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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. [ABSTRACT FROM AUTHOR]

This study aims to enhance maize water demand calculation. We calculate crop evapotranspiration (ETc) through mobile phone photography and meteorological parameters. In terms of crop coefficient (Kc) calculation, we utilize the mobile phone camera image driver to establish a real-time monitoring model of Kc based on plant canopy coverage (PGC) changes. The calculation of PGC is achieved by constructing a PGC classification network and a Convolutional Block Attention Module (CBAM)-U2Net is implemented by the segment network. For the reference crop evapotranspiration (ETo) calculation, we constructed a simplified ETo estimation model based on SVR, LSTM, Optuna LSTM, and GWO-SVM using a public meteorological data-driven program, and evaluated its performance. The results demonstrate that our method achieves high classification accuracy for the PGC 98.9% and segmentation accuracy for the CBAM-U2net-based segmentation network 95.68%. The Kc calculation model exhibits a root mean square error (RMSE) of 0.053. In terms of ETo estimation, the Optuna-LSTM model with four variables demonstrates the best estimation effect, with a correlation coefficient (R2) of 0.953. The final R2 between the estimated ETc value and the true value is 0.918, with an RMSE of 0.014. This method can effectively estimate the water demand of maize. [ABSTRACT FROM AUTHOR]

More than one-third of the global population relies on wheat as a staple food. To ultimately reduce inorganic nitrogen (N) usage through applying an organic fertilizer under drip irrigation and evaluate its effect on the yield, quality, and N utilization efficiency of winter wheat (variety Jimai 22) under various irrigation systems, an experiment was established and conducted in Yanghe Town, Jiaozhou City, from October 2020 to June 2022. The trial was designed with seven treatments, including a control (CK), to achieve a 25% total nitrogen reduction in all treatments except for CK. These treatments included drip irrigation with urea as CK, one-time application of urea through drip irrigation (FU1), one-time application of organic water-soluble fertilizer through furrow irrigation (FO1), one-time application of organic water-soluble fertilizer through drip irrigation (DO1), two-time application of organic water-soluble fertilizer through drip irrigation (DO2), one-time application of urea through drip irrigation (DU1), and two-time application of urea through drip irrigation (DU2). The results indicated that the application of a reduced N fertilizer plus an organic fertilizer significantly improved the dry matter accumulation (DMA) and the efficiency of N absorption and thus increased the grain yield. The DO2 treatment significantly exhibited a 15.5% and 16.9% increase in the DMA and the grain DMA in post-anthesis, respectively, compared to those of CK in the season of 2020–2021. Overall, the apparent nitrogen use efficiency with the drip irrigation topdressing treatments (DO1, DO2, DU1, DU2) increased significantly over two years in comparison with the urea fertilization through traditional furrow irrigation (CK), while the DO2 and DU2 treatments improved most significantly in the N use efficiency and N agronomic efficiency. Therefore, a reduced use of the inorganic N fertilizer with some organic fertilizers significantly increased the weight of thousand-grains and the yield of winter wheat, especially in the DO2 treatment, with an 11.7 t/ha and 10.9 t/ha increase, respectively, in both growing seasons of two years, while the DO2 treatment also improved the extensibility of wheat flour dough from grains harvested in both rainy (2020–2021) and less rainy (2021–2022) growing seasons. Therefore, we strongly recommend that two-time application of an organic water-soluble fertilizer through drip irrigation be the option to reduce the use of inorganic N fertilizers and increase the yield and quality of winter wheat under the conditions of this experiment. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilization plays a pivotal role in the nitrogen transport process and yield formation of field-grown Tibetan barley (Hordeum vulgare L., qingke in Chinese); however, little is known about its interaction with irrigation regimes. Here, we performed a control experiment to investigate the effects of irrigation regimes (primary irrigation and double irrigation, mentioned as W1 and W2) and N levels (0, 90, 120, and 150 kg ha−1, mentioned as N0, N9, N12, and N15) on the nitrogen accumulation, translocation, and utilization of Tibetan barley in the Tibetan Plateau during the spring barley seasons in 2022. The results showed that the highest yield (6242.28 kg ha−1) and aboveground biomass (12,354.13 kg ha−1 for anthesis; 15,827.9 kg ha−1 for maturity) were achieved in W2N15 as compared to other treatments. The maximum grain N accumulation (117.66 kg ha−1), the N translocation (54.16 kg ha−1), and the post-anthesis N accumulation (63.5 kg ha−1) were achieved in the W1N15 treatment. The N utilization efficiency increased with irrigation frequency and decreased with N application; however, the conclusion given by the N agronomic efficiency is contrary to this trend. The grain yield had significant positive correlations with the grain N accumulation (W1: r = 0.98; W2: r = 0.97) and N translocation (W1: r = 0.84; W2: r = 0.94), but significant negative correlations with the N harvest index (W1: r = −0.95; W2: r = −0.95) and N utilization efficiency (W1: r = −0.9; W2: r = −0.85). The path analysis revealed that the factors related to N utilization (β = 0.875) and the factors related to N translocation (β = −1.426) were the significant direct contributors towards grain yield. The influence of N application (total effect = 0.922) on the grain yield was much stronger than that of the irrigation regime (total effect = 0.324). Our findings can guide future efforts in designing sustainable water and N fertilizer management strategies for Tibetan barley in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Irrigation efficiency is important for the environment and the economy. SIMDualKc has been effectively used to calculate evaporation and transpiration separately in vineyards for different irrigation strategies, but not to analyze the impact of irrigation frequency. This study was conducted for the in-field adjustment of the soil wetted fraction (wf) with a time domain reflectometry (TDR) sensor as a function of different irrigation frequency treatments (T03, T07, and T15 with irrigation every 3, 7, and 15 days, respectively). Evaporation and transpiration values were estimated separately with the SIMDualKc model for different irrigation frequencies with the adjusted wf, comparing them with vineyard field measurements and analyzing the effect of different irrigation frequencies on vineyard yield. The wf in T15 was higher than that in T07, which in turn was higher than that in T03. SIMDualKc indicates the most unfavorable treatment to be the T07, with higher evaporation and lower transpiration than T15 and T03, while T15 had higher evaporation and lower transpiration than T03. Although stomatic conductance also indicates the most unfavorable case to be T07, no clear differences were found between T03 and T15. No statistically significant differences were obtained in yield. The results indicate that the differences observed between irrigation frequencies are not reflected in yield but do show up in water use efficiency. [ABSTRACT FROM AUTHOR]

Irrigation districts are a pivotal infrastructure of agricultural water conservancy engineering. Implementing modernization will be the main task of large-scale irrigation districts for a considerable amount of time in the future. In this study, four typical large-scale irrigation districts in North China were investigated: the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts. The concept of a modern irrigation district was deconstructed to establish an evaluation index system which includes four second-level indicators, twelve third-level indicators, and thirty fourth-level indicators. A hybrid approach based on AHP and OWA was used to quantify indicator weights used in group decision making. TOPSIS was introduced to measure the modernization level of the four irrigation districts. An obstacle factor diagnosis model was applied to search for key obstacle factors that will affect the modernization and improvement of the irrigation districts. The results showed that (1) the modernization levels of the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts in 2020 and 2025 were 0.3916 and 0.5755, 0.3748 and 0.5396, 0.4493 and 0.6012, and 0.2343 and 0.6166, respectively. The evaluation results indicate that the four irrigation districts are still in the beginning phase (or even preparation phase) of the modernization process. (2) Eight indicators were identified as the main common obstacle factors for the four evaluated irrigation districts, including the irrigation water-use efficiency factor, the coverage proportion of information technology, the proportion of efficient water conservation irrigation areas, and so on. (3) There are two effective methods to enhance the modernization level of the four irrigation districts: improving water resource utilization efficiency and strengthening the management system with an emphasis on informatization. The present study can enrich the theoretical evaluation of irrigation districts and provide a scientific basis for the modernized construction and management of irrigation districts in China. [ABSTRACT FROM AUTHOR]

