Abstract
The long-term dynamic comprehensive evaluation of the water resource carrying capacity (WRCC) and the analysis of its potential driving mechanism in arid areas are contemporary research issues and technical means of mitigating and coordinating the conflict between severe resource shortages and human needs. The purpose of this study was to explore the distribution of the WRCC and the spatiotemporal heterogeneity of drivers in arid areas based on an improved two-dimensional spatiotemporal dynamic evaluation model. The results show that (1) the spatial distribution of the WRCC in Xinjiang, China, is high in the north, low in the south, high in the west, and low in the east. (2) From 2005 to 2020, the centers of gravity of the WRCC in northern and southern Xinjiang moved to the southeast and west, respectively, and the spatial distribution exhibited slight diffusion. (3) The factors influencing the WRCC exhibit more obvious spatial and temporal heterogeneity. The domestic waste disposal rate and ecological water use rate were the main factors influencing the WRCC in the early stage, while the GDP per capita gradually played a dominant role in the later stage. (4) In the next 30 years, the WRCC in Xinjiang will increase. The results provide a theoretical reference for the sustainable development of water resources in arid areas.
Similar content being viewed by others
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
Abbaspour KC, Faramarzi M, Ghasemi SS, Yang H (2009) Assessing the impact of climate change on water resources in Iran. Water Resour Res 45. https://doi.org/10.1029/2008wr007615
Arrow K, Bolin B, Costanza R, Dasgupta P, Folke C (1995) Economic growth, carrying capacity, and the environment. Ecol Econ 15:91–95
Bahtebay J, Zhang F, Ariken M, Chan NW, Tan ML (2021) Evaluation of the coordinated development of urbanization-resources-environment from the incremental perspective of Xinjiang, China. J Clean Prod 325. https://doi.org/10.1016/j.jclepro.2021.129309
Chai N, Zhou W (2022) The DPSIRM - grey cloud clustering method for evaluating the water environment carrying capacity of Yangtze River economic Belt. Ecol Indic 136. https://doi.org/10.1016/j.ecolind.2022.108722
Cheng H, Zhu L, Meng J (2022) Fuzzy evaluation of the ecological security of land resources in mainland China based on the pressure-state-response framework. Sci Total Environ 804:150053. https://doi.org/10.1016/j.scitotenv.2021.150053
Doungmanee P (2016) The nexus of agricultural water use and economic development level. Kasetsart J Soc Sci 37:38–45. https://doi.org/10.1016/j.kjss.2016.01.008
Feng Q, Tian Y, Yu T, Yin Z, Cao S (2019) Combating desertification through economic development in northwestern China. Land Degrad Dev 30:910–917. https://doi.org/10.1002/ldr.3277
Gao F, Zhang Y, Chen Q, Wang P, Yang H, Yao Y, Cai W (2018) Comparison of two long-term and high-resolution satellite precipitation datasets in Xinjiang, China. Atmos Res 212:150–157. https://doi.org/10.1016/j.atmosres.2018.05.016
Guo Y, Yao Y, Yi P (2007) Method and application of dynamic comprehensive evaluation. Syst Eng Theory Pract 27:154–158. https://doi.org/10.1016/s1874-8651(08)60060-5
Han C, Zheng J, Guan J, Yu D, Lu B (2022) Evaluating and simulating resource and environmental carrying capacity in arid and semiarid regions: a case study of Xinjiang. J Clean Prod 338. https://doi.org/10.1016/j.jclepro.2022.130646
Han X, Wang P, Wang J, Qiao M, Zhao X (2020) Evaluation of human-environment system vulnerability for sustainable development in the Liupan mountainous region of Ningxia. Environ Dev 34. https://doi.org/10.1016/j.envdev.2020.100525
He Y, Wang Z (2022) Water-land resource carrying capacity in China: changing trends, main driving forces, and implications. J Clean Prod 331. https://doi.org/10.1016/j.jclepro.2021.130003
