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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Spatial analysis of flood susceptibility in Coastal area of Pakistan using machine learning models and SAR imagery

Environmental Earth Sciences, Год журнала: 2025, Номер 84(5)

Опубликована: Фев. 18, 2025

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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Leveraging machine learning algorithms for improved disaster preparedness and response through accurate weather pattern and natural disaster prediction

Frontiers in Environmental Science, Год журнала: 2023, Номер 11

Опубликована: Ноя. 2, 2023

Globally, communities and governments face growing challenges from an increase in natural disasters worsening weather extremes. Precision disaster preparation is crucial responding to these issues. The revolutionary influence that machine learning algorithms have strengthening catastrophe response systems thoroughly explored this paper. Beyond a basic summary, the findings of our study are striking demonstrate sophisticated powers forecasting variety patterns anticipating range catastrophes, including heat waves, droughts, floods, hurricanes, more. We get practical insights into complexities applications, which support enhanced effectiveness predictive models preparedness. paper not only explains theoretical foundations but also presents proof significant benefits provide. As result, results open door for governments, businesses, people make wise decisions. These accurate predictions catastrophes emerging may be used implement pre-emptive actions, eventually saving lives reducing severity damage.

Язык: Английский

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Identifying obstacles encountered at different stages of the disaster management cycle (DMC) and its implications for rural flooding in Pakistan

Frontiers in Environmental Science, Год журнала: 2023, Номер 11

Опубликована: Март 9, 2023

The world has seen a number of natural hazards, but among them, floods are perhaps the most frequent devastating hazard, resulting in more human causalities and financial losses. Rural inundation become an issue concern various parts world, including Pakistan. Over past few decades, it been hard for local institutions rural populations to recover from trauma inflicted by these events. disaster risk management cycle is well-known tool coping with disasters their consequences. Yet, DRM efficacy questioned settings. Thus, this paper applied programmatic strategy understand challenges authorities communities face managing flood risks through conventional Khyber Pakhtunkhwa province, study objective was accomplished using both qualitative exploratory research designs. Four (namely, Peshawar, Charsadda, Nowshera, Dera Ismail Khan) historical record flooding were chosen focus group discussion (32 total) purposive sampling method. Additionally, 31 key informant interviews undertaken pertinent institutions. We employed thematic analysis classify responses obstacles into stages cycle. findings groups provided some new insight issues encountered community members divided four stages: 1-mitigation, 2-preparedness, 3-rescue relief (R&R), 4-rehabilitation recovery (R&R). Based on findings, seems that still rely reactive strategies deal hazards ad hoc basis. Poor governance lack present development trajectories also highlighted as reasons why challenging. There urgent need perform susceptibility assessments multiple develop specialized plans follow reduction principles adaptation climate change. This recommends incorporating resilience change current prevent or reduce future areas.

Язык: Английский

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