A meta-analysis was conducted with the aim of exploring the influence of irrigation on potato yield, evapotranspiration (ET), and water-use efficiency (WUE) in northern China, considering factors such as irrigation methods, growing region, irrigation water-use efficiency (IWUE), irrigation frequency, soil types, and nitrogen (N) fertilizer rate. Overall, irrigation significantly increased potato yield and ET by an average of 45 and 54% compared to non-irrigation, respectively, but did not significantly increase the WUE. The increase in potato yield under irrigation is the most evident in aeolian sandy soil in northeast China and northwest China. Drip irrigation demonstrated the highest positive impact on both yield and WUE. Optimal yields were achieved with an irrigation amount ranging from 100 to 200 mm, while the highest WUE was observed with an irrigation amount of 30–50 mm. When the amount of irrigation exceeded 100 mm, the irrigation significantly resulted in decreased WUE compared to non-irrigation. The relative increase in yield per unit of irrigation amount and IWUE gradually decreased and eventually stabilized when the irrigation amount exceeded 100 mm. Therefore, the yield and WUE perform best when the irrigation amount is below 100 mm and the irrigation frequency is less than three times for sprinkling and flood irrigation methods. The greatest increases in yield and WUE under irrigation were found under a moderate N rate (150–250 kg N ha−1). Additionally, the relative increase in yield per unit of irrigation amount decreases gradually as the organic matter content increases. These findings suggest that the optimal benefits from irrigation might be realized when the irrigation amount is below 100 mm, with a moderate nitrogen fertilizer application and an irrigation frequency of three times. However, it is essential to consider local environmental factors such as the growing region, soil types, and organic carbon content. [ABSTRACT FROM AUTHOR]

This study aims to enhance maize water demand calculation. We calculate crop evapotranspiration (ETc) through mobile phone photography and meteorological parameters. In terms of crop coefficient (Kc) calculation, we utilize the mobile phone camera image driver to establish a real-time monitoring model of Kc based on plant canopy coverage (PGC) changes. The calculation of PGC is achieved by constructing a PGC classification network and a Convolutional Block Attention Module (CBAM)-U2Net is implemented by the segment network. For the reference crop evapotranspiration (ETo) calculation, we constructed a simplified ETo estimation model based on SVR, LSTM, Optuna LSTM, and GWO-SVM using a public meteorological data-driven program, and evaluated its performance. The results demonstrate that our method achieves high classification accuracy for the PGC 98.9% and segmentation accuracy for the CBAM-U2net-based segmentation network 95.68%. The Kc calculation model exhibits a root mean square error (RMSE) of 0.053. In terms of ETo estimation, the Optuna-LSTM model with four variables demonstrates the best estimation effect, with a correlation coefficient (R2) of 0.953. The final R2 between the estimated ETc value and the true value is 0.918, with an RMSE of 0.014. This method can effectively estimate the water demand of maize.

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.

Although irrigation systems largely sustain global agricultural production, their efficiency is often alarmingly low. While irrigation water (blue water) is critical for the water-saving irrigation of rice with a high water demand, the process and efficiency of irrigation water utilization need clarification. In this study, we examined the three commonly used irrigation and drainage patterns (frequent shallow irrigation (FSI), wet and shallow irrigation (WSI), and rain-catching and controlled irrigation (RCI)) in rice fields. We developed a tracking method for irrigation water flow decomposition, which includes irrigation water evapotranspiration (IET), irrigation water drainage (IDR), irrigation water leakage (IPC), and irrigation water field residual (IRE). Using this method, we established an irrigation water efficiency evaluation index system and a comprehensive evaluation method. Our tracking method is relevant to describing the irrigation water performance under varying irrigation and drainage patterns. The results revealed that the average irrigation water input for the three irrigation and drainage patterns between 2015 and 2018 was roughly 312.5 mm, wherein IET accounted for 148 mm. However, more than 50% of the irrigation water outflow, comprising IDR, IPC, and IRE, exceeded the total amount of irrigation water input. The mean values of the gross irrigation efficiency (GIE), net irrigation efficiency (NIE), and effective consumption ratio (ECR) for all treatments in the three-year period were 0.63, 0.47, and 0.75, respectively. Additionally, the irrigation water use efficiency was significantly higher in dry years compared to wet years. The fuzzy composite rating values of the three irrigation and drainage models from 2015 to 2018 were RCI, WSI, and FSI, in descending order, under varying precipitation conditions. The RCI patterns maintained a high composite rating value (greater than 3.0) under different precipitation conditions. Previous efficiency calculations disregarded the blue–green water migration process and did not differentiate the blue–green water flow direction in agricultural fields, creating significant biases in the outcomes. This study's method offers a new approach to evaluate the use of blue water resources in farmland. [ABSTRACT FROM AUTHOR]

Irrigation water is the main type of water consumption in the Yanqi Basin irrigation district of Xinjiang, which is an oasis-type irrigation district in the arid region of Northwest China. With the continuous expansion of cultivated areas, there is an increasing demand for irrigation water, resulting in an irrigation efficiency paradox and the phenomenon of "the more water-saving, the more water-scarce". In this study, the water balance method and the improved IWMI (International Water Management Institute) water balance method were used with remote sensing and statistical data from 1980 to 2020 to analyze the changes in the irrigation water supply, consumption, and loss for improvement in irrigation water use efficiency (IWUE) in the Yanqi Basin. The results showed that there was an upward trend in the cultivated land area in the irrigation district of Yanqi Basin, as monitored with remote sensing from 1980 to 2020, and the values from the remote sensing data were higher than those from the yearbooks. According to the remote sensing data, the arable land area in the irrigation district increased from 1672 km2 in 1980 to 2494 km2 in 2020, thus showing a trend of expansion. The traditional water use efficiency in the irrigation district showed an increasing trend. The lowest value for the field water-use coefficient was 0.70 in 1998, and it exceeded to 0.81 from 2009 to 2020. The canal water-use coefficient was as low as 0.50 in 1998 and increased from 0.54 in 2009 to 0.82 in 2020. The irrigation water-use coefficient increased from 0.35 in 1998 to 0.68 in 2020, with a general upward trend. In this study, the water consumption ratio indicator DFg (depleted fraction), determined using the improved water balance method, increased from 0.8390 in 1980 to 0.8562 in 2020, although it showed an overall decreasing trend, and the average was 0.8436. Cultivated land's actual irrigation water consumption per unit area reached the highest value of 8.41 × 106 m3/hm2/a in 2011 and the minimum value of 4.01 × 106 m3/hm2/a in 2020, and from 1980 to 2020 it showed a decreasing trend, while the total water diversion showed an increasing trend due to the continuous expansion of arable land. From 1980 to 2020, water diversion into the irrigation district changed from 1.214 km3 to 1.000 km3, and it reached a maximum of 1.593 km3 in 2000; water diversion into the irrigation district showed an overall upward trend. The positive impact of the post-2000 water conservation phase with the adaptation of water-saving irrigation technology was clear, as the findings showed an increase in IWUE in the Yanqi Basin irrigation district. These results provide a theoretical basis for breaking the paradox of irrigation efficiency, which can be used in the water resource management of irrigation districts. [ABSTRACT FROM AUTHOR]

