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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Living with Floods Using State-of-the-Art and Geospatial Techniques: Flood Mitigation Alternatives, Management Measures, and Policy Recommendations

Water, Год журнала: 2023, Номер 15(3), С. 558 - 558

Опубликована: Янв. 31, 2023

Flood, a distinctive natural calamity, has occurred more frequently in the last few decades all over world, which is often an unexpected and inevitable hazard, but losses damages can be managed controlled by adopting effective measures. In recent times, flood hazard susceptibility mapping become prime concern minimizing worst impact of this global threat; nonlinear relationship between several causative factors dynamicity risk levels makes it complicated confronted with substantial challenges to reliable assessment. Therefore, we have considered SVM, RF, ANN—three ML algorithms GIS platform—to delineate zones subtropical Kangsabati river basin, West Bengal, India; experienced frequent events because intense rainfall throughout monsoon season. our study, adopted are efficient solving non-linear problems assessment; multi-collinearity analysis Pearson’s correlation coefficient techniques been used identify collinearity issues among fifteen factors. research, predicted results evaluated through six prominent statistical (“AUC-ROC, specificity, sensitivity, PPV, NPV, F-score”) one graphical (Taylor diagram) technique shows that ANN most modeling approach followed RF SVM models. The values AUC model for training validation datasets 0.901 0.891, respectively. derived result states about 7.54% 10.41% areas accordingly lie under high extremely danger zones. Thus, study help decision-makers constructing proper strategy at regional national mitigate particular region. This type information may helpful various authorities implement outcome spheres decision making. Apart from this, future researchers also able conduct their research byconsidering methodology

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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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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Multi-hazard could exacerbate in coastal Bangladesh in the context of climate change

Journal of Cleaner Production, Год журнала: 2024, Номер 457, С. 142289 - 142289

Опубликована: Апрель 23, 2024

Язык: Английский

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Flood hazard forecasting and management systems: A review of state-of-the-art modelling, management strategies and policy-practice gap

International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 108, С. 104539 - 104539

Опубликована: Май 8, 2024

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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Addressing energy poverty through education: How does gender matter?

Energy Economics, Год журнала: 2024, Номер 141, С. 108029 - 108029

Опубликована: Ноя. 10, 2024

Язык: Английский

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Influencing Factors and Risk Assessment of Precipitation-Induced Flooding in Zhengzhou, China, Based on Random Forest and XGBoost Algorithms

International Journal of Environmental Research and Public Health, Год журнала: 2022, Номер 19(24), С. 16544 - 16544

Опубликована: Дек. 9, 2022

Due to extreme weather phenomena, precipitation-induced flooding has become a frequent, widespread, and destructive natural disaster. Risk assessments of have thus popular area research. In this study, we studied the severe that occurred in Zhengzhou, Henan Province, China, July 2021. We identified 16 basic indicators, random forest algorithm was used determine contribution each indicator Zhengzhou flood. then optimised selected indicators introduced XGBoost construct risk index assessment model flooding. Our results four primary for study area: total rainfall three consecutive days, daily rainfall, vegetation cover, river system. The storm flood evaluation constructed from 12 indicators: elevation, slope, water system index, night-time light brightness, land-use type, proportion arable land area, gross regional product, elderly population, medical rescue capacity. After streamlining bottom terms rate, it had best performance, with an accuracy rate reaching 91.3%. Very high-risk areas accounted 11.46% 27.50% respectively, their distribution more significantly influenced by extent heavy direction systems, types; medium-risk largest, accounting 33.96% area; second-lowest-risk low-risk together 27.09%. highest were Erqi, Guanchenghui, Jinshui, Zhongyuan, Huizi Districts western part Xinmi City; these should be given priority attention during disaster monitoring early warning prevention control.

Язык: Английский

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