Agricultural Irrigation Water Use Research Articles

Response of photosynthesis, population physiological indexes, and yield of cotton in dry areas to the new technology of "dry sowing and wet emergence".

In arid areas, exploring new "dry sowing wet emergence (DSWE)" water-saving irrigation techniques may become one of the most important ways to reduce agricultural irrigation water use and improve economic efficiency. The study was conducted in a two-year field trial in 2021 and 2022, setting up three seedling emergence rates (W1: 6 mm, W2: 10.5 mm, W3: 15 mm) and two drip frequencies (D1: 2 times, D2: 4 times) for a total of six irrigation combinations. The results indicate that under the "DSWE" irrigation pattern, in contrast to the low frequency treatment, the photosynthetic efficiency of cotton leaves in the high-frequency treatment is significantly higher. The stomatal conductance of cotton leaves has increased by 6.67% within two years, and the net photosynthetic rate has risen by 12.22%. Compared with the CK treatment, there is no remarkable difference in the photosynthetic indicators of the W3D2 treatment, while the net photosynthetic rate has increased by 1.68%. The population physiological indicators of each treatment group exhibit a trend of initially increasing and then decreasing as the growth period prolongs. The differences in the group population physiological indicators of cotton at the seedling stage among different seedling water treatments are relatively minor. The high frequency treatment maintains a relatively high level throughout the growth period. Compared with the low-frequency treatment, the yields of lint cotton and seed cotton in the high-frequency treatment have increased by 14.77% and 20.89%, respectively. Compared with the winter irrigation technology, there are no significant differences in the cotton yield and quality indicators of the "DSWE" high-frequency and high-seedling water treatment (W3D2). Over two years, the average unit yields of lint and seed cotton have decreased by 1.95% and 3.01%, respectively. Nevertheless, irrigation water during the growth period declined by 38.46%. The appropriate "DSWE" irrigation technology (W3D2) can significantly enhance the physiological indicators of cotton, ensuring crop yield and quality while significantly reducing the amount of agricultural irrigation water.

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

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.

Influence of anthropogenic nitrogen inputs and legacy nitrogen change on riverine nitrogen export in areas with high agricultural activity

Increased riverine nitrogen (N) concentrations due to human activities is one of the leading causes of water quality decline, worldwide. Therefore, quantitative information about the N exported from watershed to the river (TN exports) is essential for defining N pollution control practices. This paper evaluated the changes in net anthropogenic N inputs (NANI) and the N stored in land ecosystems (legacy N) in the Jianghan Plain (JHP) from 1990 to 2019 and their impacts on TN exports. Moreover, an empirical model was developed to estimate TN exports, trace its source, and predict its future variations in 2020–2035 under different scenarios. According to the results, NANI exhibited a rise-decrease-rise-decrease M-shaped trend, with N fertilizer application being the dominant driver for NANI change. In terms of the NANI components, non-point-source was the primary N input form (96%). Noteworthy is that the correlation between NANI and TN exports became weaker over time, and large differences in changing trends were observed after 2014. A likely cause for this abnormal trend was that the accumulation of N surplus in soil led to N saturation in agricultural areas. Legacy N was also an important source of TN exports. However, the contribution of legacy N has rarely been considered when defining N pollution control strategies. An empirical model, incorporating legacy N, agricultural irrigation water use, and cropland area ratio, was developed. Based on this model, legacy N contributed a large proportion (15–31%). Furthermore, the results of future predictions indicated that legacy N had a larger impact on future TN exports changes compared to other factors, and increased irrigation water would increase rather than decrease TN exports. Therefore, an integrated N management strategy considering the impact of NANI, legacy N, and irrigation water use is crucial to control N pollution in areas with intensive agriculture.

Application of Cosmic-Ray Neutron Sensor Method to Calculate Field Water Use Efficiency

Field water use efficiency is an important parameter for evaluating the quality of field irrigation in irrigated areas, which directly affects the country’s food security and water resource allocation. However, most current studies use point-scale soil moisture (SM) or remote sensing water balance models to calculate the field water use coefficient, which cannot avoid errors caused by the spatial heterogeneity of SM and insufficient spatial resolution of remote sensing data. Therefore, in this study, the cosmic-ray neutron sensor (CRNS), Time-Domain Reflectometers (TDR) and Automatic Weather Stations (AWS) were used to monitor the meteorological and hydrological data such as SM, atmospheric pressure, and precipitation in the experimental area of Jinghuiqu Irrigation District for three consecutive years. The scale of the CRNS SM lies between the point and the remote sensing. Based on the CRNS SM, the calculation method for canal head and tail water was used to calculate the field water use efficiency to evaluate the level of agricultural irrigation water use in the experimental irrigation area. The results showed that CRNS could accurately detect the change in SM, and four irrigation events were monitored during the winter wheat growth period from October 2018 to June 2019; the calculation result of field water use efficiency in the experimental area was 0.77. According to the field water use efficiency of the same irrigation area from October 2013 to October 2015 in other studies, the field water use efficiency during the growing period of winter wheat in this area increased from 0.503 to 0.770 in 2013–2019, indicating a significant improvement in the field water use level. In general, this study not only solves the problem of low calculation accuracy of field water use efficiency caused by the mismatch of SM monitoring scales but also explores the application potential of CRNS in agricultural irrigation management and water resource allocation.

