Uncertainty in floodplain delineation: expression of flood hazard and risk in a Gulf Coast watershed

2012 ◽  
Vol 27 (19) ◽  
pp. 2774-2784 ◽  
Author(s):  
Jason Christian ◽  
Leonardo Duenas-Osorio ◽  
Aarin Teague ◽  
Zheng Fang ◽  
Philip Bedient
Keyword(s):  
Gulf Coast ◽  
Flood Hazard ◽  
Hazard And Risk ◽  
Floodplain Delineation

Pairwise Elicitation for a Decision Support Framework to Develop a Flood Risk Response Plan

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
MiguelAndres Guerra ◽  
Yekenalem Abebe
Keyword(s):  
Decision Making ◽  
Flood Risk ◽  
Flood Hazard ◽  
Addis Ababa ◽  
Pairwise Comparison ◽  
Multicriteria Decision Making ◽  
Risk Response ◽  
Hazard And Risk ◽  
Response Plan ◽  
Decision Making Framework

There are several ways of quantifying flood hazard. When the scale of the analysis is large, flood hazard simulation for an entire city becomes costly and complicated. The first part of this paper proposes utilizing experience and knowledge of local experts about flood characteristics in the area in order to come up with a first-level flood hazard and risk zoning maps, by implementing overlay operations in Arc GIS. In this step, the authors use the concept of pairwise comparison to eliminate the need for carrying out a complicated simulation to quantify flood hazard and risk. The process begins with identifying the main factors that contribute to flooding in a particular area. Pairwise comparison was used to elicit knowledge from local experts and assigned weights for each factor to reflect their relative importance toward flood hazard and risk. In the second part of this paper, the authors present a decision-making framework to support a flood risk response plan. Once the highest risk zones have been identified, a city can develop a risk response plan, for which this paper presents a decision-making framework to select an effective set of alternatives. The framework integrates tools from multicriteria decision-making, charrette design process to guide the pairwise elicitation, and a cost-effective analysis to include the limited budget constraint for any city. The theoretical framework uses the city of Addis Ababa for the first part of the paper. For the second part, the paper utilizes a hypothetical case of Addis Ababa and a mock city infrastructure department to illustrate the implementation of the framework.

scholarly journals Simulation of flood hazard and risk in the Danube basin with the Future Danube Model

2018 ◽  
Vol 12 ◽  
pp. 14-26 ◽  
Author(s):  
Fred F. Hattermann ◽  
Michel Wortmann ◽  
Stefan Liersch ◽  
Ralf Toumi ◽  
Nathan Sparks ◽  
...  
Keyword(s):  
Flood Hazard ◽  
Danube Basin ◽  
The Future ◽  
Hazard And Risk

Improving the robustness of flood catastrophe models in insurance through academia-industry collaboration

2020 ◽  
Author(s):  
Valentina Noacco ◽  
Francesca Pianosi ◽  
Thorsten Wagener ◽  
Kirsty Styles ◽  
Stephen Hutchings
Keyword(s):  
Sensitivity Analysis ◽  
Flood Hazard ◽  
Insurance Industry ◽  
Insurance Companies ◽  
Exceedance Probability ◽  
Structural Uncertainty ◽  
Probability Curve ◽  
Data Limitations ◽  
Hazard And Risk ◽  
University Of Bristol

