Irrigation Amount Research Articles

Enhancing root physiology for increased yield in water-saving and drought-resistance rice with optimal irrigation and nitrogen.

Water-saving and drought-resistance rice (WDR) plays a vital role in the sustainable development of agriculture. Nevertheless, the impacts and processes of water and nitrogen on grain yield in WDR remain unclear. In this study, Hanyou 73 (WDR) and Hyou 518 (rice) were used as materials. Three kinds of nitrogen fertilizer application rate (NFAR) were set in the pot experiment, including no NFAR (nitrogen as urea applied at 0 g/pot), medium NFAR (nitrogen as urea applied at 15.6 g/pot), and high NFAR (nitrogen as urea applied at 31.2 g/pot). Two irrigation regimes, continuous flooding cultivation and water stress, were set under each NFAR. The relationships between root and shoot morphophysiology and grain yield in WDR were explored. The results demonstrated the following: 1) under the same irrigation regime, the grain yield of two varieties increased with the increase of NFAR. Under the same NFAR, the reduction of irrigation amount significantly reduced the grain yield in Hyou 518 (7.1%-15.1%) but had no substantial influence on the grain yield in Hanyou 73. 2) Under the same irrigation regime, increasing the NFAR could improve the root morphophysiology (root dry weight, root oxidation activity, root bleeding rate, root total absorbing surface area, root active absorbing surface area, and zeatin + zeatin riboside contents in roots) and aboveground physiological indexes (leaf photosynthetic rate, non-structural carbohydrate accumulation in stems, and nitrate reductase activity in leaves) in two varieties. Under the same NFAR, increasing the irrigation amount could significantly increase the above indexes in Hyou 518 (except root dry weight) but has little effect on Hanyou 73. 3) Analysis of correlations revealed that the grain yield of Hyou 518 and Hanyou 73 was basically positively correlated with aboveground physiology and root morphophysiology, respectively. The grain yield could be maintained by water stress under medium NFAR in WDR. The improvement of root morphophysiology is a major factor for high yield under the irrigation regime and NFAR treatments in WDR.

Compensation of cotton yield by nitrogen fertilizer in non-mulched fields with deficit drip irrigation

Irrigation and fertilization are the main measures used by farmers to maintain crop yield and quality, especially in arid and semi-arid regions. To investigate the compensation of cotton yield loss due to deficit drip irrigation in non-mulched fields by increasing nitrogen (N) fertilizer application, a split-plot experiment with irrigation amount as the main plot and N application as the subplot was carried out in southern Xinjiang, China. The experiment included two irrigation amounts of 450 mm (deficit irrigation, W1) and 540 mm (full irrigation, W2) and three N application rates of 150 kg ha−1 (F1), 225 kg ha−1 (F2), and 300 kg ha−1 (F3). From the cotton seedling stage, ET0 (reference evapotranspiration) was calculated from daily meteorological data and irrigation was applied when the cumulative ET0-P reached 45 ± 3 mm. The results showed that irrigation and fertilization significantly affected soil moisture and total N, which in turn affected cotton growth, biomass formation, and yield (P<0.05). Soil water storage (SWS) increased by 15.9% on average under W2 compared to W1. F2 and F3 decreased SWS by 5.0%-5.1% and 7.7%-10.9% respectively, compared to F1. Total soil nitrogen in W2 was on average 13.3% lower than W1, and F2 and F3 were 4.4%-11.1% and 11.3%-16.5% lower than F1, respectively. Aboveground biomass increased significantly with increasing irrigation and N amounts and was 47.9% higher in W2F3 than in W1F1. However, the increased biomass was not translated into yield and excessive accumulation of root and stem biomass reduced cotton yield. Under full irrigation (W2), cotton yield increased and then decreased with increasing N application. Cotton yield in F2 increased by 3.4% and 8.6% compared to F1 and F3, respectively. Under deficit irrigation (W1), N fertilizer compensation increased with increasing N application, and cotton yield in F3 increased by 10.3% and 15.0% compared to F1 and F2, respectively (P<0.05). TOPSIS analysis showed that W1F3 had the highest rank, followed by W1F2. The results indicated that W1F3, irrigation amount of 450 mm and N application rate of 300 kg ha−1, could be proposed for cotton fields under non-mulched drip irrigation in southern Xinjiang, China.

