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Given rapid socio-economic development, increasing food demand and decreasing available resources, the challenge of seasonal fluctuations of surface water has become a major problem in the agricultural sector, causing a change in consumption from surface water to groundwater resources and reduction of farmers' income. Therefore, optimal programming...
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... achieve this aim, four main crops of wheat, potatoes, cucumbers and tomatoes have been considered, accounting for 80% of the total area under cultivation in these areas. Table 2 provides the gross water requirement per hectare of crops selected during the different seasons (Regional Water Company of Kerman province in Iran 2017). ...Citations
... The first category of models targets a single farmer benefit by analyzing the water resource system Tong et al., 2018). The second category of models is based on systems engineering theory, in which multiple optimization objectives, such as economic, irrigation, and environmental benefits, are incorporated into the models (Noël and Cai, 2017;Mirzaei and Azarm, 2022). The first two types of models are based on a top-down research methodology that successfully reproduces macrolevel patterns by analyzing the spatial patterns of the available outcome data. ...
... The biobjective model of this study is solved using an incremental ε-constraint method, and the optimal set of effective solutions is extracted. In the Pareto effective solution, the optimal solution can be selected on the basis of the opinions and perceptions of decision makers and stakeholders, for which the TOPSIS method is used (Aires and Ferreira, 2019;Jin et al., 2023;Liu et al., 2019;Mirzaei et al., 2022). ...
... One is that the agricultural cropping patterns need to be changed. The other is that the distribution of water resources needs to be optimized in time and space (Su et al., 2014;Mirzaei et al., 2022). Given the multiplicity of optimization objectives, researchers have indicated that establishing multiobjective linear programming can maximize the benefits of water resource distribution in the region by optimizing cropping patterns and water resource allocation (Keramatzadeh et al., 2011;Hasanvand et al., 2018). ...
... Crop water requirement is the amount of water equal to what is lost from the cropped field by evapotranspiration [4]. Soil type, climate change, topographical location, and crop type are highly affect the quantity of crop water requirement [5]. Climate change denotes significant and enduring shifts in Earth's climate, driven by human activities due to emitting of greenhouse gases like CO 2 , CH 4 , and N 2 O, and altering temperature, precipitation, and wind patterns [6]. ...
Crop water requirement and irrigation scheduling in Lower Kulfo Catchment of southern Ethiopia have not assessed under climate change scenarios, and the allocation of crop land also not optimal that signifcantly challenges to crop productivity.Therefore, this study was conducted to evaluate the effects of climate change on future crop water requirements, and irrigation scheduling, and to allocate cropland optimally. Bias of projected precipitation and temperature were corrected by utilizing Climate Model data with the hydrologic modeling tool (CMhyd). Alongside, crop water requirements and irrigation scheduling were assessed using Crop Water Assessment Tool. After estimating crop water requirement, crop land were allocated optimally using General Algebraic Modeling System programming with non-negativity constraints (scenario 1), and non-negativity constraints based on farmers adaptation (scenario 2). Average reference evapotranspiration from 2030 to 2050 and 2060 to 2080 was increased by 11.9 %, and 16.2 %, respectively compared with the reference period (2010-2022). The total seasonal crop water requirements were 4,529 mm, 4866.7 mm, and 5272.2 mm under 2010 to 2022, 2030 to 2050, and 2060 to 2080 climate change scenarios, respectively. The meean irrigation interval in 2010-2022, 2030 to 2050, and 2060 to 2080 climate change scenarios were 8 days, 7 days, and 5 days, respectively. This irrigation interval was decreased by 14 % (2030-2050), and 34 % (2060-2080) compared with the reference period. In 2030 to 2050 and 2026 to 2080 climate change scenarios, the required irrigation water at the inlet of main canal increased by 6.8 %, and 18 %, respectively. The optimal allocated area for tomato (60.4 %), maize (20.8 %), and watermelon (18.8 %) in scenario 1 with net benefit of 1.47*108 Ethiopian Birr. The allocated areas in scenario 2 were (48 %) for maize, (31.6 %) for tomato, and (20.4 %) for watermelon with 1.34*10 8 Ethiopian Birr net benefit it was reduced by 19.1 % compared with the net benefit in scenario 1. Fruit crops alone may not suffice for local food needs and to address this, small farmers should grow maize, tomato, and watermelon. This research aids policymakers in encouraging climate-resilient agriculture and improving small-scale farmers' awareness through conducting workshops and training.
