Inter-basin water transfer is a large-scale artificial method to transfer water from water-surplus areas to water-deficient areas, so as to promote the economic development of water-deficient areas. In this paper, water call options are introduced to improve the management of inter-basin water transfer. As the seller of water call options, the water diversion area benefits from water call options, as well as bears the risk of a water shortage caused by the exercises of water call options. On the one hand, the economic benefit of the system can be maximized by choosing the maximum water availability and the exercise prices of water call options. On the other hand, by using water call options, the water diversion area obtains certain economic compensation and the water receiving area gains additional water to ensure water security in dry seasons. By considering the uncertainties in the process of water resource management, an interval two-stage stochastic multi-objective mixed integer programming (ITSMMIP) model is developed for supporting decisions of water resource allocation when water call options are applied in inter-basin water transfer. The results prove the effectiveness of the model.
References
[1]
(2015) China’s South-North Water Transfer Project. Chinese American Forum, 30, 36-38.
[2]
Frederick, K.D. (1998) Marketing Water: The Obstacles and the Impetus. Resource, 132, 7-10.
[3]
Zeng, X.T., et al. (2014) Inexact Mathematical Modeling for the Identification of Water Trading Policy under Uncertainty. Water, 6, 229-252. https://doi.org/10.3390/w6020229
[4]
Ramos, A.G. and Garrido, A. (2004) Formal Risk-Transfer Mechanisms for Allocating Uncertain Water Resources: The Case of Option Contracts. Water Resources Research, 40, 73-74. https://doi.org/10.1029/2004WR003340
[5]
Hansen, K., Kaplan, J. and Kroll, S. (2014) Valuing Options in Water Markets: A Laboratory Investigation. Environmental & Resource Economics, 57, 59-80. https://doi.org/10.1007/s10640-013-9659-6
[6]
Rey, D., Calatrava, J. and Garrido, A. (2016) Optimisation of Water Procurement Decisions in an Irrigation District: The Role of Option Contracts. Australian Journal of Agricultural and Resource Economics, 60, 130-154. https://doi.org/10.1111/1467-8489.12110
[7]
Tomkins, C.D. and Weber, T.A. (2010) Option Contracting in the California Water Market. Journal of Regulatory Economics, 37, 107-141. https://doi.org/10.1007/s11149-009-9107-2
[8]
Ha, M. and Gao, Z. (2017) Optimization of Water Allocation Decisions under Uncertainty: The Case of Option Contracts. Journal of Ambient Intelligence and Humanized Computing, 8, 809-818. https://doi.org/10.1007/s12652-017-0551-z
[9]
Byrnes, J., Crase, L., Dollery, B., et al. (2010) Water Options Contracts to Facilitate Intersectoral Trade. WIT Transactions on Ecology and the Environment, 112, 83-92. https://doi.org/10.2495/978-1-84564-406-2/09
[10]
Jafarzadegan, K., Abed-Elmdoust, et al. (2014) A Stochastic Model for Optimal Operation of Inter-Basin Water Allocation Systems: A Case Study. Stochastic Environmental Research & Risk Assessment, 28, 1343-1358. https://doi.org/10.1007/s00477-013-0841-8
[11]
Luo, B. (2003) Adaption to Climate Change through Water Trading under Uncertainty—An Inexact Two-Stage Nonlinear Programming Approach. Journal of Environmental Informatics, 2, 58-68. https://doi.org/10.3808/jei.200300022
[12]
Gu, J.J., Guo, P. and Huang, G.H. (2013) Inexact Stochastic Dynamic Programming Method and Application to Water Resources Management in Shandong China under Uncertainty. Stochastic Environmental Research & Risk Assessment, 27, 1207-1219. https://doi.org/10.1007/s00477-012-0657-y
[13]
Molinos-Senante, M., Hernández-Sancho, F., Mocholí-Arce, M., et al. (2014) A Management and Optimisation Model for Water Supply Planning in Water Deficit Areas. Journal of Hydrology, 515, 139-146. https://doi.org/10.1016/j.jhydrol.2014.04.054
[14]
Han, Y., Huang, Y.F., Wang, G.Q., et al. (2011) A Multi-Objective Linear Programming Model with Interval Parameters for Water Resources Allocation in Dalian City. Water Resource Management, 25, 449-463. https://doi.org/10.1007/s11269-010-9708-7
[15]
Dou, X. (2018) China’s Inter-Basin Water Management in the Context of Regional Water Shortage. Sustainable Water Resources Management, 4, 519-526. https://doi.org/10.1007/s40899-017-0134-3
[16]
Huang, G.H. and Loucks, D.P. (2000) An Inexact Two-Stage Stochastic Programming Model for Water Resources Management under Uncertainty. Civil Engineering and Environmental Systems, 17, 95-118. https://doi.org/10.1080/02630250008970277
[17]
Stancu-Minasian, I.M. (1984) Stochastic Programming with Multiple Objective Functions. D. Reidel Publishing Co., Dordrecht.
[18]
Caballero, R., Cerda, E., Munoz, M.M., et al. (2000) Relations among Several Efficiency Concepts in Stochastic Multiple Objective Programming. In: Haimes, Y.Y. and Steuer, R.E., Eds., Research and Practice in Multiple Criteria Decision Making, Springer, Berlin, 57-68. https://doi.org/10.1007/978-3-642-57311-8_4
[19]
Abdelaziz, F.B., Aouni, B. and Fayedh, R.E. (2007) Multi-Objective Stochastic Programming for Portfolio Selection. European Journal of Operational Research, 177, 1811-1823. https://doi.org/10.1016/j.ejor.2005.10.021
[20]
Caballero, R., Cerdá, E., del Mar Muñoz, M., et al. (2004) Stochastic Approach versus Multiobjective Approach for Obtaining Efficient Solutions in Stochastic Multiobjective Programming Problems. European Journal of Operational Research, 158, 633-648. https://doi.org/10.1016/S0377-2217(03)00371-0
[21]
Li, Y.P. and Huang, G.H. (2008) Interval-Parameter Two-Stage Stochastic Nonlinear Programming for Water Resources Management under Uncertainty. Water Resources Management, 22, 681-698. https://doi.org/10.1007/s11269-007-9186-8
