Proababilistic Approach to Deterministic Inundation Map Informed by Geographical Factors

2020 ◽  
Author(s):  
Jae-Ung Yu ◽  
Minkyu Jung ◽  
Jin-Young Kim ◽  
Hyun-Han Kwon
Keyword(s):  
Logistic Regression ◽  
Flood Risk ◽  
Flood Control ◽  
Hydrological Cycle ◽  
Flood Hazard ◽  
Control Measures ◽  
Geographical Information ◽  
Target Area ◽  
Hazard Map ◽  
Flood Hazard Map

<p>Urbanization causes extension of impervious surface interrupting natural hydrological cycle, which may increase in the number of disaster factors causing difficulties in terms of flood management. Flood control measures should prioritize identification of areas where flooding is expected to occur, considering various spatial characteristics distributed over the areas at risk. In this study, a probabilistic flood risk assessment was performed. The flood hazard map for a 100-year return level was used to illustrate the concept of a probabilistic model. Here, we trained the model to obtain the relationship between the estimated inundation area and potential predictors such as elevation, slope, curve number, and distance to the river. In this study, a Bayesian logistic regression analysis was performed to impose probabilities on the inundation for each grid. Finally, the flood risk was provided with the population for the entire target area through the model.</p><p> </p><p>Keywords: Bayesian Inference, Flood Hazard Map, Geographical Information, Logistic Regression</p><p> </p><p>Acknowledgement</p><p>This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 19AWMP-B121100-04)</p>

Probabilistic Flood Hazard Maps at Ungauged Locations Using Multivariate Extreme Values Approach

2020 ◽  
Author(s):  
Kiran Kezhkepurath Gangadhara ◽  
Srinivas Venkata Vemavarapu
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Flood Plain ◽  
Hydrologic Model ◽  
Regional Frequency Analysis ◽  
Hazard Map ◽  
Hazard Maps ◽  
Flood Hydrograph ◽  
Flood Hazard Map ◽  
Flood Hazard Maps

<p>Flood hazard maps are essential for development and assessment of flood risk management strategies. Conventionally, flood hazard assessment is based on deterministic approach which involves deriving inundation maps considering hydrologic and hydraulic models. A flood hydrograph corresponding to a specified return period is derived using a hydrologic model, which is then routed through flood plain of the study area to estimate water surface elevations and inundation extent with the aid of a hydraulic model. A more informative way of representing flood risk is through probabilistic hazard maps, which additionally provide information on the uncertainty associated with the extent of inundation. To arrive at a probabilistic flood hazard map, several flood hydrographs are generated, representing possible scenarios for flood events over a long period of time (e.g., 500 to 1000 years). Each of those hydrographs is routed through the flood plain and probability of inundation for all locations in the plain is estimated to derive the probabilistic flood hazard map. For gauged catchments, historical streamflow and/or rainfall data may be used to determine design flood hydrographs and the corresponding hazard maps using various strategies. In the case of ungauged catchments, however, there is a dearth of procedures for prediction of flood hazard maps. To address this, a novel multivariate regional frequency analysis (MRFA) approach is proposed. It involves (i) use of a newly proposed clustering methodology for regionalization of catchments, which accounts for uncertainty arising from ambiguity in choice of various potential clustering algorithms (which differ in underlying clustering strategies) and their initialization, (ii) fitting of a multivariate extremes model to information pooled from catchments in homogeneous region to generate synthetic flood hydrographs at ungauged target location(s), and (iii) routing of the hydrographs through the flood plain using LISFLOOD-FP model to derive probabilistic flood hazard map. The MRFA approach is designed to predict flood hydrograph related characteristics (peak flow, volume and duration of flood) at target locations in ungauged basins by considering watershed related characteristics as predictor/explanatory variables. An advantage of the proposed approach is its ability to account for uncertainty in catchment regionalization and dependency between all the flood hydrograph related characteristics reliably. Thus, the synthetic flood hydrographs generated in river basins appear more realistic depicting the observed dependence structure among flood hydrograph characteristics. The approach alleviates several uncertainties found in conventional methods (based on conceptual, probabilistic or geomorphological approaches) which affect estimation of flood hazard. Potential of the proposed approach is demonstrated through a case study on catchments in Mahanadi river basin of India, which extends over 141,600 km<sup>2</sup> and is frequently prone to floods. Comparison is shown between flood hazard map obtained based on true at-site data and that derived based on the proposed MRFA approach by considering the respective sites to be pseudo-ungauged. Coefficient of correlation and root mean squared error considered for performance evaluation indicated that the proposed approach is promising.</p>