... Irrigation of crops in agriculture faces challenges due to severe shortages of surface water resources, leading to an excessive reliance on groundwater reservoirs by farmers. Consequently, farmers in arid and semi-arid regions are compelled to excessively draw from subterranean water sources, resulting in a rapid decline in groundwater levels and posing a threat to delicate ecosystems and sustainable water supply (Gleeson et al. 2012;Mirzaei et al. 2022). ...
... Adaptation strategies such as controlling the cultivation of high waterrequirement crops and transitioning toward crops with higher economic value have been adopted in various regions, as highlighted in research by Mirzaei et al. (2022). However, a review of previous studies indicates that policies restricting the cultivation of water-intensive crops like rice and maize may not always lead to significant reductions in water demand adaptation. ...
The escalating utilization of groundwater resources within watersheds is a growing concern attributed to factors such as population growth, agricultural expansion, and diminishing surface water availability due to recurring droughts and climate variations. This surge in groundwater usage has precipitated conflicts among various water user groups, notably between agricultural and environmental stakeholders. The primary goal of this chapter is to devise and introduce an optimization framework for the allocation of groundwater resources, with the aim of mitigating conflicts between the objectives of the agricultural and environmental sectors. This framework considers all technical-hydrological constraints and, crucially, analyzes the cooperative behavior of farmers as a pivotal aspect in addressing these conflicts. In the initial segment of the literature review, the focus was on investigating the strategies and policies employed for the effective management of groundwater resources. The findings from this review highlighted a predominant reliance on demand management policies compared to supply management policies in the management of groundwater resources across various basins. In the second part of the study, an integrated modeling tool was designed and developed for the optimal allocation of groundwater resources. The optimization model was meticulously formulated, providing a comprehensive framework that can serve as a valuable tool for decision-making. This model stands out for its ability to address the conflicting objectives of maximizing economic benefits for farmers while also promoting the conservation of environmental goods and services. By taking into account technical constraints and hydrological interconnections at the basin level, the model is well-equipped to facilitate conflict resolution and support the optimal allocation of groundwater resources. By incorporating considerations of technical feasibility, hydrological dynamics, and the dual objectives of economic benefit and environmental protection, the optimization model emerges as a robust tool for guiding resource allocation strategies within watershed contexts. The third part of the study evaluated the policy of restricting the extraction of groundwater resources in order to implement the model of optimal allocation of these resources at the basin level. The results of this part showed that the successful implementation of the policy of restricting the extraction of groundwater resources and the implementation of the optimal pattern of allocation of these resources requires the analysis of farmers’ behavior at the basin level. Therefore, the simulation of farmers’ behavior in cooperation with such a policy and model was described by the agent-based method.
... The impending pressure on the food system is exacerbated by a 70% increase in food demand projected by 2050, further straining water resources (alexandratos & Bruinsma, 2012;Wu et al., 2022;Wubalem, 2023). The escalating threats of global climate change add another layer of complexity to the water scarcity challenge, potentially altering irrigation regimes and affecting agricultural output (amiri et al., 2023;gong et al., 2015;Mirzaei et al., 2022). developing regions, particularly africa, where nearly 80% of freshwater is diverted for irrigation agriculture, face a dual challenge of increasing water consumption and a rising population suffering from water shortages and climate change impacts (Moisa et al., 2022;Tolera et al., 2023). in this regard, 33.3% of africa's population suffers from water shortages and climate change, which will make things more difficult (abedin et al., 2019;Rahman et al., 2023). ...
