Impacts of irrigation efficiency improvement on water use, water consumption and response to water price at field level

Berbel, Julio; Gutiérrez‐Martín, Carlos; Expósito, Alfonso

doi:10.1016/j.agwat.2018.02.026

Cited by 82 publications

(34 citation statements)

References 38 publications

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“…A number of studies have attempted to assess the impact of irrigation water use improvements on water saving, highlighting that the expansion of irrigated land and changes in crop patterns are major factors behind this effect [93,94]. Our results show that irrigation efficiency enhancement generally reduces water use, yet this factor has only a minor effect on irrigated land increases [11]. Nevertheless, changes in crop patterns are expected, with an increase in irrigated land devoted to permanent crops, in line with empirical studies [49,50] and prospects from stakeholders.…”

Section: Discussionmentioning

confidence: 60%

“…In this regard, irrigation efficiency gains can contribute to lower water use and reduce crop-responsiveness to water costs. As illustrated by Berbel et al [11], who conducted a microeconomic analysis to investigate the effects of irrigation efficiency enhancement on water use and water consumption on maize in the Mediterranean, water demand functions are more inelastic as irrigation efficiency increases.…”

Section: Discussionmentioning

confidence: 99%

“…That is why there are limited assessments that have analysed the impacts of climate change on agricultural and food markets considering the water dimension, despite the broadly acknowledged need to incorporate the water dimension in climate change research [7][8][9]. Studies that explored economic impacts of water use in agriculture were primarily conducted at the basin, farm, and plot levels, providing relevant insights into agriculture and water interrelations [10,11]. However, these studies generally neglected market feedback, which is an important driver in agricultural production [12].…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of Agricultural Development to Water-Related Drivers: The Case of Andalusia (Spain)

Martínez

Blanco

2019

Water

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Future agricultural development will be challenged by the impacts of climate change on water, which are expected to be particularly strong in southern European regions. Thus, exploring interrelations between agriculture and water under climate change is essential to frame informed policies that ensure sustainable water management while enhancing food production. Nevertheless, studies that address future agriculture development focus on climate-induced changes in crop productivity and often disregard the water dimension. In this research, we have conducted a sensitivity analysis of agricultural development to drivers of water use in Andalusia in 2050 based on outcomes from the CAPRI-Water model. The results from the analysis show that water cost is the most determinant factor in shaping agricultural land, offsetting the impact of the driver of water availability. In contrast, irrigation water use is driven not only by water cost but also by irrigation efficiency. The magnitude of the sensitivity to these drivers differs significantly across crops. Policies aimed at improving resource use efficiency can contribute to strengthening the resilience and adaptation capacity of future agricultural systems to climate change. To achieve this goal, the policies must consider crop sensitivity to irrigation costs and the potential rebound effect.

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Section: Discussionmentioning

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sensitivity of Agricultural Development to Water-Related Drivers: The Case of Andalusia (Spain)

Martínez

Blanco

2019

Water

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“…Therefore, it was not possible to numerically compare the results of the present study with those of the previous ones. In previous studies [2,21,[75][76][77][78][79][80][81], the AW is carried out between different sectors in the region, between the catchment areas, between irrigation networks, and between cultivated crops (e.g., the AW to all lands cultivated with wheat in a region). In some relatively similar studies, the water is allocated at farm level, but for the entire growing season and not on a monthly basis.…”

Section: Discussionmentioning

confidence: 99%

Irrigation Water Allocation at Farm Level Based on Temporal Cultivation-Related Data Using Meta-Heuristic Optimisation Algorithms

Saeidian

Mesgari

Pradhan

et al. 2019

Water

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The present water crisis necessitates a frugal water management strategy. Deficit irrigation can be regarded as an efficient strategy for agricultural water management. Optimal allocation of water to agricultural farms is a computationally complex problem because of many factors, including limitations and constraints related to irrigation, numerous allocation states, and non-linearity and complexity of the objective function. Meta-heuristic algorithms are typically used to solve complex problems. The main objective of this study is to represent water allocation at farm level using temporal cultivation data as an optimisation problem, solve this problem using various meta-heuristic algorithms, and compare the results. The objective of the optimisation is to maximise the total income of all considered lands. The criteria of objective function value, convergence trend, robustness, runtime, and complexity of use and modelling are used to compare the algorithms. Finally, the algorithms are ranked using the technique for order of preference by similarity to ideal solution (TOPSIS). The income resulting from the allocation of water by the imperialist competitive algorithm (ICA) was 1.006, 1.084, and 1.098 times that of particle swarm optimisation (PSO), bees algorithm (BA), and genetic algorithm (GA), respectively. The ICA and PSO were superior to the other algorithms in most evaluations. According to the results of TOPSIS, the algorithms, by order of priority, are ICA PSO, BA, and GA. In addition, the experience showed that using meta-heuristic algorithms, such as ICA, results in higher income (4.747 times) and improved management of water deficit than the commonly used area-based water allocation method. and Huang et al. [42] used the GA-PSO hybrid algorithm for the optimal management of water resources. Davijani, Banihabib, Anvar, and Hashemi [9] compared the use of PSO and GA algorithms for allocating water to agricultural, industrial, and municipal consumptions over one year.The ICA is successfully used in a variety of applications related to industrial, civil, mechanical, electrical, and computer engineering [43]. Hosseini-Moghari et al. [44] used this algorithm for water resource management. Karamouz et al. [45] compared the suitability of the ICA and PSO algorithms for allocating reservoir water to agricultural, industrial, and urban consumers. Many studies have used the BA for various applications [46]. However, to the best of our knowledge, it is not used in AW.Considering the preceding review on the use of these algorithms in water resource management and other applications, the reasons for selecting GA, BA, ICA, and PSO algorithms in this study are as follows: (1) They are among the most commonly used meta-heuristic algorithms.(2) On similar problems, the performance of these algorithms was acceptable. (3) The solution space of this study is continuous, while the ICA and PSO are inherently continuous, and GA and BA are also applicable to continuous issues.The aim of this study is to model the AW to farms as...

