With the growth of population and human activities, the shortage of water resources has become a more serious concern in recent years. Many countries and regions are facing the serious problem of water shortages, which not only poses a great threat to commercial activities but also poses a great threat to human beings [1
]. The scarcity of water resources seriously restricts the development of human society. As the largest freshwater user in industry, agriculture accounts for more than 70% of global freshwater consumption among all water-consuming sectors. In addition, inefficient water-use patterns also exacerbate the conflict between water demand and water supply in the agricultural water management system [2
]. Water is the main resource of the agricultural food industry, and pressures to reduce consumption in line with conserving environmental and natural resources are considered to be the dominant driving force of agricultural water management in the food supply chain [3
]. How to ensure the realization of agricultural water savings on the basis of food security has become a major global concern in the 21st century [4
] within the water-intensive industries [5
]. In the context of water scarcity, water resource management has attracted the interest of various disciplines, and the role of the private sector in integrated water resource management in the agri-food supply chain is growing [6
]. In addition, the concept of water management has further aroused private sector interest in integrated water management, in which the role of corporations as water managers transforms the global water governance landscape by participating in water management and mitigating the negative environmental and social impacts of their supply chains. Water management has been identified as a new framework for enterprises to participate in water resource management [7
]. With the improvement of consumers’ awareness of environmental protection, consumers’ demand for water-saving products increases, thus making enterprises more responsible for their water resource management [8
]. At the same time, a series of tools, assurance, and certification programs related to enterprise water resource management has emerged. This reflects the increased awareness of the operational, environmental, and reputational risks in the corporate sector, and this trend is accompanied by increasing pressure from multiple stakeholders to demonstrate transparency in water management [9
The current production systems in the agri-food industry are highly dependent on water [10
]. For the company, there is a drive to improve profitability and competitiveness from the management of water, as efficient water management helps to reduce production costs [11
]. Water management practices can also improve the participation of the various stakeholders in the supply chain, encourage not only the companies themselves but also suppliers, customers, Non-Governmental Organization (NGOs), and the public sector to participate in water management practices [12
]. Policy pressures are seen as another major driver in the agricultural food supply chain. Policymakers tend to formulate new policies, urging food companies to pay more attention to the management of water in agriculture in order to improve its sustainable supply chain performance [13
]. The commission stressed that agriculture needs a more flexible approach to better cope with the current and future economic, social, and environmental challenges. Hence, supporting the resilience of agricultural systems has become an important objective of the post-2020 Common Agricultural Policy recommendations [14
In terms of agricultural water resources management, Jellasonn [15
] systematically analyzed 1086 articles by Scopus and Google scholars and found that long-term arid desertification and water dryness are common features of long-term challenges for smallholders to achieve resilience and agricultural sustainability in arid regions. Through a statistical analysis of the water resources in Tunisia, an arid country in the Mediterranean Sea, Ahmed [16
] found that the use of unconventional water resources (saltwater and treated wastewater) has become very urgent. The selection of water-saving and drought-resistant, and saline-alkali resistant varieties through the drip irrigation system is very important for agricultural development. Yu [17
] conducted a meta-analysis of global drylands (81 studies and 836 paired observations) to evaluate the response of various crops to drought and found that improving crop water-use efficiency can ensure the sustainable development of food production in drylands. Wang [18
] used the results of a Tobit model to show that agricultural investment and production, economic growth, industrial structure adjustment, and agricultural plant structure adjustment have important effects on agricultural water-use efficiency.
