Agricultural Water Use Efficiency Research Articles

Assessing Irrigation Efficiency Improvements in Paddy Fields Using Granular SWMM Simulations

As water scarcity intensifies due to climate change, improving the efficiency of agricultural water use has become increasingly critical. Current irrigation systems often experience significant water losses, especially in paddy fields in South Korea that largely rely on open-channel water supply networks. However, previous studies have simulated irrigation improvement strategies by aggregating multiple paddy fields into larger unites rather than modeling them individually, which limits the accurate representation of field conditions. To address this limitation, we applied a granular simulation approach, collecting detailed input data through field surveys. Using this granular model, the study evaluated strategies to enhance irrigation efficiency in paddy fields serviced by the Baekma Agricultural Reservoir in South Korea. We assessed four scenarios: the current open-channel system, conversion of open channels to closed conduits, installation of farm ponds, and a combination of closed conduits and farm ponds. These scenarios were simulated using the Strom Water Management Model (SWMM), meticulously configured to represent individual paddy fields and channel networks. The results show that converting open channels to closed conduits increased irrigation efficiency by 5.4% compared to the current open-channel system. Combining closed conduits with farm ponds achieved the highest efficiency, although the independent effect of farm ponds was minimal. These findings suggested that converting open-channels to closed conduits was a highly effective solution for reducing water losses, while farm ponds played a limited role. This study provides valuable insights into the development of precise irrigation strategies, offering a detailed assessment of real-world conditions in paddy fields.

Are Water Use Efficiency and Effectiveness Relatively Lower in Arid Zones? Comparative Analyses of the Water Productivity of Typical Crops

Agriculture is the largest water user of all sectors. In arid regions in particular, achieving efficient water use in agriculture is an important way to solve water scarcity. However, the difference in water use efficiency between arid and humid regions has long been a focus of academic debate. Many studies consider water use efficiency to be higher in humid areas due to the abundance of water resources. This view is based on the fact that less irrigation in humid areas may lead to higher crop yields and better conditions for agricultural production; however, it ignores the efforts of researchers and agricultural workers in arid zones who have attempted to develop efficient water-saving technologies, as well as the effect of natural conditions on agricultural production. Correctly evaluating the efficiency of agricultural water use in arid zones is important for achieving efficient use of water resources, as well as for water management decisions. This study calculates the yield structure and water productivity of typical crops in both arid and humid regions in China based on the footprint theory and other methodologies. This approach allows for an accurate assessment of irrigation water benefits in various regions, providing a scientific basis for improving agricultural water use efficiency under different climatic conditions. The study results indicate that the average reliance on blue water for wheat and cotton gradually increases from 49.9% to 93.6% as regional aridity intensifies, ranging from the Central China Humid Region to the Northwest China Arid Region. Similarly, the average contribution of blue water to crop yield rises from 31.0% to 100%, while irrigation water productivity increases from 0.27 kg·m−3 to 0.53 kg·m−3. Finally, this study concludes that, in arid zones with lower precipitation and more hours of sunshine, a higher dependence on blue water for crop growth and development leads to a higher productivity of irrigation water. In addition, in arid zones, the focus should be on optimizing the use of irrigation water and improving irrigation technology and efficiency, while, in humid zones, there should be more use of natural precipitation to efficiently reduce dependence on irrigation water.

How can agricultural water use efficiency be promoted in the North China Plain?

Water resources are reliable guarantees for high quality development of agriculture in the North China Plain. Improving agricultural water use efficiency is one of the essential ways to solve agricultural water resources shortage. This study measured agricultural water use efficiency (AWUE) using a stochastic frontier analysis (SFA) model and estimated agricultural water-saving potential (AWP) for 74 prefecture-level cities in the North China Plain. The main factors that influenced AWUE were further identified by developing spatial econometric models. The results showed that: (1) From 2000 to 2020, the AWUE of the study area ranged from 0.701 to 0.755 and first rose then fell, and then leveled off. (2) Spatially, the best AWUE was in the central part, followed by the north, and the worst was in the south, and nearly 65% of prefectural cities had annual average AWUE below 0.8. (3) Significant gaps in AWUE and AWP were observed in different regions. Shijiazhuang, Anyang, Hebi and Xinxiang should be considered as key targets to improve AWUE. (4) The effective irrigation degree, per sown area annual precipitation, and annual average temperature had positive effect on AWUE. Increasing the corn sowing area appropriately and reducing the input of per sown area machinery power could also improve AWUE. Therefore, adopting deep plowing measures, developing semi-arid agriculture, and advancing water-saving irrigation technology were feasible ways to improve AWUE and contribute to sustainable agriculture in the North China Plain. These findings can provide a reference for the formulation of high-water efficiency agricultural management strategies in other similar major grain-producing areas.

