Literature DB >> 26318687

A spatial assessment framework for evaluating flood risk under extreme climates.

Yun Chen1, Rui Liu2, Damian Barrett3, Lei Gao4, Mingwei Zhou5, Luigi Renzullo6, Irina Emelyanova7.   

Abstract

Australian coal mines have been facing a major challenge of increasing risk of flooding caused by intensive rainfall events in recent years. In light of growing climate change concerns and the predicted escalation of flooding, estimating flood inundation risk becomes essential for understanding sustainable mine water management in the Australian mining sector. This research develops a spatial multi-criteria decision making prototype for the evaluation of flooding risk at a regional scale using the Bowen Basin and its surroundings in Queensland as a case study. Spatial gridded data, including climate, hydrology, topography, vegetation and soils, were collected and processed in ArcGIS. Several indices were derived based on time series of observations and spatial modeling taking account of extreme rainfall, evapotranspiration, stream flow, potential soil water retention, elevation and slope generated from a digital elevation model (DEM), as well as drainage density and proximity extracted from a river network. These spatial indices were weighted using the analytical hierarchy process (AHP) and integrated in an AHP-based suitability assessment (AHP-SA) model under the spatial risk evaluation framework. A regional flooding risk map was delineated to represent likely impacts of criterion indices at different risk levels, which was verified using the maximum inundation extent detectable by a time series of remote sensing imagery. The result provides baseline information to help Bowen Basin coal mines identify and assess flooding risk when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in this research offers the Australian mining industry, and social and environmental studies around the world, an effective way to produce reliable assessment on flood risk for managing uncertainty in water availability under climate change.
Copyright © 2015. Published by Elsevier B.V.

Entities:  

Keywords:  AHP; GIS; Inundation; MODIS; Multi-criteria decision making

Year:  2015        PMID: 26318687     DOI: 10.1016/j.scitotenv.2015.08.094

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Effluent trading in river systems through stochastic decision-making process: a case study.

Authors:  Mohammad Amin Zolfagharipoor; Azadeh Ahmadi
Journal:  Environ Sci Pollut Res Int       Date:  2017-07-15       Impact factor: 4.223

Review 2.  A systematic review of the flood vulnerability using geographic information system.

Authors:  Shiau Wei Chan; Sheikh Kamran Abid; Noralfishah Sulaiman; Umber Nazir; Kamran Azam
Journal:  Heliyon       Date:  2022-03-08
  2 in total

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