Flood Risk Analysis Research Articles

Emergency risk management for landslide dam breaks in 2018 on the Yangtze River, China

In October and November of 2018, the upper reach of the Yangtze River was blocked twice by landslide dams. A large landslide dam on a major river can impound a huge amount of water and trigger catastrophic flooding once it fails, imposing great risk to the downstream communities. Considering the chain of large dams and densely populated cities along the river, there is an urgent need to improve the system resilience of the Yangtze River to the landslide dam break hazard. This study presents a basin-scale emergency risk management framework based on an overtopping-erosion based dam failure model and a 1-D flood routing analysis model. Basin-wide inundation and detailed flood risk analyses are carried out considering engineering risk mitigation measures, which will facilitate the decision-making on future emergency risk mitigation plans. The proposed framework is applied to the landslide dam on the Yangtze River in November 2018. Results show that excavating a 15 m-depth diversion channel could effectively mitigate the flood risk of downstream areas. Further mitigation measures, including evacuation, removal of obstacles in the river, and preparation of certain intercept capacity in downstream reservoirs, are suggested based on the hazard chain risk analysis. The mitigation results in the case prove the effectiveness of the proposed framework. The incorporation of open-access global databases enables the application of the framework to any large river basin worldwide.

Can 7000 Years of flood history inform actual flood risk management? A case study on Lake Mondsee, Austria

Flood risk models typically rely on discharge records of time series no longer than a few hundred years, which leads to high uncertainty in the estimates for major flood events. In this paper, we investigate the capability of geological flood records retrieved from lake sediment cores to prolong available data sets, lower the uncertainty of flood risk analysis, and detect changes in flood patterns by releasing the common assumption of stationarity. Paleoflood records of Lake Mondsee, Austria, covering 7000 years are linked to flood damage data of the considered catchment area to calculate (1) the average annual damage, i.e. the fair premium and (2) the damage at 99.5% Value at Risk, i.e. the Solvency II capital requirement. To illustrate our results, the performance of a hypothetical catastrophe fund for these 7000 years is studied at current vulnerability levels. Our findings show that high resolution paleoflood records with robust chronologies and flood information have significant impacts on flood model outcomes for disaster risk management and that damage potentials derived merely from recent damage data may overestimate actual risks.

Bridge-specific flood risk assessment of transport networks using GIS and remotely sensed data

A novel framework for the expedient assessment of flood risk to transportation networks focused on the response of the most critical and vulnerable infrastructure assets, the bridges, is developed, validated and applied. Building upon the recent French guidelines on scour risk (CEREMA, 2019), this paper delivers a thorough methodology, that incorporates three key, risk parameters: (i) the hydrodynamic loading, a hazard component of equal significance to scour, for the assessment of hazard; (ii) the correlation of select scour indicators with a new index relating to flow velocity, a primary measure of the adverse impacts of flow–structure interaction, enabling a more accurate and automated, assessment of bridge susceptibility to scour; (iii) the use of a new, comprehensive indicator, namely the Indicator of Flood Hazard Intensity (IFHI) which incorporates, in a simple yet efficient way, the key parameters controlling the severity of flood impact on bridges, namely flow velocity, floodwater height, flow obstruction, and sediment type. The framework is implemented for the analysis of flood risk in a case study area, considering an inventory of 117 bridges of diverse construction characteristics, which were affected by a major flood that impacted Greece in September 2020. The reliability of the method is validated against an extensive record of inspected and documented bridge damages. Regional scale analysis is facilitated by the adoption of the Multi-Criteria Decision-Making method for flood hazard indexing, considering geomorphological, meteorological, hydrological, and land use/cover data, based on the processing of remotely sensed imagery and openly available geospatial datasets in GIS.