<p>To quantify risk from natural hazards and ensure a robust decision-making process in the insurance industry, uncertainties in the mathematical models that underpin decisions need to be efficiently and robustly captured. The complexity and sheer scale of the mathematical modelling often makes a comprehensive, transparent and easily communicable understanding of the uncertainties very difficult.  Models predicting flood hazard and risk have shown high levels of uncertainty in their predictions due to data limitations and model structural uncertainty. Moreover, uncertainties are estimated to increase with climate change, especially for higher warming levels.</p><p>Global Sensitivity Analysis (GSA) provides a structured approach to quantify and compare the relative importance of parameter, data and structural uncertainty. GSA has been implemented successfully in tools such as the Sensitivity Analysis For Everybody (SAFE) toolbox, which is currently used by more than 2000 researchers worldwide. However, tailored tools, workflows and case studies are needed to demonstrate GSA benefits to practitioners and accelerate its uptake by the insurance industry.</p><p>One such case study has been the collaboration between the University of Bristol and JBA Risk Management on JBA’s new Global Flood Model, whose technology and flexibility has allowed to test a catastrophe model in ways not possible in the past. JBA has gained great insight into the sensitivity of modelled losses to uncertainties in the model datasets and analysis options. This has helped to explore the key sensitivities of the results to the assumptions made, for example to visualise how the distribution of modelled losses varies by return period and explore which parameters have the biggest impact on loss for the part of the Exceedance-Probability curve of interest. This information is essential for insurance companies to form their view of risk and to empower model users to adequately communicate uncertainties to decision-makers.</p>

scholarly journals Quantification of Continuous Flood Hazard using Random Forrest Classification and Flood Insurance Claims at Large Spatial Scales: A Pilot Study in Southeast Texas

2020 ◽  
Author(s):  
William Mobley ◽  
Antonia Sebastian ◽  
Russell Blessing ◽  
Wesley E. Highfield ◽  
Laura Stearns ◽  
...  
Keyword(s):  
Pilot Study ◽  
Random Forest ◽  
Spatial Information ◽  
Gulf Coast ◽  
Flood Hazard ◽  
Spatial Scales ◽  
High Sensitivity ◽  
Machine Learning Techniques ◽  
Flood Insurance ◽  
Flood Hazards

Abstract. Pre-disaster planning and mitigation necessitates detailed spatial information about flood hazards and their associated risks. In the U.S., the FEMA Special Flood Hazard Area (SFHA) provides important information about areas subject to flooding during the 1 % riverine or coastal event. The binary nature of flood hazard maps obscures the distribution of property risk inside of the SFHA and the residual risk outside of the SFHA, which can undermine mitigation efforts. Machine-learning techniques provide an alternative approach to estimating flood hazards across large spatial scales at low computational expense. This study presents a pilot study for the Texas Gulf Coast Region using Random Forest Classification to predict flood probability across a 30,523 km2 area. Using a record of National Flood Insurance Program (NFIP) claims dating back to 1976 and high-resolution geospatial data, we generate a continuous flood hazard map for twelve USGS HUC-8 watersheds. Results indicate that the Random Forest model predicts flooding with a high sensitivity (AUC 0.895), especially compared to the existing FEMA regulatory floodplain. Our model identifies 649,000 structures with at least a 1 % annual chance of flooding, roughly three times more than are currently identified by FEMA as flood prone.

scholarly journals Index-based flood risk assessment for Metro Manila

2020 ◽  
Vol 20 (3) ◽  
pp. 851-859 ◽  
Author(s):  
C. J. Rubio ◽  
I. S. Yu ◽  
H. Y. Kim ◽  
S. M. Jeong
Keyword(s):  
Risk Assessment ◽  
Land Use Planning ◽  
Flood Risk ◽  
Flood Hazard ◽  
The Philippines ◽  
Flood Risk Assessment ◽  
Disaster Insurance ◽  
Metro Manila ◽  
Hazard And Risk ◽  
Populated Region

Abstract This study focuses on index-based flood risk assessment in Metro Manila, the capital region of the Philippines and most densely populated region in the country. Its objective is to properly address urban characteristics in flood risk assessment by introducing a specific urban-type set of physical, social, economic and ecological indicators. Analytical hierarchy process (AHP) was used to quantify the optimal selection weights for each of the selected 14 indicators. Five levels of flood risk will be presented in spatial maps using geographic information system (GIS) ranging from Very Low Risk to Very High Risk. Results of this study are expected to aid in understanding flood hazard and risk in Metro Manila. Moreover, the resulting flood risk information can be used as a decision tool in policy making, land-use planning, developing guidelines and countermeasures and flood disaster insurance.