REVIEW AND COMPARATIVE STUDY OF HYDROLOGICAL MODELS FOR RAINFALL-RUNOFF MODELLING

Water is considered as an important resources for human existence on the earth. In order to simulate or optimized hydrological data for various water resources management, several hydrological models are very useful to attain this aim for water resources management and as a decision support tools. A rainfall-runoff model is a quantitative prototype explaining the rainfall-runoff interactions at basin scale. The hydrological models have peculiarities in terms of capabilities for various water resources management. This paper tends to reviewed over fifty (50) papers that are peculiar to hydrological models as applicable to rainfall-runoff modeling. It involved evaluating and comparing different hydrological models used in simulating rainfall process converting into surface runoff for water use efficiency. Several runoff models such as Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), Precipitation-Runoff Modeling System (PRMS), Variable Infiltration Capacity model (VIC), LISt-based Erosion Model (LISEM), MIKE Surface Water - Groundwater Hydrology (MIKE SHE) and Runoff Prophet were critically assessed. Rainfall-runoff models are globally utilized for different applications to enhance water use efficiency across different sectors. However, types of hydrological models by examining various hydrological models, model accuracy by evaluating the accuracy and reliability of each model in predicting runoff from rainfall data, scope of applications by determining the adequacy of the models for numerous geographical regions and climatic circumstances, complexity and usability by assessing the complexity of the models, their data requirements, ease of use and computational efficiency, also the models advantages and limitations in capturing the dynamics of the rainfall-runoff process were critically assessed. This was to aid modeling objectives. It was inferred that HEC-HMS is widely applied for modelling precipitation-runoff processes in watersheds of various sizes, aiding in flood forecasting, reservoir operation, and water management for agricultural and urban water use efficiency. SWAT is used for assessing the impact of land management practices (e.g., crop rotation, irrigation, land use changes) on water resources, including runoff generation and water quality, thus optimizing water use efficiency in agriculture. PRMS is applied to model the transport of water via complex hydrological systems, aiding in watershed management and water use efficiency assessments. In conclusion, this comparative review seeks to guide water scientists, the users of hydrological models and hydrological engineers in selecting the most suitable models for their specific modelling needs for sustainable water resources management.

A Review on the Optimization of Irrigation Schedules for Farmlands Based on a Simulation–Optimization Model

Agriculture is the most important sector that is consuming water resources. In the context of global water scarcity, how to use limited water resources to improve water use efficiency in agriculture or achieve maximum crop yield and fruit quality is of great significance for ensuring food and water security. Optimizing irrigation schedules is an effective measure to improve water use efficiency, where crop models also play an important role. However, there is little research summarizing the optimization of irrigation schedules based on crop models. This study provides a systematic review on how to optimize irrigation schedules based on crop models and simulation–optimization models. When optimizing irrigation schedules based on crop models, the selected models are usually mechanistic agro-hydrological models. Irrigation scenarios and optimization objectives are mainly focused on both crop and water aspects, such as maximizing crop yield, fruit quality, water productivity, and irrigation water productivity. Minimizing crop water consumption and total irrigation amounts serve as optimization objectives, and irrigation quantity, irrigation frequency, and irrigation interval serve as decision variables. In saline areas or low fertilizer utilization areas, the optimization objectives and decision variables also involve some indicators related to salt and nitrogen, such as the maximum desalination rate, minimum salt content, fertilizer utilization efficiency, nitrogen fertilizer productivity, nitrogen fertilizer utilization efficiency, nitrogen leaching rate, which serve as the optimization objectives, and the irrigation water salinity, or fertilization schedules serve as the decision variables. When optimizing irrigation schedules based on simulation–optimization models, the models have mainly been upgraded from water-production function to crop mechanism models. In addition, optimization algorithms have been upgraded from traditional optimization techniques to intelligent optimization algorithms. Decision-making techniques are used to make decisions on optimization results. In addition, the spatial scale for the optimization problem of irrigation schedules was developed from fields to regions, and the time scale was developed from the growth stage, beginning with months, and shortening to ten days, then to a day, and then to an hour. This study also provides a detailed introduction to widely used optimization algorithms, such as genetic algorithms, as well as decision techniques. At the same time, it is proposed that the future should focus on improving crop models and analyzing uncertainty in research on irrigation schedule optimization, which is of great significance for the precise regulation of irrigation schedules.