Water-use efficiency (WUE) directly affects the water consumption of agricultural production and is of great importance to local and regional water savings. Agricultural water-use efficiency is also a key indicator reflecting the effective allocation of water and the improvement of water productivity in different agricultural sectors. These research results can provide important references for agricultural water management in the middle reaches of the Huaihe River Basin and other similar areas in Northwest China. Hadizadehf conducted a survey on paddy farmers, using exploratory factor analysis, revealing the influence of rice farmers on the agricultural water management considering five factors: (i) the usability of the irrigation infrastructure, (ii) planting patterns, (iii) the support of local institutes, (iv) irrigation experience, and (v) traditional beliefs. These factors combined accounted for 60.1% of the total balance of water management in agriculture. These findings provide a better understanding of the drivers of integrated agricultural water management by paddy farmers and help policymakers focus on strategies to improve irrigation water productivity and support more sustainable water use in rice production in the study area and in similar drought-crop regions around the world [19
Wu modeled the Borley Ecoecosystem Productivity Simulator with remote sensing data and observation data of ground stations as input and believed that drought index based on remote sensing data could promote dynamic agricultural drought assessment, and the obtained drought index could provide dynamic information for real-time monitoring. These results can provide important references for agricultural water resources management in arid areas [20
]. Guiqin, based on gray relation analysis (GRA), developed a method to estimate the agricultural water vulnerability and identified the main factors that influence the development of agricultural drought susceptibility [21
]. Ridouttb believes that in the life cycle of a product, the primary production stage often has the greatest impact on water resources, but it should also consider the interaction between different stages of the supply chain and how the company’s role in water management affects its supply chain, as global supply chains are becoming more and more complex. The impact on water resources is often far away from the final consumer of products [22
]. A variety of water conditions can lead to an imbalance of space and time distribution of water resources and have a profound influence on the risk of water shortage. In order to meet our demand for water resources, changes to the water supply in space and time are necessary to determine the critical path of resilience and the critical point at which the natural freshwater system is reformed [23
Water governance continues to be a challenge for human society, with the increasing scale and frequency of adverse events caused by climate and anthropogenic change and the occurrence of crises in water resources systems [25
]. Through planning the use of water resources, it is found that there is a potential synergistic effect of water-use planning on water resilience [27
]. The interaction between water managers, users, and water components affects the implementation of water planning [28
]. On the supply side of water resources, economic capacity and rapid access to funds are the main economic factors affecting the resilience of water supply systems [29
]. Drip irrigation, which has been widely used in arid areas in recent years, can make an important contribution to more sustainable water use in drought-prone areas, but the autonomy of localized irrigation systems needs more attention from local governments [30
]. Liu used the support vector machine model based on the improved gray wolf optimization algorithm (IGWO-SVM) to evaluate the resilience of agricultural irrigation in a severe cold region and put forward targeted suggestions for local water resources management [32
In terms of water resilience, Hashimotot is the first to assess the sustainability of water systems using traditional reliability, resilience, and vulnerability (RRV) criteria. These performance criteria refer to how likely the system is to fail (reliability), how severe the consequences of failure (vulnerability) are, and how quickly it can recover from failure (resilience) [33
]. Resilience is defined as the ability of a water management system to “bounce back”, that is, absorb and then recover from water scarcity events and return to normal system functioning [34
]. The concept of resilience has become increasingly prominent in water policy and research over the past decade [35
]. Resilience criteria denote the ability of water resource systems to absorb the impact of an event and return to an acceptable operational condition after a disturbance. These performance criteria refer to how likely a system is to fail (reliability), how severe its consequences are (vulnerability), and how quickly it can recover from failure (resilience) [36
]. Imanim developed a new application using artificial neural networks (ANN) to predict water quality resilience and simplify resilience assessment [37
Kharrazia examines system-level configurations and trade-offs related to water resource resilience management using a holistic approach called ecological network analysis (ENA) [38
]. Xue B. [39
] investigated different crops functional types of drought field level and watershed hydrology resilience and found the hydrological resilience of crops is related to drought intensity and water-use efficiency. These research results can provide important references for crop water efficiency and the choice of crops in arid regions [38
]. Royr established a framework for agricultural resilience that includes three capacities (absorptive, adaptive, and transformative) and five dimensions (social, economic, ecological, physical, and institutional). Using a combination of top-down and bottom-up approaches, 15 indicators were developed to assess the resilience of coastal agricultural systems that were used to develop a strategy for the management of coastal agricultural systems in Bangladesh [40
]. Lim developed a risk-based interval optimization modeling method for agricultural water allocation in view of the complexity of uncertainty and risks in agricultural water management systems. The method includes a conditional value at risk (CVaR) model, a two-stage stochastic programming (ITSP) model with inexact probability (IPS), and a stochastic boundary interval (RBI) in general framework. This method can balance the expected benefits, penalties, and risks of agricultural water allocation at the same time, solve the uncertainty of agricultural water supply and demand in the form of probability distribution and random boundary interval [41
Behboudian, M. [36
] used a new method for quantifying the total resilience of water management scenarios. The effects of climate change on water supply and demand were investigated using calibrated soil and water assessment tools and water distribution models. Water resource system resilience is measured from five aspects. The first aspect defines resilience as the strength of the system to resist crossing performance thresholds (reliability). In the second aspect, if the system exceeds the performance threshold, the recovery rate of the system after the disturbance is assessed. Violations of the performance threshold have been factored into a third dimension (vulnerabilities), which takes into account the severity of the failure. The fourth dimension is resilience to extreme events with unknown probability, which includes four sub-criteria, namely speed, robustness, resourcefulness, and redundancy (4R). The fifth criterion takes into account the ecological status of the system (ecological index). To compare water resource management options (alternatives), a method based on analytical evidence reasoning (ER) was used [42
]. NAMW proposed a practical method to assess water supply vulnerability and sustainability by using climate change based on time-dependent analysis of water supply and demand and applied the vulnerability assessment model to evaluate and predict the potential impact of agricultural water demand and supply on reservoir operation, so as to improve local water management under climate variability and change [43
]. Dardon Villem [44
] believes that susceptibility, resilience, robustness, and adaptability are the four key concepts of system dynamics in the event of a disturbance. However, making them operable for agricultural systems using quantitative dynamic methods remains a challenge [43
According to previous research results, work on water resources management in the agricultural supply chain is mainly concerned with the agricultural water-use efficiency and mainly focuses on the management of water reduction in specific stages of the agricultural supply chain (usually primary production), for example, using drip irrigation technology and wastewater recycling technology. The driving factors for water management in the agricultural supply chain are mainly the background of water shortage, policy pressures, and private sector participation. Moreover, the imbalance of the spatial and temporal distribution of water resources encountered by various water sources has a profound impact on the risk of water shortage. The artificial change of water supply in space and time is the key approach to resilience, and there is a potential synergistic effect on the planning and use of water resources and water resilience. The main research on the resilience of water resources is to evaluate the resilience of water resources by establishing various resilience frameworks, but the quantitative assessment of the resilience of water resources management has not been introduced into the agricultural supply chain. Furthermore, there is also a lack of a comprehensive framework for the resilience of water resources management of the entire agricultural supply chain.