Shortages of water resources and labor make it urgent to improve irrigation efficiency and automation. To respond to this need, this study demonstrates the development of an adaptive border irrigation system. The inflow is adjusted based on the functional relationship between the advance time deviation and the optimal adjustment inflow rate, thereby avoiding the real-time calculation of infiltration parameters required by traditional real-time control irrigation systems. During the irrigation process, the inflow rate is automatically adjusted based only on the advance time deviation of the observation points. The proposed system greatly simplifies the calculation and reduces the requirements for field computing equipment compared with traditional real-time control irrigation systems. Field validation experiments show that the proposed system provides high-quality irrigation by improving the application efficiency, distribution uniformity, and comprehensive irrigation performance by 11.3%, 10.7%, and 11.0%, respectively. A sensitivity analysis indicates that the proposed system maintains a satisfactory irrigation performance for all scenarios of variations in natural parameters, flow rates, and border length. Due to its satisfactory irrigation performance, robustness, facile operation, and economical merit compared with traditional real-time control irrigation systems, the proposed system has the potential to be widely applied. [ABSTRACT FROM AUTHOR]

Spain is one of the main producers of black truffle (Tuber melanosporum Vittad.), a fungus of great economic importance. Black truffles are usually cultivated in Quercus ilex orchards, as water availability is one of the most important factors influencing truffle production. Optimizing watering systems is essential to reduce the amount of water wasted. Nevertheless, up to now, no study has been carried out comparing the efficiency of different irrigation systems in truffle plantations. The aim of this study was to compare the efficiency of two different irrigation systems, namely a drip irrigation system and a micro-sprinkler system, in a Quercus ilex plantation situated in Burgos, Spain. Our data showed that there were no differences between the two irrigation systems in terms of truffle yields, the number of truffles, quality (based on truffle size), or the date of truffle harvesting. However, when other parameters were taken into consideration, such as the economic and environmental impact of installing and running these systems, drip irrigation was deemed the superior irrigation system because it uses less water. This study validates for the first time the use of drip irrigation rather than a micro-sprinkler system (the most commonly used in truffle plantations) because of its greater water use efficiency, which is an increasingly important consideration given future climate change scenarios marked by global water scarcity. [ABSTRACT FROM AUTHOR]

The core component of a properly functioning drip irrigation system is the drip irrigation emitter. Irrigation water containing impurities and sand particles can easily lead to clogging of the drip irrigation emitter, reducing the efficiency of the drip irrigation system. In this paper, orthogonal tests were used to optimize the flow channel structure, combined with the computational fluid dynamics–discrete element method (CFD-DEM) to analyze the flow index and sand particle motion characteristics. Clear water tests and short-cycle anticlogging tests were used to validate the results of the numerical simulation, and the relationship between the hydraulic performance and anti-clogging performance was revealed via linear regression. The results showed that the structural parameters of drip irrigation emitters were important factors affecting the flow index and sand movement characteristics. The order from largest to smallest was the turning angle, amount of interdental reference, flow channel depth, flow channel width, and width of the top base. The sand passage rate and the percentage decrease in velocity can be used as important indicators of anti-clogging performance, and there was a negative correlation between the two indicators. The flow channel with a 65° turning angle had the lowest flow index, and the sand passage rate can reach up to 91.48%; the reason was that the main flow region velocity was higher, the vortex region and the sand energy loss were small, which was not easy to clog. The equation for the relationship between flow index and sand passage rate was a negative correlation for drip irrigation emitters between a 65° and 75° turning angle. The drip irrigation emitter with a 65° turning angle had better hydraulic performance and anti-clogging performance. [ABSTRACT FROM AUTHOR]

This study assessed the equity in irrigation water uses and its impacts on paddy yield and water productivity among rice farmers in the Kano River Irrigation Project. Two hundred and twenty-five (225) respondents were used for the data collection from January to June 2021. The data were analyzed using the Kruskal Walli's test, Tukey kramer post-Hoc test, physical water productivity, and the Logit model. The results indicated that the downstream farmers had the lowest mean yield (1625 kg/acre), lowest access to irrigation water, and lowest irrigation water use (2430 m3/acre). However, they had the highest water productivity (0.66 kg/m3) against 0.44 kg/m3 and 0.58 kg/m3 for middle and upstream farmers, respectively. The logit regression results disclosed that the farm locations, quantity of irrigation water, access to irrigation water, and training on water use were statistically significant determinant of paddy output. Efforts to teach farmers about the actual crop water requirements are needed to promote irrigation water efficiency and conserve scarce resources for other competing users. [ABSTRACT FROM AUTHOR]

To improve water use efficiency and productivity, particularly in irrigated areas, reliable water accounting methodologies are essential, as they provide information on the status and trends in irrigation water availability/supply and consumption/demand. At the collective irrigation system level, irrigation water accounting (IWA) relies on the quantification of water fluxes from the diversion point to the plants, at both the conveyance and distribution network and the irrigated field level. Direct measurement is the most accurate method for IWA, but in most cases, there is limited metering of irrigation water despite the increasing pressure on both groundwater and surface water resources, hindering the water accounting procedures. However, various methodologies, tools, and indicators have been developed to estimate the IWA components, depending on the scale and the level of detail being considered. Another setback for the wide implementation of IWA is the vast terminology used in the literature for different scales and levels of application. Thus, the main objectives of this review, which focuses on IWA for collective irrigation services, are to (i) demonstrate the importance of IWA by showing its relationship with water productivity and water use efficiency; (ii) clarify the concepts and terminology related to IWA; and (iii) provide an overview of various approaches to obtain reliable data for the IWA, on the demand side, both at the distribution network and on-farm systems. From the review, it can be concluded that there is a need for reliable IWA, which provides a common information base for all stakeholders. Future work could include the development of user-friendly tools and methodologies to reduce the bridge between the technology available to collect and process the information on the various water accounting components and its effective use by stakeholders. [ABSTRACT FROM AUTHOR]

Due to rising food demand and the limitation of water resources, achieving water security is essential. The lettuce crop is affected when grown under limited water supplies as it produces small heads, especially during the late growing stage. For this reason, it is important to maximize water use efficiency and crop productivity. Two successive experiments were conducted during 2021 and 2022 to reduce losses via deep percolation using a geotextile layer at different soil depths under different irrigation levels of the lettuce crop (Lactuca sativa L. var. capitata). This study aims to reduce water losses due to deep percolation and improve crop growth and yield parameters for iceberg lettuce under subsurface drip irrigation in sandy loam soil conditions. In order to achieve these aims, different amounts of irrigation (100, 80, and 60% of crop evapotranspiration "ETc") and a geotextile layer at different soil depths (20, 30, and 40 cm from the soil surface) were used. The results revealed that the use of a geotextile layer with 20 and 30 cm depths significantly improved irrigation application efficiency and noticeably increased soil water content in the root zone. The observed results during both seasons showed that geotextile layers at 20, 30, and 40 cm depths under irrigation of 100% ETc significantly increased vegetative growth characteristics (plant height, head diameter, head circumference, head volume, plant fresh weight, and leaf area) and crop productivity compared to the control (without geotextile). In particular, the geotextile layer at a 30 cm depth under irrigation of 100% of ETc was the most statistically effective treatment in this study, with yield values of 69.3 and 67.5 t ha−1 in the two seasons, respectively. However, the treatments of geotextile layers at 20 and 30 cm depths under irrigation of 80% of ETc also recorded statistically effective results for crop growth parameters and yield in this study. In general, geotextiles can be used at different depths as an irrigation management practice to reduce deep percolation in the field. [ABSTRACT FROM AUTHOR]