Hjerppe T, Taskinen A, Kotamaki N, Malve O, Kettunen J (2017) Probabilistic evaluation of ecological and economic objectives of river basin management reveals a potential flaw in the goal setting of the EU Water Framework Directive. Environ Manage 59:584–593. https://doi.org/10.1007/s00267-016-0806-z
Huang B, Wu B, Barry M (2010) Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices. Int J Geogr Inf Sci 24:383–401. https://doi.org/10.1080/13658810802672469
Lefever DW (1926) Measuring geographic concentration by means of the standard deviational ellipse. Am J Sociol 32:88–94. https://doi.org/10.1086/214027
Li D, Zuo Q, Jiang L, Wu Q (2023) An integrated analysis framework for water resources sustainability considering fairness and decoupling based on the water resources ecological footprint model: a case study of Xinjiang. J Clean Prod 383. https://doi.org/10.1016/j.jclepro.2022.135466
Li JY, Cui LB, Dou M, Ali A (2022) Corrigendum to “Water resources allocation model based on ecological priority in the arid region” [Environ. Res. 199 (2021) 1-11/111201]. Environ Res 213:113572. https://doi.org/10.1016/j.envres.2022.113572
Li L, Li J, Yu R (2020) Characteristics of summer regional rainfall events over Ili River Valley in Northwest China. Atmos Res 243. https://doi.org/10.1016/j.atmosres.2020.104996
Li Y, Chen Y (2021) Variable precondition S-type cloud algorithm: theory and application on water resources carrying capacity assessment. Ecol Indic 121. https://doi.org/10.1016/j.ecolind.2020.107209
Liao X, Ren Y, Shen L, Shu T, He H, Wang J (2020) A “carrier-load” perspective method for investigating regional water resource carrying capacity. J Clean Prod 269. https://doi.org/10.1016/j.jclepro.2020.122043
Lima ML, Barilari A, Massone HE, Pascual M (2022) Incorporating local researchers’ and decision makers’ preferences for groundwater resources management in a spatial multi-voiced decision model. J Environ Manage 302:113954. https://doi.org/10.1016/j.jenvman.2021.113954
Liu P, Lü S, Han Y, Wang F, Tang L (2022) Comprehensive evaluation on water resources carrying capacity based on water-economy-ecology concept framework and EFAST-cloud model: a case study of Henan Province. Ecol Indic 143. https://doi.org/10.1016/j.ecolind.2022.109392
Liu RZ, Borthwick AG (2011) Measurement and assessment of carrying capacity of the environment in Ningbo, China. J Environ Manage 92:2047–2053. https://doi.org/10.1016/j.jenvman.2011.03.033
Lu L, Lei Y, Wu T, Chen K (2022) Evaluating water resources carrying capacity: the empirical analysis of Hubei Province, China 2008–2020. Ecol Indic 144. https://doi.org/10.1016/j.ecolind.2022.109454
Luo M, Liu T, Meng F, Duan Y, Bao A, Xing W, Feng X, De Maeyer P, Frankl A (2019) Identifying climate change impacts on water resources in Xinjiang, China. Sci Total Environ 676:613–626. https://doi.org/10.1016/j.scitotenv.2019.04.297
Malthus TR (1826) An essay on the principle of population; or, a view of its past and present effects on human happiness; with an inquiry into our prospects respecting the future removal or mitigation of the evils which it occasions, 1. London: John Murray. https://doi.org/10.5962/bhl.title.49216
Maurya SP, Singh PK, Ohri A, Singh R (2020) Identification of indicators for sustainable urban water development planning. Ecol Indic 108. https://doi.org/10.1016/j.ecolind.2019.105691
Peng J, Zhang J (2022) Urban flooding risk assessment based on GIS- game theory combination weight: a case study of Zhengzhou City. Int J Disaster Risk Reduct 77. https://doi.org/10.1016/j.ijdrr.2022.103080
Peng T, Deng H, Lin Y, Jin Z (2021) Assessment on water resources carrying capacity in karst areas by using an innovative DPESBRM concept model and cloud model. Sci Total Environ 767:144353. https://doi.org/10.1016/j.scitotenv.2020.144353
Ren C, Guo P, Li M, Li R (2016) An innovative method for water resources carrying capacity research–metabolic theory of regional water resources. J Environ Manage 167:139–146. https://doi.org/10.1016/j.jenvman.2015.11.033
