Flood susceptibility mapping contributes to disaster risk reduction: A case study in Sindh, Pakistan

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 108, С. 104503 - 104503

Опубликована: Апрель 23, 2024

Floods are a widespread and damaging natural phenomenon that causes harm to human lives, resources, property has agricultural, eco-environmental, economic impacts. Therefore, it is crucial perform flood susceptibility mapping (FSM) identify susceptible zones mitigate reduce damage. This study assessed the damage caused by 2022 flash in Sindh identified flood-susceptible based on frequency ratio (FR) analytical hierarchy process (AHP) models. Flood inventory maps were generated, containing 150 sampling points, which manually selected from Landsat imagery. The points split into 70% for training 30% validating results. Furthermore, fourteen conditioning factors considered analysis developing FSM. final FSM categorized five zones, representing levels very low high. results areas under high Ghotki (FR 4.42% AHP 5.66%), Dadu 21.40% 21.29%), Sanghar 6.81% 6.78%). Ultimately, accuracy was evaluated using receiver operating characteristics area curve method, resulting 82%, 83%), 91%, 90%), 96%, 95%). enhances scientific understanding of impacts across diverse regions emphasizes importance accurate informed decision-making. findings provide valuable insights supportive policymakers, agricultural planners, stakeholders engaged risk management adverse consequences floods.

Язык: Английский

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Flood susceptibility assessment of the Agartala Urban Watershed, India, using Machine Learning Algorithm

Environmental Monitoring and Assessment, Год журнала: 2024, Номер 196(2)

Опубликована: Янв. 4, 2024

Язык: Английский

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Modelling on assessment of flood risk susceptibility at the Jia Bharali River basin in Eastern Himalayas by integrating multicollinearity tests and geospatial techniques

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 10(2), С. 2393 - 2419

Опубликована: Дек. 16, 2023

Abstract Climate change and anthropogenic factors have exacerbated flood risks in many regions across the globe, including Himalayan foothill region India. The Jia Bharali River basin, situated this vulnerable area, frequently experiences high-magnitude floods, causing significant damage to environment local communities. Developing accurate reliable susceptibility models is crucial for effective prevention, management, adaptation strategies. In study, we aimed generate a comprehensive zone model catchment by integrating statistical methods with expert knowledge-based mathematical models. We applied four distinct models, Frequency Ratio model, Fuzzy Logic (FL) Multi-criteria Decision Making based Analytical Hierarchy Process evaluate of basin. results revealed that approximately one-third basin area fell within moderate very high flood-prone zones. contrast, over 50% was classified as low demonstrated strong performance, ROC-AUC scores exceeding 70% MAE, MSE, RMSE below 30%. FL AHP were recommended application among areas similar physiographic characteristics due their exceptional performance training datasets. This study offers insights policymakers, regional administrative authorities, environmentalists, engineers working region. By providing robust research enhances prevention efforts thereby serving vital climate strategy regions. findings also implications disaster risk reduction sustainable development areas, contributing global towards achieving United Nations' Sustainable Development Goals.

Язык: Английский

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Enhancing Flooding Depth Forecasting Accuracy in an Urban Area Using a Novel Trend Forecasting Method

Water Resources Management, Год журнала: 2024, Номер 38(4), С. 1359 - 1380

Опубликована: Янв. 10, 2024

Язык: Английский

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Utilizing Remote Sensing and GIS Techniques for Flood Hazard Mapping and Risk Assessment

Civil Engineering Journal, Год журнала: 2024, Номер 10(5), С. 1423 - 1436

Опубликована: Май 1, 2024

In this paper, a comprehensive flood hazard map for the vicinity of King Talal Dam in Jordan, utilizing advanced remote sensing (RS) and GIS methodologies, is developed. Key geographical environmental factors, encompassing terrain slope, elevation, aspect, proximity to water streams, drainage density, land use/land cover, are integrated highlight areas with increased risk. This study, by employing novel theoretical approach, harnesses synergistic capabilities RS collect analyze geospatial data. The Analytic Hierarchy Process (AHP) applied assign weights various flood-conditioning quantifying their relative importance risk assessment. Through weighted sum overlay technique, aforementioned factors categorize levels from very low high. study successfully maps hazards, identifying near main channels, ravines, lower-elevation prone flooding. research provides robust framework assessment, contributing valuable knowledge fields management disaster mitigation. It underscores continuous monitoring updating accommodate changing use, climate, hydrological conditions. innovative application offers crucial insights urban planners policymakers, emphasizing need proactive strategies flood-prone serving as model similar regions. Doi: 10.28991/CEJ-2024-010-05-05 Full Text: PDF

Язык: 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, Год журнала: 2024, Номер 2, С. 100019 - 100019

Опубликована: Март 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%.