Future Climate Change Impacts on Rice in Uttar Pradesh, India's Most Populous Agrarian State

AbstractUttar Pradesh, with a population of 237 million, is the largest agrarian state in India, located in the Indo‐Gangetic plains. Rice cultivation is widespread across all districts of Uttar Pradesh, which have varying climate regimes, irrigation infrastructures, crop management practices, and farm sizes. The state is characterized by different agroecological zones (AEZs) with semi‐arid to sub‐humid climates with significant variability in monsoon rainfall. In this study, the impact of climate change on Kharif‐season rice is estimated using crop‐climate scenarios in Uttar Pradesh. A process‐based Crop Simulation Model, Crop Estimation through Resource and Environment Synthesis‐Rice, was simulated with bias‐corrected and downscaled climate data for historical (1995–2014) and three future periods (the 2030s, 2050s, and 2090s) for two mitigation pathways (SSP2‐4.5 and SSP5‐8.5) from the Coupled Model Intercomparison Project 6. Phenology, irrigation amount, crop evapotranspiration, yield, and water use efficiency were evaluated and assessed for all AEZs. Based on the ensemble of 16 climate models, rainfed rice yield increased in the AEZs of western Uttar Pradesh due to increased rainfall, while in eastern Uttar Pradesh yield decreased, under both shared socioeconomic pathways (SSPs). Irrigated rice yield decreased in all AEZs under both SSPs due to an increase in temperature and a decrease in the length of the growing period, with reductions of up to 20% by the 2090s. Irrigation requirements decreased from the 2030s to the 2090s due to increased rainfall and decreased crop evapotranspiration. Despite the projected increase in rainfed yield, the overall rice yield is expected to decrease in the future under both SSPs.

Quantifying the Hydrological Impacts of Irrigation on a Mediterranean Agricultural Context Through Explicit Satellite‐Derived Irrigation Estimates

AbstractWater budget over anthropized basins is profoundly altered by human interventions, among which irrigation prevails. This study investigates how such water use affects hydrological flux and state variables by comparing two SURFEX/ISBA (SURFace EXternalisée/Interaction Sol Biosphère Atmosphère) Land Surface Model simulations performed over a portion of the Ebro basin (Spain) that includes a heavily irrigated area. The first simulation is forced by atmospheric input only, while the second one is fed with atmospheric forcing plus remote sensing‐derived irrigation amounts added to the liquid precipitation. Four main hydrological output variables are compared under the two configurations: surface soil moisture (SM), total evaporative flux (i.e., the sum of components from bare soil and vegetation) (E), drainage, and runoff. Results indicate that SM and E are the variables mostly impacted during the main watering season. Considering mean daily rates per each month, a maximum increase of +30% and of +220% is found over the irrigation districts in July for SM and E, respectively. The reliability of the results is supported by comparisons with satellite evapotranspiration data from MODIS (MODerate‐resolution Imaging Spectroradiometer). The inclusion of irrigation reduces the RMSE between monthly anomalies of modeled E and of MODIS reference data by 41% during the main watering season. Further validation through wavelet coherence analysis is also proposed. This study sheds light on the potential of explicit satellite‐derived irrigation water use data that, when integrated into modeling platforms, allow us to track and quantify anthropogenic impacts on water resources.

Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study

Global water scarcity has become a non-negligible problem that threatens the sustainable development of agriculture. In order to alleviate the contradiction between grain demand and water resource constraints, it is particularly important to explore appropriate irrigation strategy so as to synergistically increase grain yield and water use efficiency (WUE). The AquaCrop model were locally calibrated to simulate optimal irrigation amount for different hydrological years using a four-year field measurements (from 2017 to 2020) of maize with two irrigation levels (2400 m3/ha and 4800 m3/ha) in Shihezi, Xinjiang, China. On this basis, regulated deficit irrigation (RDI) strategies were optimized based on the variation of water consumption and soil water content (SWC) during the maize growth period. Results suggest that the optimal irrigation amount under static strategy (fixed proportion irrigation in growing season) in the wet, normal, and dry years was 4733 m3/ha, 5381 m3/ha, and 6090 m3/ha, respectively. In dynamic strategies, the optimized RDI4 (65% Ir (the amount of water required for each irrigation interval) at R2-R5 stage) and RDI5 strategy (85% Ir at V6-V12 stage and 85% Ir at R2-R5 stage) can save irrigation water while maintaining high yield. Under the premise of basically maintaining high yield (18Mg/ha), compared with each year's irrigation amount of 4800 m3/ha, the RDI4 strategy can reduce the irrigation amount by 4.33% in 2017; although the irrigation amount was slightly increased by 2.77% under the RDI5 strategy in 2018, the yield could be increased by 3.65%; in 2019, the RDI5 strategy can save 49.44% of irrigation water, and the RDI4 strategy will save 24.13% of irrigation water in 2020. From this study, it is recommended that a single irrigation amount of 65% Ir in R2 to R5 stages of maize growth or 85% Ir in V6 to V12 stages and 85% Ir in R2 to R5 stages can save irrigation water while maintaining high yield (18 Mg/ha).