Towards a modelling, optimization and predictive control framework for smart irrigation

Smart irrigation scheduling is a promising approach for improving the efficiency and sustainability of agricultural water use, especially in arid and semi-arid lands. In this paper, we present a design and simulation of a model predictive controller for smart irrigation scheduling. The proposed controller is based on a mathematical model of the irrigation system, which is used to predict the future states of the system and determine the optimal irrigation schedule for a given crop and field. This study further evaluates the impact of the predictive control framework on crop yield, water use efficiency (WUE), and water savings in tomato production. Three control strategies, including manual control, open-loop control, and model predictive control (MPC), were compared using a Completely Randomized Design (CRD) methodology. Results indicate that MPC outperforms the other strategies, yielding the highest average crop yield of 20 t/ha and demonstrating superior WUE at 10.4 kg/m3. Additionally, MPC significantly reduces water consumption, achieving a 29 % and 8 % savings compared to manual and open-loop control, respectively. These findings underscore the efficacy of MPC in optimizing crop yield, conserving water resources, and promoting sustainable agriculture practices. The proposed controller has the potential to address the global water scarcity challenge and contribute to the sustainability of agriculture in arid and semi-arid lands.

Thermal imaging from UAS for estimating crop water status in a Merlot vineyard in semi-arid conditions

AbstractThermal remote sensing indicators of crop water status can help to optimize irrigation across time and space. The Crop Water Stress Index (CWSI), calculated from thermal data, has been widely used in irrigation management as it has a proven association with evapotranspiration ratios. However, different approaches can be used to calculate the CWSI. The aim of this study is to identify the most robust method for estimating the CWSI in a commercial Merlot vineyard using high-resolution thermal imaging from Unoccupied Aerial Systems (UAS). To that end, three different methods were used to estimate the CWSI: Jackson’s model (CWSIj), Wet Artificial Reference Surface (WARS) method (CWSIw), and the Bellvert approach (CWSIb). A simpler indicator calculated as the difference between canopy and air temperature (Tc–Ta) was the benchmark to beat. The water status of a vine cultivar with anisohydric behavior (Merlot) in a vineyard in central Spain was assessed for two years with different agroclimatic conditions. Canopy temperature (Tc) was obtained from UAS flights at 9:00 h and 12:00 h solar hour over eight days during the irrigation period (June–August), and from vines under five different irrigation treatments. Stem water potential (SWP), stomatal conductance (gs), and leaf temperature (TL) were recorded at the time of the flights and compared with the thermal indices (CWSIj, CWSIw, CWSIb) and the benchmark indicator (Tc–Ta). Results show that the simpler indicator of water stress, Tc–Ta, performed better at identifying varying levels of crop hydration than CWSIb or CWSIw at 12:00 h. Under conditions of extreme aridity, the latter indices were less accurate than the physically-based CWSIj at 12:00 h, which had the highest correlation with SWP (r = 0.84), followed by the benchmark index Tc–Ta (r = 0.70 at 12:00). Considering the current climatic trends towards aridification, the CWSIj emerges as a useful operational tool, with robust performance across days and times of day. These results are important for irrigation management and could contribute to improving water use efficiency in agriculture.

