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LIU Liying. Spatial evaluation and sensitivity analysis of water resource security in Guizhou Province under climate change[J]. CARSOLOGICA SINICA, 2020, 39(5): 714-723. doi: 10.11932/karst2020y35
Citation: LIU Liying. Spatial evaluation and sensitivity analysis of water resource security in Guizhou Province under climate change[J]. CARSOLOGICA SINICA, 2020, 39(5): 714-723. doi: 10.11932/karst2020y35

Spatial evaluation and sensitivity analysis of water resource security in Guizhou Province under climate change

doi: 10.11932/karst2020y35
  • Publish Date: 2020-10-25
  • It is of great significance to the protection of water resource security in karst areas by the analysis of spatio-temporal evolution of water resource security under the climate change. Using GA-BP neural network model, the spatial differentiation of water resource security in Guizhou Province was evaluated, and its sensitivity to climate change was analyzed. The results show that the water resource security took on obvious spatial heterogeneity in the study area. From 2001 to 2015, the water resource security in Qiannan was always the weakest in province. Guiyang improved the most obviously, and Anshun changed the least. When the rate of change is same, the change of annual average rainfall has the greatest impact on the water resource security, with the increase of 10%, the water resource security index increases by 0.95%, followed by the impact of unit surface water resource change, and the unit groundwater resource change had minimal impact. The most sensitive areas to rainfall change are Zunyi, Bijie, Liupanshui and Qianxinan. The results can provide scientific and technological support for the regulation and development of water resources in Guizhou Province.

     

