Research On Chance-constrained Programming For Regional Water Resources Management

Water resources are the main power and support of social economy. However, along with the rapid development of agriculture and industry, water shortage goes to be serious, which becomes one of the most significant factors restricting economic development. Thus, effective planning for agricultural and industrial water resources is essential for easing current water crisis. However, such a planning effort is always associated with multiple uncertain factors, e.g. resources, economy, environment, which challenge the capabilities of traditional deterministic programming methods. Therefore, the aim of this study is to propose advanced inexact optimization approaches based on chance-constrained programming to handle the uncertainties for supporting rational decision making. The improved approaches will then be introduced into agricultural and industrial water resources management systems. Firstly, based on indepth analysis of prominent uncertainty in groundwater level, a modified fuzzy credibility-constrained programming for agricultural water resources management (MFCCP-AWM) is developed and then applied to an irrigation zone in Ulla mooring basin in Xinjiang province. Secondly, according to water shortage and conflicts of demand among different firms, an interval chance-constrained programming model for industrial water resources management (ICCP-IWM) is proposed for supporting water allocation under uncertainty. The results demonstrate that the MFCCP-AWM model can deal with uncertainties among groundwater levels expressed as fuzzy sets, and provide more optimal schemes for decision makers. In addition, the ICCP-IWM model can generate optimal allocation schemes for industrial managers, and handle uncertainties of the quantities among fresh water, recycle water and waste water; furthermore, it can also tackle the tradeoff between system cost and system-failure risk. In summary, the proposed MFCCP-AWM and ICCP-IWM models in this study are valuable for local decision makers to formulate corresponding decision alternatives, and provide new ideas for future research, being of theoretical value and practical significance.