Improving dryland maize productivity and water efficiency with heterotrophic ammonia-oxidizing bacteria via nitrification and cytokinin activity

A two-year field experiment conducted under dryland conditions in semi-humid and drought-prone regions of China aimed to assess the effect of ammonia-oxidizing bacterial on maize water use efficiency and yield. A heterotrophic ammonia-oxidizing bacteria (HAOB) strain S2_8_1 was used. Six treatments were applied: (1) no irrigation + HAOB strain (DI), (2) no irrigation + blank culture medium (DM), (3) no irrigation control (DCK), (4) irrigation + HAOB (WI), (5) irrigation + blank culture medium (WM), and (6) irrigation control (WCK). Results revealed that HAOB treatment increased maize growth, yield, and water use efficiency over controls, regardless of whether the year was wet or dry. This improvement was attributed to the accelerated nitrification in the rhizosphere soil due to HAOB inoculation, which subsequently led to increased levels of leaf cytokinins. Overall, these findings suggest that HAOB inoculation holds promise as a strategy to boost water use efficiency and maize productivity in dryland agriculture.

Soil water dynamics and deep percolation in an agricultural experimental area of the North China Plain over the past 50 years: Based on field monitoring and numerical modeling

The unregulated irrigation systems used in the late 20th century have led to increasingly severe deep percolation (DP) in the agricultural irrigation areas of the North China Plain. This has become an important factor limiting the efficient utilization of water resources and sustainable environmental development in these irrigation areas. However, the thick vadose zone is hydrodynamically exceptionally complex. The soil hydrological cycle is constantly changing under the influence of major climate change and human activity, thereby causing changes in DP that are difficult to quantify accurately. Here, the Luancheng Agricultural Irrigation District in North China was selected for a continuous 20-year in situ experiment. Soil-water dynamics were monitored using neutron probes and tensiometers, to determine the complete annual soil-water cycle and the hydrodynamic properties of the thick vadose zone irrigation district. For 1971–2021, DP was simulated using the HYDRUS-1D model and was verified by fitting observed values. Soil water content (SWC) exhibited similar trends in years that differed in terms of the amounts of irrigation and precipitation. The 0–100 cm soil layer was significantly affected by precipitation and other factors, and recharge >60 mm/d caused percolation. DP occurred mostly after irrigation or during the period of intensive precipitation in July–October. The maximum percolation rate was 16.9 mm/d under the present irrigation method. The main factors leading to DP were soil water storage capacity (R2 = 0.86) and precipitation (R2 = 0.54). Under the evolution of irrigation measures in the last 50 years, the average DP has gradually decreased from 574.2 mm (1971–1990) to 435.5 mm (2005–2021). However, a substantial amount of precipitation and irrigation water infiltrated the soil and percolated into the deep soil layer without being utilized by the crop. Therefore, there is an urgent need to consider measures to reduce DP to improve water-use efficiency in agriculture.

Deficit Irrigation with Silicon Application as Strategy to Increase Yield, Photosynthesis and Water Productivity in Lettuce Crops.

In regions where water is a limited resource, lettuce production can be challenging. To address this, water management strategies like deficit irrigation are used to improve water-use efficiency in agriculture. Associating this strategy with silicon (Si) application could help maintain adequate levels of agricultural production even with limited water availability. Two lettuce crop cycles were conducted in a completely randomized design, with a factorial scheme (2 × 3), with three irrigation levels (60%, 80% and 100%) of crop evapotranspiration (ETc), and with and without Si application. To explore their combined effects, morphological, productive, physiological and nutritional parameters were evaluated in the crops. The results showed that deficit irrigation and Si application had a positive interaction: lettuce yield of the treatment with 80% ETc + Si was statistically similar to 100% ETc without Si in the first cycle, and the treatment with 60% ETc + Si was similar to 100% ETc without Si in the second cycle. Photosynthetic rate, stomatal conductance, intercellular CO2 concentration, transpiration rate and total chlorophyll content increased under water-stress conditions with Si application; in the first cycle, the treatment with 80% ETc + Si increased by 30.1%, 31.3%, 7.8%, 28.46% and 50.3% compared to the same treatment without Si, respectively. Si application in conditions of water deficit was also beneficial to obtain a cooler canopy temperature and leaves with higher relative water content. In conclusion, we found that Si applications attenuate water deficit effects and provide a strategy to ameliorate the yield and water productivity in lettuce crops, contributing to more sustainable practices in agriculture.