Rice mutants, selected under severe drought stress, show reduced stomatal density and improved water use efficiency under restricted water conditions.

Rice is among the least water-use-efficient crops, and rice plants utilise most of their water uptake for transpirational cooling via stomata. To improve water-use efficiency (WUE) in rice, reducing stomatal density and size could help optimise transpiration and photosynthesis. In this study, we compared two series of purple rice stomata mutants: the Stomatal Model Mutant (SMM) identified by microscopic observation of flag-leaf stomata, and the Drought-selected Model Mutant (DMM) generated through screening under severe water stress. After undergoing two rounds of severe water stress between -60 to -80 Ym, right before the R1-2 reproductive stage, three DMMs were selected based on their rapid recovery rate and % filled-grain percentage. The three DMMs displayed 618-697 stomatal units per mm2, similar to the SMMs low-density stomata mutant (JHN 8756 (LD)). Furthermore, the four SMMs, three DMMs and the Jao Hom Nin wild type (JHN WT) were treated with two restricted water condition schemes from seedlings to harvest. The total amount of irrigation and precipitation during the experiment was 78.1 L/plant (69.1 mm/plant) for the less restricted water condition (LR) and 47.5 L/plant (42 mm/plant) for the more restricted water condition (MR). Water condition treatments had no effects on stomatal density and stomatal index. In contrast, genotypes and restricted water condition schemes affected plant height, tillers/plant, % filled grains and shoot dry weight (SDW). The three DMMs and the JHN 8756 (LD), the SMM's low-density stomata mutant, displayed greater resilience towards more restricted water conditions than the SMMs and the JHN wild type. Particularly, DMMs were tolerant to more restricted water condition treatments, showing no SDW penalties. Together, the DMMs and the JHN 8756 (LD) displayed higher WUE under these conditions of more restricted water conditions. A rigorous screening process to distinguish tolerant mutants with a rapid drought recovery rate from severe water stress could pave the way to isolate more mutants with better stomatal functionality and resilience in preparation for imminent climate changes.

Alfalfa Cultivation Patterns in the Yellow River Irrigation Area on Soil Water and Nitrogen Use Efficiency

Establishing lucerne field is an efficient way to protect natural steppes, alleviate conflicts between meadows and livestock, and promote the development of animal husbandry. However, problems such as extensive field management, valuing yield over quality, and low resource utilization are endemic in production. Exploring reasonable cultivation patterns can contribute to improving the current situation of artificial grassland production and promoting the high-quality development of husbandry and prataculture. Lucerne the field experiment was carried out in Jingtai, Gansu Province, China in 2021–2022; this study compared and analyzed the effects of three cultivation patterns—ridge tillage with plastic film mulching (PM), ridge tillage with biodegradable film mulching (BM), and traditional flat planting (FP)—on soil water, heat, and fertilizer, as well as lucerne growth, yield, quality, and water and nitrogen use efficiency. The results show that: (1) during the growth period of lucerne, PM and BM treatments augment the average moisture content of the soil layer of 0–120 cm by 31.19% and 24.03% compared to the FP treatment, respectively. In the soil layer of 0–40 cm, PM and BM treatments abate the soil moisture content of the ridges by an average of 19.29% and 7.89% compared to that in the ditches, respectively. In the soil layer of 40–120 cm, PM and BM treatments elevate the soil moisture content of the ridges by 4.40% and 4.65% on average compared to that in the ditches, respectively. The average soil temperature in a soil layer of 5–25 cm shows PM &gt; BM &gt; FP. In contrast with the FP treatment, PM and BM treatments increase the soil temperature of the ridges by an average of 1.87 °C and 0.96 °C and decrease that of the ditches by an average of 0.47 °C and 0.46 °C, respectively. After two years of planting, the three cultivation patterns all promote the soil nutrient content. Compared to the FP treatment, PM and BM treatments increase the organic matter content by 9.94% and 19.94%, respectively. (2) Ridge tillage with film mulching can evidently stimulate the growth of lucerne and enhance yield and quality. Compared to the FP treatment, PM and BM treatments enhance plant height by an average of 15.37% and 4.04%, stem diameter by an average of 34.14% and 14.58%, yield by an average of 21.20% and 14.77%, crude protein content by an average of 13.47% and 7.68%, and relative feed value by an average of 8.71% and 4.41%, respectively. (3) During the two-year growing period, the irrigation amount of lucerne was 508.60–615.30 mm, and the evapotranspiration was 563.70–761.80 mm. Compared to the FP treatment, PM and BM treatments hoist water use efficiency by an average of 43.50% and 17.56%, nitrogen partial factor productivity by an average of 21.20% and 15.22%, and net income by an average of 14.78% and 11.05%, respectively. In summary, in ridge tillage, both ordinary film mulching and biodegradable film mulching can create a favorable soil environment for lucerne growth and heighten production effect. The former has a better effect on advancing the lucerne production effect, and the latter exhibits superior performance in improving soil fertility.

