Big Data Approaches for coastal flood risk assessment and emergency response

James A Pollard,Tom Spencer,Simon Jude

doi:10.1002/wcc.543

James A Pollard, Tom Spencer + Show 1 more

Open Access

https://doi.org/10.1002/wcc.543

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Abstract

Big Data Approaches (BDAs) refers to the combined use of historic datasets, incoming data streams, and the array of related technologies designed to shed new light on societal and environmental complexities through novel organizational, storage, and analytical capabilities. Despite widespread recognition of the commercial benefits of BDAs, application in the environmental domain is less well articulated. This represents a missed opportunity given that the dimensions used to characterize BDAs (volume, variety, velocity, and veracity) appear apt in describing the intractable challenges posed by global climate change. This paper employs coastal flood risk management as an illustrative case study to explore the potential applications in the environmental domain. Trends in global change including accelerating sea level rise, concentration of people and assets in low‐lying areas and deterioration of protective coastal ecosystems are expected to manifest locally as increased future flood risk. Two branches of coastal flood risk management are considered. First, coastal flood risk assessment, focusing on better characterization of hazard sources, facilitative pathways, and vulnerable receptors. Second, flood emergency response procedures, focusing on forecasting of flooding events, dissemination of warnings, and response monitoring. Critical commentary regarding technical, contextual, institutional, and behavioral barriers to the implementation of BDAs is offered throughout including a discussion of two fundamental difficulties associated with applying BDAs to coastal flood risk management: the role of BDAs in the broader flood system and the skill requirements for a generation of data scientists capable of implementing Big Data Approaches.This article is categorized under: Social Status of Climate Change Knowledge > Knowledge and Practice Climate, History, Society, Culture > Technological Aspects and Ideas

Highlights

All writing that offers an opinion on the buzzword “Big Data” begins by grappling with a definition of the term itself (Chen, Mao, & Liu, 2014; Kitchin, 2014; Vitolo, Elkhatib, Reusser, & Macleod, 2015)
This paper explores potential applications of Big Data Approaches (BDAs) to address challenges associated with both these branches of coastal flood risk management
The SPRC approach takes place in advance of the flood event itself and seeks to characterize the interaction between hazard sources, facilitative pathways and vulnerable receptors to establish the potential consequences of a given risk “event.” It is at these “event” and “engineering” scales that BDAs can be applied to greatest effect (Figure 1)

Summary

| INTRODUCTION

All writing that offers an opinion on the buzzword “Big Data” begins by grappling with a definition of the term itself (Chen, Mao, & Liu, 2014; Kitchin, 2014; Vitolo, Elkhatib, Reusser, & Macleod, 2015). The SPRC approach takes place in advance of the flood event itself and seeks to characterize the interaction between hazard sources (surge, waves, rain), facilitative pathways (defenses, coastal bathymetry, ecosystems) and vulnerable receptors (residential and commercial property, critical infrastructure) to establish the potential consequences (flooding, increased insurance premiums, psychological impacts) of a given risk “event.” It is at these “event” and “engineering” scales that BDAs can be applied to greatest effect (Figure 1). This first BDA concerns characterization of the SPRC framework in a given coastal context. More than anywhere, ease of access should not be a mandate for use (Table 2)

| DISCUSSION

Findings

Natural language processing of social media

| CONCLUSION