Sindhu S, Nehra V, Luthra S (2017) Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: case study of India. Renew Sustain Energy Rev 73:496–511. https://doi.org/10.1016/j.rser.2017.01.135
Smeets E, Weterings R (1999) Environmental indicators:Typology and overview. Technical report
Song L (2021) Dynamic comprehensive evaluation of environmental carrying capacity of industrial transfer sites in Central China: a case study of Wanjiang Urban Belt(in Chinese). Finance and Trade Research. https://doi.org/10.1016/j.ocecoaman.2021.105981
Sun J, Miao J, Mu H, Xu J, Zhai N (2022) Sustainable development in marine economy: assessing carrying capacity of Shandong province in China. Ocean Coast Manag 216. https://doi.org/10.1016/j.ocecoaman.2021.105981
Wang A, Liao X, Tong Z, Du W, Zhang J, Liu X, Guo E, Liu M (2022) Spatiotemporal variation of ecological carrying capacity in Dongliao River Basin. Ecol Indic 135. https://doi.org/10.1016/j.ecolind.2022.108548
Wang C, Hou Y, Xue Y (2017) Water resources carrying capacity of wetlands in Beijing: analysis of policy optimization for urban wetland water resources management. J Clean Prod 161:1180–1191. https://doi.org/10.1016/j.jclepro.2017.03.204
Wang J, Mu X, Chen S, Liu W, Wang Z, Dong Z (2021a) Dynamic evaluation of water resources carrying capacity of the Dianchi Lake Basin in 2005–2015, based on DSPERM framework model and simulated annealing-projection pursuit model. Reg Sustain 2:189–201. https://doi.org/10.1016/j.regsus.2021.06.003
Wang Q, Zhan L (2019) Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: an empirical analysis of Sichuan and Chongqing, China. Energy 176:353–364. https://doi.org/10.1016/j.energy.2019.03.158
Wang S, Zhao Q, Pu T (2021) Assessment of water stress level about global glacier-covered arid areas: a case study in the Shule River Basin, northwestern China. J Hydrol Reg Stud 37. https://doi.org/10.1016/j.ejrh.2021.100895
Wang T, Jian S, Wang J, Yan D (2022) Dynamic interaction of water–economic–social–ecological environment complex system under the framework of water resources carrying capacity. J Clean Prod 368. https://doi.org/10.1016/j.jclepro.2022.133132
Wang X (2022) Pre-assessment for ice disaster in Ning-Meng reaches of the Yellow river based on improved TOPSIS under three-parameter interval grey number. Int J Disaster Risk Reduct 83. https://doi.org/10.1016/j.ijdrr.2022.103430
Wang Z, Song K, Hu L (2010) China’s largest scale ecological migration in the Three-River Headwater region. Ambio 39:443–446. https://doi.org/10.1007/s13280-010-0054-z
Whittingham MJ, Stephens PA, Bradbury RB, Freckleton RP (2006) Why do we still use stepwise modelling in ecology and behaviour? J Anim Ecol 75:1182–1189. https://doi.org/10.1111/j.1365-2656.2006.01141.x
Wu D, Liu M (2022) Assessing adaptability of the water resource system to social-ecological systems in the Beijing-Tianjin-Hebei region: based on the DPSIR-TOPSIS framework. Chinese J Popul Resour Environ 20:261–269. https://doi.org/10.1016/j.cjpre.2022.09.007
Wu L, Su X, Ma X, Kang Y, Jiang Y (2018) Integrated modeling framework for evaluating and predicting the water resources carrying capacity in a continental river basin of Northwest China. J Clean Prod 204:366–379. https://doi.org/10.1016/j.jclepro.2018.08.319
Wu Q, Zuo Q, Ma J, Zhang Z, Jiang L (2021) Evolution analysis of water consumption and economic growth based on decomposition-decoupling two-stage method: a case study of Xinjiang Uygur Autonomous Region. Sustain Cities Soc 75. https://doi.org/10.1016/j.scs.2021.103337
Wu W-p, Zhu Y-f, Zeng W-k, Wang M, Yang D-x, Chen W-f (2021) Green efficiency of water resources in Northwest China: spatial-temporal heterogeneity and convergence trends. J Clean Prod 320. https://doi.org/10.1016/j.jclepro.2021.128651
