Research On Water Resources Allocation Model Considering Hierarchical Decision Under Multiple Uncertainties

Sustainable and efficient water resources management is a significant concern for many countries,particularly in the backdrop of a burgeoning population,urbanization expansion,and global water shortage crisis.Presently,unreasonable water planning strategies have exacerbated problems of water resource deficiency,which has become a limiting factor for economic development in many regions.Consequently,it is desired to formulate a reliable water resource management approach for alleviating the water shortage.However,the actual water allocation system is extremely complex,characterized by multi-objective,multi-users,multi-level,multiple uncertainties,and nonlinearity,etc.The high complexities made the traditional optimization model face difficulties in real-world studies.Therefore,in order to deal with these extremely complex situations in many practical problems of water resources management,it is urgent to adopt comprehensive and advanced methods and develop advanced tools for supporting water resources management.Based on the in-depth analysis and effective characterization of the complexity factors in the water resources allocation system,from the perspective of comprehensive management of the system,this study introduces bi-level programming,multi-objective programming,and multiple uncertain optimization technologies,and then develops the water resources allocation model with comprehensive consideration the system complexity,which is used in the case study of water resources allocation in the Dongjiang River basin.These methods include:(1)a dual-randomness bi-level interval multi-objective programming(DR-BIMP)method.The DR-BIMP is first improved from the traditional stochastic chance-constrained programming to double-sided stochastic chance-constrained programming and then combined with interval parameter programming,bi-level programming,and multi-objective programming.DR-BIMP is capable of: 1)tackling the problem of multiple conflicting tendencies among hierarchical decision-makers in complex water management systems through bi-level hierarchical strategy;2)characterize the interval dual-randomness uncertain information expressed as interval format and probability density functions.Then,it is applied to plan the water resources management system of the Dongjiang River basin.Discrete interval solutions of the water allocation scheme are generated.Moreover,the results show that the higher the probability of default,the higher the total water available for allocation,the more water resources allocated by all sectors,and the improvement of various decision-making objectives.(2)an integrated bi-level multi-objective programming(IBMP)with the consideration of dual random fuzzy information.Aiming at the problem of DR-BIMP's lack of considering the dual uncertainties of the same parameter,based on the DR-BIMP model,the IBMP method was developed by coupling random fuzzy variable tools.The IBMP method combines the advantages of the DRBIMP method,in particular,it broadens the ability to deal with the compound uncertainty(i.e.,randomness and vagueness)of the same parameter.Therefore,this method was also used in water resources planning in the Dongjiang River basin,the results indicate that: 1)when the violation probabilities remain unchanged,there is an obvious increase of the upper bound of water allocated by each sector and a decreasing trend of the lower bound from high value to low ones as ?-cut levels increasing,and the gap between the interval results will narrow;2)when ?-cut levels unchanged and the violation probabilities increase,the water allocation pattern of each sector would be increased;3)as the violation probabilities increase,each objective value gradually becomes better.This trend is consistent with the results obtained by the DR-BIMP method;4)and the upper bound of the economic benefit objective is decreasing and while the corresponding lower bound is increasing as ?-cut levels increases,meanwhile,the gap between interval results will narrow;On the other hand,the variation trend of social benefit objective presents an opposite trend.Overall,this research establishes several optimization methods to tackle the complexities of the system,which is an improvement and expansion of traditional optimization techniques.Through the coupling of multiple methods,the advantages of various optimization technologies can be fully utilized,and the depth of method research is continuously strengthened.And specific case studies show that the developed method can effectively deal with various complex problems in the water resources system,and the results obtained can help decision-makers formulate reasonable water resources planning policies.