Trends of meteorological and hydrological droughts and associated parameters using innovative approaches

AA Arra, S Alashan, E Şişman - Journal of Hydrology, 2024 - Elsevier
Climate change and drought have profound effects on hydro-meteorological series. In
addition to spatial, these effects could be on annual, seasonal, monthly, or daily temporal …

Improvement of drought forecasting by means of various machine learning algorithms and wavelet transformation

T Tuğrul, MA Hinis - Acta Geophysica, 2024 - Springer
Drought, which is defined as a decrease in average rainfall amounts, is one of the most
insidious natural disasters. When it starts, people may not be aware of it, which is why …

Study on multiscale-multivariate prediction and risk assessment of urban flood

Y Wang, H Xiao, D Wang, J Zhang - Environmental Modelling & Software, 2024 - Elsevier
Few studies have explored the impact of drivers on urban flood at multi-time scales, and few
studies have assessed the urban flood risk based on accurate description and quantification …

Spatiotemporal Analysis for Rainfall Prediction Using Extreme Learning Machine Cluster.

R Fredyan, MRN Majiid… - International Journal on …, 2023 - search.ebscohost.com
Rainfall prediction is an essential study as a guideline for water resources management to
manage disasters. Still, earlier research cares much about temporal information, only …

[HTML][HTML] A deep learning perspective on meteorological droughts prediction in the Mun River Basin, Thailand

M Waqas, PT Hliang, P Dechpichai, A Wangwongchai - AIP Advances, 2024 - pubs.aip.org
Accurate drought prediction is crucial for enhancing resilience and managing water
resources. Developing robust forecasting models and understanding the variables …

Multi-Step-Ahead Rainfall-Runoff Modeling: Decision Tree-Based Clustering for Hybrid Wavelet Neural-Networks Modeling

A Molajou, V Nourani, AD Tajbakhsh… - Water Resources …, 2024 - Springer
This paper introduces a novel hybrid approach for predicting the rainfall-runoff (rr)
phenomenon across different data division scenarios (50%-50%, 60%-40%, and 75%-25%) …

Ensemble learning paradigms for flow rate prediction boosting

KL Kouadio, J Liu, SK Kouamelan, R Liu - Water Resources Management, 2023 - Springer
In response to the issue of water scarcity in recent years, international organizations, in
collaboration with many governments, have initiated several drinking water supply projects …

Meteorological Drought Prediction Based on Evaluating the Efficacy of Several Prediction Models

AR Zarei, MR Mahmoudi, A Pourbagheri - Water Resources Management, 2024 - Springer
The prediction of drought is critically important for early warning and mitigation of its impacts.
Selecting the most appropriate prediction model provides opportunities for reducing the …

Comparison of LSTM and SVM methods through wavelet decomposition in drought forecasting

T Tuğrul, MA Hınıs, S Oruç - Earth Science Informatics, 2025 - Springer
Many researchers are working to prevent, monitor and identify drought, which is one of the
most insidious and dangerous natural disasters that negatively affects life. For this purpose …

Apa Barajı havzasındaki hidrolojik parametrelerin makine öğrenmesi ile tahmini

T Tuğrul - 2024 - acikerisim.aksaray.edu.tr
Son yıllarda, özellikle de sanayi devriminden sonra insanoğlunun suya olan ihtiyacı
artmıştır. Canlılar için yaşamsal önemi tartışılmaz olan bu suyun, gelecekteki ve mevcut …