Influence of Biochar Application Rate, Particle Size, and Pyrolysis Temperature on Hydrophysical Parameters of Sandy Soil

Sandy areas occupy a huge amount of land worldwide, but due to their characteristics, they are mostly low in fertility and low in organic matter. Sandy soils have coarse texture, high saturated hydraulic conductivity, low soil organic carbon, and poor aggregate stability and water retention capacity; therefore, it is necessary to add organic additives to them. The objective of this study was to assess the effect of particle size and application rate of biochar (BC) produced under different pyrolysis temperatures on the porosity P, available water content for plants AWC, saturated hydraulic conductivity Ks, and contact angle CA of sandy soil. The results show that an application of BC to sandy soil significantly increased AWC by 76–168%, CA by 252–489%, P by 6–11%, and significantly reduced Ks by 37–90%. Statistical analysis of the effect of three examined factors (BC application rate, particle size, and pyrolysis temperature) revealed that P, AWC, and Ks were affected by all three factors, while CA was affected only by BC application rate and particle size. The statistically significant interaction between the two factors was found for P (temperature × rate and size × rate), AWC (temperature × size), and Ks (size × rate). Statistically significant interaction among the three factors was not found for any hydrophysical parameter. The application of BC to amend sandy soils can be seen as a strategy to mitigate drought conditions and to reduce the amount of irrigation, saving water. Further investigations are needed with regard to the BC application under climate conditions with long hot and dry periods, which may promote soil water repellency.

Effects of Water and Nitrogen Control on the Growth Physiology, Yields, and Economic Benefits of Lycium barbarum Plants in a Lycium barbarum + Alfalfa System.

