scholarly journals A FlOOD RISK CURVE DEVELOPMENT FOR INUNDATION DISASTER CONSIDERING SPATIO-TEMPORAL RAINFALL DISTRIBUTION

2015 ◽  
Vol 71 (4) ◽  
pp. I_1483-I_1488
Author(s):  
Tomohiro TANAKA ◽  
Yasuto TACHIKAWA ◽  
Kazuaki YOROZU
Keyword(s):  
Flood Risk ◽  
Rainfall Distribution ◽  
Risk Curve ◽  
Spatio Temporal

scholarly journals A flood risk curve development for inundation disaster considering spatio-temporal rainfall distribution

2015 ◽  
Vol 370 ◽  
pp. 57-62 ◽  
Author(s):  
T. Tanaka ◽  
Y. Tachikawa ◽  
K. Yorozu
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Disaster ◽  
Exceedance Probability ◽  
Maximum Rainfall ◽  
Economic Changes ◽  
Risk Curve ◽  
Spatio Temporal ◽  
Annual Maximum Rainfall ◽  
Risk Curves

Abstract. To manage flood disaster with an exceeding designed level, flood risk control based on appropriate risk assessment is essential. To make an integrated economic risk assessment by flood disaster, a flood risk curve, which is a relation between flood inundation damage and its exceedance probability, plays an important role. This research purposes a method to develop a flood risk curve by utilizing a probability distribution function of annual maximum rainfall through rainfall-runoff and inundation simulations so that risk assessment can consider climate and socio-economic changes. Among a variety of uncertainties, the method proposed in this study considered spatio-temporal rainfall distributions that have high uncertainty for damage estimation. The method was applied to the Yura-gawa river basin (1882 km2) in Japan; and the annual economic benefit of an existing dam in the basin was successfully quantified by comparing flood risk curves with/without the dam.

scholarly journals A Multi-Criteria Decision Support System in the Analysis of Flood Risk and Vulnerability Mapping in Suleja, Niger State, Nigeria

2019 ◽  
Vol 2 ◽  
pp. 1-7 ◽  
Author(s):  
Nura Khaliel Umar ◽  
Halima Sadiya Abdullahi ◽  
Ado Kibon Usman
Keyword(s):  
Flood Risk ◽  
Hazard Map ◽  
Ahp Method ◽  
Rainfall Distribution ◽  
Weighted Overlay ◽  
Causative Factors ◽  
Priority Weights ◽  
Vulnerability Map ◽  
Hierarchy Process ◽  
Pair Wise Comparison

<p><strong>Abstract.</strong> This study aims at assessing flood risk factors and mapping areas vulnerable to flood in Suleja of Niger State, Nigeria, using Geo-spatial techniques. The method follows a multi-parametric approach and integrates some of the flood causative factors as: rainfall distribution, elevation and slope, drainage network and density, landuse/ land-cover and soil type. The Spatial Multi-Criteria Analysis (MCA) was used to rank and display potential locations, while the Analytical Hierarchy Process (AHP) method was employed using pair-wise comparison to compute the priority weights of each factor. The various layers were integrated in weighted overlay tool in ArcGIS to generate the final vulnerability map (high, moderate and low). The normalized criterion weights were obtained for each factor, and the results shows that, rainfall (34) and slope (31) have the highest influence on flood in the study area. The Consistency Ratio (CR) with an acceptable level of 0.05 was obtained which further validated the strength of the judgement. The factor weights from the AHP were incorporated to produce a Geo-hazard map and it showed that areas that are high vulnerable to flood in Suleja constitute about 37%, while moderate and low vulnerable areas constitute about 45% and 18% respectively. Elements at high risk of flood are those found at the extreme northeast, where elevation is very low, southwest where rainfall distribution is high and on low lying areas along the depressions. Therefore using the Geo-hazard map as a guide, local councils and other stakeholders can act to prepare for potential floods.</p>

scholarly journals How are flood risk estimates affected by the choice of return-periods?

2011 ◽  
Vol 11 (12) ◽  
pp. 3181-3195 ◽  
Author(s):  
P. J. Ward ◽  
H. de Moel ◽  
J. C. J. H. Aerts
Keyword(s):  
Flood Risk ◽  
Damage Model ◽  
Area Under The Curve ◽  
Flood Management ◽  
Exceedance Probability ◽  
Return Periods ◽  
Inundation Maps ◽  
Risk Estimates ◽  
Risk Curve ◽  
Inundation Extent

Abstract. Flood management is more and more adopting a risk based approach, whereby flood risk is the product of the probability and consequences of flooding. One of the most common approaches in flood risk assessment is to estimate the damage that would occur for floods of several exceedance probabilities (or return periods), to plot these on an exceedance probability-loss curve (risk curve) and to estimate risk as the area under the curve. However, there is little insight into how the selection of the return-periods (which ones and how many) used to calculate risk actually affects the final risk calculation. To gain such insights, we developed and validated an inundation model capable of rapidly simulating inundation extent and depth, and dynamically coupled this to an existing damage model. The method was applied to a section of the River Meuse in the southeast of the Netherlands. Firstly, we estimated risk based on a risk curve using yearly return periods from 2 to 10 000 yr (€ 34 million p.a.). We found that the overall risk is greatly affected by the number of return periods used to construct the risk curve, with over-estimations of annual risk between 33% and 100% when only three return periods are used. In addition, binary assumptions on dike failure can have a large effect (a factor two difference) on risk estimates. Also, the minimum and maximum return period considered in the curve affects the risk estimate considerably. The results suggest that more research is needed to develop relatively simple inundation models that can be used to produce large numbers of inundation maps, complementary to more complex 2-D–3-D hydrodynamic models. It also suggests that research into flood risk could benefit by paying more attention to the damage caused by relatively high probability floods.