An Assessment of Flood Hazard and Risk Zoning in the Lower Nam Phong River Basin, Thailand

2016 ◽  
Vol 7 (7) ◽  
pp. 1147
Author(s):  
Kittiwet Kuntiyawichai ◽  
Quan Van Dau ◽  
Winai Sri-Amporn ◽  
Fransiscus Xaverius Suryadi
Keyword(s):  
River Basin ◽  
Flood Hazard ◽  
Risk Zoning ◽  
Hazard And Risk

scholarly journals A review of the flood hazard and risk management in the South Asian Region, particularly Pakistan

2020 ◽  
Vol 10 ◽  
pp. e00651
Author(s):  
Syed Muzzamil Hussain Shah ◽  
Zahiraniza Mustaffa ◽  
Fang Yenn Teo ◽  
Mansoor Abdul Hamid Imam ◽  
Khamaruzaman Wan Yusof ◽  
...  
Keyword(s):  
Risk Management ◽  
South Asian ◽  
Flood Hazard ◽  
The South ◽  
Asian Region ◽  
Hazard And Risk ◽  
South Asian Region

scholarly journals The Spatial Dependence of Flood Hazard and Risk in the United States

2019 ◽  
Vol 55 (3) ◽  
pp. 1890-1911 ◽  
Author(s):  
Niall Quinn ◽  
Paul D. Bates ◽  
Jeff Neal ◽  
Andy Smith ◽  
Oliver Wing ◽  
...  
Keyword(s):  
United States ◽  
Spatial Dependence ◽  
Flood Hazard ◽  
The United States ◽  
Hazard And Risk

scholarly journals Flood hazard and risk modelling framework for ungauged streams and watersheds

2017 ◽  
Author(s):  
Γεώργιος Παπαϊωάννου
Keyword(s):  
Flood Hazard ◽  
Risk Modelling ◽  
Modelling Framework ◽  
Hazard And Risk

Στην παρούσα διδακτορική διατριβή παρουσιάζεται μια ολιστική προσέγγιση για την εκτίμηση και χαρτογράφηση των πλημμυρών σε λεκάνες απορροής και χειμάρρους με ελλιπή ή ανύπαρκτα μετεωρολογικά και υδρομετρικά δεδομένα. Η παρούσα έρευνα αποδεικνύει ότι η χρήση κλασσικών τεχνικών και μεθόδων για την διερεύνηση του φαινομένου της πλημμύρας μπορεί να συντελέσει στην δημιουργία ενός έγκυρου και αποτελεσματικού πλαισίου προσομοίωσης για την εκτίμηση πλημμυρικού κινδύνου και επικινδυνότητας σε χειμαρρικά υδατορρεύματα και υδρολογικές λεκάνες με ελλιπή δεδομένα. Τα τρία συστήματα που πλαισιώνουν το ενιαίο μεθοδολογικό πλαίσιο έχουν ως στόχο την 1) εκτίμηση και την χαρτογράφηση πιθανών περιοχών πλημμυρικής κατάκλισης, 2) εκτίμηση και ποσοτικοποίηση της ευαισθησίας και της αβεβαιότητας συγκεκριμένων παραμέτρων στην διαδικασία της μοντελοποίησης πλημμύρας. Επομένως, το προτεινόμενο μεθοδολογικό πλαίσιο ή ξεχωριστά τα επιμέρους συστήματα μπορούν να αποτελέσουν πολύτιμα εργαλεία για τους ιθύνοντες αποφάσεων με στόχο την παραγωγή έγκυρων και υψηλής ακρίβειας σχεδίων διαχείρισης πλημμυρικού κινδύνου και επικινδυνότητας σε λεκάνες απορροής και χειμάρρους με ελλιπή δεδομένα.

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