To fill this gap, this paper focuses on improving water management resilience at multiple stages of the agri-food supply chain. A conceptual framework for integrated water management in the agricultural supply chain is proposed by summarizing the main findings of current research, combining agricultural water management with resilience, and taking agriculture in Northwest China as an example. Through the combination of ISM and ANP, a multi-level hierarchical structure model composed of direct factors, indirect factors, and basic factors is obtained. The study considers the agricultural water management supply chain, moving from a single phase to multiple stages and moving from a focus on agricultural water-use efficiency to consider more widely the resilience of agricultural water resources.
This study uses a quantitative approach to investigate the factors influencing the resilience of water resource management in the agricultural supply chain and proposes an integrated model. In order to consider the interaction network among various factors of the water resource management, a structural model was used to establish the hierarchical structure of water management resilience in the agricultural supply chain. The main influencing factors of water resources management in the agricultural supply chain were determined, including crop selection, water audit control system, wastewater recycling, and investment in water-saving technology. This model can effectively reflect the focus of improving the resilience of water resources management in agricultural supply chains. This water resource management resilience assessment method can be applied to the group decision-making method in agricultural supply chain management and can also be used to determine the interdependence among the key factors affecting the resilience of agricultural water resources. Some main conclusions can be drawn.
The model combined with the analytical network process method and interpretative structural model can be used to analyze the relationship between the factors affecting the resilience of water resources management in the agricultural supply chain. The interpretative structural model (ISM) was then used to build a three-level evaluation network. Surface direct factors include investment in water-saving technologies, reduction in waste, careful use of chemical agents, improved water retention in soils, public sector water management policies, crop selection; Indirect factors include the recycling of wastewater, the improvement of traditional crops, the setting of reasonable water prices, and the identification of water risk; The basic factors include stakeholder participation, awareness of water conservation, the establishment of a water audit control system, and integration of water management into corporate strategy, reflecting the root and nature of the problems affecting the resilience of water management in the agricultural supply chain.
A network analysis method was used to calculate the weight of each factor. The establishment of water audit control system in the system is the main factor, followed by crop characteristics, accounting for 0.23. Crops, established water audit control systems, the choice of wastewater recycle use, and impact on water-saving technology investment are the main factors of agricultural water management resilience in the supply chain.
This research used the ISM method and analytic network process to comprehensively and systematically consider the agricultural water management of supply chain resilience. The mutual influence between the evaluation index and the importance of every index was used to determine the causal relationship between influencing factors. This provides a more scientific analytical framework for the development of agricultural supply chain water resources management ability in Northwest China. Furthermore, this also provides beneficial guidance for practitioners involved in agricultural supply chain management and the effective allocation of water resources.
Each index was quantified, and the weight of each index in each dimension was calculated by using the ANP method, and the resilience of water resources management in the agricultural supply chain was evaluated. According to the results, the five dimensions of agricultural supply chain management of water resources have varying significance on resilience. This suggests that, when making the appropriate interventions, measures need to be considered and weighted by the proportion of different dimensions to effectively improve the resilience of water resources management in the agricultural supply chain. According to earlier studies on arid areas in China, most of the areas have similar management systems and environmental characteristics. Therefore, the procedures identified in this study can be incorporated into a new approach to promote resilience assessment of water management in the agricultural supply chain through multiple indicators. Further, these findings and are generally applicable to other regions with similar levels of economic development, climatic characteristics, and management systems. However, the main factors affecting the resilience of agricultural supply chain water resources management will change with the development of the economy, policies and institutions, climate and environment, and other objective factors influencing the development of water-saving technology. Therefore, in future work, we will focus on the application of this evaluation method. It is necessary to apply the ISM-ANP model to establish a resilience framework for water management in the agricultural supply chain in order to help governments, farmers, and agricultural supply chain companies develop preventive, early warning, and mitigation measures using predictive analysis techniques.