The cycle of food insecurity caused by poor water management practices poses major concerns for the sustainability of living balance in Southwestern Ethiopia’s smallholder agricultural areas. The prior study looked at crop land suitability assessments. However, there are still knowledge gaps on irrigation infrastructure sites. As a result, this research was launched to evaluate the surface water irrigation (SWI) potential of river watersheds in the Gomma area, southwestern Ethiopia. To identify possible SWI, biophysical parameters such as topography, stream order, soil texture, land use-land cover, drainage density, and climate elements were analyzed. Potential SWI sites were identified using multiple-criteria decision-making analysis from the sources of information reviewed, which were applied for selecting suitable sites. A comparison matrix, weighted analysis, Boolean-operations, and survey approaches. The analysis findings reveal that about 16% of the Gomma is highly suitable (S1) for drip or sprinkler surface water irrigation (SWI) schemes, while 7% and 77% of the total fall under the categories of moderate and unsuitable for SWI, respectively. At the catchment level, the most irrigable catchments in Didessa, Naso, Awetu, Tamsa, and Urgessa were found to be approximately 1838, 1626, 1484, 1107, and 910 ha of total area, respectively. In contrast to prior outcomes, the eventual eligibility map of foreseeable SWI zones are squarely distributed over the study region. In conclusion, to optimize the impact on agricultural productivity and water resource management, it is advised to prioritize the implementation of drip or sprinkler surface water irrigation (SWI) schemes in areas identified as highly suitable.
... Several authors explored new efficiencies in water practices, including approaches utilising changes in water use policy, or at the macro level of water resource management (for example, Fowler et al. 2023)). Optimising irrigation systems is seen as an ongoing way of preserving water resources (Chaloob 2016;Singh 2016;Li et al. 2017;Pastori et al. 2017;Multsch et al. 2017;Liu and Li 2018;Juwono et al. 2018a, b;Kropp 2018;Song et al. 2019;Zhang et al. 2019;Cervantes-Gaxiola et al. 2020;Gurav and Regulwar 2020;Rezaei and Safavi 2020;Roje et al. 2020;Yue et al. 2020;Nanda et al. 2021;Mirzaei et al. 2022;Sabale and Jose 2022;Gong et al. 2023;Liu et al. 2022;Cheng et al. 2023;Kousar et al. 2023;Santos 2023;Yang et al. 2023). Complementary to that has been a move to investigate more water-wise crops (Chaloob 2016;Li et al. 2017;Ikudayisi 2017;Ikudayisi et al. 2018;Daghighi et al. 2017;Gong et al. 2020;Jha et al. 2020;Roje et al. 2020;Dai et al. 2021;Sabale and Jose 2022;Mohammadzadeh et al. 2022;Liu et al. 2022;Huang et al. 2023;Jain et al. 2023;Shabanzadeh-Khoshrody et al. 2023). ...
Optimising the use of natural resources for food production in the context of changing climate is an increasingly important issue. Optimisation techniques have been shown to be remarkably effective for planning problems, and tools regional planners and farmers can use to determine the viability of agricultural land use planning into the future. This paper systematically reviews the recent literature in this area and draws out the key emerging themes: few studies to date have explicitly incorporated climate projections into optimisation models; increased tension for water resources between stakeholders; and various agricultural production systems of complex versions of crop planning. From this review it can be seen that increasing concentration on the use of climate projection models within agriculturally-oriented optimisation processes is a necessity.
... Notably, crops with high net returns, such as tomatoes, experienced substantial increases in allocated areas. Recent studies have predominantly employed optimization models to maximize crop yield or minimize water consumption [12][13][14][15][16][17][18]. However, these models often allocate areas for different crops without considering their actual market demands. ...