Flash flood hazard mapping based on AHP with GIS and satellite information in Kampong Speu Province, Cambodia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chhuonvuoch Koem ◽  
Sarintip Tantanee
Keyword(s):  
Land Use ◽  
Flash Flood ◽  
Flood Hazard ◽  
Geographical Information ◽  
Hazard Mapping ◽  
Hazard Map ◽  
Content Type ◽  
Satellite Information ◽  
Flood Hazard Map ◽  
Hazard Levels

Purpose Cambodia is considered one of the countries that are most vulnerable to adverse effects of climate change, particularly floods and droughts. Kampong Speu Province is a frequent site of calamitous flash floods. Reliable sources of flash flood information and analysis are critical in efforts to minimize the impact of flooding. Unfortunately, Cambodia does not yet have a comprehensive program for flash flood hazard mapping, with many places such as Kampong Speu Province having no such information resources available. The purpose of this paper is, therefore, to determine flash flood hazard levels across all of Kampong Speu Province using analytical hierarchy process (AHP) and geographical information system (GIS) with satellite information. Design/methodology/approach The integrated AHP–GIS analysis in this study encompasses ten parameters in the assessment of flash flood hazard levels across the province: rainfall, geology, soil, elevation, slope, stream order, flow direction, distance from drainage, drainage density and land use. The study uses a 10 × 10 pairwise matrix in AHP to compare the relative importance of each parameter and find each parameter’s weight. Finally, a flash flood hazard map is developed displaying all areas of Kampong Speu Province classified into five levels, with Level 5 being the most hazardous. Findings This study reveals that high and very high flash flood hazard levels are identified in the northwest part of Kampong Speu Province, particularly in Aoral, Phnum Srouch and Thpong districts and along Prek Thnot River and streams. Originality/value The flash flood hazard map developed here provides a wealth of information that can be invaluable for implementing effective disaster mitigation, improving disaster preparedness and optimizing land use.

scholarly journals A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Hazard ◽  
Cloud Model ◽  
Flood Disaster ◽  
Assessment System ◽  
Assessment Model ◽  
Flood Risk Assessment ◽  
Emergy Theory

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

scholarly journals Improving the understanding of flood risk in the Alsatian region by knowledge capitalization: the ORRION participative observatory

2018 ◽  
Author(s):  
Florie Giacona ◽  
Brice Martin ◽  
Benjamin Furst ◽  
Rüdiger Glaser ◽  
Nicolas Eckert ◽  
...  
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Common Knowledge ◽  
Synoptic Situation ◽  
Target Area ◽  
15Th Century ◽  
Key Factor ◽  
Data Content ◽  
Rich Data ◽  
Knowledge Capitalization

Abstract. Despite the strong societal impact of natural hazards, their documentation remains incomplete, with only a few inventories exceeding the past two centuries. Surprisingly enough, this also applies to Europe, a densely populated territory, and to floods, which along with storms is the most common and damage-causing natural hazard in this area. In addition, existing inventories have often been compiled by scientists and technicians and are used for risk management in a top-down manner, although the participation of all parties concerned has been recognized as a key factor for disaster reduction. To address this double paradox, the present article presents the regional flood risk observatory ORRION for the Alsatian region, northeastern France, and its very rich data content. Stemming from two successive interdisciplinary and transnational French-German research projects, ORRION was designed as a participative online platform where information is shared between individuals, stakeholders, engineers, and scientists. This original approach aims at maximizing knowledge capitalization and contributes to building a common knowledge base for flood risk. ORRION is organized by events including all river floods that have likely arisen from a single synoptic situation. For each event, it documents information sources, date of occurrence, causes, and consequences in terms of damage and affected river basins and municipalities. ORRION contributed toward renewing our knowledge of flood hazard and risk in the target area. Notably, here, long chronicles of floods are derived for 13 rivers, the Rhine and most of its main Alsatian tributaries, and for all Alsatian municipalities, most of them since the end of the 15th century, but over more than one millennium for the Rhine. Their main characteristics according to various typologies (seasonality, causes, severity, etc.) are analyzed. Major developments over the study period related to sources, land use, and/or climate change are identified. The advantages and limitations of the approach are discussed and the potential to expand both data exploitation and the building of common flood risk knowledge are listed.

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