scholarly journals Flood Risk Assessment and Quantification at the Community and Property Level in the State of Iowa

2021 ◽  
Author(s):  
Enes Yildirim ◽  
Ibrahim Demir
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Flood Risk Assessment ◽  
Study Region ◽  
Study Results ◽  
Flood Maps

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.

The Value of Drones for Bespoke Local Flood Risk Assessment in the Licungo Basin

2020 ◽  
Author(s):  
Michael Andrew Manalili ◽  
Guy Schumann ◽  
Lara Prades ◽  
Sophia Rosa ◽  
Domingos Reane ◽  
...  
Keyword(s):  
Risk Assessment ◽  
At Risk ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Local Level ◽  
Local Scale ◽  
High Impact ◽  
Flood Risk Assessment ◽  
Response Planning

<p>Floods and their impacts are highly local in nature and vulnerable population and exposed assets are most at risk in coastal monsoonal regions. This is aggravated if the region is also exposed to tropical cyclones, such as Mozambique and the Licungo basin along the eastern coastline of the country.</p><p>In order to be better prepared against future high-impact flood events, Mozambique’s National Institute for Disaster Management (INGC) has mapped the watershed of the country’s central Licungo River with drones to reduce flood risks and improve emergency response planning. The mapping is intended to “minimize risks” and promote timely preparation of actions when cyclones and floods are expected in the area.</p><p>In the proposed project, the acquired drone terrain model and collected field data (water levels) will be used to drive a bespoke localized 2-D flood model to accurately reproduce flood hazard and risk in the central Licungo basin for the 2013 and 2015 flood disasters. In addition, high-resolution population and exposure layers have been used to define bespoke local flood risk maps.</p><p>Accurate flood risk assessment of past events at the local scale can better inform decision support systems and facilitate the decision-making process and preparedness for future high-impact events. Knowing who is at risk where and when is vital information that is missing in many vulnerable regions and is most of the time not available at the required local level.</p><p>Moreover, global or large-scale flood prediction models do not contain the necessary detail to infer meaningful flood risk at the local level and such models are known to be inaccurate, albeit they represent best efforts at the scales they are simulating. However, to what degree these models are wrong at the local scale of impact and what is needed to improve them is not known, largely because local flood data and bespoke predictions of flood risk are missing at the local scale for many vulnerable regions. The collected high-resolution data and the local flood risk assessment this project proposes would allow the validation of large-scale modeling efforts thereby advancing our understanding of model limitations and would create opportunities to improve them at large scales.</p>

scholarly journals Process-based flood risk assessment for Germany

2021 ◽  
Author(s):  
Nivedita Sairam ◽  
Fabio Brill ◽  
Tobias Sieg ◽  
Patric Kellermann ◽  
Kai Schröter ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Systems Approach ◽  
Economic Damage ◽  
Flood Risk Assessment ◽  
Continuous Simulation ◽  
Hazard Exposure ◽  
Risk Estimates

<p>Floods affect people worldwide and account for more than USD 100 billion losses on average every year. Hazard, Exposure and Vulnerability are the three components that influence flood risk. Flood Risk Management (FRM) decisions especially, with respect to new flood defense schemes and resilience initiatives are generally taken based on the assessment of impacts for hazard scenarios. Current large-scale studies are comprehensive in terms of sectors covered in impact assessment. However, these studies often deploy generalized data and methods on the model components resulting in coarse risk estimates with low spatial resolution.</p><p>In this study, we use process-based models with 100m resolution on the national scale within a systems approach to develop and simulate a 5000 year flood event catalogue for Germany. The events are then analyzed per economic sector, including residential, commercial and agriculture sectors. The risk chain includes continuous simulation of high-resolution hazard maps, obtained from coupled hydrology and hydraulic models; NUTS3-level exposure asset values further disaggregated to ATKIS land-use data and calibrated object-level vulnerability models that provide high-resolution quantification of economic damage. Spatial dependence of flood events is addressed by the continuous simulation approach. For each model component in the risk assessment (hazard, exposure and vulnerability), uncertainty in data and methods are integrated into the risk predictions. Based on these simulations, we present a sector-wise flood risk assessment for Germany along with the reliability of the risk estimates. This process-based, systemic flood risk assessment is valuable for policy making, adaptation planning and estimating insurance premiums.</p>