In the production of economic forests, there are common issues such as excessive application of water and fertilizer, redundant plant growth, and low economic benefits. Reasonable water and fertilizer management can not only help address these problems but also improve the absorption and use efficiency of water and fertilizer resources by plants, promoting the green and efficient development of the fruit and forestry industry. In order to explore a suitable water and nitrogen management mode for Lycium barbarum, field experiments were conducted in this study from 2021 to 2022. Specifically, four irrigation modes (according to the proportion ratio of soil moisture content to field moisture capacity θf, 45-55% θf (W1, severe water deficiency), 55-65% θf (W2, moderate water deficiency), 65-75% θf (W3, mild water deficiency), and 75-85% θf (W4, sufficient irrigation)) and four nitrogen application levels (0 kg·ha-1 (N0, no nitrogen application), 150 kg·ha-1 (N1, low nitrogen application level), 300 kg·ha-1 (N2, medium nitrogen application level), and 450 kg·ha-1 (N3, high nitrogen application level)) were set up to analyze the influences of water and nitrogen control on the plant height, stem diameter, chlorophyll content, photosynthetic characteristics and yield, and economic benefits of Lycium barbarum in the Lycium barbarum + Alfalfa system. The study results show that the plant height and stem diameter increment of Lycium barbarum increase with the irrigation amount, increasing first and then decreasing with the increase in the nitrogen application level. Meanwhile, the chlorophyll contents in Lycium barbarum continuously increase throughout their growth periods, with Lycium barbarum treated with W4N2 during all growth periods presenting the highest contents of chlorophyll. In a Lycium barbarum + Alfalfa system, the daily variation curve of the Lycium barbarum net photosynthetic rate presents a unimodal pattern, with maximum values of the daily average net photosynthetic rate and daily carboxylation rate appearing among W4N2-treated plants (19.56 μmol·m-2·s-1 and 157.06 mmol·m-2·s-1). Meanwhile, the transpiration rates of Lycium barbarum plants continuously decrease with the increased degree of water deficiency and decreased nitrogen application level. W1N2-treated plants exhibit the highest leaf daily average water use efficiency (3.31 μmol·s-1), presenting an increase of 0.50-10.47% in efficiency compared with plants under other treatments. The coupling of water and nitrogen has significantly improved the yields and economic benefits of Lycium barbarum plants, with W4N2-treated and W3N2-treated plants presenting the highest dried fruit yield (2623.07 kg·ha-1) and net income (50,700 CNY·ha-1), respectively. Furthermore, compared with other treatment methods, these two treatment methods (W4N2 and W3N2) exhibit increases of 4.04-84.08% and 3.89-123.35% in dried fruit yield and net income indexes, respectively. Regression analysis shows that, in a Lycium barbarum + Alfalfa system, both high yields and economic benefits of Lycium barbarum plants can be achieved using an irrigation amount of 4367.33-4415.07 m3·ha-1 and a nitrogen application level of 339.80-367.35 kg·ha-1. This study can provide a reference for improving the productivity of Lycium barbarum plants and achieving a rational supply of water and nitrogen in Lyciun barbarum + Alfalfa systems in the Yellow River Irrigation Area of Gansu, China, and other similar ecological areas.

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

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

Effect of Different Nitrogen Levels on Water and Nitrate Distribution in Aeolian Sandy Soil under Drip Irrigation

Understanding the distribution of water and nitrate nitrogen in the soil profile is crucial for the reasonable operation of fertigation, and it is also fundamental for controlling and regulating nitrate nitrogen in the root zone, thereby meeting a crop’s requirements. The application rates of fertilizer and water directly influence this distribution of water and nitrate nitrogen. However, the effects in Aeolian sandy soil, a type of developing soil bordering deserts, remain ambiguous. In this study, field experiments for different drip fertigation treatments in Aeolian sandy soil were conducted to investigate the soil water distribution, as well as that of nitrate nitrogen. A completely randomized experimental design was implemented, encompassing three levels of irrigation amount: low (W1), medium (W2), and high (W3), and three levels of nitrogen application rate: low (F1), medium (F2), high (F3). After the completion of each irrigation treatment, soil samples were extracted at 10–20 cm intervals. The soil water and nitrate nitrogen contents in the profiles of these samples were measured. The experimental results revealed that increasing the nitrogen application rate facilitated the retention of greater amounts of water and nitrate nitrogen in the soil profile. However, with an increase in the nitrogen application rate, both soil water and nitrate nitrogen exhibited a radial tendency to move away from the drip emitter. Some moved upward and accumulated in surface soil near a ridge furrow, while some moved downward and remained in a deeper area approximately 30 cm horizontally from the emitter at depths of 40–60 cm. The uniformity of the water distribution decreased with increasing nitrogen application under low water conditions, with a reversal of this trend observed in medium and high water treatments. The effect of nitrogen application level on the uniformity of the nitrate nitrogen distribution was not significant. There was no significant correlation between the average soil water content and nitrate nitrogen content along the horizontal direction, however, a positive correlation existed in the vertical direction. In the whole profile, increasing the nitrogen application enhanced the correlation under low water conditions, but under medium and high water conditions, this trend was the opposite. This implies that, to avoid nitrate nitrogen leaching or limiting in a specific area, a moderate nitrogen application level is advisable. Under low water conditions, nitrogen application showed a positive effect on the nitrate nitrogen content, and a higher application is recommended. In cases of substantial water irrigation or rainy years, the nitrogen application rate should be decreased.