Assessment of Broccoli (Brassica oleracea) Cultivation under Two Irrigation Systems in Central Iraq

A field experiment was conducted in the Abbasiya area of Najaf Governorate, located in the Middle Euphrates region during the winter season of 2022-2023. The primary focus of the study was to evaluate the performance of two irrigation systems, nano-irrigation, and subsurface drip irrigation, on broccoli plants grown in clay soil. The experimental design followed a Complete Randomized Block Design (CRBD). Nano-irrigation demonstrated several advantages over subsurface drip irrigation. It exhibited a reduction inater con-sumption and lower energy requirements for water pumping opera-tions. Notably, the root length of broccoli plants was significantly greater under the nano-irrigation system, with an increase of 18.2 cm compared to the drip irrigation system. The use of nano-irrigation resulted in better water use efficiency and energy efficien-cy, leading to improved root development in the broccoli plants. The study results indicated that nano-irrigation offers benefits in terms of water conservation and plant growth promotion, ultimately leading to increased overall productivity. This makes nano-irrigation an appealing option for improving water use efficiency in agriculture, particularly in regions that face water scarcity. Moreo-ver, there was no significant difference in yield between the nano-irrigation and subsurface drip irrigation systems.

Optimal allocation of soil and water resources in agriculture under the total regional evapotranspiration indicator: A case study in Guangping, China

There is a mismatch between crop water demand, the spatial and temporal distribution of natural rainfall, surface water sources, and arable land resources in the North China Plain. This has been compensated for by massive groundwater exploitation, and as a result, ground water levels have continuously declined and groundwater landing funnels have formed in some areas. Consequently, there is an urgent need for the rational allocation of soil and water resources. In this study, regional soil types and the corresponding crops in Guangping County, Hebei Province, China, alongside the regional annual average total water consumption were used to determine reasonable allocations for crop planting structures, with an aim of maximizing the water utilization efficiency and economic benefits while also achieving a regional groundwater dynamic equilibrium. Daily meteorological data from 1973 to 2021, including precipitation, temperature, sunshine hours, wind speed, and humidity, as well as crop data, including irrigation systems and crop growth status, were collected. Water consumption models for eight soil types and seven typical crops forming 56 calculation partitions were established to obtain annual average water consumption values for the different crops. The maximum economic benefit and water-use efficiency were then used as the objective functions and total water consumption as the control condition for the non-dominated sorted genetic algorithm-Ⅱ (NSGA-II), to optimize the allocation of soil and water resources in the region; the adjusted quantities for the different crops cultivated under different soil types in the study area were obtained. The areas growing sweet potato and vegetable-fruits were found to increase by 0.5255 km2 and 4.4452 km2, respectively, when compared to the pre-optimization period, whereas the areas with winter wheat-summer maize, millet, peanut, cotton, and summer maize decreased by 1.3481 km2, 0.1812 km2, 0.7316 km2, 2.0896 km2, and 0.62 km2, respectively. The economic benefit increased from 810.37 to 853.64 million yuan, while the water-use efficiency increased from 1.5426 kg/m3 to 1.5859 kg/m3. The results provide a basis for soil and water resource management in the region and a technical reference for similar areas to improve agricultural water-use efficiency and economic benefits.

Enhancement of Soil Organic Carbon, Water Use Efficiency and Maize Yield (Zea mays L.) in Sandy Soil through Organic Amendment (Grass Peat) Incorporation