Individualized and Combined Effects of Future Urban Growth and Climate Change on Irrigation Water Use in Central Arizona

AbstractIrrigation in agricultural and urban settings is responsible for nearly 80% of the water use in the Phoenix Metropolitan Area. Over the last three decades, there has been a continuous decrease in cropland area and its water consumption. Meanwhile, urbanization has increased outdoor irrigation to maintain residential areas and parks. Given these trends, irrigation water use (IWU) is subject to large uncertainties which challenge land and water management. In this work, we used a land surface model with an irrigation module to quantify urban and agricultural IWU under the individualized and combined effects of future urban growth and anticipated climate change. A large set of scenario combinations (96 in total) allowed us to bracket plausible pathways of IWU change in the 21st Century. We found that land use change reduced IWU by −4.6% to −0.1% due to savings from crop‐urban conversion, while climate change effects led to increases in IWU by +3.8% to +8.6%. When combined, total IWU changed from +2.5% to +5.8% in the intermediate future (2041–2070) and from −0.5% to 6.8% in the far future (2071–2100). These outcomes suggest that water savings from land use change will likely not be able to compensate for the increasing demand from urban irrigation when considering climate change, under current irrigation practices. Our approach to model the interconnections between land and water under climate change can be used to support sustainable water planning in cities in other arid regions.

Performance evaluation of vetiver and pampas plants in reducing the hazardous ions of treated municipal wastewater for agricultural irrigation water use

Abstract Phytoremediation is one of the simple and cost-effective methods introduced in recent years as a solution for eliminating environmental pollution. This study aims to assess the feasibility and effectiveness of using vetiver grass and pampas grass plants in removing the main pollutants and improving the physical and chemical properties of the treated municipal wastewater, for use in agriculture and drip irrigation systems. This study was conducted in the form of a factorial experiment with two factors of plant type (vetiver grass and pampas grass) and residence time (in five levels: 3, 6, 9, 12, and 15 days) and in a completely randomized design with three replications. The results showed that although both plant types had a high potential to reduce the undesirable properties of treated wastewater with a residence time of 15 days, pampas grass exhibited better performance in most of the studied characteristics. This plant, even with a residence time of 3 days, reduced the concentration of chloride, sodium, calcium, carbonate, and bicarbonate and also the sedimentation index by 58.82, 38.64, 40.03, 73.91, 45.44, and 88.16%, respectively. Moreover, pampas grass reduced the salinity and hardness of water by 48.84 and 23.32%, respectively, and the electrical conductivity and TDS by at least 18.32% in 3 days. According to the findings of this study, pampas grass is a better option than its competitor, vetiver grass, to reduce pollution in treated urban wastewater and improve wastewater quality for use in agriculture and drip irrigation systems.

Comprehensive assessment of the water environment carrying capacity based on the spatial system dynamics model, a case study of Yongding River Basin in North China

The Chinese water environment system is severely degraded by intensive anthropogenic activities. To relieve these problems, the national government has proposed to establish a comprehensive evaluation system of water environment carrying capacity (WECC). However, few studies provide a comprehensive depiction of the spatiotemporal heterogeneity of WECC within a basin/region owing to the limitations of interdisciplinary research methods. By integrating the system dynamics model, cellular automaton model, and gridded geographic information system technology, we developed a spatial system dynamics model to explore the spatiotemporal pattern of the WECC of Yongding River Basin in North China. The spatial system dynamics model works well and the simulation accuracy was close to 85%. Our results showed that inadequate water resources and water quality induced the overloaded WECC in Yongding River Basin, which was unevenly distributed within the river basin. From 2017 to 2035, Zhangjiakou often suffered an overload of WECC throughout the year due to quantity-related water shortages. However, in Beijing's mountainous area, the WECC status of control units 1 and 4 was in good status owing to sufficient water quantities. Considering the overload of the WECC and its feedback relationship with anthropogenic activities, effective and feasible management measures, such as reducing agricultural irrigation water use and domestic pollution, improving the rate of sewage collection and treatment, or industrial restructuring should be prioritized in this arid river basin. Our study improved methodologies in WECC modeling for river basins, helped overcome difficulties in revealing the spatiotemporal dynamic patterns of WECC, proposed a calculation method of WECC in terms of population and GDP, and verified that the threshold of WECC was not static, which provides information for finding a balance between economic development and water safety, especially in regions with water scarcity.