  • [1]
    张利平,陈小凤,赵志鹏,等.气候变化对水文水资源影响的研究进展[J].地理科学进展,2008,27(3):60-67.
    [2]
    Teegavarapu R S V . Modeling climate change uncertainties in water resources management models[J]. Environmental Modelling & Software, 2010, 25(10): 1261-1265.
    [3]
    吕新苗,吴绍洪,杨勤业.全球环境变化对我国区域发展的可能影响评述[J].地理科学进展,2003,22(3):260-269.
    [4]
    侯文娟,高江波,彭韬,等.结构—功能—生境框架下的西南喀斯特生态系统脆弱性研究进展[J].地理科学进展,2016,35(3):58-68.
    [5]
    夏军,石卫.变化环境下中国水安全问题研究与展望[J].水利学报,2016,47(3):292-301.
    [6]
    贺向辉,梁虹,戴洪刚,等.喀斯特地区枯水资源时空演变的探讨:以贵阳地区为例[J].贵州师范大学学报(自然版),2007,25(3):29-34.
    [7]
    Lasha Asanidze ,Guranda Avkopashvili , Kukuri Tsikarishvili ,et al.Geoecological Monitoring of Karst Water in Georgia,Caucasus(Case Study of Racha Limestone Massif)[J].Open Journal of Geology,2017,7(4):822-829.
    [8]
    Wang W, Zhang G H,Liu C H. A New Attempt to Evaluate the Renewable Capacity of A Typical Karst,Groundwater System by Using 13C and 14C A Case Study of Karst,Groundwater in Pingyi-Feixian County, Shandong Province[J]. Acta Geologica Sinica(English Edition), 2018,92(1):424-425.
    [9]
    Wenping M,Qiang W,Yuan X,et al.Using numerical simulation for the prediction of mine dewatering from a karst water system underlying the coal seam in the Yuxian Basin,Northern China[J].Environmental Earth Sciences, 2018,77(5):215.
    [10]
    Xu Y,Wang S,Bai X,et al.Runoff response to climate change and human activities in a typical karst watershed,SW China[J].PLoS ONE,2018,13(3):e0193073.doi:10.1371/journal.pone.0193073.
    [11]
    Xia J,Ning L,Wang Q,et al.Vulnerability of and risk to water resources in arid and semi-arid regions of West China under a scenario of climate change[J].Climatic Change, 2017,144(3): 549-563.
    [12]
    Dai D,Sun M,Xu X,et al.Assessment of the water resource carrying capacity based on the ecological footprint:a case study in Zhangjiakou City,North China[J].Environmental Science and Pollution Research,2019.26(11):11000-11011.
    [13]
    张凤太,王腊春,苏维词,等.基于熵权集对耦合模型的表层岩溶带“二元”水资源安全评价[J].水力发电学报,2012,31(6):70-76.
    [14]
    苏印,官冬杰,苏维词.基于SPA的喀斯特地区水安全评价:以贵州省为例[J].中国岩溶,2015,34(6):560-569.
    [15]
    杨全明,王浩,赵先进.浅析贵州水资源安全保障对策[J].国土资源科技管理,2005,22(2):54-58.
    [16]
    姚望,周子琴,张凤太.基于PSR模型的贵州省水资源安全诊断与影响因素分析[J].人民珠江,2019,40(8):32-38.
    [17]
    章 程,蒋忠诚,Chris Groves ,袁道先.岩溶IGCP国际合作30年与岩溶关键带研究展望[J].中国岩溶,2019,38(3):301-306.
    [18]
    Gleeson T, Wada Y , Bierkens M F ,et al. Water balance of global aquifers revealed by groundwater footprint, Nature,2012, 488(7410), 197-200.
    [19]
    Taylor R G. Ground water and climate change[J].Nat. Clim. Change,2012, 3(4):322-329.
    [20]
    Martin J B, Kurz M J, Khadka M B. Climate control of decadal-scale increases in apparent ages of eogenetic karst spring water[J]. Journal of Hydrology, 2016, 540:988-1001.
    [21]
    Chu H, Wei J, Wang R, et al. Characterizing the interaction of groundwater and surface water in the karst aquifer of Fangshan, Beijing (China)[J]. Hydrogeology Journal, 2016, 25(2):1-14.
    [22]
    Dimki? D, Dimki? M, Soro A, et al. Overexploitation of karst spring as a measure against water scarcity[J]. Environmental Science & Pollution Research, 2017, 24(25):1-11.
    [23]
    Hartmann A, Goldscheider N, Wagener T, et al. Karst water resources in a changing world: Review of hydrological modeling approaches[J]. Reviews of Geophysics, 2014, 52(3):218-242.
    [24]
    Mcgill B M, Altchenko Y, Hamilton S K, et al. Complex interactions between climate change, sanitation, and groundwater quality: a case study from Ramotswa, Botswana[J]. Hydrogeology Journal, 2019,27:997-1015.
    [25]
    李汇文,王世杰,白晓永,等.气候变化及生态恢复对喀斯特槽谷碳酸盐岩风化碳汇的影响评估[J].生态学报,2019,39(16):6158-6172.
    [26]
    郑群威,苏维词,杨振华,等.基于集对分析法的喀斯特地区水资源安全动态变化及原因分析:以贵州省为例[J].中国岩溶,2019,38(6): 846-857.
    [27]
    张凤太,王腊春,苏维词.基于DPSIRM概念框架模型的岩溶区水资源安全评价[J].中国环境科学,2015,35(11):3511-3520.
    [28]
    杨梅,卿晓霞,王波.基于改进遗传算法的神经网络优化方法[J].计算机仿真,2009,26(5):198-201.
    [29]
    崔东文.基于相空间重构原理的遗传神经网络模型在城市需水预测中的应用[J].水利水电科技进展,2014,34(1):85-89.
    [30]
    池再香,李贵琼,白慧,等.干季贵州省东西部区域干湿状况差异分析[J].中国农业气象,2016,37(3):361-367.
    [31]
    楚文海,鄢贵权,苏维词,等.贵州典型喀斯特流域水资源可持续利用对策研究[J].水利学报,2008(06):118-122.
    [32]
    楚文海.脆弱生态约束下典型喀斯特流域水资源可持续利用评价[D].贵阳:贵州大学,2007.
    [33]
    曹欢.喀斯特地区生态系统健康评价与管理研究[D].贵阳:贵州大学,2011.
    [34]
    宋松柏.区域水资源可持续利用指标体系及评价方法研究[D].杨凌:西北农林科技大学,2003.
    [35]
    Zhang,Jun-Yi,Wang,La-Chun. Assessment of water resource security in Chongqing City of China: What has been done and what remains to be done?[J]. Natural Hazards, 2015, 75(3):2751-2772.
    [36]
    杨梅,卿晓霞,王波.基于改进遗传算法的神经网络优化方法[J].计算机仿真,2009,26(5):198-201.
    [37]
    崔东文.基于相空间重构原理的遗传神经网络模型在城市需水预测中的应用[J].水利水电科技进展,2014,34(1):85-89.
    [38]
    王孜昌, 王宏艳. 贵州省气候特点与植被分布规律简介[J]. 贵州林业科技, 2002(4):47-51.
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