Analyzing flash flood risk in a section of ntawogba creek, Port Harcourt city, Rivers State

Flood is a natural disaster and occurred in different forms. It is also a factor of climate change. Flash flood is a type of flood that occurs within few hours of intensive precipitation. It poses serious threat to urban areas, particularly in less developed countries. Geospatial technology has been very useful in mapping spatial extent and quantified damages associated with flash flood events. Proximity analysis and AHP has been widely utilized in modeling flash flood vulnerable zones. Little was known about MCA ranking method which is considered appropriate for few parameters in making complex decisions. This study utilized MCA ranking method to analyzed flash flood risk within Ntawogba Creek, Port Harcourt, Rivers State. Rainfall, slope model, impervious surface and distance to river were used in the decision making. The datasets were processed into common spatial referenced system. Each criterion was scaled from 5 to 1, with 5 being very high risk and 1 very low risk area. Weights were assigned to the criteria based on the importance, with higher weight to criterion that is more important in the decision making process. The weights are; distance to water channel 48, impervious surface 25, slope 22 and rainfall 5. The results obtained showed area of 93.0ha as very high flash flood risk representing 6% of the area. This zone was located along Ntawogba Creek and on major roads. Total area of high risk zone was 864.1ha representing 56%, moderate risk and low risk zone was 452.2ha and 134.7ha with 29.3 5 and 8.7% respectively. For further study, drainage density and soil infiltration should be included in the flash flood risk analysis.

Assessment of the Relationship between Land Use and Flood Risk Based on a Coupled Hydrological–Hydraulic Model: A Case Study of Zhaojue River Basin in Southwestern China

As an ecological consequence of intensified anthropogenic activities, more frequent extreme rainfalls have resulted in significant increases in water levels and discharge in southwestern China. This phenomenon presents a significant challenge in flood risk and ecological management. Land use is one of the major factors significantly affecting the flooding process, and it is inextricably tied to the ecological risk of floods. Hence, flood risk estimates based on land use are essential for flood control and land use planning. In this study, a coupled hydrologic–hydraulic model was developed to analyze the relationship between flood ecological risk and land use in order to provide new insights into current flood risk management practices. Ten real flood events (of different magnitudes) in the Zhaojue river basin (650 km2) were chosen to evaluate the credibility and performance of the coupled model’s application. Promising results were obtained, with sufficient reliability for flood risk assessment purposes. The results of our flood risk analysis also indicated that the model effectively reproduced overland flow and competently accounted for flood evolution. This work is significant in the understanding of the mechanism of the flood process and its relationship with land use, and it can be used in decision support for the prevention and mitigation of flood disasters and for land use planning.

Conceptual and Analytical Framework as Flood Risk Mapping Subsidy

There are still gaps in defining values and category classifications of exposed items in quantitative damage analysis. This paper proposes a framework that refines the development of flood risk analysis at a local scale. This study first performs a quantitative risk analysis, based mainly on secondary data; it then attempts to communicate the results graphically, aiming to reduce the financial and human resources required. We propose an easily standardized database in a GIS environment, analyzing the influence of a reservoir for flood control and the construction of replicable local-scale risk curves. Hydrological (HEC-HMS) and 2D hydrodynamic (HEC-RAS) models were used to simulate hydrographs considering different return periods. For damage estimation, the processing included vectorization of lots, building use definition with Google Street View, classification of standard designs, and a field survey to validate those classes. In monetary value, this study calculated the effect of the construction of a reservoir for damage reduction, showing the potential to determine the effectiveness of measures adopted to mitigate flood impacts. In addition, for each simulated return period, exposure, hazard, and damage maps can be established, making it possible to perform a complete risk analysis.

Flood risk analysis of reservoirs based on full-series ARIMA model under climate change

