Stochastic multi-objective decision making for sustainable irrigation in a changing environment

doi:10.1016/j.jclepro.2019.03.183

Journal of Cleaner Production

Volume 223, 20 June 2019, Pages 928-945

https://doi.org/10.1016/j.jclepro.2019.03.183 Get rights and content

Highlights

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A stochastic multi-objective model is presented for sustainable irrigation.
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Mutual contradictions of society, economy, and resources are coordinated.
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Effects of uncertainty and climate change on irrigation water allocation are evaluated.
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Sustainability of the studied irrigation system is evaluated.
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Various managerial insights of irrigation allocation are offered.

Abstract

Agricultural water scarcity is a global problem and effective management of limited water resources for irrigation to meet socioeconomic demands for sustainable development is a huge challenge. A stochastic multi-objective non-linear programming (SMONLP) model is developed for the identification of sound irrigation water allocation schemes. The SMONLP model improves upon previous methods by tackling contradictions of society-economy-resources as well as reflecting uncertainty expressed as probability distributions in an agricultural irrigation system. The SMONLP model permits in-depth analyses of various water allocation policies that are associated with different levels of water supply and climate change. The developed SMONLP model is applied to optimal irrigation allocation in a semi-arid river basin in China. Results reveal that the model coordinates the regulation of interactions of society-economy-resources by balancing the targets of water productivity, allocation equity, profit, economic benefit risk, blue water utilization, and leakage loss. Moreover, surface water availability associated with different violation risk probabilities can lead to the changes in comprehensive benefit of society-economy-resources and irrigation shortages. Nearly each of the 17 irrigation regions suffers from water deficit, because water is insufficient to satisfy the requirement of crops, however, the degree of water shortage is gradually weakened when flow level ranges from low to high. The coordination degree is also used to evaluate the sustainability of water allocation and the results of comparison show that the irrigation water allocation under RCP 4.5 presents lower coordination of society-economy-resources which are mainly attributed to the aggravated contradiction between water supply and demand. A real world study demonstrates the practicability of the developed model, allowing the river basin authorities to determine irrigation water allocation strategies in a changing environment, thus promoting sustainable development of agricultural irrigation systems.

Introduction

A major socio-economic and global sustainability issue is the increasing severity of water shortages due to increasing demands and decreasing supplies (Abdulbaki et al., 2017). Agriculture is the biggest water consumer of water resources and more water is needed for irrigation to increase food production for the burgeoning global population. However, water is transferred from low-value agricultural irrigation to high-value users, such as domestic, industrial and hydroelectric (Liu et al., 2017). Besides, the low efficiency of irrigation water utilization and less than up-to-date management of agricultural irrigation systems intensify irrigation water crisis, putting additional stress on the performance of agriculture. Such problems are particularly acute in primarily agricultural countries, such as China. Therefore, optimal management of agricultural irrigation is a potential way to mitigate water shortages, thus promoting agricultural water management.

Irrigation management through optimization modelling has received considerable attention for identifying effective irrigation water allocation strategies (Norry et al., 2012, Singh, 2014, Yang et al., 2015, Ren et al., 2017). Many studies have optimized irrigation water resources with the aim of maximizing crop yield or consequent benefits (Georgiou and Papamichail, 2008, Guo et al., 2014). However, agricultural irrigation systems are complex due to the interactions among natural resources, social, economic and ecological environment elements. For sustainable development of agricultural irrigation systems, irrigation management, comprehensively considering these elements, is needed. Sustainable development entails the tradeoff in balancing the benefit from both social and economic dimensions satisfying the water requirement of ecological environment through effective utilization of limited water resources without influencing the development of future generations (Cai et al., 2002, Li et al., 2019). To this end, multi-objective programming models have received much attention.

Some researchers have dealt with sustainable management of agricultural irrigation systems using multi-objective programming. For example, Fasakhodi et al. (2010) optimized sustainability indicators expressed as “net return/water consumption” and “labor employment/water consumption” using a multi-objective fractional goal programming in an agricultural irrigation system. Gurav and Regulwar (2012) presented a multi-objective sustainable irrigation planning model maximizing the net benefit, crop production, employment generation, and manure utilization. Li et al. (2017) proposed a fuzzy multi-objective non-linear programming to optimally allocate irrigation water resources balancing the objectives of crop yield, water cost, and water utilization. However, more elements associated with society, economy, and resources need to be considered in order to more efficiently resolve conflicts in agricultural irrigation systems. For example, although crop yield can be regarded as an indicator of social benefit through satisfying food security, agricultural water managers aspire to improve irrigation efficiency rather than simply increase crop production especially in arid and semi-arid regions that have severe water shortages. Additionally, for large agricultural irrigation systems, the equitable access to irrigation water, which is closely related to social stability, is critical for eradicating poverty. Besides net profit, the risk of diminishing economic returns attributed to the variation in water availability should also be considered to better reflect the economic benefit. Further, irrigation water-saving as well as leakage loss should be taken into account to improve water utilization efficiency. However, few studies have simultaneously considered these elements associated with society, economy and resources to seek participatory management options for the sustainable utilization of water resources in agricultural irrigation systems.

