Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 371, P. 123094 - 123094

Published: Nov. 2, 2024

Language: Английский

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Mapping Groundwater Potential Zones in the Widyan Basin, Al Qassim, KSA: Analytical Hierarchy Process-Based Analysis Using Sentinel-2, ASTER-DEM, and Conventional Data

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 766 - 766

Published: Feb. 22, 2025

Groundwater availability in semi-arid regions like the Widyan Basin, Kingdom of Saudi Arabia (KSA), is a critical challenge due to climatic, topographic, and hydrological variations. The accurate identification groundwater zones essential for sustainable development. Therefore, this study combines remote-sensing datasets (Sentinel-2 ASTER-DEM) with conventional data using Geographic Information System (GIS) analytical hierarchy process (AHP) techniques delineate potential (GWPZs). basin’s geology includes Pre-Cambrian rock units Arabian Shield southwest Cambrian–Ordovician northeast, Saq Formation serving as main aquifer. Six soil types were identified: Haplic Calcic Yermosols, Calcaric Regosols, Cambic Arenosols, Orthic Solonchaks, Lithosols. topography varies from steep areas northwest nearly flat terrain northeast. Hydrologically, basin divided into 28 sub-basins four stream orders. Using GIS-based AHP weighted overlay methods, GWPZs mapped, achieving model consistency ratio 0.0956. categorized excellent (15.21%), good (40.85%), fair (43.94%), poor (0%). GWPZ was validated by analyzing 48 water wells distributed area. These range fresh primary saline water, depths varying between 13.98 130 m. Nine wells—with an average total dissolved solids (TDS) value 597.2 mg/L—fall within zone, twenty-one are fifteen classified remaining fall TDS values reaching up 2177 mg/L. results indicate that central zone area suitable drilling new wells.

Language: Английский

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Remote sensing assessment of dam impact on arid basins in Southern Saudi Arabia: A machine learning and space-for-time approach

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102221 - 102221

Published: Feb. 3, 2025

Language: Английский

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Flood risk assessment in the Swat river catchment through GIS-based multi-criteria decision analysis

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: April 9, 2025

Extreme climatic events, such as floods, are becoming increasingly frequent and severe worldwide, including in Pakistan. The Swat River Catchment (SRC), located the eastern Hindukush region of Pakistan, is highly susceptible to flooding due its unique geographical conditions. However, despite region’s susceptibility, comprehensive flood risk assessments that integrate hazard, vulnerability, exposure components remain limited. To address this gap, study assesses SRC using 22 indicators distributed across three core dimensions risk: exposure. Flood hazard was modeled 11 indicators, broadly categorized into environmental, hydrological, aspects, while vulnerability evaluated through socio-economic factors, proximity, land use characteristics. Exposure analyzed based on population metrics critical infrastructure. All data were converted thematic layers GIS, systematically weighted Analytical Hierarchy Process (AHP) combined produce maps respectively. These then integrated a equation generate final map. results reveal 31% area high zone, 27% moderate zones, 23% low risk, 19% safe areas. validated Area Under Curve (AUC) technique, yielding value 0.92, which indicates reliability. By presenting first assessment for SRC, provides valuable insights flood-prone areas distribution. highlight urgent need enhanced management, especially urban developed methodology serves tool disaster management authorities planners, helping them make risk-informed decisions, allocate resources efficiently, implement targeted mitigation strategies.

Language: Английский

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Delineation of Groundwater Potential Using the Bivariate Statistical Models and Hybridized Multi-Criteria Decision-Making Models

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3273 - 3273

Published: Nov. 14, 2024

Identifying groundwater potential zones in a basin and developing sustainable management plan is becoming more important, especially where surface water scarce. The main aim of the study to prepare maps (GWPMs) considering bivariate statistical models frequency ratio (FR), weight evidence (WoE), multi-criteria decision-making (MCDM) model Technique for Order Preference by Similarity an Ideal Solution (TOPSIS) hybridized with FR WoE. Two distance measures, Euclidean Manhattan, were used TOPSIS evaluate their effect on GWPMs. research focused Burdur Lake catchment located southwest Türkiye. In total, 74 wells high yields chosen randomly analysis, 52 (70%) training, 22 (30%) testing processes. Sixteen conditioning factors selected. area under receiver operating characteristic (AUROC) true skill statistics (TSS) utilized examine goodness-of-fit prediction accuracy approaches. TOPSIS-WoE-Manhattan WoE gave best AUROC values 0.915 0.944 training processes, respectively. TSS 0.827 0.864 obtained TOPSIS-FR-Euclidean

Language: Английский

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