Язык: Английский

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An integrated statistical-geospatial approach for the delineation of flood-vulnerable sub-basins and identification of suitable areas for flood shelters in a tropical river basin, Kerala

Geosystems and Geoenvironment, Год журнала: 2024, Номер 3(2), С. 100251 - 100251

Опубликована: Янв. 3, 2024

Flood vulnerability assessment is crucial for effective flood management and mitigation strategies. The present study aims to understand the of Kallada River Basin (KRB) identify suitable areas safe sheltering facilities in basin. As part this, morphometric analysis KRB was carried out by dividing basin into fifty-eight 4th-order sub-basins sub-basin-wise terrain characteristics degree flooding. GIS tools were used assess various morphometrical parameters, such as drainage frequency, texture ratio, ruggedness number, relief, bifurcation length overland flow, density, circularity ratio area, geo-environmental factors sand percent, rainfall, mean slope these basins. parameters exhibited distinct spatial trends, with higher values primarily concentrated east northeast parts certain western others. Using hierarchical cluster analysis, categorized six clusters, revealing that 51% vulnerable floods, 26% moderately vulnerable, 22% not vulnerable. Sub-basins central found be highly flooding, while those eastern showed moderate or mapping validated using data from 2018 2019 confirming its accuracy. Additionally, weighted overlay method identified shelters suitable, areas. SB53 SB55 have most areas, emphasizing their potential shelter locations. findings this can competent authorities initiate develop targeted preparedness measures similar river basins, particularly context increasing events during last few years.

Язык: Английский

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Geospatial Mapping and Meteorological Flood Risk Assessment: A Global Research Trend Analysis

Environmental Management, Год журнала: 2024, Номер unknown

Опубликована: Окт. 12, 2024

Abstract Flooding is a global threat causing significant economic and environmental damage, necessitating policy response collaborative strategy. This study assessed research trends advances in geospatial meteorological flood risk assessment (G_MFRA), considering the ongoing debate on management adaptation strategies. A total of 1872 original articles were downloaded BibTex format using Web Science (WOS) Scopus databases to retrieve G_MFRA studies published from 1985 2023. The annual growth rate 15.48% implies that field has been increasing over time during period. analysis practice highlights key themes, methodologies, emerging directions. There exists notable gap data methodologies for between developed developing countries, particularly Africa South America, highlighting urgency coordinated efforts cohesive actions. challenges identified body extant literature include technical expertise, complex communication networks, resource constraints associated with application gaps methodologies. advocates holistic approach disaster through ecosystem-based underpins Sustainable Development Goals develop innovative techniques models potential influence decision-making domain. Addressing these requires networked partnership community, institutions, countries.

Язык: Английский

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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping

Geomatics Natural Hazards and Risk, Год журнала: 2024, Номер 15(1)

Опубликована: Июнь 12, 2024

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 efficiently reduce space. Through comprehensive comparisons established algorithms such as Artificial Bee Colony (ABC) Gray Wolf Optimizer (GWO), MSA refined selection, identifying 'elevation' 'distance streams' optimal factors. Statistical validations Friedman Wilcoxon signed-rank tests confirmed significant superiority over competing algorithms. Ensemble classifiers (bagging, boosting, stacking) then applied reduced Comprehensive evaluation revealed boosting outperformed traditional techniques reaching 98.75% 0.9896 Area Under Curve (AUC), 98.95% harmonic mean precision recall (F1-score). Precision high-risk zones was underlined via spatial prediction, confirming integrated framework's ability significantly improve forecast accuracy. The findings aid disaster management powerful geographic data-poor regions. framework adaptable globally flood-prone areas similar constraints. As climate change expected increase extreme rainfall events, communities will need robust data-driven methodologies mapping. Key recommendations current include investigating hybrid methods better inputs analyzing transferability across hydro-climatic zones.

Язык: Английский

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Flood risk mapping under changing climate in Lower Tapi river basin, India

Stochastic Environmental Research and Risk Assessment, Год журнала: 2024, Номер 38(6), С. 2231 - 2259

Опубликована: Март 4, 2024

Язык: Английский

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