Agricultural Water Use Research Articles

Improved production and quality of peppers irrigated with regenerated water by the application of 24-epibrassinolide

Water shortage for crop irrigation is reducing agricultural production worldwide and the use of sewage treatment plant (STP) water to irrigate horticultural fields is a solution to avoid the use of drinkable water in agriculture. In this study, two different genotypes of pepper (Red Cherry Small and Italian green) were irrigated with STP water, as an alternative to potable water. Moreover, the foliar application of a molecule with biostimulant properties (24-epibrassinolide; EBR) was tested as a strategy to ameliorate the production and quality of fruits. Both genotypes differed on their tolerance to the suffered oxidative stress due to their different salinity tolerance, but fruit commercial weight was reduced by 49% on the salt sensitive and by 37% on the salt tolerant. Moreover, ascorbic acid was also decreased by 37% after STP water irrigation in the Red Cherry Small peppers. However, EBR applications alleviated STP watering stress effects improving pepper plants fruit production and quality parameters, such as ascorbic acid and capsaicinoids. These results have important economic and environmental relevance to overcome present and future water deficiencies in the agricultural sector derived from climate change, guaranteeing the maintenance of production in peppers irrigated with STP water for a more sustainable agriculture following relevant circular economy actions.

Determinants of water consumption in Thailand: sustainable development of water resources

PurposeFreshwater availability is reducing globally, due to increasing demand with population growth and climate change and is disproportionately impacting developing countries. This study aims to investigate the dynamics of water access and consumption across all regions of Thailand with various characteristics and water systems. Understanding the relationship between institutional, economic and climate variables in Thailand’s water management is important for water scarcity planning. Our paper fills a gap in the literature by examining the determinants of water consumption and exploring potential water management policies.Design/methodology/approachThe authors empirically analyze the determinants of water consumption in Thailand, including institutional, economic and climate variables. The authors use data sets from both metropolitan and provincial waterworks authorities (PWA), as well as economic and meteorological macro-level data. The authors also adopt an auto-regressive distributed lag (ARDL) model and a Johansen cointegration test to estimate short- and long-run effects of the variables on water consumption.FindingsThe authors confirm a negative relationship between water pricing and consumption and verify a positive relationship between economic growth and water consumption across most regions of Thailand. Furthermore, the authors reveal a clear relationship between climate factors and water consumption and an inverse relationship between income and water consumption in metropolitan area. Findings indicate that authorities, especially PWA, should examine high water use in agriculture and develop regulations to ensure equitable water distribution to sustain economic growth. The authors recommend that water prices are increased within specific income thresholds to prevent impacting low-income families and to secure higher public revenue. In pursuit of environmental sustainability, the authors also recommend increasing public awareness of freshwater scarcity through education programs and investment in water-saving technologies. Differences among regions should be considered when developing water management strategies, which could be monitored through the respective water boards.Originality/valueThis study provides deep insight into the key factors that drive both water prices and water consumption in poor and rich areas. The unique nature of the research indicated that the paper will be of interest to policymakers and the academic community. The findings are relevant for water consumption management in Thailand and other developing countries with similar characteristics.

Understanding the Food‐Energy‐Water Nexus in Mixed Irrigation Regimes Using a Regional Hydroeconomic Optimization Modeling Framework

AbstractUnderstanding the nexus between food, energy, and water systems (FEW) is critical for basins with intensive agricultural water use as they face significant challenges under changing climate and regional development. We investigate the food, energy, and water nexus through a regional hydroeconomic optimization (RHEO) modeling framework. The crop production in RHEO is estimated through a hierarchical regression model developed using a biophysical model, AquaCropOS, forced with daily climatic inputs. Incorporating the hierarchical model within the RHEO also reduces the computation time by enabling parallel programming within the AquaCropOS and facilitates mixed irrigation—rainfed, fully irrigated and deficit irrigation—strategies. To demonstrate the RHEO framework, we considered a groundwater‐dominated basin, South Flint River Basin, Georgia, for developing mixed irrigation strategies over 31 years. Our analyses show that optimal deficit irrigation is economically better than full irrigation, which increases the groundwater pumping cost. Thus, considering deficit irrigation in a groundwater‐dominated basin reduces the water, carbon, and energy footprints, thereby reducing FEW vulnerability. The RHEO also could be employed for analyzing FEW nexus under potential climate change and future regional development scenarios.