In this study, a new method for determining the depth of frozen soil, Impulse Response Time Domain Reflectometry, is discussed. This method uses the principle of impedance measurement and the law of time–frequency domain convolution to convert the frequency-domain reflection signal into a time-domain signal and accurately determines the soil freezing front by measuring the difference between the impedance of frozen soil and unfrozen soil. The advantage of this method is that it solves the problems of small bandwidth, long rising edge time, and large measurement errors in the traditional TDR method to effectively improve the measurement accuracy of the soil-freezing front. Under laboratory conditions, soils of different textures (sand, loess, black soil, and red soil) were selected for experimental determination, and the results showed that compared with the traditional TDR method, the RMSE of the I-TDR method was small, and the method was applicable under different soil texture conditions, which could provide a new method for monitoring frozen soil in cold areas. In addition, the application of this method has important guiding significance for improving the efficiency of winter irrigation water, especially for guiding agricultural production, farmland irrigation, drainage engineering construction, meteorological frozen soil monitoring, and other aspects in cold and arid areas. [ABSTRACT FROM AUTHOR]

Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management. [ABSTRACT FROM AUTHOR]

Potatoes require water and fertilizer management systems to optimize economic outcomes and fertilizer use, especially in arid areas such as Ningxia, China. In this study, three irrigation quotas (1200 (W1), 1650 (W2), and 2100 (W3) m3/hm2) and three nitrogen application treatments (110 (N1), 190 (N2), and 270 (N3) kg/hm2) were evaluated. Potato growth, final yield, and quality indices were assessed in relation to fertility periods, irrigation utilization efficiency, nitrogen and fertilizer bias productivity, and economic efficiency, using the TOPSIS model. Stem thickness and plant height varied significantly with irrigation and nitrogen treatments; total yield and vitamin C, reducing sugar, and starch contents were the highest under the W3N1, W3N1, W1N2, and W2N3 treatments, increasing by 54.56, 17.00, 69.00, and 45.00%, respectively, compared with those in the control. The regression relationships between water and nitrogen regulation and yield, irrigation water use efficiency, nitrogen fertilizer bias productivity, and economic efficiency agreed with the binary quadratic regression model, and the coefficients of determination (R2) were >0.85. W3N1 was optimal for model yield, nitrogen fertilizer bias productivity, and economic efficiency, and W1N3 was optimal for irrigation water use efficiency. Our findings will help optimize potato management in central Ningxia. [ABSTRACT FROM AUTHOR]

In hyper-arid and arid zones, management of crop water requirements is considered a vital component for sustaining crop production. The efficiency of the irrigation method and the application of many kinds of organic matter are practices that should be followed in Egypt to maximize the use of irrigation water. Two field experiments were conducted during the two successive winter seasons of 2020/2021 and 2021/2022 to study the effect of drip irrigation systems and of several types of compost on yield and yield attributes of four cultivars of wheat in newly reclaimed sandy soils. Studied factors were irrigation levels based on the amount of water evapotranspiration (ET) (I1, I2, I3) and the application of compost types (Com1, Com2 and Com3) on four bread wheat cultivars. The parameters measured at each irrigation level were: heading date (day), plant height (cm2), number of spikes/m2, number of grains/spike, 1000-grain weight (g), grain yield (t/fed.), Biological yield (kg/fed.) and harvest index (%). The farmyard manure (Com3) gave the maximum values under irrigation shortages, reflected in producing the maximum values for traits measured in the 2020/2021 season as compared to (Com1) or (Com2) applications, which scored lower values for the traits for the different cultivars for wheat. The interaction (I1, I2) × Com3 × (Mis1, Mis2) led to a significant increase during both seasons for all the yield and yield components studied. A drip irrigation system at the level of 80% of ET and application of Com3 is recommended to optimize wheat productivity from the unit area. The savings in water irrigation would allow expansion of the cultivated area to decrease the gap between local crop production and local requirements. [ABSTRACT FROM AUTHOR]

The shortage of water resources makes it urgent to increase agricultural irrigation efficiency. In response to this need, this study develops a real-time adaptive control irrigation (RACI) system for border irrigation. Avoiding the need for traditional real-time control systems to calculate soil infiltration properties in real-time, RACI adjusts the inflow rate based on the difference between the actual and expected advance time. Simulations of the collected data are used to evaluate and analyze the sensitivity of RACI to input parameters, and field experiments were carried out to further verify the irrigation performance and efficiency. The experimental results indicate that RACI delivers an average application efficiency, distribution uniformity, requirement efficiency, and deep percolation of 0.930, 0.884, 0.954, and 0.070, respectively. A sensitivity analysis of irrigation input parameters (infiltration parameter, roughness coefficient, inflow rate, and slope) shows that the irrigation performance of RACI remains satisfactory even when the parameters are varied. Given the satisfactory irrigation performance and robustness and the more facile operation than traditional real-time control systems, RACI has the potential to become widely used. [ABSTRACT FROM AUTHOR]

A field study in an orchard of Korla fragrant pear tested three levels of irrigation (as varying proportions of evapotranspiration; namely, W1: 70% ETC, W2: 85% ETC, and W3: 100% ETC) and four methods of applying such irrigation; namely, F1: surface drip, F2: subsurface, F3: root zone infiltration, and CK: flood irrigation (as the control or check). The effects of the different treatments were evaluated in terms of plant growth (shoot length and leaf area), fruit yield and quality, and the distribution of water and salt in soil. For a given method of irrigation, soil moisture content, wet-front displacement, the length of new shoots, and leaf area under W3 were significantly higher than those under W1 and W2. The salt content under W3 was also significantly lower than that under W1 and W2, whereas the yield was significantly higher—by 5.89–13.85% compared to that under W2 and by 4.08–13.13% compared to that under W1. For a given volume of irrigation, yield, water-use efficiency, and fruit quality were significantly higher under F3 and F2 than those under F1. Soil water was more uniformly distributed and its content was significantly higher under F3 than the corresponding values under F1 or F2. The salt content of the root zone was the lowest under F3, and most of the soil salt was in soil layers deeper than 80 cm, but there was no significant difference between F3 and F2 (p < 0.05). There were also no significant differences in shoot length and leaf area among the three irrigation methods (F1, F2, and F3) (p < 0.05). Compared to that under F1, root zone infiltration under W1 was 3.61% greater, that under W2 was 6.58% greater, and that under W3 was 5.43% greater. The irrigation water-use efficiency and production factor efficiency for nitrogen under F3 and F2 were significantly higher than those under F1 (p < 0.05). Principal component analysis showed that the comprehensive score for fruit quality under different volumes of irrigation was the highest under W3, was intermediate under W2, and was the lowest under W1. The corresponding ranking of different irrigation methods was F2, F3, F1, and CK. Comprehensive analysis showed that yield, quality, and the efficiency of utilization of water and fertilizer were higher under the combination W3F3 than under any other combination—therefore, irrigation at 100% of evapotranspiration applied through root zone infiltration is recommended for Korla fragrant pear. The research results can provide a theoretical basis for the optimal use of water and for salt control in pear in Korla, Xinjiang. [ABSTRACT FROM AUTHOR]