scholarly journals Large-scale flood risk assessment using a coupled model chain

2016 ◽  
Vol 7 ◽  
pp. 11005 ◽  
Author(s):  
Bruno Merz ◽  
Heiko Apel ◽  
Nguyen Viet Dung ◽  
Daniela Falter ◽  
Yeshewatesfa Hundecha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Coupled Model ◽  
Flood Risk Assessment ◽  
Model Chain

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

2018 ◽  
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.

scholarly journals Flood Risk Assessment for the Long-Term Strategic Planning Considering the Placement of Industrial Parks in Slovakia

2020 ◽  
Vol 12 (10) ◽  
pp. 4144 ◽  
Author(s):  
Henrich Grežo ◽  
Matej Močko ◽  
Martin Izsóff ◽  
Gréta Vrbičanová ◽  
František Petrovič ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Flow ◽  
Flow Simulation ◽  
Current Data ◽  
Economic Losses ◽  
Historical Maps ◽  
Flood Risk Assessment ◽  
Industrial Parks ◽  
Flood Maps

The intention of the article is to demonstrate how data from historical maps might be applied in the process of flood risk assessment in peri-urban zones located in floodplains and be complementary datasets to the national flood maps. The research took place in two industrial parks near the rivers Žitava and Nitra in the town of Vráble (the oldest industrial park in Slovakia) and the city of Nitra (one of the largest industrial parks in Slovakia, which is still under construction concerning the Jaguar Land Rover facility). The historical maps from the latter half of the 18th and 19th centuries and from the 1950s of the 20th century, as well as the field data on floods gained with the GNSSS receiver in 2010 and the Q100 flood line of the national flood maps (2017), were superposed in geographic information systems. The flood map consists of water flow simulation by a mathematical hydrodynamic model which is valid only for the current watercourse. The comparison of historical datasets with current data indicated various transformations and shifts of the riverbanks over the last 250 years. The results proved that the industrial parks were built up on traditionally and extensively used meadows and pastures through which branched rivers flowed in the past. Recent industrial constructions intensified the use of both territories and led to the modifications of riverbeds and shortening of the watercourse length. Consequently, the river flow energy increased, and floods occurred during torrential events in 2010. If historical maps were respected in the creation of the flood maps, the planned construction of industrial parks in floodplains could be limited or forbidden in the spatial planning documentation. This study confirmed that the flood modelling using the Q100 flood lines does not provide sufficient arguments for investment development groups, and flood maps might be supplied with the data derived from historical maps. The proposed methodology represents a simple, low cost, and effective way of identifying possible flood-prone areas and preventing economic losses and other damages.

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

2016 ◽  
Vol 11 (6) ◽  
pp. 1128-1136 ◽  
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.

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

2018 ◽  
Vol 18 (8) ◽  
pp. 2127-2142 ◽  
Author(s):  
Michalis I. Vousdoukas ◽  
Dimitrios Bouziotas ◽  
Alessio Giardino ◽  
Laurens M. Bouwer ◽  
Lorenzo Mentaschi ◽  
...  
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 policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into 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) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth–damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and 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 datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

scholarly journals River-dike-floodplain system Interactions and temporal dynamics for large-scale flood risk assessment

2021 ◽  
Author(s):  
Mostafa Farrag ◽  
Sergiy Vorogushyn ◽  
Dung Viet Nguyen ◽  
Karin de Bruijn ◽  
Bruno Merz
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Flood Risk Assessment ◽  
River Dike
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