Xiong J, Wang X, Zhao D, Zhao Y (2022) Spatiotemporal pattern and driving forces of ecological carrying capacity during urbanization process in the Dongting Lake area China. Ecol Indic 144. https://doi.org/10.1016/j.ecolind.2022.109486
Xu H, Ye M, Li J (2008) The water transfer effects on agricultural development in the lower Tarim River, Xinjiang of China. Agric Water Manag 95:59–68. https://doi.org/10.1016/j.agwat.2007.09.004
Zhang C, Dong J, Leng G, Doughty R, Zhang K, Han S, Zhang G, Zhang X, Ge Q (2023) Attenuated cooling effects with increasing water-saving irrigation: satellite evidence from Xinjiang China. Agric For Meteorol 333. https://doi.org/10.1016/j.agrformet.2023.109397
Zhang J, Dong Z (2022) Assessment of coupling coordination degree and water resources carrying capacity of Hebei Province (China) based on WRESP2D2P framework and GTWR approach. Sustain Cities Soc 82. https://doi.org/10.1016/j.scs.2022.103862
Zhang Q, Sun P, Li J, Singh VP, Liu J (2015) Spatiotemporal properties of droughts and related impacts on agriculture in Xinjiang, China. Int J Climatol 35:1254–1266. https://doi.org/10.1002/joc.4052
Zhang X, Xu D, Wang Z (2021) Optimizing spatial layout of afforestation to realize the maximum benefit of water resources in arid regions: a case study of Alxa. J Clean Prod 320. https://doi.org/10.1016/j.jclepro.2021.128827
Zhang Y, Khan SU, Swallow B, Liu W, Zhao M (2022) Coupling coordination analysis of China’s water resources utilization efficiency and economic development level. J Clean Prod 373. https://doi.org/10.1016/j.jclepro.2022.133874
Zhao Y, Wang Y, Wang Y (2021) Comprehensive evaluation and influencing factors of urban agglomeration water resources carrying capacity. J Clean Prod 288. https://doi.org/10.1016/j.jclepro.2020.125097
Żogała-Siudem B, Jaroszewicz S (2021) Fast stepwise regression based on multidimensional indexes. Inf Sci 549:288–309. https://doi.org/10.1016/j.ins.2020.11.031
Zou D, Cong H (2021) Evaluation and influencing factors of China’s industrial water resource utilization efficiency from the perspective of spatial effect. Alex Eng J 60:173–182. https://doi.org/10.1016/j.aej.2020.06.053
Zuo Q, Guo J, Ma J, Cui G, Yang R, Yu L (2021) Assessment of regional-scale water resources carrying capacity based on fuzzy multiple attribute decision-making and scenario simulation. Ecol Indic 130. https://doi.org/10.1016/j.ecolind.2021.108034
Zyoud SH, Kaufmann LG, Shaheen H, Samhan S, Fuchs-Hanusch D (2016) A framework for water loss management in developing countries under fuzzy environment: integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Syst Appl 61:86–105. https://doi.org/10.1016/j.eswa.2016.05.016
Funding
This work was supported by the National Science and Technology Basic Resources Survey Special Project (2021xjkk1001).
Author information
Authors and Affiliations
Contributions
Juan Yang: methodology, software, writing—original draft. Jianghua Zheng: review and suggestions. Chuqiao Han: writing—review and editing. Zhe Wang: methodology. Binbin Lu: review and suggestions.
Corresponding author
Ethics declarations
Ethics approval
This manuscript is only submitted to this journal. The data used in this study did not involve human participants and/or animals.
Consent to participate
Not applicable.
Consent for publication
The author has read and approved the manuscript, and agrees to submit and publish the manuscript.
Conflict of interest
The authors declare no competing interests.
Additional information
Responsible Editor: Xianliang Yi
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Yang, J., Zheng, J., Han, C. et al. Analysis of sustainable water resource management and driving mechanism in arid region: a case study of Xinjiang, China, from 2005 to 2020. Environ Sci Pollut Res 31, 15900–15919 (2024). https://doi.org/10.1007/s11356-024-32092-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-024-32092-9