IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling

B Mohammadi, MJS Safari, S Vazifehkhah - Scientific Reports, 2022 - nature.com
As a complex hydrological problem, rainfall-runoff (RR) modeling is of importance in runoff
studies, water supply, irrigation issues, and environmental management. Among the variety …

[HTML][HTML] A conceptual metaheuristic-based framework for improving runoff time series simulation in glacierized catchments

B Mohammadi, S Vazifehkhah, Z Duan - Engineering Applications of …, 2024 - Elsevier
Glacio-hydrological modeling is a key task for assessing the influence of snow and glaciers
on water resources, essential for water resources management. The present study aims to …

Rainfall-runoff modeling using LSTM-based multi-state-vector sequence-to-sequence model

H Yin, X Zhang, F Wang, Y Zhang, R Xia, J Jin - Journal of Hydrology, 2021 - Elsevier
Rainfall-runoff modeling is a challenging and important nonlinear time series problem in
hydrological sciences. Recently, among the data-driven rainfall-runoff models, those ones …

Rainfall-runoff modeling using long short-term memory based step-sequence framework

H Yin, F Wang, X Zhang, Y Zhang, J Chen, R Xia… - Journal of Hydrology, 2022 - Elsevier
Rainfall-runoff modeling, a nonlinear time series process, is challenging and important in
hydrological sciences. Among the data-driven approaches, those ones based on the long …

Evaluation of rainfall–runoff model performance under non-stationary hydroclimatic conditions

P Deb, AS Kiem - Hydrological Sciences Journal, 2020 - Taylor & Francis
Understanding of rainfall–runoff model performance under non-stationary hydroclimatic
conditions is limited. This study compared lumped (IHACRES), semi-distributed (HEC-HMS) …

Rainfall-Runoff modelling using SWAT and eight artificial intelligence models in the Murredu Watershed, India

PR Shekar, A Mathew, VP Gopi - Environmental Monitoring and …, 2023 - Springer
The growing concerns surrounding water supply, driven by factors such as population
growth and industrialization, have highlighted the need for accurate estimation of streamflow …

Improving the performance of rainfall-runoff models using the gene expression programming approach

H Esmaeili-Gisavandani, M Lotfirad… - Journal of Water and …, 2021 - iwaponline.com
In this study, five hydrological models, including the soil and water assessment tool (SWAT),
identification of unit hydrograph and component flows from rainfall, evapotranspiration, and …

Runoff predictions in ungauged basins using sequence-to-sequence models

H Yin, Z Guo, X Zhang, J Chen, Y Zhang - Journal of Hydrology, 2021 - Elsevier
How to improve the performance of runoff predictions in ungauged basins (PUB) is
challenging. Recently, the long short-term memory (LSTM) based models have excellent …

[HTML][HTML] Influence of climate change on water partitioning in agricultural watersheds: Examples from Sweden

Y Grusson, I Wesström, E Svedberg, A Joel - Agricultural Water …, 2021 - Elsevier
Future climate change is predicted to increase precipitation volume in Sweden, and also to
modify precipitation patterns and produce more intense rainfall events. This study examined …

Modeling long-term rainfall-runoff time series through wavelet-weighted regularization extreme learning machine

A Alizadeh, A Rajabi, S Shabanlou, B Yaghoubi… - Earth Science …, 2021 - Springer
As one of the most critical points of Iran, Lake Urmia has always been subjected to
ecosystem changes due to severe water level drops. Many basins serve to feed the lake, eg …