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Development and implementation of a spatial unit non-overlapping water stress index for water scarcity evaluation with a moderate spatial resolution

机译:具有适度空间分辨率的缺水评估的空间单位非重叠水分胁迫指数的开发和实现

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摘要

Water scarcity is a serious global problem, and accurate estimations are urgently needed. The Water stress index (WSI) is one of the most commonly used methods for global or large scale water scarcity evaluation, but this method lacks of consideration of water demand and water supply positions non-overlapped spatial distribution, tends to overestimate water stress when applied to a moderate resolution grid (e.g., 1 km). In this study, we used a non-overlapping water supply-and-demand unit approach to improve the calculation scheme and constructed a spatial unit non-overlapping WSI model (Sun-WSI model). We then applied the new model to the Yarlung Tsangpo-Brahmaputra River (TBR) and estimated monthly water stress from 2006 to 2012 with a 1 km spatial resolution. The results showed that the determination coefficient (R-2) between the normalized Drought Index (DI) and water stress was mainly in the range of 0.2-0.7, accounting for 77.4% of the study area. The spatial pattern of water stress estimated by the Sun-WSI model was consistent with the DI. Further analysis showed that both overall and grid water stress estimated by the Sun-WSI model were close to the results from existing studies; however the Sun-WSI model had a higher spatial resolution. With a 1 km resolution, the Sun-WSI model performed better than the conventional WSI with respect to both overall results and spatial details. This suggests that the Sun-WSI model is suitable for evaluating regional or moderate-resolution grid water scarcity. (C) 2016 Elsevier Ltd. All rights reserved.
机译:缺水是一个严重的全球性问题,迫切需要准确的估算。水分胁迫指数(WSI)是用于全球或大规模缺水评估的最常用方法之一,但是该方法缺乏对水需求的考虑,并且供水位置没有重叠的空间分布,应用时往往会高估水分胁迫到中等分辨率的网格(例如1 km)。在这项研究中,我们使用非重叠供水和需求单位方法来改进计算方案,并构建了空间单位非重叠WSI模型(Sun-WSI模型)。然后,我们将新模型应用于Yarlung Tsangpo-Brahmaputra河(TBR),并以1 km的空间分辨率估算了2006年至2012年的每月水压力。结果表明,归一化干旱指数(DI)和水分胁迫之间的测定系数(R-2)主要在0.2-0.7范围内,占研究区域的77.4%。 Sun-WSI模型估计的水分胁迫的空间格局与DI一致。进一步的分析表明,Sun-WSI模型估计的总体和网格水分胁迫都与现有研究的结果相近。但是,Sun-WSI模型具有较高的空间分辨率。在1 km的分辨率下,Sun-WSI模型在整体结果和空间细节方面均比常规WSI更好。这表明,Sun-WSI模型适用于评估区域或中等分辨率的网格缺水情况。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Ecological indicators》 |2016年第10期|422-433|共12页
  • 作者单位

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China|Guizhou Normal Univ, Sch Geog & Environm Sci, Guiyang 550001, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China|Satellite Environm Ctr MEP, Beijing 100094, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China|Guizhou Normal Univ, Sch Geog & Environm Sci, Guiyang 550001, Peoples R China;

    Beijing Normal Univ, Sch Geog, State Key Lab Remote Sensing, Beijing Key Lab Remote Sensing Environm & Digital, Beijing 100875, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Water scarcity; Spatial unit non-overlapping; Hyper-resolution; Yarlung Tsangpo-Brahmaputra River;

    机译:水资源稀缺;空间单位不重叠;超分辨率;雅鲁藏布-布拉马普特拉河;

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