Cropping pattern optimization considering water shadow price and virtual water flows: A case study of Yellow River Basin in China

Cropping pattern determines the agricultural water use requirement and efficiency, as well as economic benefits of crop production. Agricultural water resources include blue water (irrigation water) and green water (soil moisture from precipitation), which have different shadow prices. The virtual water (VW) flow embedded in the interregional food trade causes burden shifts of water resources pressures in space. However, these intertwined economic and social effects have been neglected in regional cropping structure management. Using the case of the Yellow River Basin in China, here, we propose a two-stage multi-objective cropping pattern optimization scheme to maximize crop economic output, while minimize blue water scarcities (the first stage), and considered the criteria of maximum economic benefits of the interprovincial crop-related VW flows based on the shadow prices of crop green and blue water use (the second stage). Results show considerable differences in shadow prices of crop water use by colures, crops and location. With the optimized cropping pattern, which appropriately expands the planting scale of vegetables with higher water shadow price and comparative advantage and reduces the crop planting with lower water shadow price and intensive blue water consumption (e.g., soybean and wheat), blue water scarcity can be alleviated by ∼20%, combined with a ∼5% increase in crop economic output and up to ∼3% (800 million USD) higher benefits of VW flows. The premise to achieve above goals is to improve crop water resources utilization efficiency and break down the barriers of dietary preferences and trade policy.

Connotation, calculation and influencing factors of the water-use rights benchmark price: A case study of agricultural water use in the Ningxia Yellow River irrigation area

Connotation, calculation and influencing factors of the water-use rights benchmark price: A case study of agricultural water use in the Ningxia Yellow River irrigation area

Assessment of agricultural adaptations to climate change from a water-energy-food nexus perspective

Adapting agriculture to climate change without deteriorating natural resources (e.g., water and energy) is critical to sustainable development. In this paper, we first comprehensively evaluate six agricultural adaptations in response to climate change (2021–2050) through the lens of the water-energy-food (WEF) nexus in Saskatchewan, Canada, using a previously developed nexus model—WEF-Sask. The adaptations involve agronomic measures (early planting date, reducing soil evaporation, irrigation expansion), genetic improvement (cultivars with larger growing degree days (GDD) requirement), and combinations of individual adaptations. The results show that the selected adaptations compensate for crop yield losses (wheat, canola, pea), caused by climate change, to various extents. However, from a nexus perspective, there are mixed effects on water productivity (WP), total agricultural water (green and blue) use, energy consumption for irrigation, and hydropower generation. Individual adaptations such as early planting date and increased GDD requirement compensate for yield losses in both rainfed (0–60 %) and irrigated (18–100 %) conditions with extra use of green water (5–7 %), blue water (2–14 %), and energy for irrigation (2–14 %). Reducing soil water evaporation benefits the overall WEF nexus by compensating for rainfed yield losses (25–82 %) with less use of blue water and energy consumption for irrigation. The combination of the above three adaptations has the potential to sustain agricultural production in water-scarce regions. If irrigation expansion is also included, the combined adaptation almost fully offsets agricultural production losses from climate change but significantly increases blue water use (143–174 %) and energy consumption for irrigation while reducing hydropower production (3 %). This study provides an approach to comprehensively evaluating agricultural adaptation strategies, in response to climate change, and insights to inform decision-makers.

Spatial Association Network and Driving Factors of Agricultural Eco-Efficiency in the Hanjiang River Basin, China

Reducing agricultural emissions and promoting carbon sequestration are vital for China to achieve its dual carbon goals. Achieving the green transformation of agricultural watersheds requires a thorough understanding of the internal transmission relationships within the watersheds and the underlying spatial correlation structures. This paper used the SBM-3E model to calculate the agricultural ecological efficiency of 17 prefecture-level cities in the Hanjiang River Basin (HRB) from 2010 to 2020, taking agricultural carbon emissions and a comprehensive non-point source pollution index as the unexpected output. The Gravity model and social network analysis methods were used to analyze the evolution characteristics of the network structure of agricultural ecological efficiency, and the secondary assignment procedure method was used to identify the driving factors from the planting structure, water use structure, and resource endowment. First, from 2010 to 2020, the overall agricultural ecological efficiency in the HRB demonstrates a declining trend, with efficiency values of 12.15, 9.40, and 6.67 in the upper, middle, and lower reaches, respectively. Second, the spatial correlation network density of agricultural ecological efficiency in the HRB is 0.17, with a network efficiency of 0.89. The correlation among units within the basin is relatively low, but stability is high. Moreover, the individual network spillover absorption capacity exhibits heterogeneity, and the status of each subject within the watershed follows a “core-edge” structure. Third, total water consumption and corn cultivation have a positive impact on the agricultural ecological efficiency network in the HRB, whereas agricultural water use and rice cultivation negatively influence the network. We propose policy recommendations to facilitate the advancement of green development in China’s agricultural watersheds and the achievement of the dual carbon goals.