The efficient use of organic amendment (OM) is considered an economic, environmental and sustainable practice to improve soil quality, especially the accumulation of organic carbon (C) and water use efficiency (WUE) in dryland agriculture. However, the effect of different OM on soil nutrients, organic carbon fractions, water content and maize yield is unclear in arid and semi-arid regions with sandy soil. Field experiments with four OM, grass peat (GP), biochar (BC), organic fertilizer (OF) and maize straw (MS), were conducted with an equivalent amount of C input on the southeastern edge of Mu Us Sandy Land in China. Results indicated that the soil nutrients and labile organic carbon (DOC, MBC, KMnO4-C and POC) concentrations were higher under OM (GP, BC, OF and MS) treatments than in CK in the 0–0.10 m soil layers. GP treatment remarkably improved carbon pool index values (1.63, 2.51 and 2.24, respectively) in all layers compared to CK (1.00). At maturity stages of maize, the soil water content (SWC) under GP and OF treatments (11.3–13.4%) was remarkably higher than that in CK treatment (around 10.0%). Yield and WUE were remarkably greater in GP and OF treatments compared to CK. The results proved that GP amendment is superior for barren sandy soil than BC, OF and MS treatments in improving soil nutrients, organic carbon sequestration, WUE and crop yield in China.

Influence of energy poverty on agricultural water efficiency using a panel data study in China

The research attention is increasingly directed towards the effective integration of the 17 United Nations Sustainable Development Goals (SDGs) within the limitations of the real world and amidst intersectoral conflicts. In light of the inextricable relationship between irrigation and energy, the objective of this study is to identify potential avenues for achieving the SDG6 and SDG7 goals of enhancing water use efficiency in agriculture and eradicating energy poverty, respectively. Utilizing data from 30 Chinese provinces from 2002 to 2017, this study explores the dynamic influence of energy poverty on agricultural water efficiency with a system generalized method of moments methodology. The findings suggest that energy poverty may greatly reduce agricultural water efficiency. The heterogeneity study shows that when agricultural water efficiency grows, the negative impacts of energy poverty continue to fade. Based on an assessment of various processes, results suggest that non-farm employment and cropping structure modification is a prominent conduit via which energy poverty negatively influences agricultural water efficiency.

Surface temperature adjustment in METRIC model for monitoring crop water consumption in North China Plain

Evapotranspiration is the real water consumption element in agricultural water management. In order to improve the efficiency of agricultural water use and maintain the sustainable development of agriculture, more and more attention has been paid to the improvement of monitoring and management of farmland evapotranspiration. In this study, MODIS data and the Temperature Vegetation Dryness Index (TVDI) were used in the METRIC model to estimate evapotranspiration for winter wheat and summer corn in the North China Plain. In order to decrease the error caused by the spatial heterogeneity of air temperature in the estimation of evapotranspiration, based on the characteristics of cold pixels with surface temperatures close to their air temperature, the TVDI was used to assist the selection of cold pixels and obtain the spatial variation trend of air temperature with latitude from all cold pixels in the study area. The influence of the spatial heterogeneity of air temperature on the surface temperature at the time of the satellite overpass was corrected accordingly, thereby the estimation accuracy of evapotranspiration was improved. A METRIC-TVDI model was established and the evapotranspiration of winter wheat and summer corn in Hebei Plain was estimated from 2017 to 2019. The average evapotranspiration of the winter wheat over these three years were 361 mm, 327 mm and 354 mm respectively, and that of summer corn were 394 mm, 388 mm and 405 mm respectively. Based on the farmland water balance, the irrigation water consumption (evapotranspiration minus precipitation) of winter wheat and summer corn rotation were 324 mm, 134 mm and 360 mm respectively. This kind of crop rotation pattern consumed more groundwater for irrigation, especially the winter wheat. In order to realize the balance of groundwater between exploitation and replenishment in Hebei Plain, more water-saving irrigation technologies should be adopted to reduce the evapotranspiration and improving water use efficiency.

Streamlining Different Plant Breeding Methods to Enhance Water Use Efficiency in Agricultural Systems

The relevance of Water in human life and agro-ecosystems has been extensively illustrated for decades around the globe. Despite the reality that the earth is mostly surrounded by water, its utility has been limited to domestic consumption and agricultural purposes. Thus, tweaking water usage in agricultural systems has been a tricky problem in order to meet the requirements of the growing population and to obtain more crop yield per drop of water in agriculture. In this review, an attempt has been made to revisit the methods available to improve water use efficiency in agriculture.