• A novel full-series ARIMA stochastic model has been built. • This model can reflect the statistical characteristics of past and future floods. • The BMA method was utilized to analyze the uncertainty of flood frequency curves. • More comprehensive and reliable flood risks considering the weight of each GCM have been obtained. To assess the flood risks of reservoirs in a changing environment, this study considers the uncertainty of future floods and argues that the future flood projected by Global Climate Models (GCMs) is only one of the possibilities. This possibility contains some main statistical characteristics of future floods. The autoregressive integrated moving average (ARIMA) model was used to extract such statistical characteristics of the future flood series. Moreover, the initial values of the model were assumed to obey the probability distribution derived from historical floods. Hence, a novel full-series ARIMA stochastic model which can simultaneously reflect the statistical characteristics of past and future floods has been built to simulate the possible future extreme floods. Synthetic flood series under different future climate scenarios were randomly generated by the proposed model. Then the flood risks exceeding the design flood and check flood can be obtained. The Bayesian model averaging (BMA) method was used to weight the flood risks projected by each GCM to better incorporate the uncertainty of GCMs. The Yangfanggou Reservoir in Yalong River basin of China was selected as a case study. The future flood risks under three Representative Concentration Pathways (RCPs) were assessed. The results highlight that future flood risks have an increasing trend. Under future RCP2.6, RCP4.5 and RCP8.5 scenarios, the risk rates of exceeding design flood are in the range of 0.63%–0.74%, 1.31%–4.58% and 2.63%–5.23%, respectively. The risk rates of exceeding check flood are in the range of 0.20%–0.25%, 0.41%–2.14% and 0.97%–2.48%, respectively. This study provides a comprehensive evaluation of flood risk and could be useful when planning to fortify existing structures and update design standards.

Flood risk assessment and quantification at the community and property level in the State of Iowa

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

Hazard Flood Mapping and Monitory in Parts of the Niger Delta Region Using Sentinel 1 Synthetic Aperture Radar

In this study, the RGB band and threshold techniques were used to distinguish between the flooded area and permanent water bodies with the use of Sentinel 1 images to map and monitor flood hazards in Yenagoa, Bayelsa State. The acquired images were before the flood events in January 2019 and during the events in October and November 2019 with the aid of Snap 7.0 and ArcGIS software. The preprocessing of Sentinel-1 images and the mapping procedure have been described in detail, and the results have been evaluated. The results show that the Sentinel 1 sensor can rapidly provide quality data in mapping floods. The applied techniques, RGB and Threshold, show a clear disparity between permanent water bodies and floods by applying contact stretch to histograms. Zones with low backscatter signify flooded areas in red, with high radar response signifying land in the archive indicating surfaces. Areas with black indicate permanent waterbodies, while areas with white indicate built up areas. The estimated significant difference in mean water surface for January and October 2019 is -0.23 dB, while for January and November 2019 it is-0.36 decibels (dB). The difference between October and November 2019 is -0.12 decibels (dB) for the estimated mean water surface in the study area. Therefore, emphasizing remote sensing and GIS as essential tools for flood mapping, risk analysis, and better flood management is therefore essential.

Hypothetical failure of the Khassa Chai dam and flood risk analysis for Kirkuk, Iraq

Many of Iraqi's high-hazard dams lack an Emergency Action Plan, which should include a flood inundation map to show which downstream areas would be flooded if the dams were to fail. This article presents the results of the simulation of a hypothetical 2D dam break for the 58 m high Khassa Chai dam in Kirkuk, Iraq, using HEC-RAS 2D 5.0.7 software. The Khassa Chai dam is situated 7.4 km north of Kirkuk. The simulations revealed that the dam-break flood will affect eight major bridges and the majority of Kirkuk city's metropolitan neighborhoods. Within an hour, the floodwaters will reach the city's center. The flood hazard map revealed that if the Khassa Chai dam fails, many people, vehicles, and structures will be at danger. The findings of this paper can be used to identify evacuation routes and refuge sites as well as build suitable warning systems in order to limit the risk for fatalities if the Khassa Chai dam fails. Moreover, as the effect of modeling bridges downstream of failed dams has not been explored yet, to the knowledge of the authors, eight bridges have been modeled. It was concluded that ignoring bridges in such a large dam break model will not affect the results significantly, which saves the time of data collection and model development.

Commercial Real-Estate at Risk: An Examination of Commercial Building and Economic Impacts in the United States Using a High-Precision Flood Risk Assessment Tool

