Forecasting daily extreme events is crucial, particularly amidst the escalating severity of
tropical storms and hurricanes in the East and Gulf coasts of the United States. The intensity …

Reservoirs and dams are critical infrastructures that play essential roles in flood control,
hydropower generation, water supply, and navigation. Accurate and reliable dam outflow …

Accurate daily streamflow forecasting is crucial for effective flood control and water
management. However, the non-stationary nonlinearity in actual streamflow poses a …

Wildfires increasingly threaten ecosystems and infrastructure, making accurate burn severity
map** (BSM) essential for effective disaster response and environmental management …

Abstract Machine learning (ML) is emerging as a promising tool for modeling hydro-
ecological processes due to the increasing availability of large environmental data …

This study introduces a framework that strategically applies a Long Short-Term Memory
(LSTM)-based approach for monthly runoff prediction in South Africa and Central Asia. The …

Accurate wildfire severity map** (WSM) is crucial in environmental damage assessment
and recovery strategies. Machine learning (ML) and remote sensing technologies are …

This paper presents deep learning using LSTM, machine learning employing RF and GB
algorithms, and the rating curve (RC) that can be used for estimating daily streamflow at the …

Reliable streamflow forecasting is crucial for several tasks related to water-resource
management, including planning reservoir operations, power generation via Hydroelectric …

This study evaluates the efficacy of five machine learning algorithms Support Vector
Regression (SVR), Decision Tree (DT), Random Forest (RF), Light Gradient Boosting …