Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index

Kabenge, Martin; Elaru, Joshua; Wang, Hongtao; Li, Fengting

doi:10.1007/s11069-017-3024-y

Cited by 87 publications

(56 citation statements)

References 44 publications

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“…Given the absence of river discharge data for Dharan, we adopted the GIS-based FHI method. Based on the results of previous studies, seven criteria-variables were selected to construct the FHI: distance from streams (Butler et al 2006), elevation (Chen et al 2015), flow accumulation (Kazakis et al 2015), lithology (Tehrany et al 2013), land use (Yalcin and Akyurek 2004), rainfall intensity (Ouma and Tateishi 2014), and slope (Kabenge et al 2017) (Table 1).…”

Section: Flood Hazard Assessmentmentioning

confidence: 99%

“…Water flows from higher elevations and slopes to lower elevations and slopes. Lower slopes decrease the speed of runoff and are more quickly inundated than higher slopes (Kabenge et al 2017). High values of flow accumulation indicate concentrated flows and consequently higher flood hazard zones (Kazakis et al 2015).…”

Section: Flood Hazard Assessmentmentioning

confidence: 99%

“…However, to determine the weight of each variable for flood and earthquake hazards, AHP method was used (Saaty 2008). AHP is a widely used a multi-criteria, decision-making tool that serves a basis for integrating and determining the importance of criteria-variables (Althuwaynee et al 2014;Kazakis et al 2015;Kabenge et al 2017;Hoque et al 2018). We prepared a pairwise comparison matrix for flood and earthquake hazards.…”

Section: Weighting Criteria-variables Using Ahpmentioning

confidence: 99%

“…Hence, risk assessment, and ultimately vulnerability reduction, are processes that require multidisciplinary knowledge of various coupled physical and social processes to calculate the cumulative level of risk posed by hazards. Studies of natural hazard risk frequently emphasize the impacts of an individual hazard, such as landslides (Althuwaynee et al 2014;Pellicani et al 2017), floods (Kazakis et al 2015;Kabenge et al 2017), earthquakes (Theilen-Willige 2010; Dhar et al 2017), drought (Lehner et al 2006), sea level rise (Hinkel et al 2014), tropical cyclones (Hoque et al 2018), or wildfires (Adab et al 2013). However, in reality, many locations are prone to multiple natural hazards that can occur simultaneously or manifest in a set of cascading events (Kappes et al 2012).…”

Section: Introductionmentioning

confidence: 99%

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A geospatial analysis of multi-hazard risk in Dharan, Nepal

Aksha

Resler

Juran

et al. 2020

Geomatics, Natural Hazards and Risk

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Natural hazard risk assessment generally focuses on a single hazard type, such as earthquakes, landslides, or floods. This emphasis tends to consider physical processes in isolation. However, most locations are simultaneously at risk to multiple, interacting hazards that generate cascading effects or synergies. Although scholars have proposed a multi-hazard risk framework based on probabilities, the quality and quantity of data required for such an approach are often unavailable in developing countries. Using geospatial and socioeconomic data, this study represents a first step in assessing multi-hazard risk in the city of Dharan, Nepal. Three hazards-landslides, floods, and earthquakes-were considered for an integrated hazard assessment using statistical methods and the Analytic Hierarchy Process (AHP). We employed a Social Vulnerability Index (SoVI) to create a vulnerability map of the study area, which was then combined with a multi-hazard hazard map to produce a total risk map. Our results indicate that eastern Dharan along the Seuti River and southwestern Dharan on the left bank of the Sardu River are at high risk to multiple hazards. Central Dharan and the hills in the western portion of the city are categorized as low risk areas. Data limitations, such as availability and spatial resolution, did not allow for dynamic modeling; however, our results identified the spatial extent of low to high risk areas, which can inform future disaster planning. For example, the methodology and results of this study could assist in the development of disaster risk reduction programs and policies. ARTICLE HISTORY

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Section: Flood Hazard Assessmentmentioning

confidence: 99%

Section: Flood Hazard Assessmentmentioning

confidence: 99%

Section: Weighting Criteria-variables Using Ahpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A geospatial analysis of multi-hazard risk in Dharan, Nepal

Aksha

Resler

Juran

et al. 2020

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

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“…However, in many cases, a lack of reliable data hinders the simulation processes. This issue, particularly for flood hazard assessment, has been highlighted by Kabenge et al [38] in their recent work [38].…”

Section: Resultsmentioning

confidence: 96%

Assessing Flood Hazard at River Basin Scale with an Index-Based Approach: The Case of Mouriki, Greece

Patrikaki¹,

Kazakis

Kougias

et al. 2018

Geosciences

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Defining flood-prone areas is particularly important for policy makers, in order to design mitigation strategies and implement flood risk management planning. The present research applies a multicriteria index method to assess flood hazard areas at a river basin scale, in a geographic information system (GIS) environment. The developed methodology has been applied for an area in northeastern Greece, by processing information of seven parameters: flow accumulation, distance from the drainage network, elevation, land use, rainfall intensity and geology. The method assigns a relative importance to each of the parameters for the occurrence and magnitude of flooding, and the relevant weight values are defined through an "analytical hierarchy process". Subsequently, and according to the relative importance of each index, the spatial information is superimposed, resulting in a flood hazard map of the studied region, an area in northern Greece. The obtained results indicate flood-prone zones, with a very high flood hazard mainly occurring at the lowlands in the vicinity of the drainage network. The provided flood hazard map supports planning activities and mitigation plans that are crucial to protect both the agricultural activities and existing infrastructure from future flood events.

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Temporal variations in rainfall patterns in Kilembe, Uganda

2021

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This study investigated rainfall variabilities in Kilembe. Secondary (monthly rainfall) data for the study were obtained from the Uganda National Meteorological Authority in Kampala, Uganda, for the period 1986–2016. To determine the temporal variation of rainfall, a Mann–Kendall method and Sen's slope estimator test were used. The results showed that March, April, May, October, and November represented the smallest coefficient of variation indicating modest variability of rainfall in these months, whereas June and July had the largest coefficient of variation. The month of July recorded an overall lowest average rainfall and a decreasing trend in rainfall. The study further revealed a historical general upward trend in rainfall between 1986 and 2016 in Kilembe. The trend in the monthly and annual rainfall is partly attributed to the Intertropical Convergence Zone, influx of moisture from Congo Forest, and climate change. The area recorded also two peaks of rainfall in the year, one in April and another in September, revealing a bimodal pattern of rainfall. The findings indicate that the government should adopt policy measures in the form of an adaptive strategy in order to save the people in the impacted areas.

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Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index

Cited by 87 publications

References 44 publications

A geospatial analysis of multi-hazard risk in Dharan, Nepal

A geospatial analysis of multi-hazard risk in Dharan, Nepal

Assessing Flood Hazard at River Basin Scale with an Index-Based Approach: The Case of Mouriki, Greece

Temporal variations in rainfall patterns in Kilembe, Uganda

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