Smart resilience is the beneficial result of the collision course of the fields of data science and urban resilience to flooding. The objective of this study is to propose and demonstrate a smart flood resilience framework that leverages heterogeneous community-scale big data and infrastructure sensor data to enhance predictive risk monitoring and situational awareness. The smart flood resilience framework focuses on four core capabilities that could be augmented by the use of heterogeneous community-scale big data and analytics techniques: (1) predictive flood risk mapping; (2) automated rapid impact assessment; (3) predictive infrastructure failure prediction and monitoring; and (4) smart situational awareness capabilities. We demonstrate the components of these core capabilities of the smart flood resilience framework in the context of the 2017 Hurricane Harvey in Harris County, Texas. First, we present the use of flood sensors for the prediction of floodwater overflow in channel networks and inundation of co-located road networks. Second, we discuss the use of social media and machine learning techniques for assessing the impacts of floods on communities and sensing emotion signals to examine societal impacts. Third, we describe the use of high-resolution traffic data in network-theoretic models for nowcasting of flood propagation on road networksmore »
This paper develops the concept of flood problem framing to understand decision-makers’ priorities in flood risk management in the Los Angeles Metropolitan Region in California (LA Metro). Problem frames shape an individual’s preferences for particular management strategies and their future behaviors. While flooding is a complex, multifaceted problem, with multiple causes and multiple impacts, a decision-maker is most likely to manage only those dimensions of flooding about which they are aware or concerned. To evaluate flood decision-makers’ primary concerns related to flood exposure, vulnerability, and management in the LA Metro, we draw on focus groups with flood control districts, city planners, nonprofit organizations, and other flood-related decision-makers. We identify numerous concerns, including concerns about specific types of floods (e.g., fluvial vs pluvial) and impacts to diverse infrastructure and communities. Our analyses demonstrate that flood concerns aggregate into three problem frames: one concerned with large fluvial floods exacerbated by climate change and their housing, economic, and infrastructure impacts; one concerned with pluvial nuisance flooding, pollution, and historic underinvestment in communities; and one concerned with coastal and fluvial flooding’s ecosystem impacts. While each individual typically articulated concerns that overlapped with only one problem frame, each problem frame was discussed by numerous more »
This paper investigates the primary concerns that planners, flood managers, and other decision-makers have about flooding in Southern California. This is important because the way that decision-makers understand flooding shapes the way that they will plan for and respond to flood events. We find that some decision-makers are primarily concerned with large floods affecting large swaths of infrastructure and housing; others are concerned with frequent, small floods that mobilize pollution in low-income areas; and others are concerned with protecting coastal ecosystems during sea level rise. Our results also highlight key priorities for research and practice, including the need for flexible and accessible flood data and education about how to evacuate.
- Award ID(s):
- 1940171
- Publication Date:
- NSF-PAR ID:
- 10390620
- Journal Name:
- Weather, Climate, and Society
- Volume:
- 15
- Issue:
- 1
- Page Range or eLocation-ID:
- p. 45-58
- ISSN:
- 1948-8327
- Publisher:
- American Meteorological Society
- Sponsoring Org:
- National Science Foundation
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