Agricultural Total Water Consumption Coefficient and Its Spatial Correlation Network in Yangtze River Economic Belt

Agriculture contributes extensively to the economic development of countries; however, it is one of the main water-consuming industries. Revealing the characteristics and network structure of agricultural water use efficiency (AWUE) is conducive to green and coordinated development of agriculture. Considering that analyzing the variation of AWUE is helpful to calculating the AWUE, this study aims to calculate the total water consumption coefficient of the agricultural sector in the Yangtze River Economic Belt (YEB) by using the China interregional input-output tables in 2012 and 2017. The gravity model was modified to deduce the spatial correlation network of agricultural total water consumption coefficient (ATWCC), and the social network analysis method was used to analyze the network structural characteristics. The results show that: (1) compared to 2012, the AWUE of YEB in 2017 improved, with a decrease of ATWCC from 532.5 to 387.5 m3/10,000-yuan, account for 27.2%; (2) The network relevance of ATWCC of YEB’s 11 provinces (cities) enhanced, the rank relationship within the network and the network structure was relatively stable; (3) The spatial correlation network formed several network centers, Zhejiang and Jiangsu in the eastern coastal area were the main destinations of the spatial spillover of the spatial correlation network.

Spatial-temporal evolution of water resources utilization efficiency in Jiangsu Province

Abstract Improving water resource utilization efficiency is essential in alleviating the crisis of water resource shortage and promoting the sustainable development of the social economy. Based on the data envelopment analysis (DEA) and Malmquist index, the agricultural, industrial, and domestic water resource utilization efficiency of Jiangsu Province from 2011 to 2020 are evaluated, respectively. The results show that the DEA efficiency of agriculture and industrial water use is greater than that of domestic while the improvement of agricultural and domestic water efficiency is larger than that of industrial. Temporally, the water use efficiency was on an increasing trend from 2011 to 2020, and technological progress is the main factor in improving the water resource utilization efficiency. Spatially, the water use efficiency of southern cities in Jiangsu Province is higher than that of northern and central cities, but the difference between cities is gradually narrowing. To improve the efficiency of water resource efficiency, the government should formulate water resource management policies according to local conditions.

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

AbstractThe High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km3/year in 1985 to 18.2 km3/year in 2015, while irrigated croplands increased from 71,928 km2 in 1985 to 78,464 km2 in 2015 in the entire HPA. The hydroclimatic time‐series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time‐series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.

A dynamic model for salinity and sodicity management on agricultural lands: Interactive simulation approach

In this research, a dynamic simulation model, SAMIMI (Salinity/Sodicity Management with an Interactive Model Interface), is developed for managing the effects of agricultural water use and crop choices on soil salinization and sodification, and their impacts on crop yields. SAMIMI integrates the vertical hydraulic flow, solute transport, and crop processes in feedback by a compartmental, non-linear model architecture. With its holistic integrated approach to salinity /sodicity processes, it adopts a system dynamics approach. Though it is simplified in spatial resolution, the model credibility is sufficiently evaluated with indirect structure tests and against the data by Hydrus-1D, and soil-column experiments that were conducted as part of the SAMIMI (Salinity/Sodicity Management Interdisciplinary Multi-Institutional Network) project conducted in the semi-arid Konya Closed Basin of Turkey. Model analysis provide valuable insights to the role of irrigation efficiency, water quality and crop choices on soil degradation and yield losses, which are important for learning about and management of salinity/sodicity related problems: Although irrigation efficiency is desirable for water conservation purposes, it may result in higher salinity /sodicity levels because of insufficient leaching in well drained soil profiles. Salinity and sodicity have opposite effects on soil hydraulic conductivity, and while low saline irrigation water is desirable for agricultural production, under relatively high sodic conditions, it can lead to reduced hydraulic conductivity which can degrade soil characteristics to the detriment of crops. Salinity is not simply correlated with relative irrigation water consumption but with the crop salt tolerance as well. Hence, low water consuming crops with high salt tolerance can lead to over salinization, rendering the soil profiles inappropriate for cultivation of salt vulnerable crops, if not sufficiently leached before by precipitation and/or good-quality irrigation water. The model is published as a publicly available online interactive simulation tool with a fast-simulating user-friendly interface targeting researchers, students, experts, farmers and policy makers.

