Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Environmental Sciences Europe, Journal Year: 2024, Volume and Issue: 36(1)

Published: Oct. 15, 2024

Abstract Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations method limitations. In this study, zonation in Nile districts of Damietta branch, Egypt, delineated assessed by integrating remote sensing with a geographic information system, an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness modified water positioning stream power Fournier drainage density, distance river, sediment transport lithology) used for producing susceptibility (FSZ) six parameters (total population, hospital, land use/land cover, population road road) utilized vulnerability zonation. Multicollinearity analysis applied identify highly correlated independent variables. Sensitivity studies have been assess effectiveness AHP model. The results indicate that high very classes cover 21.40% 8.26% area, respectively. 14.07%, 27.01%, 29.26% research respectively, zones classified as low, moderate found. Finally, FSZ validated using receiver operating characteristics curve area under (AUC) analysis. A higher AUC value (0.741) validation findings demonstrated validity approach. study will help planners, hydrologists, managers resources manage areas susceptible flooding reduce potential harm.

Language: Английский

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Integrated GIS and analytic hierarchy process for flood risk assessment in the Dades Wadi watershed (Central High Atlas, Morocco)

Results in Earth Sciences, Journal Year: 2024, Volume and Issue: 2, P. 100019 - 100019

Published: March 18, 2024

Flood risk assessment is crucial for delineating flood hazard zones and formulating effective mitigation strategies. Employing a multi-criteria decision support system, this study focused on assessing Risk Index (FHI) at the Dades Wadi watershed scale. Seven main flood-causing criteria were broadly selected, namely flow accumulation, distance from hydrographic network, drainage network density, land use, slope, rainfall, permeability. The relative importance of each criterion prioritized as per their contribution toward risk, which employed blend Analytical Hierarchy Process (AHP) Geographic Information System (GIS)/Remote Sensing (RS) techniques. significance was determined based to hazard, established through an AHP pair-wise comparison matrix. efficacy model performed with consistency ratio 0.08, indicated that weight confirmed. Among criteria, hydrologic accumulation factor identified most influential (weight: 3.11), while permeability exhibited least prominence 0.58). Approximately 40.36% total area, equivalent around 1319, 89 km2, concentrated within very high flood-risk situated near rivers. In contrast, area approximately 399,943 km2 (56.33%) low zone. validation FHI map encompassed application Receiver Operating Characteristic Curve (ROC) technique, revealing Area Under (AUC) 85%.

Language: Английский

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Advanced modeling for flash flood susceptibility mapping using remote sensing and GIS techniques: a case study in Northeast Algeria

Environmental Earth Sciences, Journal Year: 2024, Volume and Issue: 83(2)

Published: Jan. 1, 2024

Language: Английский

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Monitoring and modeling vulnerability of land use changes in the current flood hazard conditions using novel hybrid GIS-based approaches and remote sensing data

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Jan. 18, 2025

Language: Английский

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Landfill site selection in hilly terrains: An integrated RS-GIS approach with AHP and VIKOR

Waste Management Bulletin, Journal Year: 2025, Volume and Issue: 3(1), P. 332 - 348

Published: Feb. 1, 2025

Language: Английский

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Geospatial Assessment and Mapping Landslide Susceptibility for the Garo Hills Division, Meghalaya, India

Geological Journal, Journal Year: 2025, Volume and Issue: 60(5), P. 1184 - 1201

Published: Feb. 19, 2025

ABSTRACT Creating accurate and effective Landslide Susceptibility (LS) maps can aid disaster prevention mitigation efforts provide sufficient public safety. The primary aim of this study is to develop an LS map for the Garo Hills region in Meghalaya, India, using weight evidence (WoE), frequency ratio (FR), Shannon entropy (SE) methods. A comprehensive landslide inventory catalogued 98 events from 2000 2023 analysis, nine key geographical environmental parameters were prepared. Conducted multicollinearity correlation analysis identify mitigate collinearity issues between factors. model's performance was analysed through area under curve (AUC) value receiver operating characteristic (ROC) curves three recent landslides. results showed that FR method achieved highest accuracy, with successive rate (SRC) AUC predictive (PRC) values 0.860 0.940, respectively, classified susceptibility at sites as high, moderate, low. WoE effectively identified landslides site high very zones, achieving SRC PRC 0.844 0.915, respectively. SE robust predicting landslide‐prone areas, comparable other methods (0.913), though its (0.771) lower. Developed revealed zones account approximately 10% 3% area, predominantly near roads, steep slopes, higher elevations. information valuable civilians government authorities involved hazard monitoring management.

