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Smarter water quality monitoring in reservoirs using interpretable deep learning models and feature importance analysis
This study utilized datasets from an ongoing monitoring project conducted in Wadi Dayqah
Dam, the largest reservoir in Oman. The dataset comprises information on ten water quality …
Dam, the largest reservoir in Oman. The dataset comprises information on ten water quality …
Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques
Urban flood risks have intensified due to climate change and dense infrastructural
development, necessitating innovative assessment approaches. This study aimed to …
development, necessitating innovative assessment approaches. This study aimed to …
[HTML][HTML] A critical review of hurricane risk assessment models and predictive frameworks
Hurricanes are one of the most destructive natural disasters that can cause catastrophic
losses to both communities and infrastructure. Assessment of hurricane risk furnishes a …
losses to both communities and infrastructure. Assessment of hurricane risk furnishes a …
Improving long-term flood forecasting accuracy using ensemble deep learning models and an attention mechanism
Floods, as major natural disasters, cause massive property destruction and death.
Understanding the occurrence time of this event by advance notice helps consider …
Understanding the occurrence time of this event by advance notice helps consider …
City scale urban flooding risk assessment using multi-source data and machine learning approach
Q Wei, H Zhang, Y Chen, Y ** Rapid-Onset Coastal Flooding: A Systematic Literature Review
A Re, L Minola, A Pezzoli - Water, 2025 - mdpi.com
Increases in the magnitude and frequency of extreme flood events are among the most
impactful consequences of climate change. Coastal areas can potentially be affected by …
impactful consequences of climate change. Coastal areas can potentially be affected by …
Integrated ensemble learning approach for multi-depth water quality estimation in reservoir environments
Water quality is paramount for the well-being of ecosystems and organisms, so assessing
water quality variables (WQVs) is imperative. Despite existing research on predicting WQVs …
water quality variables (WQVs) is imperative. Despite existing research on predicting WQVs …
Hydrodynamics-based assessment of flood losses in an urban district under changing environments
In order to accurately assess the urban flood losses under changing environments, a flood
losses assessment framework has been proposed based on a bidirectional coupled 1D/2D …
losses assessment framework has been proposed based on a bidirectional coupled 1D/2D …
Assessment of urban flood susceptibility based on a novel integrated machine learning method
H Yang, T Zou, B Liu - Environmental Monitoring and Assessment, 2025 - Springer
Flood susceptibility assessment is the premise and foundation to prevent flood disaster
events effectively. To accurately assess urban flood susceptibility (UFS), this study first …
events effectively. To accurately assess urban flood susceptibility (UFS), this study first …
Nonlinear influences of climatic, vegetative, geographic and soil factors on soil water use efficiency of global karst landscapes: Insights from explainable machine …
C Li, S Zhang, Y Ding, S Ma, H Gong - Science of The Total Environment, 2025 - Elsevier
Abstract Soil Water Use Efficiency (SWUE) represents a vital metric for assessing the
relationship between carbon acquisition and soil moisture (SM) depletion in terrestrial …
relationship between carbon acquisition and soil moisture (SM) depletion in terrestrial …