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极端气候下的洪水风险评估空间评估框架。

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

机构信息

CSIRO Land and Water, Canberra, Australia.

CSIRO Land and Water, Canberra, Australia; Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, China.

出版信息

Sci Total Environ. 2015 Dec 15;538:512-23. doi: 10.1016/j.scitotenv.2015.08.094. Epub 2015 Aug 28.

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.

摘要

近年来,澳大利亚煤矿面临着一个主要挑战,即密集降雨事件导致的洪水风险不断增加。鉴于气候变化问题日益严重,以及洪水预计会加剧,对洪水泛滥风险进行评估对于了解澳大利亚采矿业的可持续矿山水资源管理至关重要。本研究以昆士兰州的鲍文盆地及其周边地区为例,开发了一种用于评估区域洪水风险的空间多准则决策原型。在 ArcGIS 中收集和处理了包括气候、水文学、地形、植被和土壤在内的空间网格化数据。根据极端降雨、蒸散、水流、潜在土壤水分保持、数字高程模型(DEM)生成的高程和坡度以及从河网提取的排水密度和接近度,基于时间序列观测和空间建模导出了几个指数。使用层次分析法(AHP)对这些空间指数进行加权,并在空间风险评估框架下,将其整合到基于 AHP 的适宜性评估(AHP-SA)模型中。绘制了区域洪水风险图,以表示不同风险水平下标准指数的可能影响,该图使用遥感图像时间序列可检测到的最大淹没范围进行了验证。该结果为鲍文盆地煤矿在制定适应战略和未来实施缓解措施时提供了基线信息,以帮助识别和评估洪水风险。本研究中开发的框架和方法为澳大利亚采矿业以及全球社会和环境研究提供了一种有效的方法,可在气候变化下对水资源可用性的不确定性进行洪水风险可靠评估。

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