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“…(2) The construction and management of the irrigation area: modernization of the construction and management of the irrigation area (which encompasses engineering construction, management systems and mechanisms, and the application of advanced irrigation technology) is an important component in improving irrigation water use efficiency, extreme natural disaster governance, and regional ecological sustainable development, thus providing strong support for the development of modern water-saving agriculture [25,[31][32][33][34][35]. (3) Economic policy: an increasing number of studies have found that economic policy (including subsidy policies, water price policies, and water use restrictions) can affect the preferences and behaviors of peasant households, and provide them with incentives to use water-saving irrigation technology and to change their crop planting structure, which leads to changes in the water use efficiency of agricultural irrigation [36][37][38]. In addition, some scholars have found that other factors such as geographic spatial distribution [30,39], irrigation strategies and planting patterns [40][41][42], and crop types [9,43] have an impact on the water use efficiency of agricultural irrigation.The diversity and complexity of influencing factors make it difficult to predict irrigation water use efficiency and, to our best knowledge, there are few predictive studies on irrigation water use efficiency.…”

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confidence: 99%

Prediction of Technological Change under Shared Socioeconomic Pathways and Regional Differences: A Case Study of Irrigation Water Use Efficiency Changes in Chinese Provinces

et al. 2019

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Technological changes in water use efficiency directly influence regional sustainable development. However, few studies have attempted to predict changes in water use efficiency because of the complex influencing factors and regional diversity. The Chinese Government has established a target of 0.6 for the effective utilization coefficient of irrigation water, but it is not clear how the coefficient will change in different provinces in the future. The purpose of this study is to predict irrigation water use efficiency changes using a conditional convergence model and combined with the shared socioeconomic pathways (SSPs) scenario settings and hydro-economic (HE) classification to group 31 Chinese provinces by their different economic and water resources conditions. The results show that the coefficient exponentially converges to 0.6 in half the provinces under SSP1 (sustainability), SSP2 (middle of the road), and SSP5 (conventional development) by 2030, whereas SSP3 (fragmentation) and SSP4 (inequality) are generally inefficient development pathways. HE-3 provinces (strong economic capacity, substantial hydrological challenges) achieve the greatest efficiency improvements (with all coefficients above 0.6), and SSP1 is a suitable pathway for these provinces. HE-2 provinces (strong economic capacities, low hydrological challenges) have relatively low efficiency because they lack incentives to save water, and SSP1 is also suitable for these provinces. For most HE-1 provinces (low economic capacity, low hydrological challenges), the coefficients are less than 0.6, and efforts are required to enhance their economic capacity under SSP1 or SSP5. HE-4 provinces (low economic capacity, substantial hydrological challenges) would improve efficiency in a cost-efficient manner under SSP2. utilization efficiency of natural resources, is a possible way to solve the current dilemma of sustainable development [3,4], because it has a direct impact on the total scale of natural resource utilization, and thus directly influences whether the regional social economy is in a sustainable development state [5,6]. Technological change in agriculture irrigation water use efficiency is of fundamental significance for solving water scarcity and increasing crop productivity, and achieving highly efficient irrigation is crucial to balancing water resources input and sustainable agricultural economic growth [7][8][9].The theory of technological change generally distinguishes two types of technological change: technological catch-up and technological diffusion. Technological catch-up concerns the knowledge production function and occurs through the mechanism of learning by doing. It requires continuous additional capital inputs and manufacturers, and the labor force must constantly learn and master new skills in the production process, which brings about extensive progress in social productivity [3,[10][11][12]. Technological diffusion is brought about by technological transmission and is mainly realized through open trade, technology transfer,...

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Impacts of irrigation efficiency improvement on water use, water consumption and response to water price at field level

Cited by 82 publications

References 38 publications

Sensitivity of Agricultural Development to Water-Related Drivers: The Case of Andalusia (Spain)

Sensitivity of Agricultural Development to Water-Related Drivers: The Case of Andalusia (Spain)

Irrigation Water Allocation at Farm Level Based on Temporal Cultivation-Related Data Using Meta-Heuristic Optimisation Algorithms

Prediction of Technological Change under Shared Socioeconomic Pathways and Regional Differences: A Case Study of Irrigation Water Use Efficiency Changes in Chinese Provinces

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