Agricultural production in oases requires extensive irrigation and nitrogen (N) inputs, which result in a high incidence of non-point-source pollution. Information on how soil texture affects crop productivity and water and N use efficiency is needed to improve N management in oases. A two-year field study with six free-draining leaching pits was set up to quantify soil water content (SWC), drainage, yield, N uptake, soil residual N, N leaching, water-use efficiency (WUE), and N fertilizer-use efficiency (NFUE) on sandy-textured soils in a young oasis field (24 years, YOF) and loam-textured soils in an old oasis field (>60 years; OOF) within an intensive oasis agricultural zone in Northwest China. The results showed that sand content in the YOF was significantly higher than that in the OOF (p < 0.01), while both clay and silt contents in the YOF were significantly lower than those in the OOF (p < 0.01). Soil water storage (SW) in the 0–100 cm soil layer, evapotranspiration water-use efficiency (WUEET) and irrigation water-use efficiency (WUEIrrig) in the OOF were, respectively, 87.1, 23.5, and 24.1% higher than those in the YOF (p < 0.05), and deep drainage in the YOF was 6.2 times higher than that in the OOF (p < 0.01). Maize N uptake and soil N accumulation in the OOF in the 0–100 cm soil layer were, respectively, 33.4 and 10.3% higher than those in the YOF (p < 0.05), and N leaching loss in the YOF was 1.65 times higher than that in the OOF (p > 0.01). Crop yield and NFUE in the OOF were, respectively, 23.9 and 27.2% higher than those in the YOF (p < 0.05). These results indicated that sandy-textured soils with high sand content were not conducive to water and N retention, resulting in lower crop yields and water- and fertilizer-use efficiency in YOF. Therefore, it is imperative that management practices in sandy-textured land promote improvements in soil structure and maintain the long-term productivity of the young cultivated fields. [ABSTRACT FROM AUTHOR]

Water is a key factor in global food security, which is critical to agriculture. The use of mathematical models is a strategy for managing water use in agriculture, and it is an effective way to predict the effect of irrigation management on crop yields if the accuracy of these models is demonstrated. The CROPWAT and SALTMED models were tested in this study, with water quantities applied to surface and drip irrigation (SI and DI) systems to estimate irrigation scheduling and wheat yield. For this purpose, field experiments were conducted for two consecutive years to study the effects of irrigation water levels of 80%, 100%, and 120% crop evapotranspiration (I80, I100, and I120) on the yield and water productivity (WP) of wheat in SI and DI systems. Irrigation treatments affected yield components such as plant height, number of spikes, spike length, and 1000-kernel weight, though they were not statistically different in some cases. In the I80 treatment, the biological yield was 12.8% and 8.5% lower than in the I100 and I120 treatments, respectively. I100 treatment under DI resulted in the highest grain yield of a wheat crop. When DI was applied, there was a maximum (22.78%) decrease in grain yield in the I80 treatment. The SI system was more water-consuming than the DI system was, which was reflected in the WP. When compared with the WP of the I80 and I100 treatments, the WP was significantly lower (p < 0.05) in the I120 treatment in the SI or DI system. To evaluate irrigation scheduling and estimate wheat yield response, the CROPWAT model was used. Since the CROPWAT model showed that increasing irrigation water levels under SI for water stress coefficient (Ks) values less than one increased deep percolation (DP), the I120 treatment had the highest DP value (556.15 mm on average), followed by the I100 and I80 treatments. In DI, I100 and I120 treatments had Ks values equal to one throughout the growing seasons, whereas the I80 treatment had Ks values less than one during wheat's mid- and late-season stages. The I100 and I80 treatments with DI gave lower DP values of 93.4% and 74.3% compared with that of the I120 treatment (on average, 97.05 mm). The I120 treatment had the lowest irrigation schedule efficiency in both irrigation systems, followed by the I100 and I80 treatments. In both seasons, irrigation schedule deficiencies were highest in the I80 treatment with DI (on average, 12.35%). The I80 treatment with DI had a significant yield reduction (on average, 21.9%) in both seasons, while the irrigation level treatments with SI had nearly the same reductions. The SALTMED model is an integrated model that considers irrigation systems, soil types, crops, and water application strategies to simulate soil water content (SWC) and crop yield. The SALTMED model was calibrated and validated based on the experimental data under irrigation levels across irrigation systems. The accuracy of the model was assessed by the coefficients of correlation (R), root mean square errors (RMSE), mean absolute errors (MAE), and mean absolute relative error (MARE). When simulating SWC, the SALTMED models' R values, on average, were 0.89 and 0.84, RMSE values were 0.018 and 0.019, MAE values were 0.015 and 0.016, and MARE values were 8.917 and 9.133%, respectively, during the calibration and validation periods. When simulating crop yield, relative errors (RE) for the SALTMED model varied between −0.11 and 24.37% for biological yield and 0.1 and 19.18% for grain yield during the calibration period, while in the validation period, RE was in the range of 3.8–29.81% and 2.02–25.41%, respectively. The SALTMED model performed well when simulating wheat yield with different water irrigation levels under SI or DI. [ABSTRACT FROM AUTHOR]

Water use efficiency ( W U E ) is one of the most widely used indicators in agricultural water management. Although this indicator has obvious advantages, it is limited to measuring the relationship between crop yield and corresponding water use. In recent years, many researchers have noted that understanding the economic efficiency of water use ( E E W U ) could have great water-saving potential, while it has been poorly investigated with respect to China's agricultural water management. This paper assesses E E W U through a household farmer-level survey in the piedmont region of North China. First, E E W U of crops are estimated based on agricultural water consumption (including irrigation water and effective precipitation) and profit (including gross profit and net profit); Second, the impact of monthly price changes in 2019 and annual price changes in 2014–2019 on E E W U is analysed. Main conclusions are as follows: (1) E E W U values of cash crops such as apple and cauliflower are much higher than those of grain crops such as wheat and maize; (2) For different crops, the median economic efficiency of irrigation water ( E E W i U ) and total water ( E E W t U ) range from 31.71 to 99.54 ¥/m3 and 11.31 to 44.05 ¥/m3, respectively; (3) The multi-year average E E W i U and E E W t U ranged from 4.75 to 63.99 ¥/m3 and from 2.67 to 31.71 ¥/m3, respectively. Economic efficiency of water use shows a slightly downward trend in the period of study, which would contradict the trend towards the use of more water-efficient technologies and shows an even larger margin of improvement in the domain of agricultural water efficiency. The results provide a powerful reference for the management of agricultural water use through economic leverage. [ABSTRACT FROM AUTHOR]

The coverage of center pivot irrigation systems used around the world has increased. One potential factor driving their adoption is improved water application efficiency relative to some other sprinkler or surface irrigation approaches. Center pivot irrigation systems may be further improved by dynamic elevation spray application (DESA). DESA systems adjust the nozzle height in response to plant growth and canopy heterogeneities. The DESA approach is relatively new and there is uncertainty in its economic viability and worthiness of further investigation. Thus, an economic scenario analysis was performed to explore the potential economic benefits of DESA based on permutations of irrigation pivot efficiency without DESA, water-saving potential of DESA, and water cost. The weighted costs and benefits of the height-adjusted approach for a set of water cost savings scenarios showed the net return price with the water cost savings per season. We show that DESA could have economic viability at current component costs and is worthy of further investigation and refinement. [ABSTRACT FROM AUTHOR]

