Pre-and post-dam river water temperature alteration prediction using advanced machine learning models
Dams significantly impact river hydrology by changing the timing, size, and frequency of low
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
Ensemble neural networks for the development of storm surge flood modeling: A comprehensive review
This review paper focuses on the use of ensemble neural networks (ENN) in the
development of storm surge flood models. Storm surges are a major concern in coastal …
development of storm surge flood models. Storm surges are a major concern in coastal …
Enhancing flood risk assessment through integration of ensemble learning approaches and physical-based hydrological modeling
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 …
(RF), LightGBM, and CatBoost for flooding susceptibility maps (FSMs) in the Vietnamese Vu …
Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin
Despite its large size, the Congo Basin (CB), which spans ten countries, has remained an
area of particular interest for scientific discovery due to gaps in Earth science, environmental …
area of particular interest for scientific discovery due to gaps in Earth science, environmental …
A robust deep-learning model for landslide susceptibility mapping: A case study of Kurdistan Province, Iran
We mapped landslide susceptibility in Kamyaran city of Kurdistan Province, Iran, using a
robust deep-learning (DP) model based on a combination of extreme learning machine …
robust deep-learning (DP) model based on a combination of extreme learning machine …
Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test
Abstract Knowledge of the stage-discharge rating curve is useful in designing and planning
flood warnings; thus, developing a reliable stage-discharge rating curve is a fundamental …
flood warnings; thus, developing a reliable stage-discharge rating curve is a fundamental …
River flow rate prediction in the Des Moines watershed (Iowa, USA): A machine learning approach
Prediction of flow rate in rivers is essential for the planning and management of water
resources. This study shows that, based on a Machine Learning approach, accurate models …
resources. This study shows that, based on a Machine Learning approach, accurate models …
Hybrid machine learning approach for landslide prediction, Uttarakhand, India
P Kainthura, N Sharma - Scientific reports, 2022 - nature.com
Natural disasters always have a damaging effect on our way of life. Landslides cause
serious damage to both human and natural resources around the world. In this paper, the …
serious damage to both human and natural resources around the world. In this paper, the …
GIS-based ensemble computational models for flood susceptibility prediction in the Quang Binh Province, Vietnam
Recently, floods are occurring more frequently every year around the world due to increased
anthropogenic activities and climate change. There is a need to develop accurate models for …
anthropogenic activities and climate change. There is a need to develop accurate models for …
Evaluation of neural network models for landslide susceptibility assessment
Identifying and assessing the disaster risk of landslide-prone regions is very critical for
disaster prevention and mitigation. Owning to their special advantages, neural network …
disaster prevention and mitigation. Owning to their special advantages, neural network …