Efficiently optimizing cropping patterns is crucial for the sustainable agriculture development, especially in arid regions like Saudi Arabia. This study specifically aimed to gradually optimize cropping patterns in Saudi Arabia over next decade. The cropping pattern of 2023 according to ministry of environment water and agriculture was assessed to identify crops with potential for optimization based on economic revenue, water consumption. Subsequently, three optimization strategies were devised: maximizing total income, minimizing total water consumption, and maximizing productivity. The strategy focused on maximizing income projected a remarkable 17.6/% increase in total agricultural income by simply increasing the current water resources by 4.2%. On the other hand, the strategy aimed at minimizing water consumption could save 13.4% of water resources, but it would result in 4.6% reduction in total income. Alternatively, the strategy prioritizing productivity maximization would lead to a significant 15.6% increase in total income while reducing water resources by 0.7%.
... In this regard, the global demand for water, energy, and food (WEF) resources is expected to increase by more than 50% on average by 2050 (Zuo et al. 2021;Schull et al. 2020). Furthermore, in the past decades, economic development along with the occurrence of environmental phenomena, such as climate change and land use changes, has led to excessive demand for these key resources (Mabhaudhi et al. 2019;Azarm et al. 2022;Mirzaei et al. 2022b). The continuation of this trend and the ever-increasing demand for WEF resources, while threatening the security of these strategic resources, will be an obstacle to the attainment of sustainable development globally (Feng et al. 2022). ...
Today, growing the production of the agricultural sector in order to meet the increasing demand of food is happening through excessive consumption of water resources, energy, chemical fertilizers, and pesticides, especially in developing countries. Therefore, the present study aims to design a new approach for sustainable management of resources and realization of clean production in the agricultural sector. In order to design the new approach of the present study, the integration of two concepts of water-energy-food (WEF) nexus and decoupling pollution-agricultural growth (DEC) was used. The proposed approach is modeled through the multi-objective programming model by optimizing the WEF and DEC indices, which is the first research effort in this field. In this regard, the performance of this approach was evaluated in Jiroft County in Kerman province, Iran. The results of the study showed that the consumption of chemical fertilizers and pesticides in the optimal pattern with the simultaneous provision of WEF and gross margin (GM) goals (optimal 1) is about 110 kg and 0.19 l per hectare, respectively, more than the proposed pattern (optimal 3). On the other hand, the consumption of water and energy resources in the optimal pattern with the simultaneous provision of DEC and GM goals (optimal 2) is about 8785 cubic meters and 1108 MJ per hectare more than the proposed pattern (optimal 3), respectively. Therefore, this approach, due to the simultaneous integration of two concepts of sustainable development in the agricultural sector, can overcome the weakness of the WEF nexus in not paying attention to the issues of environmental pollution affected by the use of chemical inputs and the weakness of separating pollution-agricultural growth in not paying attention to the management of water and energy resources in the agricultural sector.
... The results showed that the proposed optimization model significantly increased the index of available water resources in the return period of 2, 10, and 50 years. Mirzaei et al. (2022) developed a model of irrigation water allocation using multistage stochastic programming in accordance with surface water supply fluctuations to estimate the best strategies for cropping patterns in the irrigation network of the Jiroft plain in Kerman Province, Iran. In this area, surface water resources cannot meet the water needs of the region, even by using optimal cropping patterns, and this has led to overuse of groundwater resources. ...
In the current century, the sustainable production of agricultural products is one of the main challenges facing humanity. The amount of water consumption, energy, and net income as important components of the sustainability of agricultural systems is of special priority and importance. This study used linear and multi-objective programming models with the aim of maximizing five indicators of cost efficiency (CE), irrigation efficiency (IE), energy productivity (EP), energy efficiency (EE), and food efficiency (FE) to determine the cropping pattern of small-scale farms cultivated per hectare in the agricultural year. There are 160 questionnaires classified by random sampling method in agricultural sectors in Inner Mongolia, China. The results showed that determining the cropping pattern using multi-objective planning increases irrigation efficiency and energy efficiency compared with linear modeling. Considering the conditions of limited water resources in the region and the policies of the country in the agricultural sector, cropping patterns with the objective functions of maximization of IE and CE were proposed.