Water deficit, especially during summer, is currently one of the most important stress factors that influence olive oil production in olive orchards. A precision irrigation strategy, based on daily trunk growth, was assessed and compared with one continuous deficit, one full irrigation, and two different regulated deficit irrigation strategies. All of them were tested in a super high-density olive orchard located in northeast Spain, in which oil production, main oil production components, applied irrigation water, and water productivity were assessed. For this purpose, the crop was monitored from budding to harvesting, mainly during the summer months in which the Precision strategy only applied water after two days of negative daily trunk growth. Maximum monthly water savings for the Precision strategy reached 91.8%, compared with full irrigation, while major annual mean water savings reached 50% for the continuous deficit strategy and 31.2% for the Precision strategy, which also reduced irrigation events by up to 19.7%, compared with the full irrigation strategy. Oil production and oil production components varied depending on the irrigation strategies providing the Control, one of the regulated deficit irrigations, and Precision higher values than the other strategies; oil yield results differ, nonetheless. The Precision strategy showed an overall better performance. Despite this, it did not achieve the highest water saving, it achieved higher water productivity. [ABSTRACT FROM AUTHOR]

In the view of increasing water demands in agriculture, efficient water use is a key factor in potato production. The aim of this study was to compare two deficit (80% and 90%) and one abundant (120%) gun sprinkler irrigation levels with the longtime used irrigation level of a farmer (100%). Irrigation was supplied during the 2021 growing season on a loamy sand site in Mecklenburg–Western Pomerania, Germany. Yield and tuber quality of the high-amylopectin potato (HAPP) variety “Waxy/Henriette” were assessed in a three-grade tuber size distribution. Five economic indicators were used to assess the suitability of the investigated irrigation levels to secure economic responses. Yield and starch yield did not significantly differ between the 90% (561.1 dt ha−1 and 102.0 dt ha−1) and the 100% irrigation levels (559.1 dt ha−1 and 102.3 dt ha−1), with total production increasing by 2.0 dt ha−1 and starch production decreasing by 0.4 dt ha−1 at the 90% irrigation level. Tuber lesions decreased the economic responses at all irrigation levels. Potentially, 87,469 m3 of irrigation water (125.8 m3 ha−1) could have been saved on the loamy sand starch potato sites of the local farm (695.3 ha) in 2021.

A long-term field experiment was conducted from 2002 to 2014 for the evaluation of yield and water productivity of three winter wheat varieties-Kharkof, Scout 66, and TAM107--under sprinkler irrigation at New Mexico State University Agricultural Science Center at Farmington, NM. Winter wheat daily evapotranspiration was estimated following the United Nations Food and Agriculture Organization FAO crop coefficient approach (ETc = Kc ETo), and crop water use efficiency (CWUE), evapotranspiration water use efficiency (ETWUE), and irrigation water use efficiency (IWUE) were estimated for each growing season. There was inter-annual variation in seasonal precipitation and irrigation amounts. Seasonal irrigation amounts varied from 511 to 787 mm and the total water supply varied from 590 to 894 mm with precipitation representing a range of 7.7-24.2%. Winter wheat daily actual evapotranspiration (ETc) varied from 0.1 to 14.5 mm/day, averaging 2.7 mm/day during the winter wheat growing seasons, and the seasonal evapotranspiration varied from 625 to 890 mm. Grain yield was dependent on winter wheat variety, decreased with years, and varied from 1843.1 to 7085.7 kg/ha. TAM107 obtained the highest grain yield. Winter wheat CWUE, IWUE, and ETWUE were also varietal dependent and varied from 0.22 to 1.01 kg/m3, from 0.26 to 1.17 kg/m3, and from 0.29 to 0.92 kg/m3, respectively. CWUE linearly decreased with seasonal water, and IWUE linearly decreased with seasonal irrigation amount, while CWUE, IWUE, and ETWUE were positively correlated with the grain yield for the three winter wheat varieties, with R2 ≤.85 for CWUE, R2 ≤ 0.69 for IWUE, and R2 ≤ 0.89 for ETWUE. The results of this study can serve as guidelines for winter wheat production in the semiarid Four Corners regions. Additional research need to be conducted for optimizing winter wheat irrigation management relative to planting date and fertilization management to reduce the yield gap between winter wheat actual yield and the national average yield. [ABSTRACT FROM AUTHOR]

Canola is a cash crop produced for its highly-valued seed, and as a protein source for animal feed. While winter canola is produced mainly in the high plains, it is expanding to new environments, and is greatly incorporated into crop systems with advantages in terms of increasing crop yield and improving soil health. The objectives of this study were to evaluate eight winter canola genotypes for seed yield, and to determine their water productivity under semiarid climates and high elevations in the Four Corners region at Farmington, New Mexico. A field experiment was conducted at the New Mexico State Agricultural Science Center at Farmington for five growing seasons. Eight genotypes of winter canola (Baldur, Flash, Safran, Sitro, Virginia, Visby, Wichita, and Sumner) were arranged into the randomized complete block design. The field was fully irrigated with a center pivot irrigation system. Results showed that winter canola seed yield was dependent on genotype, varying from 2393 to 5717 kg/ha. The highest yield was achieved by Sitro, and the lowest yield by Sumner. There was inter-annual variation in canola nitrogen-use efficiency (NUE), irrigation water-use efficiency (IWUE), and crop water-use efficiency (CWUE). NUE varied from 12.9 to 50.4 kg seed/kg N, with the highest NUE achieved by Sitro, and the lowest by Sumner. IWUE varied from 0.34 to 0.80 kg/m3, and canola CWUE from 0.28 to 0.69 kg/m3. The highest water productivity was achieved by Sitro. The results of this study showed full assessment of canola production under the semiarid climate in the Four Corners region, and could improve crop productivity and profitability. [ABSTRACT FROM AUTHOR]

Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management.

In the past few decades, combinations of remote sensing technologies with ground-based methods have become available for use at the level of irrigated fields. These approaches allow an evaluation of crop water stress dynamics and irrigation water use efficiency. In this study, remotely sensed and ground-based data were used to develop a method of crop water stress assessment and analysis. Input datasets of this method were based on the results of ground-based and satellite monitoring in 2012. Required datasets were collected for 19 irrigated alfalfa crops in the second year of growth at three study sites located in Saratovskoe Zavolzhie (Saratov Oblast, Russia). Collected datasets were applied to calculate the dynamics of daily crop water stress coefficients for all studied crops, thereby characterizing the efficiency of crop irrigation. Accordingly, data on the crop yield of three harvests were used. An analysis of the results revealed a linear relationship between the crop yield of three cuts and the average value of the water stress coefficient. Further application of this method may be directed toward analyzing the effectiveness of irrigation practices and the operational management of agricultural crop irrigation. [ABSTRACT FROM AUTHOR]

