Assessment of regional-scale water resources carrying capacity based on fuzzy multiple attribute decision-making and scenario simulation

Abstract This study associates the fuzzy multi-attribute decision making (FMADM) and the analytic hierarchy process (AHP) to assess the water resources carrying capacity and to tackle uncertain problems of multiple subsystems during its evaluation. For this purpose, the water resources carrying capacity evaluation index system is proposed, and the AHP-FMADM is used to evaluate the water resources carrying capacity of 15 areas in Xinjiang Uygur Autonomous Region from 2004 to 2017. Several scenarios with different weight-allocation modes are also conducted to study the influence of decision-makers’ preferences on target level. Results show that the water resources carrying capacity of all areas have been gradually improved. Overall, the economic and social indexes present an oscillation pattern with a rising, falling, and rising trend simultaneously in the study period from 2004 to 2017. The water resource utilization index varies with the amount of precipitation and reaches its peak in 2010. The ecological environment index depicts a diminishing overall trend initially before reaching a turning point in 2014. Increasing the water resources utilization and controlling rapid population growth can improve the water resources carrying capacity. The AHP-FMADM can help decision-makers to determine management plans based on their preferences, and the results of the study may contribute towards improving water resources carrying capacity.

[1]  Qiang Wang,et al.  Evaluating water resource sustainability in Beijing, China: Combining PSR model and matter-element extension method , 2019, Journal of Cleaner Production.

[2]  Parmeshwar Udmale,et al.  Early Warning Method for Regional Water Resources Carrying Capacity Based on the Logical Curve and Aggregate Warning Index , 2020, International journal of environmental research and public health.

[3]  J. M. V. Samani,et al.  A Fuzzy Group Decision Making Framework Based on ISM-FANP-FTOPSIS for Evaluating Watershed Management Strategies , 2019, Water Resources Management.

[4]  Aiqing Kang,et al.  The Water Status in China and an Adaptive Governance Frame for Water Management , 2020, International journal of environmental research and public health.

[5]  J. Traxler,et al.  Spatial modelling of the infestation indices of Aedes aegypti: an innovative strategy for vector control actions in developing countries , 2020, Parasites & Vectors.

[6]  Shahab Araghinejad,et al.  Developing an Interactive Spatial Multi-Attribute Decision Support System for Assessing Water Resources Allocation Scenarios , 2020, Water Resources Management.

[7]  Ping He,et al.  Analysis on spatio-temporal trends and drivers in vegetation growth during recent decades in Xinjiang, China , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[8]  Delu Wang,et al.  Integrated evaluation of the carrying capacities of mineral resource-based cities considering synergy between subsystems , 2020 .

[9]  Rannveig Ólafsdóttir,et al.  A novel modelling approach for evaluating the preindustrial natural carrying capacity of human population in Iceland. , 2006, The Science of the total environment.

[10]  Changlai Xiao,et al.  Development tendency analysis for the water resource carrying capacity based on system dynamics model and the improved fuzzy comprehensive evaluation method in the Changchun city, China , 2021 .

[11]  Li-Hua Feng,et al.  Application of system dynamics in analyzing the carrying capacity of water resources in Yiwu City, China , 2008, Math. Comput. Simul..

[12]  P.H.A.J.M. van Gelder,et al.  Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships’ maneuvering decisions using grey and fuzzy theories , 2019, Safety Science.

[13]  Malin Falkenmark,et al.  Towards water security: political determination and human adaptation crucial , 1998 .

[14]  Thorsten Wagener,et al.  Karst water resources in a changing world: Review of hydrological modeling approaches , 2014 .

[15]  Miguel Lloret-Climent,et al.  Stability, sensitivity and uncertainty rates in the flow equations of ecological models , 2016 .

[16]  Y. P. Li,et al.  Coupling fuzzy multiple attribute decision-making with analytic hierarchy process to evaluate urban ecological security: A case study of Guangzhou, China , 2018 .

[17]  E. Berezowska-Azzag,et al.  New tool for assessing urban water carrying capacity (WCC) in the planning of development programs in the region of Oran, Algeria , 2019, Sustainable Cities and Society.

[18]  C. Zang,et al.  Economic and resource and environmental carrying capacity trade-off analysis in the Haihe River basin in China , 2020 .

[19]  Yuyao Ye,et al.  An Improved Method for Evaluating Regional Resource Carrying Capacities: A Case Study of the Tarim River Basin in Arid China , 2019, Polish Journal of Environmental Studies.

[20]  Yun Lin,et al.  Assessment on water resources carrying capacity in karst areas by using an innovative DPESBRM concept model and cloud model. , 2020, The Science of the total environment.

[21]  Zhaolong Zhang,et al.  Evaluation of the agricultural water resource carrying capacity and optimization of a planting-raising structure , 2021 .

[22]  Daniela Fuchs-Hanusch,et al.  A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS , 2016, Expert Syst. Appl..

[23]  Richard Rushforth,et al.  The vulnerability and resilience of a city's water footprint: The case of Flagstaff, Arizona, USA , 2016 .

[24]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[25]  Xuefeng Chu,et al.  Prioritization of Water Allocation for Adaptation to Climate Change Using Multi-Criteria Decision Making (MCDM) , 2019, Water Resources Management.

[26]  Matteo Convertino,et al.  Optimal information networks: Application for data-driven integrated health in populations , 2018, Science Advances.

[27]  Michael J. Schmidt,et al.  Nonparametric, data-based kernel interpolation for particle-tracking simulations and kernel density estimation , 2020, 2010.06737.

[28]  Jinxi Song,et al.  Comprehensive evaluation and scenario simulation for the water resources carrying capacity in Xi'an city, China. , 2019, Journal of environmental management.

[29]  Hongwei Lu,et al.  An integrated model of water resources optimization allocation based on projection pursuit model – Grey wolf optimization method in a transboundary river basin , 2018 .

[30]  Mohammad Valipour Khatir,et al.  Elucidation of structural relationships of SWOT: A mixed method approach based on FMADM for formulating science and technology strategies , 2019, Technology in Society.

[31]  Ferenc Szidarovszky,et al.  Conjunctive Management of Surface and Ground Water Resources Using Conflict Resolution Approach , 2016 .

[32]  Ewa Berezowska-Azzag,et al.  Water resources carrying capacity assessment: The case of Algeria's capital city , 2016 .

[33]  Xiang Yu,et al.  Assessment of water resource carrying capacity based on the chicken swarm optimization-projection pursuit model , 2020, Arabian Journal of Geosciences.

[34]  Lu Bai,et al.  Regional water resource carrying capacity evaluation based on multi-dimensional precondition cloud and risk matrix coupling model. , 2019, The Science of the total environment.

[35]  Jinhuan Wang,et al.  A “carrier-load” perspective method for investigating regional water resource carrying capacity , 2020 .

[36]  Ashok K. Mishra,et al.  Water security assessment using blue and green water footprint concepts , 2016 .

[37]  Mo Li,et al.  An innovative method for water resources carrying capacity research--Metabolic theory of regional water resources. , 2016, Journal of environmental management.

[38]  Guohe Huang,et al.  An inexact programming approach for supporting ecologically sustainable water supply with the consideration of uncertain water demand by ecosystems , 2011 .

[39]  A. Stein,et al.  Identifying the Links Among Poverty, Hydroenergy and Water Use Using Data Mining Methods , 2020, Water Resources Management.

[40]  Aijun Li,et al.  Scenario analysis of low-carbon development of energy industry with restriction of water resource in Xinjiang , 2018, Journal of Water and Climate Change.