In agricultural irrigation systems, optimal water resources allocation schemes vary in response to the temporal changes of available water resources (Zhang and Guo, 2018, Li et al., 2018). Such schemes can be based on stochastic mathematical programming wherein parameters in the objective function or constraints are represented by probability distributions. A major type of stochastic programming is chance constrained programming (CCP) which requires that all of the constraints be satisfied in a proportion of cases under given probability levels and is effective for optimization where the right-hand-side coefficients are random (Guo and Huang, 2009, Guo et al., 2010). In order to evaluate the impact of fluctuations of irrigation water availability on irrigation allocation schemes, incorporating CCP into the multi-objective programming model for sustainable irrigation management is essential, but has rarely been considered in the literature. Besides, irrigation water allocation is under constant threat from changing environment mainly embodying climate change and human activities. Climate change seems to have shifted the balance of water supply and water demand, and thus affects irrigation water allocation. Specifically, climate change affects water supply mainly attributing to the changes in precipitation and temperature (Kang et al., 2009). And meanwhile, climate change affects irrigation water demand via physiology and phenology, effective precipitation, evapotranspiration and soil water balances (Shahid, 2011). Impact of human activities on irrigation water allocation includes withdrawal of water from both rivers and aquifer through hydraulic engineering, and man-made changes in land use and water-saving measures. How optimal irrigation water schemes change with reliability of satisfying (or risk of violating) water availability constraints being considered in a changing environment has captured the attention of decision makers.

In a changing environment, different scenarios such as different flow levels, risk confidence levels, importance levels of different targets, different climate conditions, etc. will directly and significantly cause changes of various irrigation water allocation schemes. Among various schemes of irrigation water allocation, choosing the schemes that are optimal is another issue that decision makers are interested in. Optimal schemes can be identified by evaluating various schemes. Among many evaluation methods, the synergy theory has been found as an effective way to evaluate the sustainability of water resources allocation schemes by studying the degree of coordination of each dimension of a society-economic-resources system (Li et al., 2015a, Zhao et al., 2017). However, the system of indicators used in the previous studies often involve indicators with no connection with optimal irrigation allocation, leading to a water-insensitive evaluation result. In order to solve this problem, the indicators of each dimension associated with society, economy and resources should be representative and have a direct relationship with changes of water allocation. Hence, all the objective function values of the multi-objective programming model will be considered as indicators based on the optimal irrigation water allocations in a changing environment to clearly evaluate the sustainability of agricultural irrigation systems. However, such an analysis for optimal irrigation water allocation schemes has rarely been done.

The objective of this study therefore is to develop a stochastic multi-objective non-linear programming (SMONLP) model for sustainable irrigation management in response to the above challenges. The SMONLP model will incorporate CCP into a multi-objective linear/nonlinear programming framework to cope with uncertainties expressed through probability distributions. The objective of the SMONLP model is to achieve the optimal comprehensive benefit of irrigation productivity promotion, irrigation equity, net profit increase, economic benefit loss risk, blue water saving, and leakage loss reduction. The SMONLP model will be applied to allocate limited surface water and groundwater resources to different subareas in the middle reaches of Heihe River basin, northwest of China. Results of different irrigation allocations will be generated by considering the fluctuation of water availability and climate change, and then, the sustainability of these results will be evaluated. Results of this study will offer insights into the tradeoff among system comprehensive benefit, irrigation strategy, and agriculture sustainability.

Section snippets

Overview of the problem

In an irrigation water allocation process, the available water resources consisting of both river water and groundwater will be allocated to each subarea of an irrigation-dominated river basin in which water resource is one of the major restrictions to the basin's development. Water allocation to different subareas may result in different development modes. In order to improve the sustainable development of a river basin, benefits of society, economy and resources utilization should be

Study site

The proposed model was utilized for the middle reaches of Heihe River basin. Heihe River basin is the second largest inland river basin in northwest China. Heihe River basin is divided into upper, middle and lower reaches, among which, the middle reaches (98°–101°30′E, 38°–42°N) that are between Yingluoxia hydrometric station and Zhengyixia hydrometric station are the main irrigated agricultural area, concentrating 90% of the total irrigation water use in the whole Heihe River basin. The middle

Results of SMONLP model

The SMONLP model was solved based on the weighted minimum deviation method, thus, the weights of different objectives need to be set first. In order to avoid the subjective preference for different objectives, the same weights for different objectives were set, i.e. the weight of 0.1666 for each objective function was adopted in this study. By coding the developed SMONLP model in the optimization software, optimal water allocation results for different irrigation regions in different months

Conclusion

This paper developed a stochastic multi-objective non-linear programming (SMONLP) model for sustainable irrigation in a changing environment. Three advantages that make the developed model unique by comparison with previous methods in agricultural water management are: (1) The SMONLP model balances the competing goals associated with social, economic, and resources dimensions that are interactive in an agricultural irrigation system, which will be conducive to the sustainable allocation of

Acknowledgments

This research was supported by the National Natural Science Foundation of China (No. 51809040, 91425302, 51709195), National Science Fund for Distinguished Yong Scholars of China (51825901), and Natural Science Foundation of Heilongjiang Province of China (E2018004).

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View full text

Stochastic multi-objective decision making for sustainable irrigation in a changing environment

Highlights

Abstract

Introduction

Section snippets

Overview of the problem

Study site

Results of SMONLP model

Conclusion

Acknowledgments

J. Clean. Prod.

J. Hydrol.

J. Hydrol.

Agric. Water Manag.

Adv. Water Resour.

Eur. J. Oper. Res.

J. Hydrol.

Agric. Water Manag.

Prog. Nat. Sci.

J. Hydrol.

Sci. Total Environ.

Appl. Math. Model.

Ecol. Eng.

J. Clean. Prod.

J. Clean. Prod.

Eur. J. Oper. Res.

Agric. Water Manag.

Ecol. Indicat.

J. Clean. Prod.

Waste Manag.

A framework for sustainability analysis in water resources management and application to the Syr Darya Basin

Water Resour. Res.

Water resources sustainability and optimal cropping pattern in farming system: a multi-objective fractional goal programming approach

Water Resour. Manag.

Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions

Irrig. Sci.