scholarly journals On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model

Water ◽  
2017 ◽  
Vol 9 (9) ◽  
pp. 688 ◽  
Author(s):  
Daniela Molinari ◽  
Anna Rita Scorzini
Keyword(s):  
Data Quality ◽  
Input Data ◽  
Flood Damage ◽  
Damage Estimation ◽  
Flood Damage Estimation

Sensitivity of flood damage estimation to spatial resolution

2015 ◽  
Vol 11 ◽  
pp. S370-S381 ◽  
Author(s):  
A.A. Komolafe ◽  
S. Herath ◽  
R. Avtar
Keyword(s):  
Spatial Resolution ◽  
Flood Damage ◽  
Damage Estimation ◽  
Flood Damage Estimation

scholarly journals Development of Flood Damage Estimation Model for Agriculture – Case Study in the Bago Floodplain, Myanmar

2020 ◽  
Vol 15 (3) ◽  
pp. 242-255
Author(s):  
Shelly Win ◽  
Win Win Zin ◽  
Akiyuki Kawasaki ◽  
◽  
Keyword(s):  
Questionnaire Survey ◽  
Flood Damage ◽  
Damage Function ◽  
Economic Damage ◽  
Damage Estimation ◽  
Estimation Model ◽  
Damage Cost ◽  
Extreme Flood ◽  
Spatially Distributed ◽  
Flood Damage Estimation

This paper introduces an integrated model that combines the Rainfall Runoff Inundation (RRI) and spatially distributed flood damage estimation models. There are three steps for fulfilling this purpose. The first step is the accomplishment of RRI model for the floodplain region. The second step is a questionnaire survey to analyze the economic damage to affected population and properties caused by the past flooding events; this step aims to estimate the different levels of agricultural damage cost. Finally, the economic flood damage estimation model was developed for the agricultural areas by using the stage-damage function models which were established by the multiple regression analysis of questionnaire survey data. The model results were expressed through spatially distributed flood damage maps for extreme flood events, such as those in 2014, 2015, and 2018. The results were validated by collecting damage cost data from the Department of Agricultural Lands Management and Statistics (DALMS). The final findings included comparative scenarios for reducing damage cost in the most effective and realistic way. The output product was the agricultural damage estimation model. For further research, the model was recommended for application in other study areas with different flood scales.

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