Environmental changes are predicted to exacerbate changes in flood events, resulting in consequences for exposed systems. While the availability and quality of flood risk analyses are generally increasing, very little attention has been paid to flood impacts related to the commercial market. This is notable given that the commercial market is often made up of the most valuable physical structures in communities, employs much of the local labor force, and generally plays a key role in the sustainability of economies. This study provides the first national spatial model of flood risk for commercial and multi-unit residential buildings at a property level resolution within the United States. This is achieved through the use of high-resolution inputs (hazard and property data), flood hazard information for the four major flood types, multi-return period hazard information, component-based depth-damage functions, GDP and economic multipliers information, and future facing projections. This study estimates that over the next 30 years, the absolute count of commercial and multi-unit buildings with risk will increase 8%, structural damage costs will increase 25.4%, downtime days will increase 29.1%, and economic impacts will increase 26.5%. Additionally, these impacts are concentrated in certain spatial locations. A high resolution model capturing flood risk as related to these commercial buildings is important for a comprehensive understanding of overall flood risk within the United States.Classification CodesJEL C30, E00, G17, M20, R10, R30

Flood risk analysis based on nested copula structure in Armand Basin, Iran

Flood risk analysis based on nested copula structure in Armand Basin, Iran

Expert judgment-based reliability analysis of the Dutch flood defense system

The Wettelijk Beoordelingsinstrumentarium (WBI) is the legal set of instruments for flood risk analysis in the Netherlands. Often, engineers have the impression that some failure probabilities of flood defenses resulting from these instruments are overestimated. In an effort to better estimate the failure probabilities of dikes along the Dutch river Rhine, this study sets out to assess them with experts and compare them to model results. We used Cooke’s method for combining experts’ estimates in a structured way and follow two approaches to estimate a system failure probability. In the first approach, experts estimate discharges that lead to at least one dike failure. This gives plausible results; failure probabilities between 1/30 and 1/17.000 in a year. The second approach is based on adjusting existing model-based assessment results, by estimating the model-bias and incorporating additional dependencies. This mostly leads to large, implausible, failure probabilities: Experts tend to give more conservative answers as they are asked for detailed estimates without clear reference values. This results in large uncertainty and consequently (too) high failure probabilities. Our research shows that when applied in a clear frame of reference, structured expert judgments can be successfully used for estimating the reliability of Dutch flood defenses.

Flood risk analysis using gis-based analytical hierarchy process: a case study of Bitlis Province

Floods are the most common natural disasters on earth. Population growth with global warming and climate changes increases the impact of floods on people every year. Combating natural disasters such as floods is possible with effective disaster management. An effective disaster management can only be possible with a comprehensive risk analysis. Flood risks depend on many factors such as precipitation, flow, earth slope, soil structure, and population density. A holistic flood risk analysis considering all these factors will provide a more effective disaster management. This study focuses on an assessment of flood hazard analysis in Bitlis province of Turkey using analytical hierarchy method which is a multi-parameter modeling technique. Flood hazard zones were mapped according to the weight of the selected factor by using geographic information system. It is concluded that while especially the south-western regions are exposed to high flood risk due to high stream density and precipitation, the high slope and rugged nature of this region restrict the risk mainly to the vicinity of low elevation streams and high population regions.

Identification and quantitative analysis of flash flood risks for small catchments in China: a new operational modelling approach

Identification and quantitative analysis of flash flood risks for small catchments in China: a new operational modelling approach

A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar

In recent decades, substantial efforts have been devoted in flood monitoring, prediction, and risk analysis for aiding flood event preparedness plans and mitigation measures. Introducing an initial framework of spatially probabilistic analysis of flood research, this study highlights an integrated statistical copula and satellite data-based approach to modelling the complex dependence structures between flood event characteristics, i.e., duration (D), volume (V) and peak (Q). The study uses Global daily satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) (spatial resolution of ∼5 km) during 1981–2019 to derive a Standardized Antecedence Precipitation Index (SAPI) and its characteristics through a time-dependent reduction function for Myanmar. An advanced vine copula model was applied to model joint distributions between flood characteristics for each grid cell. The southwest (Rakhine, Bago, Yangon, and Ayeyarwady) and south (Kayin, Mon, and Tanintharyi) regions are found to be at high risk, with a probability of up to 40% of flood occurrence in August and September in the south (Kayin, Mon, and Tanintharyi) and southwest regions (Rakhine, Bago, Yangon, and Ayeyarwady). The results indicate a strong correlation among flood characteristics; however, their mean and standard deviation are spatially different. The findings reveal significant differences in the spatial patterns of the joint exceedance probability of flood event characteristics in different combined scenarios. The probability that duration, volume, and peak concurrently exceed 50th-quantile (median) values are about 60–70% in the regions along the administrative borders of Chin, Sagaing, Mandalay, Shan, Nay Pyi Taw, and Keyan. In the worst case and highest risk areas, the probability that duration, volume, and peak exceed the extreme values, i.e., the 90th-quantile, about 10–15% in the southwest of Sagaing, southeast of Chin, Nay Pyi Taw, Mon and areas around these states and up to 30% in the southeast of Dekkhinathiri township (Nay Pyi Taw). The proposed approach could improve the evaluation of exceedance probabilities used for flood early warning and risk assessment and management. The proposed framework is also applicable at larger scales (e.g., regions, continents and globally) and in different hydrological design events and for risk assessments (e.g., insurance).