Trend analysis of precipitation using innovative approaches in northwestern Turkey

Precipitation is highly sensitive to climate change, and monitoring its trends over time is essential for understanding the effects of global warming on the Earth's water cycle. This study investigates the effects of climate change on monthly precipitation in the Susurluk Basin located in northwestern Turkey, using innovative trend analysis methods. Innovative Polygon Trend Analysis (IPTA) using star graphics and Improved Visualization for Innovative Trend Analysis (IV-ITA) techniques were used to analyze precipitation data from nine stations in the basin over 50 years (1970–2019), and the findings were compared to classical Mann-Kendall (MK) results. According to the trend analysis results, the MK method detected significant trends in only two months in the decreasing direction. In these decreasing trends observed at Simav and Keles stations in November, z values were calculated as −2.38 and −2.05, respectively. IPTA method detected increasing trends in 54 months and decreasing trends in 40 months; this means there is a change of more than 5% between two half series. The IV-ITA method indicated an increase of more than 40% in the low values for January, March, August, and September. In addition, there was an increasing trend of more than 40% in the high values observed in September at all stations. It was observed that mean precipitation heights increased from September to December and then decreased throughout the basin. It is predicted that decreases in precipitation during dry seasons may put intense pressure on agricultural water use and affect water quality. In addition, the increase in precipitation in spring months may increase flood events. It was determined that graphical innovative trend analysis methods are more effective in trend identification than MK, and these methods' results have much higher visual inspection and linguistic interpretation possibilities. Innovative methods allow for more flexible and in-depth analysis using different statistical parameters.

The importance of irrigation supply chains within the water footprint: an example from the Pakistani part of the Indus basin

ABSTRACT Many environmental studies have shown that a systems approach, including complete supply chains, is relevant for the assessment of the consequences of production and consumption on natural resources. This can also be applied to water. Although water consumption also includes water supply chains, often irrigation supply chains are excluded in water footprint (WF) studies. Using information from water management studies on water losses, we propose an improved WF method that includes blue crop WFs and WFs of irrigation supply chains indicating total agricultural blue WFs. A systems approach considering not only irrigation technology but whole water supply chains, also distinguishing between surface and groundwater, is needed to improve efficient blue water use in agriculture. This method is applied to the Pakistani part of the Indus basin that includes the largest man-made irrigation network in the world. The total agricultural blue WF is 1.6 times the blue crop WF. Surface water losses vary between 45 and 49%, groundwater losses between 18 and 21% and are smaller than results from water management studies. Differences between provinces and canal commands are large. The identification of hotspots provides a tool to improve water management. Earlier WF studies might have underestimated agricultural water consumption if supply chains are neglected. More water efficient agriculture should take supply chain losses into account probably requiring water management adaptations, which is more a policy than an agriculture task. WFs of supply chains are also relevant for other sectors, like industry or municipal water supply.

A scenario-specific nexus modelling toolkit to identify trade-offs in the promotion of sustainable irrigated agriculture in Ecuador, a Belt and Road country

Increased demand for food due to development and population growth has prompted irrigated agriculture expansion, posing enhanced global challenges to water, energy, and food security. To confront these challenges, an approach that considers the water-energy-food-environment nexus can address multidimensional trade-offs that complicate the efficient use of resources and the achievement of Sustainable Development Goals. In order to provide insights into solutions to these challenges for a specific case, this study develops a modelling toolkit that integrates biophysical and socioeconomic aspects of nexus components in the context of agro-export and irrigation expansion in Ecuador, a Belt and Road Country. The nexus toolkit is applied to agricultural-development scenarios defined in participatory workshops and incorporates a water resources model, a lifecycle environmental assessment, and a socioeconomic analysis. The modelling exercise is constructed around specific scenario-determined land use patterns in the Santa Elena peninsula of Ecuador. Agriculture in the peninsula is water-limited, relying on delivery infrastructure and transfers from a neighbouring catchment. Impacts on nexus components are analysed for ten crops under two potential land-use scenarios: a substantial increase in irrigated area due to investment in irrigation infrastructure; and a substantial shift in land use towards export crops. The two have distinct impact on water and energy use, global warming potential, freshwater eutrophication, terrestrial acidification, and fine particulate matter formation. The results provide insights into future water and energy resource challenges and environmental and socioeconomic trade-offs associated with likely changes in irrigation expansion. The results for scenarios show that, for example, banana production has the greatest environmental impacts (e.g. a 519% increase in global warming potential and 452% increase in fine particulate matter form for scenario 2), primarily due to water and energy requirements, despite the crop being mainly produced organically. In addition, total net income and labour demand increase (net income increases by 43% and 217% under scenarios 1 and 2, respectively) due to a larger crop area and crop intensification. Scale effects on labour demand are mainly due to labour intensity of maize in Ecuador, which is disadvantaged in the crop export scenario (an unexpected result). However, expanding irrigated areas would also increase total water and energy demand for irrigation, global warming potential, and freshwater eutrophication. This type of information enables stakeholders and decision-makers to design policies that achieve equitable and sustainable agricultural production, water use, and economic growth.

