Forecasting and early warning systems are important investments to protect lives, properties,
and livelihood. While early warning systems are frequently used to predict the magnitude …

Advances in impact modeling and numerical weather forecasting have allowed accurate
drought monitoring and skilful forecasts that can drive decisions at the regional scale. State …

The recent dry and warm years in Europe are often assessed as extreme in terms of socio-
economic and environmental losses. However, the impact of a drought is a function of its …

The machine learning algorithm 'random forest'has been applied in many areas of water
resources research including discharge simulation. Due to low setup and operation cost …

This study presents two machine learning models, namely, the light gradient boosting
machine (LightGBM) and categorical boosting (CatBoost), for the first time for predicting …

Drought is a common and costly natural disaster with broad social, economic, and
environmental impacts. Machine learning (ML) has been widely applied in scientific …

Drought has wide ranging impacts on all sectors. Despite much effort to identify the best
drought indicator to represents the occurrence of drought impacts in a particular sector, there …

Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …

This study aims to examine three machine learning (ML) techniques, namely random forest
(RF), LightGBM, and CatBoost for flooding susceptibility maps (FSMs) in the Vietnamese Vu …

Climate change is a major challenge for Indonesia due to its impact on food, water, energy
sustainability, and environmental health. Almost all Indonesian regions are exposed to …