Assessment of Proglacial Lakes in Sikkim Himalaya, India for Glacial Lake Outburst Flood (GLOF) Risk Analysis using HEC-RAS and Geospatial Techniques

Assessment of Proglacial Lakes in Sikkim Himalaya, India for Glacial Lake Outburst Flood (GLOF) Risk Analysis using HEC-RAS and Geospatial Techniques

Flood risk mapping and analysis: A case study of Andheri Khola catchment, Sindhuli district, Nepal

Nepal is one of the world's most vulnerable countries to a variety of risks, including severe floods. This could result in the loss of lives and property, the relocation of people, the damage of physical infrastructures, homes, and the disruption of people's socioeconomic functions and the country's economy in a variety of ways. River flooding is caused by heavy monsoon rainfall, weak geology, unplanned infrastructure construction along the embankments, and mining in upstream riverbeds. The Andheri Khola (river) is a tributary of the Sunkoshi River that frequently floods, affecting the inhabitants along the way. In Nepal, little effort has been made to comprehend the flood risk in tiny catchment regions such as Andheri Khola, despite the fact that this sort of small catchment is affecting Nepal's numerous new rising towns and urban areas in many ways. To analyse the one-dimensional flood plain, HEC-RAS, Ras Mapper, and ArcGIS were used. The WECS/DHM approach was used to estimate flood frequency in different return periods in order to determine the flood risk in the research area. The study finds that the floods of 2, 50, 100, and 1000 years return periods cover a maximum of 35, 41.9, 42.7, and 49.72 hectare area, respectively. The majority of the flooded sites had water depths of more than 3 meters. More than 70% of the sandy area in the study region is prone to flooding. Furthermore, the cultivated areas are located in a low to moderate risk area.

Enriching flood risk analyses with distributions of soil mechanical parameters through the statistical analysis of classification experiments

AbstractThe distributions of soil mechanical parameters required for a comprehensive flood risk assessment are often taken from the scarce literature available. This article therefore presents a method to indirectly obtain the distributions from the results of often conducted classification tests. Empirical correlation terms are used for the transformation of the classification data into stability‐relevant parameters, in particular the void ratio, the soil unit weight, the friction angle and the saturated permeability. The method is applied exemplarily to a data set collected throughout Germany in the immediate vicinity of water bodies and plausible distributions are obtained for 2/3 of the 13 soil classes considered. For the validation of the results, the extension of (inter)national databases by samples of the considered soil mechanical parameters is recommended due to the current poor validation basis.

Preparedness against floods in nearly pristine socio-hydrological systems

ABSTRACT The relations between preparedness and psycho-social attributes of people and communities exposed to river floods in a nearly pristine socio-hydrological system were investigated, applying a hydrological-hydraulic analysis of flood risk in combination with results from a survey, social cartography, semi-structured non-participant observation, and semi-structured interviews. Results show that preparedness in nearly pristine systems is noticeably different to that reported for altered systems. People adopt innovative and simple but efficient measures against floods, conditioned by (1) damage suffered during past floods, (2) perceived exposure to floods, and (3) the number of dependent people in the household. The studied system proved to be well adapted to floods but not resilient. Studying attributes that explain preparedness as part of flood risk management plans would contribute towards uncertainty reduction in risk calculations and increase the safety of goods and people from floods.