Analysis of the Spatial Correlation Network Structure of Agricultural Water Use Efficiency in Northwest China

There are some problems in Northwest China, such as the fragile ecological environment, poor basic conditions of agricultural production, low efficiency of agricultural water use, and difficulty in clarifying the path of agricultural water use efficiency (AWUE) improvement. Based on the superefficiency data envelopment analysis (DEA) model, this study increases the amount of ‘green water’ resources in the agricultural water consumption index of the input index and increases the wastewater pollutants (total chemical oxygen demand emissions; total ammonia nitrogen emissions) in the undesired output index to measure the AWUE in the northwest region. Based on the calculation results of AWUE, combined with the modified gravity model, the connection strength of AWUE between any two provinces in Northwest China is calculated, and the spatial structure and network characteristics of AWUE in this area are analysed via the social network analysis (SNA) method. The results show that the average AWUE in 2020 is nearly two times higher than that in 2011. From the situation of the northwest provinces, the average AWUE of the five provinces is in the order of Qinghai > Shaanxi > Gansu > Ningxia > Xinjiang. The AWUE value, total population, real GDP and per capita GDP of the capital cities of the five provinces in Northwest China are the key factors for the improvement of the connection intensity of AWUE. From 2011 to 2020, the connection intensity and closeness of AWUE in Northwest China increased, and there was a clear network hierarchy. The improvement in overall AWUE in the region is mainly due to the radiation and driving effect of the central province on other provinces. Based on this, the study proposes policy recommendations for gradually realising the AWUE improvement path of the central province (Shaanxi; Gansu)—cooperation circle (Shaanxi–Ningxia; Gansu–Qinghai)—the whole region. The results provide theoretical support and a quantitative basis for optimising the spatial pattern of agricultural water resources and improving AWUE in Northwest China.

Analysis of the Scale Effect and Temporal Stability of Groundwater in a Large Irrigation District in Northwest China

The depth to groundwater table (DGT) and the stability sites of groundwater were closely related parameters in groundwater research. Controlling the DGT and identifying stability sites of DGT were of great significance to prevent soil salinization and improve groundwater monitoring. In this study, using DGT data from the Hetao Irrigation District (HID) from 1991 to 2015, combined with spatial interpolation and coefficient-of-variation methods, this study explored the spatiotemporal variation characteristics and scale-effect problems of DGT from four hierarchical scales: the irrigation district, irrigation subdistrict, main canal, and branch canal. The Spearman correlation coefficient, average relative difference, and standard deviation were also used to further clarify the characteristics of groundwater time stability and its periodic variation rule. The results indicated that the spatiotemporal variation in DGT in the HID, and showed moderate variation characteristics, consistent with scale-effect features, which was deeply influenced by the regional climate and human activities. The DGT in the HID showed different temporal stabilities before and after 2000 caused by the application of Water-saving practices (WSPs). The stability sites were not entirely the same in different years or time periods, but they were all at the moderate DGT level in the HID. The results of this study can provide more insights for improving soil salinization and groundwater monitoring and provide more information for agricultural water-use efficiency and management.

Developing a Subsurface Drip Irrigation Scheduling Mode Based on Water Evaporation: Impacts Studies on Cucumbers Planted in a Greenhouse in the North China Plain

China is a country short of water resources, and improving the water use efficiency (WUE) in agriculture has become the only way to ensure sustainable development. In this article, subsurface drip irrigation (SDI) experiments of cucumber were implemented with a randomized block design comprising two factors and three levels, and the two factors were depth of drip belt buried and irrigation amount, which were determined by a 20 cm diameter pan’s water evaporation times its coefficient (Kp). The effects of schedule of SDI on soil evaporation (Es), evapotranspiration (ET), Kp, root dry matters, yield, and WUE of cucumber were studied. The results indicated that the Es and the ET decreased along with increasing depth of drip belt buried or decreasing amount of irrigation water applied. The relationships between ET and its total irrigation amount were significant linear positive correlations. Proportions of plant transpiration accounting for the ET were about 41~69% in two years, and it became bigger along with the increase of ET within a year. The Kp became smaller along with the reducing of ET. The roots of cucumber were mainly concentrated in the soil layer of 0~20 cm, and the two factors could only influence root dry weights of 0~60 cm soil layers significantly. The relationships between yield and ET were quadratic polynomial correlations. At last, an ultimate SDI scheduling mode based on water evaporation was established.

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.