Effectiveness of water infrastructure for river flood management – Part 1: Flood hazard assessment using hydrological models in Bangladesh

Abstract. This study introduces a flood hazard assessment part of the global flood risk assessment (Part 2) conducted with a distributed hydrological Block-wise TOP (BTOP) model and a GIS-based Flood Inundation Depth (FID) model. In this study, the 20 km grid BTOP model was developed with globally available data on and applied for the Ganges, Brahmaputra and Meghna (GBM) river basin. The BTOP model was calibrated with observed river discharges in Bangladesh and was applied for climate change impact assessment to produce flood discharges at each BTOP cell under present and future climates. For Bangladesh, the cumulative flood inundation maps were produced using the FID model with the BTOP simulated flood discharges and allowed us to consider levee effectiveness for reduction of flood inundation. For the climate change impacts, the flood hazard increased both in flood discharge and inundation area for the 50- and 100-year floods. From these preliminary results, the proposed methodology can partly overcome the limitation of the data unavailability and produces flood~maps that can be used for the nationwide flood risk assessment, which is presented in Part 2 of this study.

Download Full-text

Rapid Global Exposure Assessment for Extreme River Flood Risk Under Climate Change

Journal of Disaster Research ◽

10.20965/jdr.2016.p1128 ◽

2016 ◽

Vol 11 (6) ◽

pp. 1128-1136 ◽

Cited By ~ 3

Author(s):

Youngjoo Kwak ◽

◽

Yoichi Iwami ◽

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Flood Hazard ◽

Data Availability ◽

Flood Risk Assessment ◽

Daily Data ◽

Extreme Flood ◽

River Flood

Globally, large-scale floods are one of the most serious disasters, considering increased frequency and intensity of heavy rainfall. This is not only a domestic problem but also an international water issue related to transboundary rivers in terms of global river flood risk assessment. The purpose of this study is to propose a rapid flood hazard model as a methodological possibility to be used on a global scale, which uses flood inundation depth and works reasonably despite low data availability. The method is designed to effectively simplify complexities involving hydrological and topographical variables in a flood risk-prone area when applied in an integrated global flood risk assessment framework. The model was used to evaluate flood hazard and exposure through pixel-based comparison in the case of extreme flood events caused by an annual maximum daily river discharge of 1/50 probability of occurrence under the condition of climate change between two periods, Present (daily data from 1980 to 2004) and Future (daily data from 2075 to 2099). As preliminary results, the maximum potential extent of inundation area and the maximum number of affected people show an upward trend in Present and Future.

Download Full-text

Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China

Sustainability ◽

10.3390/su12041451 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1451 ◽

Cited By ~ 3

Author(s):

Guangpeng Wang ◽

Yong Liu ◽

Ziying Hu ◽

Yanli Lyu ◽

Guoming Zhang ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Metropolitan Areas ◽

Flood Management ◽

Fuzzy Synthetic Evaluation ◽

Flood Risk Assessment ◽

Land Area ◽

Assessment Report ◽

Risk Zones

Flooding is one of the most devastating natural events and leads to enormous and recurring loss of life, properties, and resources around the globe. With climate change and accelerating urbanization, flood disasters in China have increasingly affected the sustainable development of metropolitan areas. Risk assessment is an essential step in flood management and disaster mitigation, which provide a quantitative measure of flood risk. However, the difficulty of flood risk zoning is dealing with the uncertainty of the evaluation process and the complicated non-linear relationship between indicators and risk levels. To address this issue, a fuzzy synthetic evaluation (FSE) method based on combined weight (CW) was utilized in this paper to generate flood risk maps at a grid-scale (1 × 1 km). For the case study in the Beijing-Tianjin-Hebei metropolitan area (BTH) in China, fourteen indicators were selected to construct the flood risk assessment model based on the FSE approach integrated with ArcGIS. The research demonstrates that moderate, high, and very high risk zones are distributed in the southeast fluvial plain of the BTH area, accounting for 31.36% of the total land area. Meanwhile, low and very-low risk zones occupy 68.64% of the total land area, and are primarily located in the high plateau and mountain regions in the northwest. We analyzed the risk level of each county and proposed risk mitigation measures based on field investigations. The verified risk assessment results were spatially consistent with the historical flood disaster records and loss positions, indicating the accuracy and reliability of the risk assessment map using the FSE approach. Compared with the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report) and AR5 (Fifth Assessment Report) methods, FSE has significant advantages in handling uncertainty, complexity, and the non-linear relationship between indices and risk grades. This study provides a novel quantitative method for flood risk assessment in metropolitan areas and practical implications for urban flood management.

Download Full-text

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

Water ◽

10.3390/w13040420 ◽

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.

Download Full-text

Flood Hazard Assessment and Mapping of Flood Inundation Area of the Awash River Basin in Ethiopia using GIS and HEC-GeoRAS/HEC-RAS Model

Journal of Civil & Environmental Engineering ◽

10.4172/2165-784x.1000179 ◽

2015 ◽

Vol 05 (04) ◽

Cited By ~ 6

Author(s):

Getahun YS Gebre SL

Keyword(s):

River Basin ◽

Hazard Assessment ◽

Flood Hazard ◽

Flood Inundation ◽

Inundation Area ◽

Awash River Basin ◽

Flood Hazard Assessment

Download Full-text

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

10.5194/nhess-2018-127 ◽

2018 ◽

Cited By ~ 3

Author(s):

Michalis I. Vousdoukas ◽

Dimitrios Bouziotas ◽

Alessio Giardino ◽

Laurens M. Bouwer ◽

Evangelos Voukouvalas ◽

...

Keyword(s):

Climate Change ◽

Risk Assessment ◽

Flood Risk ◽

Large Scale ◽

Epistemic Uncertainty ◽

Coastal Protection ◽

Flood Risk Assessment ◽

Coastal Flood ◽

Coastal Flood Risk ◽

The Impact

Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

Download Full-text