An ensemble CNN-LSTM and GRU adaptive weighting model based improved sparrow search algorithm for predicting runoff using historical meteorological and …
Z Yao, Z Wang, D Wang, J Wu, L Chen - Journal of Hydrology, 2023 - Elsevier
Accurate prediction of river runoff is of great significance for water resources management,
flood prevention and mitigation. The causes of runoff are complex and the mechanisms …
flood prevention and mitigation. The causes of runoff are complex and the mechanisms …
Forecasting evapotranspiration in different climates using ensembles of recurrent neural networks
F Granata, F Di Nunno - Agricultural Water Management, 2021 - Elsevier
Accurate ahead evapotranspiration forecasting is crucial for irrigation planning, for wetlands,
agricultural and forest habitats preservation, and for water resource management. Deep …
agricultural and forest habitats preservation, and for water resource management. Deep …
Short-term forecasts of streamflow in the UK based on a novel hybrid artificial intelligence algorithm
In recent years, the growing impact of climate change on surface water bodies has made the
analysis and forecasting of streamflow rates essential for proper planning and management …
analysis and forecasting of streamflow rates essential for proper planning and management …
Hydraulic efficiency of green-blue flood control scenarios for vegetated rivers: 1D and 2D unsteady simulations
Flood hazard mitigation in urban areas crossed by vegetated flows can be achieved through
two distinct approaches, based on structural and eco-friendly solutions, referred to as grey …
two distinct approaches, based on structural and eco-friendly solutions, referred to as grey …
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 …
[HTML][HTML] Daily streamflow forecasting based on the hybrid particle swarm optimization and long short-term memory model in the Orontes Basin
HC Kilinc - Water, 2022 - mdpi.com
Water, a renewable but limited resource, is vital for all living creatures. Increasing demand
makes the sustainability of water resources crucial. River flow management, one of the key …
makes the sustainability of water resources crucial. River flow management, one of the key …
[HTML][HTML] Towards improved drought prediction in the Mediterranean region–modeling approaches and future directions
B Zellou, N El Moçayd… - Natural Hazards and Earth …, 2023 - nhess.copernicus.org
There is a scientific consensus that the Mediterranean region (MedR) is warming and as the
temperature continues to rise, droughts and heat waves are becoming more frequent …
temperature continues to rise, droughts and heat waves are becoming more frequent …
[HTML][HTML] Vulnerability of the rip current phenomenon in marine environments using machine learning models
Hidden and perilous rip currents are one of the primary factors leading to drownings of
beach swimmers. By identifying the coastal areas with the highest likelihood of generating …
beach swimmers. By identifying the coastal areas with the highest likelihood of generating …
Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks
DN Fabio, SI Abba, BQ Pham… - Arabian Journal of …, 2022 - Springer
Groundwater resources (GWR) are vital to agricultural crop production, everyday life, and
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
economic development. As a result, accurate groundwater level (GWL) prediction would aid …
Precipitation forecasting in Northern Bangladesh using a hybrid machine learning model
Precipitation forecasting is essential for the assessment of several hydrological processes.
This study shows that based on a machine learning approach, reliable models for …
This study shows that based on a machine learning approach, reliable models for …