Exploring Climate-Driven agricultural water shortages in a Snow-Fed basin using a water allocation model and Machine learning

Water allocation models (WAM) can capture complex feedbacks between water infrastructure, water supply, water demand, and water rights structure. They are an important tool for water managers to reduce conflict and aid in future water resource planning. Future streamflow reductions and shifts in timing are anticipated in snow-dominated watersheds of the western United States due to projected reductions in snow water storage. These basins tend to be water-limited and rely on groundwater to support agricultural demand. Water managers in the snow-fed, agricultural Walker River Basin (WRB) in California and Nevada use a dynamically coupled WAM and physically based groundwater flow model as a decision support tool. Large computation time is required to simulate groundwater dynamics, limiting the number of model scenarios that can feasibly be run to test alternative management scenarios under climate change. Machine learning (ML) techniques have been used to capture complex nonlinear hydrologic dynamics in other contexts, but to our knowledge there have not been efforts to use ML to increase computational efficiency in modeling groundwater responses to agricultural water use. We use extreme gradient boosting to replace the groundwater sub-model for the WRB decision support tool, resulting in accurate estimates of reservoir storage (monthly error almost always < 5% of reservoir capacity), streamflow (total outflow errors from −3% to 20% depending on scenario) and agricultural water shortages (-12% to 18% error in total shortage depending on scenario). For comparison, we found that omitting groundwater modeling from the WAM results in a larger overprediction of outflows (2 to 58%) and underprediction in agricultural water shortages (0 to 41%) across a range of scenarios. We use this validated ML method to explore the sensitivity of agricultural water availability to a range of streamflow volumes and streamflow timings. Results indicate that agricultural water shortages are more sensitive to annual streamflow volume in comparison to shifts in streamflow timing. Our model shows that reservoirs can buffer the impact of altered flow timing on agricultural production, except under extreme conditions in which all precipitation falls as rain (no snow storage) and streamflow peaks in the winter. Future work will explore these thresholds in more detail. While the results here are site-specific, the methodology for coupling a WAM with a ML representation of surface–groundwater interactions can be applied to a wide variety of water resource modeling applications. These results also provide a stark example of the importance of snowpack storage and groundwater management to western US water infrastructure.

Water Management for Conservation and Ecosystem Function: Modeling the Prioritization of Source Water in a Working Landscape

Conservation in working landscapes is an important aspect of stream restoration. Landowners with agricultural water rights are increasingly adding instream flow as a beneficial use of their allocated water. However, stream restoration projects commonly focus on the quantity of water dedicated to the environment and overlook water quality. For cold-water ecosystems, the preservation of natural thermal regimes is a key to conservation efforts in the face of a changing climate. This study explored the effects of increasing stream flow using alternative water sources (e.g., instream runoff versus offchannel springs) to enhance cold-water stream habitat on a working cattle ranch. Using empirical data to create a steady-state stream flow and water temperature model, we evaluated temperature benefits and management trade-offs for ecological and agricultural water use. The modeled results showed that the source of water and the method used to deliver water to the channel affected the quality and extent of cold-water habitat. Offchannel spring water cooled 7-day average maximum temperatures and 7-day average mean temperatures by as much as 3.7°C and 2.9°C, respectively, but only when potential offchannel aquatic habitat was sacrificed for mainstem habitat. When offchannel, spring-fed habitat was provided, the value of spring water to the main channel decreased. Our findings suggest that source water thermal quality is of paramount importance for enhancing ecosystem function and improving cold-water habitat in working landscapes. In addition, the restoration of a historic spring channel may provide added ecosystem benefits by enhancing aquatic habitat for cold-water species.

