Water Shortage Risk Assessment Using an Interactive Two-stage Stochastic Programming Model (Case Study: Marand Basin)

مجله اقتصاد و توسعه کشاورزی

Article 5, Volume 35, Issue 2 - Serial Number 52, July 2021, Pages 161-178   

Document Type: Research Article

DOI: 10.22067/jead.2021.69061.1017

Authors

J. Hosseinzad^* ; M. Raei Jadidi

Department of Agricultural Economics, University of Tabriz, Tabriz, Iran

Abstract

Introduction: In recent years, the problem of water scarcity is becoming one of the most challenging issues with the economic development and population growth that have involved many sectors due to its importance and economic status and has received increasing attention from governments and international research organizations. This emphasizes the need for optimal allocation of mentioned resources to balance socio-economic development and save water. Therefore, the aim of this study is to develop an uncertainty-based framework for agricultural water resources allocation and calculate the amount of water shortage after allocation and also risk evaluation of agricultural water shortage. The developed framework will be applied to a real case study in the Marand basin, northwest of Iran. Perception of the amount and severity of risk on the system can be a good guide in the optimal allocation of resources and reduction of damage.
Materials and Methods: Since various uncertainties exist in the interactions among many system components, optimal allocation of agricultural irrigation water resources in real field conditions is more challenging. Therefore, introduction of uncertainty into traditional optimization methods is an effective way to reflect the complexity and reality of an agricultural water resources allocation system. Among different methods, inexact two-stage stochastic programming (ITSP) has proved to be an effective technique for dealing with uncertain coefficients in water resources management problems. ITSP is incapable of reflecting random uncertainties that coexist in the objective function and constraints. Considering the risk of violating uncertain constraints and the stochastic uncertainty of agricultural irrigation water availability on the right hand side of constraints and uncertainties related to economic data such as the revenue and penalty in the objective function which are expressed as probability distributions, the CCP method and Kataoka’s criterion are introduced into the ITSP model, thus forming the uncertainty-based interactive two-stage stochastic programming (UITSP) model for supporting water resources management. A set of decision alternatives with different combinations of risk levels applied to the objective function and constraints can be generated for planning the water resources allocation system. In the next step, on the basis of results of UITSP agricultural irrigation water shortage risk evaluation can be conducted by using risk assessment indicators (reliability, resiliency, vulnerability, risk degree and consistency) and the fuzzy comprehensive evaluation method.
Results and Discussion: A series of water allocation results under different flow levels and different combinations of risk levels were obtained and analyzed in detail through optimally allocating limited water resources to different irrigation areas of Marand basin. The results can help decision makers examine potential interactions between risks related to the stochastic objective function and constraints. Furthermore, a number of solutions can be obtained under different water policy scenarios, which are useful for decision makers to formulate an appropriate policy under uncertainty.
The results show that the dry season, i.e., July, August and September are the peak periods of water allocation and demand in Marand basin, which in these months, despite the higher water demand, the amount of water allocation in the current situation is less, which leads to more water shortages in these months. However, the results show that by increasing the efficiency of irrigation and water allocation using the developed framework, the amount of agricultural water allocation and demand is almost balanced and in addition to reducing water shortages, it leads to control over extraction from wells. Also, the goals of the regional water organization, which is reducing the amount of water allocated in the agricultural sector, will be achieved. Comparison with actual conditions shows that the allocation of water resources using the developed framework reduces water shortages while allocation becomes more efficient. Furthermore, the net system benefits per unit water increase which will demonstrate the feasibility and applicability of the developed framework. Results of evaluation of agricultural irrigation water shortage risks indicate that the water shortage risks in the Marand basin are in the category of serious or critical risk level. Therefore, if the current trend of allocation and exploitation of water resources continues, with the population growth, climate change, increasing demand for agricultural products and changing the probability of available water in the future, the water shortage risk would increase to the unbearable risk level. The continuation of this process threatens all investments and economic foundations of this study area. Therefore, the risk of water shortage in the future should be managed by improving the water-saving technologies and also changing the cultivation pattern to drought resistant crops.
Conclusion: In this study, an uncertainty-based framework for agricultural water resources allocation and risk evaluation was developed, including model optimization of agricultural water and risk evaluation of water shortage. The developed framework is capable of fully reflecting multiple uncertainties. The developed framework will be helpful for managers in gaining insights into the tradeoffs between system benefits and related risks, permitting an in-depth analysis of risks of agricultural irrigation water shortage under various scenarios. The assessment of agricultural water shortage risk based on the results of the optimization model helps decision makers to obtain in-depth analysis of agricultural irrigation water shortage risk under various scenarios. In application of the developed framework to Marand basin, series of results of agricultural water resources allocation expressed as intervals, and agricultural water shortage risk evaluation levels under different flow levels and also different combinations of risk levels are generated. Comparison between optimal results and actual conditions of agricultural irrigation water allocation demonstrates the feasibility and applicability of the developed framework. Results of evaluation of agricultural irrigation water shortage risks indicate that the water shortage risks in the Marand basin are in the category of serious or critical risk level. Therefore, effective risk management measures should be taken first for different irrigation areas of Marand basin.

Keywords

Fuzzy comprehensive evaluation; Interactive two-stage stochastic programming; Risk evaluation; Uncertainty; Water management

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