Irrigation is required for profitable commercial potato (Solanum tuberosum L.) production. Excessive or deficit soil water availability during the growing season can have adverse effects on tuber yield, quality, and storability. A field study was conducted during the 2018 and 2019 field and storage seasons in Central Wisconsin, a region in the U.S. with a high volume of potato production, to evaluate the impacts of different irrigation rates on three chipping potato varieties, Hodag, Lamoka, and Snowden. The treatments were implemented during the late-tuber bulking and tuber maturation growth stages, and consisted of irrigation at 125%, 100%, 75%, and 50% of crop evapotranspiration (ET). Irrigation before the treatment period was at 100%ET for all plots. With the industry standard irrigation practice being at 100%ET, other treatments were designated as over-irrigation or deficit irrigation. The impact of these watering rates on tuber yield and quality was evaluated at harvest, and tuber storage quality was assessed by measuring chip fry color and sugar concentrations at 0, 4, and 8 months of storage. It was found that compared to the standard practice, the over-irrigation treatment at 125%ET when tubers reached late bulking resulted in no significant increase in total yield, marketable yield, tuber quality at harvest and during storage, as well as reduced irrigation efficiency (IE) and water-use efficiency (WUE). This treatment also increased nitrate leaching potential in both years. In comparison, deficit irrigation at 75%ET or even 50%ET during the late season had no impact on tuber growth, could increase IE and WUE in one of the two years, and showed reduced drainage. In both years, irrigation rate had no significant effects on hollow heart incidence, tuber specific gravity at harvest, and fry quality during the 8-month storage period. This study suggested that over-irrigation was not beneficial for potato production in Central Wisconsin of the U.S., and deficit irrigation during late tuber bulking and tuber maturation stages could potentially result in more sustainable water use while not penalizing tuber yield, quality and storability of chipping potatoes. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the Partial Root Zone Drying Irrigation System (PRD) as one of the modern technologies that provide irrigation water and increase the efficiency of its use on potato crop. The effect of applying the PRD conventional deficit irrigation (CDI) on the efficiency and water saving in potato crops using the drip surface (S) and subsurface (SS) irrigation methods were investigated. SALTMED model used to predict soil moisture and salinity distribution, soil nitrogen dynamics, and yield of potato crop using the different irrigation levels (150%, 100%, and 50% of Crop evapotranspiration (ETc)). The study showed that the water use efficiency (WUE) decreases with increasing levels of irrigation water, as it ranged between 2.96 and 8.38 kgm−3, 2.77 and 7.01 kgm−3 for surface irrigation PRD and CDI, respectively, when the amounts of irrigation water varied from 308 mm to 1174 mm, respectively. The study showed that the irrigation efficiencies were the highest when using PRD system in all treatments when irrigating the potato crop during the spring season, and it was more efficient in the case of using subsurface irrigation method. The results show that the soil moisture (SM) was high in 25–45 cm at 150% of ETc was 0.166 and 0.263 m3m−3 for the first and last stages of growth, respectively. 100% of ETc, (SM) was 0.296 m3m−3 at 0–25 cm, 0.195 m3m−3 at 25–45 cm, 0.179 m3m−3 at 45–62 cm, depths, respectively. whereas 50% of ETc, (SM) was 0.162 m3m−3 at 0–25 cm, 0.195 m3m−3 at 25–85 cm, depths. At 100% of ETc, soil salinity was 5.15, 4.37, 3.3, and 4.5 dSm−1, whereas at 50%, ETc, these values were 5.64, 9.6, 3.3, and 4.2 dSm−1. Statistical indicators showed that the model underestimated yield, for 150%, 100%, and 50% of ETc. Therefore, it can be concluded that yield and WUE using PRD systems were the highest in the potato crop compare to CDI surface and sub-surface, and SALTMED model can predict the moisture distribution, salinity, and yield of potatoes after accurate adjustment. [ABSTRACT FROM AUTHOR]

Irrigation scheduling and programming are very effective tools for efficient water use in a plant factory with artificial lighting (PFAL). In order to confirm optimal irrigation schemes for the production of cucumber scions and rootstocks in a PFAL, in this study, four different start points of irrigation were applied by measuring the weight of the plug tray to compare the growth of cucumber scions and rootstocks cultivated in a PFAL. Additionally, the growth characteristics of cucumber seedlings grafted with scions and rootstocks cultivated between in a greenhouse and in a PFAL were investigated. Although the growth of cucumber scions and rootstocks was highest when irrigation was conducted at 70% of water content in a medium, the growth of grafted cucumber seedlings before and after transplanting was not significantly different among the irrigation treatments in a PFAL. However, water use efficiency (WUE) during cucumber scions and rootstock production in a PFAL was higher at 60% than at 70%. Considering seedling growth and the efficiency of irrigation such as WUE and irrigation schedule, the optimal start point of irrigation during the production of cucumber scions and rootstocks in a PFAL was determined as 60% of water content in a medium. When the optimal irrigation regime was applied to the production of cucumber scions and rootstocks in a PFAL, the morphological characteristics of cucumber scions and rootstocks cultivated in a PFAL were more suitable for grafting compared with that of the cucumber scions and rootstocks cultivated conventionally in a greenhouse. The favorable environmental conditions during the cultivation of cucumber scions and rootstocks in a PFAL also positively affected the flowering response of cucumber grafted seedlings after transplanting. [ABSTRACT FROM AUTHOR]

Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high. [ABSTRACT FROM AUTHOR]

Improving water efficiency in farming systems is one of the major challenges of these decades. Water scarcity due to climate change, together with the increasing demand of food, is leading experts from around the world find appropriate indicators for water-use efficiency. In this paper we propose and test different indicators for service delivery performance, productive efficiency, and economic efficiency. Since the characteristics of the studied area and the citrus cropping system in the East of Spain are particular, we include in our analysis two other variables which are key to understanding the changes in the indicators: the obtained productivity, and the applied irrigation. The indicators and these two variables are tested with the information provided by farmers of citrus orchards belonging to an irrigation community from the East of Spain. The effect of different factors, such as cultivated varieties, type of farmer (professional or non-professional), or plantations' size, are evaluated against the productivity and irrigation performance of the evaluated orchards. The effect of excess of irrigation on the indicators is also studied with the previous factors. Finally, an artificial intelligence system is used to predict productive efficiency of an orchard, based on the size and the water supply. Among the proposed indicators, the service delivery performance indicators came out to be the least useful and might provoke overirrigation due to the lack of accuracy of the data used for its calculation. The productive and economic efficiency indicators have been useful to illustrate the remarkable effect that excess of irrigation has on water efficiency, since a reduction of 66% of productive efficiency is found for some of the analysed varieties. On other cases, a reduction of 50% in economic efficiency is detected due to the excess of irrigation. Moreover, the excess of irrigation implied higher economic efficiency in only one of the evaluated varieties. [ABSTRACT FROM AUTHOR]

Scarce water resources limit protected vegetable production in North China. Implementing efficient water-saving techniques is crucial for maintaining protected vegetable production and sustainability. A two-growing season field experiment was conducted in a glass greenhouse to explore the effects of water-saving techniques with irrigation scheduling based on soil water content on the growth and quality of pakchoi and the fate of irrigation water. Three water-saving techniques were investigated: micro-irrigation (M-0), furrow irrigation with plastic mulch (F-P), and micro-irrigation with plastic mulch (M-P) compared to furrow irrigation (F-0). F-P and M-P treatments enhanced pakchoi growth and primarily increased the total root length of the root system (0–0.2 m) compared to F-0. The two treatments further induced an improvement of pakchoi quality. Compared to M-0, F-P and M-P treatments showed better performance in reducing evaporation by 57–70% and proportion of evaporation in evapotranspiration, and consequently exhibited more pronounced effects on water saving. Irrigation water use efficiency (IWUE) was improved in F-P by 50% in both seasons and was improved in M-P by 84 and 95% in spring season and autumn season, respectively. Combining irrigation scheduling based on soil water content with plastic mulch is a feasible way to improve IWUE in protected vegetable production by reducing water consumption and enhancing crop growth. [ABSTRACT FROM AUTHOR]