scholarly journals A rainfall distribution and their influence on flood generation in the eastern Slovakia

2013 ◽  
Vol 61 (6) ◽  
pp. 1645-1652 ◽  
Author(s):  
Lenka Gaňová ◽  
Martina Zeleňáková ◽  
Pavol Purcz ◽  
Žofia Kuzevičová ◽  
Helena Hlavatá
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Ranking Method ◽  
Flood Risk Assessment ◽  
Rainfall Distribution ◽  
Causative Factors ◽  
Geographical Characteristic ◽  
Composite Maps ◽  
Flood Generation ◽  
The Impact

This paper aims to geographically assess the flood occurrence in eastern Slovakia by using one of the methods of multi-criteria analysis – rank sum method. Flood risk assessment is conducted in three specific cases: the long term period 1989–2009, the extremely wet 2010 year, and the extremely dry 2011 year. In the analyses, some of the causative factors for flooding in a basin area are taken into account. We use set of causative factors concerning mostly hydrological and physio-geographical characteristic of the target area that can be measured and evaluated such as soil type, daily precipitation (for the years 1989–2009, 2010, 2011), land use, catchment area and basin slope. For recommendation which causative factors should be preferred we use method of multicriteria analysis – ranking method. In the ranking method (RM), every factor/criterion under consideration is ranked in the order of the decision-maker’s preference. Geographic approach to flood risk assessment provides a descriptive presentation of the results obtained. Geographic information systems as a visualization tool is presented in a manner that aids understanding in a user friendly way.Regarding our task of flood risk assessment, the partial results are three composite maps, which present comparison of flood risk zones in percentage of the area in years 1989–2009, 2010, and 2011. The composite maps are background for risk assessment of the impact of rainfall on flood generation.This study of hydrological data and physio-geographical characteristic was carried out with the purpose of the identification of flood risk occurrence in eastern Slovakia. Results from our study shows, that rainfall distribution has high influence on flood risk of the area. Area percentage with very high flood risk index was calculated for “wet” year 2010 as 11.73 %, for “dry” year 2011 as 0.01 % and for period 1989–2009 as 0.28 %.

scholarly journals Dynamic maps of people exposure to floods based on mobile phone data

2020 ◽  
Author(s):  
Matteo Balistrocchi ◽  
Rodolfo Metulini ◽  
Maurizio Carpita ◽  
Roberto Ranzi
Keyword(s):  
Mobile Phone ◽  
Flood Risk ◽  
Northern Italy ◽  
Flood Risk Management ◽  
Mobile Phone Data ◽  
Test Case ◽  
Time Patterns ◽  
Management Plans ◽  
Spatio Temporal ◽  
Flood Risk Management Plans

Abstract. Floods are acknowledged as one of the most serious threats to human lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management plans can actually provide effective non-structural practices to decrease both people exposure and vulnerability. Crowding maps depending on characteristic time patterns, herein referred to as dynamic exposure maps, provide a valuable tool to enhance the flood risk management plans. In this paper, the suitability of mobile phone data to derive crowding maps is discussed. A test case is provided by a strongly urbanized area subject to frequent floodings located in the western outskirt of Brescia town (northern Italy). Characteristic exposure spatio-temporal patterns and their uncertainties were detected, with regard to land cover and calendar period. This novel methodology appears to be more reliable than crowdsourcing strategies, and has potentials to better address real-time rescues and reliefs supply.

scholarly journals Extensive spatio-temporal assessment of flood events by application of pair-copulas

2015 ◽  
Vol 370 ◽  
pp. 177-181 ◽  
Author(s):  
M. Schulte ◽  
A. H. Schumann
Keyword(s):  
River Basin ◽  
Flood Risk ◽  
Dependence Structure ◽  
Flood Events ◽  
Multivariate Statistical ◽  
Local Conditions ◽  
Extreme Flood ◽  
Multivariate Statistical Approach ◽  
Spatio Temporal ◽  
Peak Discharges

Abstract. Although the consequences of floods are strongly related to their peak discharges, a statistical classification of flood events that only depends on these peaks may not be sufficient for flood risk assessments. In many cases, the flood risk depends on a number of event characteristics. In case of an extreme flood, the whole river basin may be affected instead of a single watershed, and there will be superposition of peak discharges from adjoining catchments. These peaks differ in size and timing according to the spatial distribution of precipitation and watershed-specific processes of flood formation. Thus, the spatial characteristics of flood events should be considered as stochastic processes. Hence, there is a need for a multivariate statistical approach that represents the spatial interdependencies between floods from different watersheds and their coincidences. This paper addresses the question how these spatial interdependencies can be quantified. Each flood event is not only assessed with regard to its local conditions but also according to its spatio-temporal pattern within the river basin. In this paper we characterise the coincidence of floods by trivariate Joe-copula and pair-copulas. Their ability to link the marginal distributions of the variates while maintaining their dependence structure characterizes them as an adequate method. The results indicate that the trivariate copula model is able to represent the multivariate probabilities of the occurrence of simultaneous flood peaks well. It is suggested that the approach of this paper is very useful for the risk-based design of retention basins as it accounts for the complex spatio-temporal interactions of floods.

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