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黑河流域1995-2014年县域水资源压力评价

  • 罗开盛 ,
  • 陶福禄
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  • 1. 南京信息工程大学遥感与测绘工程学院, 南京 210044;
    2. 中国科学院地理科学与资源研究所陆地表层格局与 模拟院重点实验室, 北京 100101

收稿日期: 2016-11-04

  修回日期: 2017-08-18

  网络出版日期: 2018-03-15

基金资助

国家重点研发计划(2017YFA0604703)、国家自然科学基金(91325302)和南京信息工程大学人才启动基金(2017r091)资助

Assessment of water resource pressure of Heihe River basin at the county level from 1995 to 2014

  • LUO Kaisheng ,
  • TAO Fulu
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  • 1. School of Remote Sensing and Geomatics Engineering, Najing University of Information Science and Technology, Nanjing 210044, China;
    2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources, Chinese Academy of Sciences, Beijing 100101, China

Received date: 2016-11-04

  Revised date: 2017-08-18

  Online published: 2018-03-15

摘要

干旱和半干旱地区的县域水资源压力评价对流域水资源管理有重要意义。基于半分布式的SWAT水文模型和Man-Kendall检测,使用1995—2014年的统计数据,从水资源的用水总量、生态用水、生产用水和生活用水4方面构建县域水资源利用评价体系,分析黑河流域县域水资源压力的时空变化。结果表明,县域水资源压力存在明显的空间差异:甘州区水资源总压力最大,其次是额济纳旗和山丹。甘州和额济纳旗水资源总压力归因于过高的生产用水,而山丹水资源总压力归因于流域内最高的生态用水量。临泽和民乐的水资源压力接近可承载的极限。在变化趋势方面,祁连、肃南、高台、山丹和额济纳的生态用水压力1995—2014年呈现下降趋势,肃南下降速率最大;其他县域呈现上升趋势,甘州上升速率最大。祁连、肃南、甘州、山丹和民乐等生产用水压力呈现下降趋势;临泽、高台、肃州、嘉峪关、金塔和额济纳旗表现上升趋势。生活用水压力除肃南和甘州外,所有县域显著性增加。县域水资源压力的时空差异是县域气候、经济、人口、农业、植被、政策和城市化进程等多种因素综合作用和权衡的结果,水资源管理者和决策者需要根据县情采取不同的水资源管理政策。本研究为评价干旱和半干旱区县域水资源压力提供了方法。

本文引用格式

罗开盛 , 陶福禄 . 黑河流域1995-2014年县域水资源压力评价[J]. 中国科学院大学学报, 2018 , 35(2) : 172 -179 . DOI: 10.7523/j.issn.2095-6134.2018.02.004

Abstract

Facing the great challenge of water shortage, assessment of water resources pressure has become a prominent issue. This study used the SWAT (soil and water assessment tool) model, Mann-Kendall detection method, and the 1995-2014 statistics of Heihe River basin to analyze the spatial and temporal dynamics of water resource pressure at the level of county. The assessment indicator system includes the total water resource pressure (TP), ecology consuming water pressure (EP), product consuming water pressure (PP), and domestic consuming water pressure (DP). The results show an obvious spatial variation in water resource pressur. Ganzhou has the largest TP, followed by Ejila and Shandan. The facts attribute to the high PPs in Ganzhou and Ejila and high EP in Shandan. Linze and Mingle have high TPs, close to 1. EPs presented decrease trends in Qilian, Sunan, Gaotai, Shandan, and Ejila in 1995-2014 and the maximum occurred in Suzhou. Other counties displayed increase trends and the maximum occurred in Suzhou. The increase trends of PP occurred in Linze, Gaotai, Sunan, Jiayuguan, Jinta, and Ejila in 1995-2014, and the decrease trends in Qilian, Sunan, Ganzhou, Shandan, and Mingle. These variations in water resource pressure were the comprehensive and interactive results of climate, population, vegetation, ecology, urbanization, and policies. The dynamic variations in different counties suggest that the decision makers adopt different policies in different counties in the basin. The present study illustrates the status of the water resource pressure at the county level, and provides an example for water resource assessment of arid and semi-arid basins.

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