Language: Английский

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Evaluating Flood Susceptibility in the Brahmaputra River Basin: An Insight into Asia's Eastern Himalayan Floodplains Using Machine Learning and Multi-Criteria Decision-Making

Earth Systems and Environment, Journal Year: 2023, Volume and Issue: 7(4), P. 733 - 760

Published: Dec. 1, 2023

Abstract Floods represent a significant threat to human life, property, and agriculture, especially in low-lying floodplains. This study assesses flood susceptibility the Brahmaputra River basin, which spans China, India, Bhutan, Bangladesh—an area notorious for frequent flooding due saturation of river water intake capacity. We developed evaluated several innovative models predicting by employing Multi-Criteria Decision Making (MCDM) Machine Learning (ML) techniques. The showed robust performance, evidenced Area Under Receiver Operating Characteristic Curve (AUC-ROC) scores exceeding 70% Mean Absolute Error (MAE), Squared (MSE), Root (RMSE) below 30%. Our findings indicate that approximately one-third studied region is categorized as moderately highly flood-prone, while over 40% classified low very flood-risk areas. Specific regions with high include Dhemaji, Dibrugarh, Lakhimpur, Majuli, Darrang, Nalbari, Barpeta, Bongaigaon, Dhubri districts Assam; Coochbihar Jalpaiguri West Bengal; Kurigram, Gaibandha, Bogra, Sirajganj, Pabna, Jamalpur, Manikganj Bangladesh. Owing their strong performance suitability training datasets, we recommend application MCDM techniques ML algorithms geographically similar holds implications policymakers, regional administrators, environmentalists, engineers informing management prevention strategies, serving climate change adaptive response within basin.

Language: Английский

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Spring water suitable and vulnerable watershed demarcation using AHP-TOPSIS and AHP-VIKOR models: study on Aizawl district of North-Eastern hilly state of Mizoram, India

Environmental Earth Sciences, Journal Year: 2023, Volume and Issue: 82(3)

Published: Jan. 27, 2023

Springs are one of the vital sources water in Mizoram district North-Eastern hilly state India. However, there is a paucity literature on spring serviceability, recharge potentiality and watershed management. Therefore, present research aims to prepare suitable vulnerable map Aizawl using AHP-TOPSIS AHP-VIKOR models. Highest relief, mean slope, annual rainfall, temperature, distribution springs, geomorphic units, geological formations, stream order, concentration lineaments epicentre were considered as major suitability inducing factors. Besides, landslide, forest fire, cover area, built-up stone mining sites, proportion agricultural land, degraded open area body taken measure vulnerability across watersheds. Relative analysis (0–0.60) (0.04–1.00) shows that central part for water. Study further reveals hazard intensity anthropogenic interventions also very high compared other regions (AHP-TOPSIS—0.0–0.85 AHP-VIKOR—0.0–1.00). Consequently, maps prepared this study could act blueprint Lastly, ROC curve (0.816) slightly better its prediction (0.743).

Language: Английский

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“Flood inundation mapping of upstream region in the Adyar River basin: Integrating hydrologic engineering centre's river analysis system (HEC-RAS) approach with groundwater considerations”

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 24, P. 101085 - 101085

Published: Jan. 8, 2024

Language: Английский

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Development of carbon finance in China based on the hybrid MCDM method

Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)

Published: Jan. 23, 2024

Abstract As development progresses over time and changes in the environment take place, carbon finance has become a very interesting research topic for many scholars worldwide. This paper proposes hybrid MCDM method that combines distance solutions of TOPSIS VIKOR methods. The contribution this VIKOR, incorporating AISM models to obtain ranking Chinese pilot cities as related provinces cities. conclusion notes Guangdong Beijing are most preferred investment locations investors. In addition, technological innovation, financial sector development, an active ETS market can effectively drive level local finance. Additionally, methodology provides new ideas environmental economic assessment.

Language: Английский

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