Global climate change is affecting important natural resources including water. Increasing temperature will change rate of evaporation and transpiration, leading to variations in water availability, ground water recharge, and water consumption by plants. Thus, competition for water will be a major future challenge for agriculture. Increasing water productivity at farm level is necessary to increase the efficiency of the irrigation system, plant water−use efficiency (WUE) and to optimize irrigation management. We test the hypothesis that in field−grown, drip−irrigated nectarine trees, the roots in the un−irrigated inter−row soil produce chemical signals that increase in summer to induce stomatal closure and so increase WUE. Concentrations of abscisic acid (ABA) were determined in leaf, root, and xylem sap of drip−irrigated (D) trees in which only about 25% of the soil volume was wetted and compared with those of trees irrigated using microjets (M) in which the whole soil volume was wetted. We also examined the effects of increased ABA on root−to−shoot dry matter ratio, the ratio ABA to indole−3−acetic acid (IAA), sap pH, and fruit and shoot growth. Both D and M trees were maintained at optimal water status as judged by pre−dawn leaf water potentials (about −0.3 MPa). There were no significant differences between treatments in mean fruit size (fruit diameter) or in tree yield (total fruit weight). However, shoot length was strongly reduced in D trees (to 75%) compared to M trees (100%). The concentrations of ABA in the inter−row roots of D trees were increased by 59% and that in the leaves by 13% compared to in the M trees. Despite the similar water status of D and M trees, a clear chemical signal was triggered in terms of a significant increase in the ABA/IAA ratio. This signal influenced leaf stomatal conductance which was 40% lower in D trees than in M trees. The associated responses in photosynthesis and transpiration raised the WUE of D trees by 7%–10% compared to M trees. This field study shows that in drip−irrigated trees, an ABA root−to−shoot signal issues from the inter−row roots growing in soil that dries out during a Mediterranean summer (hot, low rainfall). This ABA−induced WUE increase was achieved principally through reduced stomatal conductance and reduced transpiration. [ABSTRACT FROM AUTHOR]

Natural biostimulants combine different elicitors that may influence economic properties of herbal crops, such as mint. Mint (Mentha longifolia L.) plants were subjected to three water levels based on container substrate capacity (CSC; 100% CSC, 70% CSC, and 50% CSC) and/or applications of four biostimulants (CRADLE™, Mobilizer™, Nanozim De'Lite™ [ND], and Nanozim NXT™ [NN]). ND and NN exhibited higher vegetative growth and root dry weight than the control (without biostimulants) and other treatments. NN produced the highest fresh and dry mint yields under all water levels. Irrigation water-use efficiency (IWUE) of NN was highest (2.78 kg m−3) with 70% CSC, whereas the control produced the lowest IWUE (1.85 kg m−3) with 100% CSC. Biostimulants boosted physiological and metabolic responses, including gas exchange, leaf water potential, relative water content, and proline accumulation of stressed plants. NN treatment with 70% CSC had the highest essential oil (EO) ratio (3.35%). Under 70% and 50% CSC with NN treatment, the proportion of 1,8-cineol increased and that of pulegone decreased in EOs. Increased antioxidant activities, reduced H2O2 levels, and increased catalase and superoxide dismutase activities were observed. Applications of ND and NN during water stress conditions increased economic and medicinal properties of mint EOs with applications in the agricultural and pharmaceutical industries. [ABSTRACT FROM AUTHOR]

Agricultural water supply (AWS) estimation is one of the first and fundamental steps of developing agricultural management plans, and its accuracy must have substantial impacts on the following decision-making processes. In modeling the AWS for paddy fields, it is still common to determine parameter values, such as infiltration rates and irrigation efficiency, solely based on literature and rough assumptions due to data limitations; however, the impact of parameter uncertainty on the estimation has not been fully discussed. In this context, a relative sensitivity index and the generalized likelihood uncertainty estimation (GLUE) method were applied to quantify the parameter sensitivity and uncertainty in an AWS simulation. A general continuity equation was employed to mathematically represent the paddy water balance, and its six parameters were investigated. The results show that the AWS estimates are sensitive to the irrigation efficiency, drainage outlet height, minimum ponding depth, and infiltration, with the irrigation efficiency appearing to be the most important parameter; thus, they should be carefully selected. Multiple combinations of parameter values were observed to provide similarly good predictions, and such equifinality produced the substantial amount of uncertainty in AWS estimates regardless of the modeling approaches, indicating that the uncertainty should be counted when developing water management plans. We also found that agricultural system simulations using only literature-based parameter values provided poor accuracy, which can lead to flawed decisions in the water resources planning processes, and then the inefficient use of public investment and resources. The results indicate that modelers' careful parameter selection is required to improve the accuracy of modeling results and estimates from using not only information from the past studies but also modeling practices enhanced with local knowledge and experience. [ABSTRACT FROM AUTHOR]

Improvements in water productivity are of primary importance for maintaining agricultural productivity and sustainability. Water potential-based irrigation management has proven effective for this purpose with many different crops, including strawberries. However, problems related to spatial variability of soil properties and irrigation efficiency were reported when applying this management method to strawberries in soils with rock fragments. In this study, a field-scale experiment was performed to evaluate the impacts of three irrigation management scales and a pulsed water application method on strawberry yield and water productivity. An analytical solution to Richards' equation was also used to establish critical soil water potentials for this crop and evaluate the effects of the variability in the soil properties. Results showed that spatial variability of soil properties at the experimental site was important but not enough to influence crop response to irrigation practices. The studied properties did not present any spatial structure that could allow establishing specific management zones. A four-fold reduction in the size of the irrigation management zones had no effect on yield and increased the water applications. Pulsed application led to significant yield (22%) and water productivity (36%) increases compared with the standard water application method used by the producer at the experimental site. [ABSTRACT FROM AUTHOR]

Irrigation efficiency is facilitated by matching irrigation rates to crop water demand based on estimates of actual evapotranspiration (ET). In production settings, monitoring of water demand is typically accomplished by measuring reference ET rather than actual ET, which is then adjusted approximately using simplified crop coefficients based on calendars of crop maturation. Methods to determine actual ET are usually limited to use in research experiments for reasons of cost, labor and requisite user skill. To pair monitoring and research methods, we co-located eddy covariance sensors with on-farm weather stations over two different irrigated crops (vegetable beans and hazelnuts). Neural networks were used to train a neural network and utilize on-farm weather sensors to report actual ET as measured by the eddy covariance method. This approach was able to robustly estimate ET from as few as four sensor parameters (temperature, solar radiation, humidity and wind speed) with training time as brief as one week. An important limitation found with this machine learning method is that the trained network is only valid under environmental and crop conditions similar to the training period. The small number of required sensors and short training times demonstrate that this approach can estimate site-specific and crop specific ET. With additional field validation, this approach may offer a new method to monitor actual crop water demand for irrigation management. [ABSTRACT FROM AUTHOR]