[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
Develo** accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …
essential for enhancing the planning and management of water resources. Over the past two …
Short‐Term Daily Univariate Streamflow Forecasting Using Deep Learning Models
EB Wegayehu, FB Muluneh - Advances in Meteorology, 2022 - Wiley Online Library
Hydrological forecasting is one of the key research areas in hydrology. Innovative
forecasting tools will reform water resources management systems, flood early warning …
forecasting tools will reform water resources management systems, flood early warning …
Streamflow forecasting by modeling the rainfall–streamflow relationship using artificial neural networks
Streamflow forecasting is a complex and fundamental hydrological phenomenon. The
accurate prediction of the streamflow helps in the planning, design, and management of …
accurate prediction of the streamflow helps in the planning, design, and management of …
Inflow forecasting using regularized extreme learning machine: Haditha reservoir chosen as case study
For effective water resource management, water budgeting, and optimal release discharge
from a reservoir, the accurate prediction of daily inflow is critical. An attempt has been made …
from a reservoir, the accurate prediction of daily inflow is critical. An attempt has been made …
Assessing machine learning models for streamflow estimation: a case study in Oued Sebaou watershed (Northern Algeria)
This paper proposes runoff models based on machine learning to estimate daily streamflows
in Oued Sebaou watershed, a Mediterranean coastal basin located in northern Algeria …
in Oued Sebaou watershed, a Mediterranean coastal basin located in northern Algeria …
Short–long-term streamflow forecasting using a coupled wavelet transform–artificial neural network (WT–ANN) model at the Gilgit River Basin, Pakistan
Streamflow forecasting is highly crucial in the domain of water resources. For this study, we
coupled the Wavelet Transform (WT) and Artificial Neural Network (ANN) to forecast Gilgit …
coupled the Wavelet Transform (WT) and Artificial Neural Network (ANN) to forecast Gilgit …
Inflow forecast of iranamadu reservoir, Sri Lanka, under projected climate scenarios using artificial neural networks
Prediction of water resources for future years takes much attention from the water resources
planners and relevant authorities. However, traditional computational models like hydrologic …
planners and relevant authorities. However, traditional computational models like hydrologic …
Streamflow estimation in a mediterranean watershed using neural network models: A detailed description of the implementation and optimization
This study compares the performance of three different neural network models to estimate
daily streamflow in a watershed under a natural flow regime. Based on existing and public …
daily streamflow in a watershed under a natural flow regime. Based on existing and public …
Review of recent trends in the hybridisation of preprocessing-based and parameter optimisation-based hybrid models to forecast univariate streamflow
Forecasting river flow is crucial for optimal planning, management, and sustainability using
freshwater resources. Many machine learning (ML) approaches have been enhanced to …
freshwater resources. Many machine learning (ML) approaches have been enhanced to …
Kernel extreme learning machine: an efficient model for estimating daily dew point temperature using weather data
Accurate estimation of dew point temperature (Tdew) has a crucial role in sustainable water
resource management. This study investigates kernel extreme learning machine (KELM) …
resource management. This study investigates kernel extreme learning machine (KELM) …