Climate change impacts on regional agricultural irrigation water use in semi-arid environments

Climate change impacts on regional agricultural irrigation water use in semi-arid environments

High-frequency monitoring of Secchi-disk depth in Taihu Lake using Himawari-8/AHI data.

Diurnal monitoring of the Secchi-disk depth (SDD) of eutrophic lakes is the basic requirement to ensure domestic, industrial, and agricultural water use in surrounding cities. The retrieval of SDD in high frequency and longer observation period is the basic monitoring requirement to guarantee water environmental quality. Taking Lake Taihu as an example, the diurnal high-frequency observation (10 mins) data of the geostationary meteorological satellite sensor AHI/Himawari-8 were examined in this study. The results showed that the AHI normalized water-leaving radiance (Lwn) product derived by the Shortwave-infrared atmospheric correction (SWIR-AC) algorithm was consistent with the in situ data, with determination coefficient (R2) all larger than 0.86 and the mean absolute percentage deviation (MAPD) of 19.76%, 12.83%, 19.03% and 36.46% for the 460 nm, 510 nm, 640 nm and 860 nm bands, respectively. 510 nm and 640 nm bands showed more better consistency with in situ data in Lake Taihu. Therefore, an empirical SDD algorithm was established based on the AHI green (510 nm) and red (640 nm) bands. The SDD algorithm was verified by in situ data showed good performance with R2 of 0.81, RMSE of 5.91 cm, and MAPD of 20.67%. Based on the AHI data and established algorithm, diurnal high-frequency variation of the SDD in the Lake Taihu was investigated and the environmental factor (wind speed, turbidity degree, and photosynthetically active radiance) corresponding to diurnal SDD variation were discussed. This study should be helpful for studying diurnal high-dynamics physical-biogeochemical processes in eutrophication lake waters.

Water distribution and scheduling model of an irrigation canal system

A complete water distribution scheme should include the scheduling of the check gates and turn out gates. This study aims to resolve the water distribution problem in irrigation districts based on channel hydrodynamic simulation and using the hydraulic factor of water level increase in backwater areas. The supply-decided water distribution and scheduling model(SD-WDSM), the demand-decided water distribution and scheduling model(dd-WDSM) were established respectively. The model was applied to the Bojili irrigation district to verify it’s applicability. The results show that the SD-WDSM can adjust the length of the backwater area through the operation of the check gate, ensuring a large flow rate at the turn out gate. The dd-WDSM was established to group the water diversion canals by rotation irrigation, and the turn out gate in the same group could open and close simultaneously, which is convenient for the administrator to operate. The two models also ensure that the water is diverted as early as possible, and the operation numbers of the check gates and the turn out gates are less. The model obtains the complete scheduling scheme of the check gates and the turn out gates in the water distribution system. This model can improve agricultural water use efficiency and promote sustainable agricultural development. The proposed model is universal and can be applied to other irrigation districts.

Coordinated power-water optimization for precision irrigation among distribution network and agricultural parks

With more and more agricultural parks are integrated to the electrical distribution network, the disordered characteristics of farmers’ irrigation water consumption will not only increase the cost of water and electricity, but also cause security problems in traditional term of rural distribution network, such as large short-term load fluctuation, overload and transformer load imbalance. In this context, this paper proposes a double-layer master–slave game model of power-water interaction and coordination between distribution network and agricultural irrigation park under photovoltaic (PV) assisted agricultural precision irrigation. The upper layer (electrical distribution network) plays an interactive game with the lower layer (agricultural irrigation parks) by establishing effective time-of-use (TOU) price. On the one hand, the electrical distribution network takes the operation security as the optimization objective, it could optimize line loss by network configuration and guides agricultural irrigation parks to consume electricity orderly by formulating electricity prices. On the other hand, agricultural irrigation parks take satisfaction and cost as the optimization objective after receiving TOU price from upper layer, and regulates the operation time and intensity of irrigation pumps to realize precise irrigation. Finally, an example is given to verify the model on the modified 148-node system. It is determined that the model can effectively support the safe and reliable operation of rural distribution network while realizing the transformation of agricultural irrigation water use from low efficiency to economical and high efficiency, so as to achieve win–win between agricultural irrigation park and distribution network.