A Deep Learning Approach for Multi-Depth Soil Water Content Prediction in Summer Maize Growth Period

Advance knowledge of soil water content (SWC) in the soil wetting layer of crop irrigation can help develop more reasonable irrigation plans and improve the efficiency of agricultural irrigation water use. To improve the accuracy of predicting SWC at multiple depths, the ResBiLSTM model was proposed, in which continuous meteorological and SWC data were gridded and transformed as model inputs, and then high-dimensional spatial and time series features were extracted by ResNet and BiLSTM, respectively, and integrated by a meta-learner. Meteorological, SWC and growth stage records data from seven typical maize monitoring stations in Hebei Province, China, during the 2016-2018 summer maize planting process were utilized for the training, evaluation and testing of the ResBiLSTM model, with model prediction targets set at 20cm, 30cm, 40cm and 50cm depths. Experimental results showed that: 1) ResBiLSTM model could achieve better model fit and prediction of meteorological and SWC data at all growth stages, with R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> within [0.818, 0.991], average MAE within [0.79%, 2.00%], and the overall prediction accuracy ranked as follows: anthesis maturity stage > seedling stage > tassel stage; 2) The average MSE of the ResBiLSTM model for the prediction of SWC in the next 1-6 days was within [3.91%, 15.82%], and the prediction accuracy decreased with the extension of the prediction time; 3) Compared with the classical machine learning model and related deep learning models, the ResBiLSTM model was able to obtain better prediction accuracy performance.

A new approach to separating the impacts of climate change and multiple human activities on water cycle processes based on a distributed hydrological model

The impacts of human activities on the natural water cycle have become increasingly severe due to population growth and economic development. Therefore, it is important to evaluate the contributions of different human activities (e.g., land-use change, industrial water use, and domestic water use) on different hydrological variables. However, existing attribution methods have shortcomings when attributing the impacts of different human activities; for instance, human activities may only be considered as one impact factor, and the total impact of all factors may not be guaranteed to equal 100% of the total change. A new approach, using multiple scenario simulations from a distributed model, was developed in this study to overcome these shortcomings. All potential contributions for one impact factor were calculated by fixing the other impact factors at different statuses, and the arithmetic mean of all potential contributions was presented as the final result. This method ensures that the sum of the contributions of all impact factors equals the total change in hydrological variables between two periods, which was demonstrated mathematically. A case study of the Wei River Basin was used to evaluate the proposed methodology, which attributed four impact factors (climate change, land-use change, industrial and domestic water use, and agricultural irrigation water use) to three hydrological variables (evapotranspiration, rainfall infiltration, and streamflow drainage into the Yellow River). The results showed that the new method could attribute the impacts of the four factors to the changes of the three annual average hydrological variables between the period 1956–1980 and the period 1981–2005; these four factors accounted for 373.3%, −33.3%, −133.3%, and −106.7% of the change in evapotranspiration, 129.8%, −2.2%, −3.5%, and −24.1% of the change in rainfall infiltration, and 75.2%, 4.4%, 13.4%, and 7.0% of the change in streamflow drainage into the Yellow River, respectively. Moreover, the sum of the relative contributions of the four impact factors to the three hydrological variables was equal to 100% at an annual time scale. To avoid the limitations of existing methods, we recommend adopting the newly proposed method for evaluating the impacts of climate change and multiple human activities on water cycle processes.

Assessment of Potential Climate Change Effects on the Rice Yield and Water Footprint in the Nanliujiang Catchment, China

The Nanliujiang catchment is one of major rice production bases of South China. Irrigation districts play an important role in rice production which requires a large quantity of water. There are potential risks on future climate change in response to rice production, agricultural irrigation water use and pollution control locally. The SWAT model was used to quantify the yield and water footprint (WF) of rice in this catchment. A combined method of automatic and manual sub-basin delineation was used for the model setup in this work to reflect the differences between irrigation districts in yield and water use of rice. We validated our simulations against observed leaf area index, biomass and yield of rice, evapotranspiration and runoff. The outputs of three GCMs (GFDL-ESM2M, IPSL-CM5A-LR and HadGEM2-ES) under three RCPs (RCP2.6, 4.5, 8.5) were fed to the SWAT model. The results showed that: (a) the SWAT model is an ideal tool to simulate rice development as well as hydrology; (b) there would be increases in rice yield ranged from +1.4 to +10.6% under climate projections of GFDL-ESM2M and IPSL-CM5A-LR but slight decreases ranged from −3.5 to −0.8% under that of HadGEM2-ES; (c) the yield and WFs of rice displayed clear differences in the catchment, with a characteristic that high in the south and low in the north, mainly due to the differences in climatic conditions, soil quality and fertilization amount; (d) there would be a decrease by 45.5% in blue WF with an increase by 88.1% in green WF, which could provide favorable conditions to enlarge irrigated areas and take technical measures for improving green water use efficiency of irrigation districts; (e) a clear rise in future grey WF would present enormous challenges for the protection of water resources and environmental pollution control in this catchment. So it should be to improved nutrient management strategies for the agricultural non-point source pollution control in irrigation districts, especially for the Hongchaojiang and Hepu irrigation districts.

