A5034672880- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Groundwater and Watershed Analysis
- Hydrological Forecasting Using AI
- Groundwater and Isotope Geochemistry
- Precipitation Measurement and Analysis
- Water Quality and Pollution Assessment
- Water resources management and optimization
- Climate variability and models
- Water Quality Monitoring Technologies
- Meteorological Phenomena and Simulations
- Geochemistry and Geologic Mapping
- Anomaly Detection Techniques and Applications
- Transboundary Water Resource Management
- Groundwater flow and contamination studies
- Water-Energy-Food Nexus Studies
- Wastewater Treatment and Nitrogen Removal
- Geophysics and Gravity Measurements
- Energy Load and Power Forecasting
- Automated Road and Building Extraction
- Tropical and Extratropical Cyclones Research
- Water Resources and Sustainability
- Hydrology and Sediment Transport Processes
- Cryospheric studies and observations
King Fahd University of Petroleum and Minerals
2016-2025
Floods, one of the most common natural hazards globally, are challenging to anticipate and estimate accurately. This study aims demonstrate predictive ability four ensemble algorithms for assessing flood risk. Bagging (BE), logistic model tree (LT), kernel support vector machine (k-SVM), k-nearest neighbour (KNN) used in this zoning Jeddah City, Saudi Arabia. The 141 locations have been identified research area based on interpretation aerial photos, historical data, Google Earth, field...
Water scarcity threatens agriculture and food security in arid regions like Saudi Arabia. The nation produces significant quantities of municipal wastewater, which, with adequate treatment, could serve as an alternative water source for irrigation, thereby reducing reliance on fossil non-renewable groundwater. This study assessed the appropriateness using treated wastewater (TWW) irrigation a dry coastal agricultural region Eastern Arabia its impact groundwater resources. Field...
Seawater intrusion (SWI) is the main threat to fresh groundwater (GW) resources in coastal regions worldwide. Early identification and delineation of such threats can help decision-makers plan for suitable management measures protect water communities. This study assesses seawater GW salinization shallow deep aquifers Al-Qatif area, eastern region Saudi Arabia. Field hydrogeological hydrochemical investigations coupled with laboratory-based isotopic analyses (18O 2H) were used this...
The city of Jeddah experienced a severe flood in 2020, resulting loss life and damage to property. In such scenarios, forecasting model can play crucial role predicting events minimizing their impact on communities. proposed study aims evaluate the performance machine learning algorithms floods non-flood regions, including Gradient Boosting, Extreme AdaBoosting Gradient, Random Forest, Light Boosting Machine, using dataset from City, Saudi Arabia. This identified fourteen continuous...
Global Digital Elevation Models (GDEMs) have been increasingly used to assess the risk of flooding worldwide. However, their effectiveness and performance flood models in areas with complex terrain, such as Jeddah, Saudi Arabia, not comprehensively studied. This study aims compare five distinct − 30-m SRTM, ASTER, 90-m MERIT, 10 m Sentinel-1 DEM, 12.5 ALOSPALSAR - estimating inundation extent depth Jeddah watershed, including three dams. Both hydrological hydraulic modeling approaches were...
This study aims to map flood susceptibility in the Qaa'Jahran watersheds located Dhamar, Yemen, using geoprocessing and computational techniques. Historical data SAR imagery were used monitor create a inventory map. The Artificial Neutral Network (ANN) was trained novel algorithm called GWO_LM, which is hybridization between Levenberg-Marquardt (LM) Grey Wolf Optimizer (GWO) meta-heuristic compared results with state of art machine learning algorithms. GWO_LM_ANN model exhibited excellent...
The excessive depletion of groundwater resources and significant climate change have exerted immense pressure on global reserves. Owing to the rising demand for drinking water, as well its use in agriculture industry, there is an increasing need evaluate capacity effectiveness underground water reservoirs (aquifers). Recently, GIS has gained attention exploration because ability provide rapid comprehensive information about further development. This study aims assess map potential a large...
The aim of this study is to build a flood simulation model for the city Hafr Al-Batin catchment area. consists hydrologic model, hydraulic and pre- post-processing tools. A geographic information system-based modelling interface was used pre-process terrain rainfall data generate input files models. Soil map data, land cover map, use digital elevation delineate physical watershed's characteristics. runoff estimation based on widely known Conservation Service curve number approach....
This study addresses the challenges of flash flood susceptibility mapping in Yemen's Qaa'Jahran Basin, characterized by complex terrain and limited hydro-meteorological data. To enhance predictive accuracy, we integrate metaheuristic feature selection with ensemble learning models. Initially, fifteen variables were retrieved using Geographic Information System (GIS) based remote sensing, setting stage for a novel algorithm. Then, Memo Search Algorithm (MSA), approach is proposed to...
Abstract Total dissolved gas (TDG) concentration plays an important role in the control of aquatic life. Elevated TDG can cause gas-bubble trauma fish (GBT). Therefore, controlling fluctuation has become great importance for different disciplines surface water environmental engineering.. Nowadays, direct estimation is expensive and time-consuming. Hence, this work proposes a new modelling framework predicting based on integration machine learning (ML) models multiresolution signal...
Population growth and land use modification in urban areas require the of accurate tools for rainfall-runoff modeling, especially where topography is complex. The recent improvement quality resolution remotely sensed precipitation satisfies a major need such tools. A physically-based, fully distributed hydrologic model conceptual semi-distributed model, forced by satellite rainfall estimates, were used to simulate flooding events very arid, rapidly urbanizing watershed Saudi Arabia. Observed...
Developing Intensity-Duration-Frequency (IDF) curves is critical for effective water resource management, infrastructure design, and flood risk mitigation, particularly in arid semi-arid regions where rainfall events are infrequent but intense. This study focuses on the development of IDF Makkah, Saudi Arabia, an region characterized by limited ground station coverage. To address data scarcity, a hybrid approach combining ground-based records remote sensing from Integrated Multi-satellite...
Land use and land cover (LULC) changes are known to significantly affect hydrological processes, directly influencing the frequency, magnitude, spatial distribution of flood events. This study focuses on understanding impact LULC dynamics in Hafr Al-Batin, Saudi Arabia, a region highly susceptible flooding due combination natural anthropogenic factors. Remote sensing data, acquired from satellite imagery for multiple time periods, will be utilized map analyze using supervised classification...
ABSTRACT Climate change has altered rainfall patterns, leading to urban flooding in Peshawar City. This study develops intensity–duration–frequency (IDF) curves assess intensities for various return periods and durations. The methodology involves downscaling bias correction of general circulation model (GCM) data, followed by feature selection using XGBoost Extra Tree rank nine GCMs. top three models were used as input four machine learning (ML) algorithms – random forest, regression tree,...