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Impacts of Human Behavioral Heterogeneity on the Benefits of Probabilistic Flood Warnings: An Agent‐Based Modeling Framework
Author(s) -
Du Erhu,
Rivera Samuel,
Cai Ximing,
Myers Laura,
Ernest Andrew,
Minsker Barbara
Publication year - 2017
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/1752-1688.12475
Subject(s) - flood myth , damages , flood warning , probabilistic logic , environmental science , environmental resource management , computer science , geography , archaeology , artificial intelligence , political science , law
Flood forecasts and warnings are intended to reduce flood‐related property damages and loss of human life. Considerable research has improved flood forecasting accuracy ( e.g., more accurate prediction of the occurrence of flood events) and lead time. However, the delivery of improved forecast information alone is not necessarily sufficient to reduce flood damage and loss of life, as people have varying responses and reactions to flood warnings. This study develops an agent‐based modeling framework that evaluates the impacts of heterogeneity in human behaviors ( i.e., variation in behaviors in response to flood warnings), as well as residential density, on the benefits of flood warnings. The framework is coupled with a traffic model to simulate evacuation processes within a road network under various flood warning scenarios. The results show the marginal benefit associated with providing better flood warnings is significantly constrained if people behave in a more risk‐tolerant manner, especially in high‐density residential areas. The results also show significant impacts of human behavioral heterogeneity on the benefits of flood warnings, and thus stress the importance of considering human behavioral heterogeneity in simulating flood warning‐response systems. Further study is suggested to more accurately model human responses and behavioral heterogeneity, as well as to include more attributes of residential areas to estimate and improve the benefits of flood warnings.