Event-based approach for probabilistic flood risk assessment

2013 ◽  
Vol 12 (4) ◽  
pp. 377-389 ◽  
Author(s):  
Marco A. Torres ◽  
Miguel A. Jaimes ◽  
Eduardo Reinoso ◽  
Mario Ordaz
2019 ◽  
Vol 19 (5) ◽  
pp. 1041-1053 ◽  
Author(s):  
Dirk Diederen ◽  
Ye Liu ◽  
Ben Gouldby ◽  
Ferdinand Diermanse ◽  
Sergiy Vorogushyn

Abstract. We present a new method to generate spatially coherent river discharge peaks over multiple river basins, which can be used for continental event-based probabilistic flood risk assessment. We first extract extreme events from river discharge time series data over a large set of locations by applying new peak identification and peak-matching methods. Then we describe these events using the discharge peak at each location while accounting for the fact that the events do not affect all locations. Lastly we fit the state-of-the-art multivariate extreme value distribution to the discharge peaks and generate from the fitted model a large catalogue of spatially coherent synthetic event descriptors. We demonstrate the capability of this approach in capturing the statistical dependence over all considered locations. We also discuss the limitations of this approach and investigate the sensitivity of the outcome to various model parameters.


10.1596/28574 ◽  
2017 ◽  
Author(s):  
Satya Priya ◽  
William Young ◽  
Thomas Hopson ◽  
Ankit Avasthi

MethodsX ◽  
2021 ◽  
pp. 101463
Author(s):  
Maurizio Tiepolo ◽  
Elena Belcore ◽  
Sarah Braccio ◽  
Souradji Issa ◽  
Giovanni Massazza ◽  
...  

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 104 ◽  
Author(s):  
Qiang Liu ◽  
Hongmao Yang ◽  
Min Liu ◽  
Rui Sun ◽  
Junhai Zhang

Cities located in the transitional zone between Taihang Mountains and North China plain run high flood risk in recent years, especially urban waterlogging risk. In this paper, we take Shijiazhuang, which is located in this transitional zone, as the study area and proposed a new flood risk assessment model for this specific geographical environment. Flood risk assessment indicator factors are established by using the digital elevation model (DEM), along with land cover, economic, population, and precipitation data. A min-max normalization method is used to normalize the indices. An analytic hierarchy process (AHP) method is used to determine the weight of each normalized index and the geographic information system (GIS) spatial analysis tool is adopted for calculating the risk map of flood disaster in Shijiazhuang. This risk map is consistent with the reports released by Hebei Provincial Water Conservancy Bureau and can provide reference for flood risk management.


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