine Learning Models
A new study in Natural Hazards uses symbolic regression to derive mathematical models that capture the combined impact of flood ...
A new study in Natural Hazards uses symbolic regression to derive mathematical models that capture the combined impact of flood ...
A meteorological and geospatial study of Karnataka's dry agro-climatic zones reveals widespread drought patterns across four decades of gridded climate ...
A Northern Hemisphere evaluation reveals that satellite products lag behind observed daily precipitation peaks while atmospheric reanalyses trigger rainfall hours ...
A preprint details the European Groundwater Monitoring database, assembling decades of harmonized groundwater records across 15,760 monitoring sites in 24 ...
A study by IIT Gandhinagar researchers found that the Ranjit Sagar reservoir reduced surface water availability in the Ravi River ...
Dual stable isotope analysis reveals that transpiration drives most annual evapotranspiration in Syngonium podophyllum, but wet monsoon conditions temporarily elevate ...
A new stochastic simulation study reveals that bridge scour is highly variable and persistent, with only a weak correspondence to ...
A study published in AI in Civil Engineering found that a hybrid machine learning model combining regression trees with random ...
A new editorial in Frontiers in Remote Sensing highlights how satellite data, including from the SWOT and ICESat-2 missions, is ...
A new study demonstrates that simple Box-Cox transformations, particularly the logarithmic transformation, significantly improve the reliability of probabilistic hourly streamflow ...
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© 2026 Scienmag - Science Magazine