Agricultural Irrigation Water Use in a Closed Basin and the Impacts on Water Productivity: The Case of the Guadalquivir River Basin (Southern Spain)

This paper analyses the agricultural irrigation water use in a closed basin and the impacts on water productivity, and examines how they have affected the ‘closure’ process of the Guadalquivir river basin observed in recent decades. Following a period of expansion in irrigation, an administrative moratorium was declared on new irrigated areas in 2005. Since then, the main policy measure has been aimed at the modernisation of irrigated agriculture and the implementation of water conservation technologies. The analysis carried out in this paper shows a significant increase in mean irrigation water productivity in the pre‐moratorium period (1989–2005), driven by the creation of new irrigated areas devoted to high value crops and with a dominant use of deficit irrigation strategies, while a second phase (2005–2012) is characterised by slower growth in terms of the mean productivity of irrigation water, primarily as a result of a significant reduction in water use per area. Findings show that productivity gains seem to have reached a ceiling in this river basin, since technological innovations (such as new crops, deficit irrigation, and water‐saving and conservation technologies) have reached the limits of their capacity to create new value.

Expansion of an Existing Water Management Model for the Analysis of Opportunities and Impacts of Agricultural Irrigation under Climate Change Conditions

The impact of climate change and increased irrigation area on future hydrologic and agro-economic conditions was analysed for a representative basin in northeastern Germany using an expanded version of the WBalMO (water balance model) for water management. The model expansion represents various temporally and spatially differentiated irrigation water use processes, including agricultural irrigation, as part of a river basin’s water management. We show that climate changes lead to increased irrigation water demands in the future, which will not always be able to be met. The resulting water deficits were shown for different crops depending on their irrigation priority and the water available. With an increased irrigation area, water deficits will rise. This may limit the profitability of agricultural irrigation. The impacts of climate change on low-flow conditions in the river are much higher than those of the increase in irrigated area alone. Therefore, any additional increases of irrigation will require careful monitoring of water availability to avoid critical impacts on river flows. The expanded model was able to replicate the processes of agricultural irrigation water use and can thus be used to test the impact of policies such as the certification of new irrigation permits.

Agricultural water-saving potential in Guanzhong Irrigation Area in different hydrologic years

There has been a rampant water shortage in the Wei River Basin in recent years, significantly affecting the ecological and economic functions of the river and drastically limiting the socio-economic development of the administrative regions within the basin. Although the respective local/national governments have adopted adjustment strategies of the water use structure, agriculture has remained the biggest water user, accounting for over half of total water use in the basin. Meanwhile, agricultural water use efficiency in the basin has been some 1 kg·m?3, much lower than that in developed countries like Israel and USA. The main reasons for the low agricultural water use efficiency have included low use of advanced technology(e.g., springklers, drop irrigation and mulching), low channel lining rates and high water contamination. In this study, we summarized the current state and trend in agricultural irrigation, calculated the agricultural water-saving potential and then developed a new mode based on current and future crop water requirement. The two main modules of the mode(resource-based water-saving and efficiency-based water-saving) were respectively representative of small-scale and large-scale water analysis. Based on main crops in typical irrigation areas, different water-saving schemes were designed and the water-saving potential of each scheme calculated. The probable water-saving amounts in the nine irrigation districts were analyzed and calculated for different hydrologic years. For instance, in years with water guarantee rates of 25%, 50%, 75% and 95%, agricultural water-saving potentials in Guanzhong Irrigation Area were respectively 30.69 million m3, 111.67 million m3, 117.50 million m3 and 125.21 million m3. Efficiency-based water-saving potential was over 50%, expect for the 25% rate water guarantee condition where it was 42%. Then based on present water-saving technology and planting structure characteristics of the nine irrigation areas, a water-saving mode was put forward which reduced water diversion by 10% and improved agricultural irrigation water use efficiency by 5%. Exploitation of agricultural water-saving potential was the basis for water resources reallocation in the region. This study also laid the base for theoretical and technical support for the development of water-saving irrigated agriculture, planning of water resources reallocation and construction of water-saving society.