TY  - JOUR
A1  - Sairam, Nivedita
A1  - Schroeter, Kai
A1  - Rözer, Viktor
A1  - Merz, Bruno
A1  - Kreibich, Heidi
T1  - Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes
JF  - Water resources research
N2  - Flood damage processes are complex and vary between events and regions. State-of-the-art flood loss models are often developed on the basis of empirical damage data from specific case studies and do not perform well when spatially and temporally transferred. This is due to the fact that such localized models often cover only a small set of possible damage processes from one event and a region. On the other hand, a single generalized model covering multiple events and different regions ignores the variability in damage processes across regions and events due to variables that are not explicitly accounted for individual households. We implement a hierarchical Bayesian approach to parameterize widely used depth-damage functions resulting in a hierarchical (multilevel) Bayesian model (HBM) for flood loss estimation that accounts for spatiotemporal heterogeneity in damage processes. We test and prove the hypothesis that, in transfer scenarios, HBMs are superior compared to generalized and localized regression models. In order to improve loss predictions for regions and events for which no empirical damage data are available, we use variables pertaining to specific region- and event-characteristics representing commonly available expert knowledge as group-level predictors within the HBM.
KW  - flood risk
KW  - flood loss model transfer
KW  - multilevel probabilistic flood loss model
Y1  - 2019
U6  - https://doi.org/10.1029/2019WR025068
SN  - 0043-1397
SN  - 1944-7973
VL  - 55
IS  - 10
SP  - 8223
EP  - 8237
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - Hudson, Paul
A1  - Pham, My
A1  - Bubeck, Philip
T1  - An evaluation and monetary assessment of the impact of flooding on subjective well-being across genders in Vietnam
JF  - Climate & development
N2  - The intangible impacts of floods on welfare are not well investigated, even though they are important aspects of welfare. Moreover, flooding has gender based impacts on welfare. These differing impacts create a gender based flood risk resilience gap. We study the intangible impacts of flood risk on the subjective well-being of residents in central Vietnam. The measurement of intangible impacts through subjective well-being is a growing field within flood risk research. We find an initial drop in welfare through subjective well-being across genders when a flood is experienced. Male respondents tended to recover their welfare losses by around 80% within 5 years while female respondents were associated with a welfare recovery of around 70%. A monetization of the impacts floods have on an individual’s subjective well-being shows that for the average female respondent, between 41% to 86% of annual income would be required to compensate subjective well-being losses after 5 years of experiencing a flood. The corresponding value for males is 30% to 57% of annual income. This shows that the intangible impacts of flood risk are important (across genders) and need to be integrated into flood (or climate) risk assessments to develop more socially appropriate risk management strategies.
KW  - Subjective well-being
KW  - flood risk
KW  - welfare
KW  - gender
KW  - resilience
KW  - intangible impacts
Y1  - 2019
U6  - https://doi.org/10.1080/17565529.2019.1579698
SN  - 1756-5529
SN  - 1756-5537
VL  - 11
IS  - 7
SP  - 623
EP  - 637
PB  - Routledge, Taylor & Francis Group
CY  - Abingdon
ER  -