HIGHLIGHTS
Cropping pattern in agriculture is investigated for the food production system considering the water, food, and energy nexus.;
Linear and multi-objective programming models with the aim of maximizing five evaluation indicators.;
The use of economic parameters in dealing with irrigation water was recognized as two suitable objective functions.;
... The planting acreage subsidy and the water-saving effort subsidy methods were used to achieve the best strategies for the government and beneficiaries. Mirzaei et al. (2022) proposed an optimal program to determine the sustainable cropping pattern by multistage stochastic programming in the Jiroft irrigation network in Kerman Province, Iran. Based on this concept, various stochastic conditions were evaluated for irrigation scenarios in a severe shortage of surface water and the farmer's tendency to overexploitation of groundwater. ...
Soil moisture content improvement is a key process in agricultural production and food security in arid and semi-arid regions. The interaction effect of crop water requirement (CWR) and soil texture on water productivity was evaluated in Harbin, Heilongjiang province, China. A field experiment with two scenarios of compost application (0, 25 ton/ha) and three levels of irrigation policies (deficit irrigation (DI = 0.75CWR), regular irrigation (RI = CWR), and full irrigation (FI = 1.25CWR)) was planned in three replications during 2021–2022. Water productivity was simulated as a criterion to improve the irrigation time for increasing the final biomass. Four strategic crops including potato, corn, wheat, and barley were incorporated into the daily simulation system. Furthermore, a machine-learning random forest algorithm was used to find the best irrigation times. The results showed that the use of adjusted irrigation time and improved soil texture can increase water productivity by reducing evaporation and deep percolation and increasing actual biomass. Estimation of irrigation time in a learning-based method will be optimal when plant growth and soil moisture are monitored on a daily basis.
HIGHLIGHTS
Water productivity was evaluated as a criteria to improve the irrigation time for considering food security.;
The improvement of the soil structure using natural compost and its interaction with irrigation water were investigated.;
Deficit irrigation and modification of irrigation time are the most important factors for increasing water productivity for wheat and potato, respectively.;
... A hydroagronomic simulation-optimization approach was simulated using soil & water assessment tool (SWAT) and the optimal cropping pattern was searched by particle swarm optimizer (PSO). Mirzaei et al. (2022) used optimal programming of the cropping pattern to consider seasonal fluctuations of surface water in the irrigation network of the Jiroft plain in Kerman Province, Iran. A model of irrigation water allocation was developed based on cropping pattern using multistage stochastic programming in accordance with surface water supply fluctuations. ...
One of the needs of a sustainable decision-making system in agriculture is to determine the role of energy in the food production cycle. Wind energy turbines can be built in agricultural fields for groundwater exploitation and reduce the cost of energy supply for the pumping system. This study was conducted to evaluate the effect of wind energy and economics on sustainable planning of agricultural water resources. A multiobjective framework was developed based on the nondominated sorting principle and water cycle optimizer. Maximization of benefit per cost ratio for the total cropping pattern and minimization of energy consumption for the growing season were addressed as the objectives of the nonlinear problem. The prediction of biomass production was made by simulating a hybrid structure between the soil moisture balance in the root zone area and the development of the canopy cover of each crop. The results showed that the objectives of the problem have been met by irrigation planning using climatic constraints and drought stresses. About 35% of the total water requirement of plants with a higher harvest index (watermelon, melon, etc.) is in the maturing stage of the shade cover.
HIGHLIGHTS
The role of wind energy variables has been considered in the agricultural yield production.;
A multiobjective framework was developed based on the nondominated sorting principle and water cycle optimizer.;
The proposed optimization method showed that the total water productivity increased significantly by 38%.;
