An Interval-based Fuzzy Chance-constrained Irrigation Water Allocation model with double-sided fuzziness

This study presents an Interval-based Fuzzy Chance-constrained Irrigation Water Allocation (IFCIWA) model with double-sided fuzziness for supporting irrigation water management. It is derived from incorporating double-sided chance-constrained programming (DFCCP) into an interval parameter programming (IPP) framework. The model integrates interval linear crop water production functions into its general framework for irrigation water allocation. Moreover, it can deal with uncertainties presented as discrete intervals and fuzziness. It can also allow violation of system constraints with double-sided fuzziness, where each confidence level consists of two reliability scenarios (i.e. minimum and maximum reliability scenarios). To demonstrate its applicability, the model is then applied to a case study in the middle reaches of the Heihe River Basin, northwest China. Therefore, optimal solutions have been generated for irrigation water allocation under uncertainty. The results indicate that planning under a lower confidence level and a minimum reliability scenario can provide maximized system benefits. System benefits under the high water level are [2.659, 7.913] x 10(9) Yuan when alpha = 0, [2.650, 7.822] x 10(9) Yuan when alpha = 0.5 and [2.642, 7.734] x 10(9) Yuan when alpha = 1.0 under the minimum reliability scenario. Furthermore, the results can support in-depth analysis of interrelationships among system benefits, confidence levels, reliability levels and risk levels. These results can effectively provide decision support for managers identifying desired irrigation water allocation plans in study area.