Integrated planning for regional development planning and water resources management under uncertainty: A case study of Xining, China

Abstract Economic restructuring, water resources management, population planning and environmental protection are subjects to inner uncertainties of a compound system with objectives which are competitive alternatives. Optimization model and water quality model are usually used to solve problems in a certain aspect. To overcome the uncertainty and coupling in reginal planning management, an interval fuzzy program combined with water quality model for regional planning and management has been developed to obtain the absolutely “optimal” solution in this study. The model is a hybrid methodology of interval parameter programming (IPP), fuzzy programing (FP), and a general one-dimensional water quality model. The method extends on the traditional interval parameter fuzzy programming method by integrating water quality model into the optimization framework. Meanwhile, as an abstract concept, water resources carrying capacity has been transformed into specific and calculable index. Besides, unlike many of the past studies about water resource management, population as a significant factor has been considered. The results suggested that the methodology was applicable for reflecting the complexities of the regional planning and management systems within the planning period. The government policy makers could establish effective industrial structure, water resources utilization patterns and population planning, and to better understand the tradeoffs among economic, water resources, population and environmental objectives.

[1]  Gordon H. Huang,et al.  Planning water resources management systems using a fuzzy-boundary interval-stochastic programming method , 2010 .

[2]  J Figueira,et al.  Stochastic Programming , 1998, J. Oper. Res. Soc..

[3]  V. Uddameri,et al.  A fuzzy simulation–optimization approach for optimal estimation of groundwater availability under decision maker uncertainty , 2014, Environmental Earth Sciences.

[4]  Y. P. Li,et al.  A multistage fuzzy-stochastic programming model for supporting sustainable water-resources allocation and management , 2009, Environ. Model. Softw..

[5]  P. Gleick,et al.  Peak water limits to freshwater withdrawal and use , 2010, Proceedings of the National Academy of Sciences.

[6]  Guohe Huang,et al.  A risk-based interactive multi-stage stochastic programming approach for water resources planning under dual uncertainties , 2016 .

[7]  Holger R. Maier,et al.  Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications , 2000, Environ. Model. Softw..

[8]  S Vedula,et al.  Multireservoir System Optimization using Fuzzy Mathematical Programming , 2000 .

[9]  R. Allen,et al.  System Dynamics to Sustainable Water Resources Management in the Eastern Snake Plain Aquifer Under Water Supply Uncertainty 1 , 2012 .

[10]  Demetris Koutsoyiannis,et al.  A blueprint for process‐based modeling of uncertain hydrological systems , 2012 .

[11]  Gordon H. Huang,et al.  IPWM: AN INTERVAL PARAMETER WATER QUALITY MANAGEMENT MODEL , 1996 .

[12]  Jie Sun,et al.  Risk forecasting of pollution accidents based on an integrated Bayesian Network and water quality model for the South to North Water Transfer Project , 2016 .

[13]  Zhong Li,et al.  Factorial fuzzy programming for planning water resources management systems , 2016 .

[14]  R. Ahlert,et al.  APPLICATIONS OF A STEADY‐STATE, ONE‐DIMENSIONAL WATER QUALITY MODEL1 , 2007 .

[15]  G H Huang,et al.  An inexact mixed risk-aversion two-stage stochastic programming model for water resources management under uncertainty , 2014, Environmental Science and Pollution Research.

[16]  C. Vörösmarty,et al.  Global water resources: vulnerability from climate change and population growth. , 2000, Science.

[17]  Bernard A. Engel,et al.  A fast mobile early warning system for water quality emergency risk in ungauged river basins , 2015, Environ. Model. Softw..

[18]  G. Huang,et al.  Integrated Planning of Urban Water Resources and Water Pollution Control Management: Case of Urumqi, China , 2016 .

[19]  D. N. Bird,et al.  Is climate change a threat for water uses in the Mediterranean region? Results from a survey at local scale. , 2016, The Science of the total environment.

[20]  A. Werritty.  Living with uncertainty: climate change, river flows and water resource management in Scotland. , 2002, The Science of the total environment.

[21]  Guohe Huang,et al.  Planning water resources systems with interval stochastic dynamic programming , 2007 .

[22]  Sajjad Ahmad,et al.  Evaluating the impact of demand-side management on water resources under changing climatic conditions and increasing population. , 2013, Journal of environmental management.

[23]  Marios Sophocleous,et al.  Global and Regional Water Availability and Demand: Prospects for the Future , 2004 .

[24]  B. Bates,et al.  Climate change and water. , 2008 .

[25]  Zoran Kapelan,et al.  Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty , 2016 .

[26]  Slobodan P. Simonovic,et al.  A fuzzy compromise approach to water resource systems planning under uncertainty , 2000, Fuzzy Sets Syst..

[27]  Carlo Giupponi,et al.  A dynamic assessment of water scarcity risk in the Lower Brahmaputra River Basin: An integrated approach , 2015 .

[28]  Ron Johnstone,et al.  A system dynamics simulation model for sustainable water resources management and agricultural development in the Volta River Basin, Ghana. , 2016, The Science of the total environment.

[29]  Yanpeng Cai,et al.  Sustainable urban water resources management considering life-cycle environmental impacts of water utilization under uncertainty , 2016 .

[30]  P. D’Odorico,et al.  Climate change and large-scale land acquisitions in Africa: Quantifying the future impact on acquired water resources , 2016 .

[31]  Y. P. Li,et al.  A type-2 fuzzy interval programming approach for conjunctive use of surface water and groundwater under uncertainty , 2016, Inf. Sci..