Smarter water quality monitoring in reservoirs using interpretable deep learning models and feature importance analysis

S Majnooni, M Fooladi, MR Nikoo, G Al-Rawas… - Journal of Water …, 2024‏ - Elsevier
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 …

Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques

A Khoshkonesh, R Nazari, MR Nikoo… - Science of the Total …, 2024‏ - Elsevier
Urban flood risks have intensified due to climate change and dense infrastructural
development, necessitating innovative assessment approaches. This study aimed to …

[HTML][HTML] A critical review of hurricane risk assessment models and predictive frameworks

SM Arachchige, B Pradhan, HJ Park - Geoscience Frontiers, 2025‏ - Elsevier
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 …

Improving long-term flood forecasting accuracy using ensemble deep learning models and an attention mechanism

M Kordani, MR Nikoo, M Fooladi… - Journal of Hydrologic …, 2024‏ - ascelibrary.org
Floods, as major natural disasters, cause massive property destruction and death.
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 …

Integrated ensemble learning approach for multi-depth water quality estimation in reservoir environments

MS Zare, MR Nikoo, G Al-Rawas, R Nazari… - Journal of Water …, 2024‏ - Elsevier
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 …

Hydrodynamics-based assessment of flood losses in an urban district under changing environments

X Wang, J **a, B Dong, Q Li, X Zhang - Natural Hazards, 2024‏ - Springer
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 …

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 …

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 …