Sangam: A Confluence of Knowledge Streams

Big Data Approaches for coastal flood risk assessment and emergency response

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dc.creator Pollard, James A.
dc.creator Spencer, Tom
dc.creator Jude, Simon
dc.date 2018-07-18T14:22:27Z
dc.date 2018-07-18T14:22:27Z
dc.date 2018-07-17
dc.date.accessioned 2022-05-25T16:37:11Z
dc.date.available 2022-05-25T16:37:11Z
dc.identifier Pollard JA, Spencer T, Jude S. (2018) Big Data Approaches for coastal flood risk assessment and emergency response. Wiley Interdisciplinary Reviews: Climate Change, Volume 9, Issue 5, September/October 2018, Article number e543
dc.identifier 1757-7780
dc.identifier https://doi.org/10.1002/wcc.543
dc.identifier http://dspace.lib.cranfield.ac.uk/handle/1826/13348
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/182206
dc.description 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.
dc.language en
dc.publisher Wiley
dc.rights Attribution 4.0 International
dc.rights http://creativecommons.org/licenses/by/4.0/
dc.subject Big Data
dc.subject coastal flood risk management
dc.subject flood emergency response
dc.subject flood risk assessment
dc.subject source-pathway-receptor
dc.title Big Data Approaches for coastal flood risk assessment and emergency response
dc.type Article


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