Trends of meteorological and hydrological droughts and associated parameters using innovative approaches
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 …
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
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 …
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 …
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 …
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 …
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
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%) …
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 …
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 …
Selecting the most appropriate prediction model provides opportunities for reducing the …
Comparison of LSTM and SVM methods through wavelet decomposition in drought forecasting
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 …
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 …
artmıştır. Canlılar için yaşamsal önemi tartışılmaz olan bu suyun, gelecekteki ve mevcut …