Sustainable management strategies for balancing crop yield, water use efficiency and greenhouse gas emissions

CONTEXTTo ensure food security in the face of climate change, it is crucial to use effective agricultural management practices that produce the triangular win-win for water, crops, and environments. OBJECTIVEThis study aimed to explore the sustainable management measures for balancing crop yield, water use efficiency (WUE) and greenhouse gas (GHG) emissions in China during 1981–2020. METHODSThe study selected the Beijing-Tianjin-Hebei (BTH) region of China as the research area, where there were sharp contradictions among water shortage, food security and polluted environment. Four irrigation treatments and four fertilization treatments were set referring to the local cultivated experiences. The daily dynamic changes in crop yield, WUE and GHG emissions were simulated by optimized Agricultural Production Systems sIMulator (APSIM) model. RESULTS AND CONCLUSIONSThe irrigations had positive impacts on crop yield and WUE in BTH region. The irrigation amount's rise caused a gradual augmentation in the total yield of winter wheat and summer maize from 1981 to 2020.The highest total yield was achieved under W4 irrigation treatment (320 mm water for winter wheat and 60 mm water for summer maize), with an annual mean of 24,579.2 kg·ha−1. The annual average WUE under the W3 irrigation treatment (240 mm water for winter wheat) was the highest, with an average of 13.9 kg·ha−1·mm−1. However, extensive fertilization exacerbated soil GHG emissions. The soil GHG emissions were found to be significant increase as the input amount of fertilization. The FI fertilization measure (no fertilization) was assessed to have the least impact on the environment, with an average GHG emissions of 0.4 Mg·CO2-eq·ha−1. The optimal goals of high yield, high WUE and low GHG emissions were achieved by choosing effective combination practices of water and nitrogen management. Overall, the W3 irrigation and F3 fertilization (180 kg/ha fertilizer for winter wheat and 120 kg/ha fertilizer for summer maize.) treatments had the maximum water-fertilizer production indexes in the BTH region. SIGNIFICANCEThis study highlights the importance of agricultural management measures for guaranteeing food security and environmental sustainability at the same time under climate change.

Experimental Study on the Migration and Distribution of Microplastics in Desert Farmland Soil Under Drip Irrigation.

The microplastics (MPs) formed by broken plastic film may migrate in the soil under drip irrigation. To investigate the migration distribution of MPs in desert farmland soil under drip irrigation conditions, our study was conducted on farmland in Xinjiang (China). A MP drip irrigation penetration migration testing device was set up in combination with Xinjiang farmland irrigation methods to conduct a migration simulation experiment. The results showed that the migration amount of MPs in soil was significantly positively correlated with the amount of drip irrigation, and significantly negatively correlated with the soil depth; in addition, the relationship between the migration amount of MPs in different types of soil was: clay < sandy loam < sandy soil. Under drip irrigation conditions, the migration rates of MPs were 30.51%, 19.41%, and 10.29% in sandy soil, sandy loam soil, and clay, respectively. The migration ability of these three particle sizes of polyethylene MPs in soil was ranked as follows: 25 to 147 μm > 0 to 25 μm > 147 to 250 μm. When the drip irrigation volume was 2.6 to 3.2 L, horizontal migration distances of MPs exceeded 5 cm, and vertical migration distances reached more than 30 cm. Our findings provide reference data for the study of soil MP migration. Environ Toxicol Chem 2024;43:1250-1259. © 2024 SETAC.

High resolution prediction and explanation of groundwater depletion across India

Food production in much of the world relies on groundwater resources. In many regions, groundwater levels are declining due to a combination of anthropogenic extraction, localized meteorological and geological characteristics, and climate change. Groundwater in India is characteristic of this global trend, with an agricultural sector that is highly dependent on groundwater and increasingly threatened by extraction far in excess of recharge. The complexity of inputs makes groundwater depletion highly heterogeneous across space and time. However, modeling this heterogeneity has thus far proven difficult. Using two ensemble tree-based regression models, we predict district level seasonal groundwater dynamics to an accuracy of R 2 = 0.4–0.6 and Pearson correlations between 0.6 and 0.8. Further using two high-resolution feature importance methods, we demonstrate that atmospheric humidity, groundwater groundwater-based irrigation, and crop cultivation are the most important predictors of seasonal groundwater dynamics at the district level in India. We further demonstrate a shift in the predictors of groundwater depletion over 1998–2014 that is robustly found between the two feature importance methods, namely increasing importance of deep-well irrigation in Central and Eastern India. These areas coincide with districts where groundwater depletion is most severe. Further analysis shows decreases in crop yields per unit of irrigation over those regions, suggesting decreasing marginal returns for largely increasing quantities of groundwater irrigation used. This analysis demonstrates the public policy value of machine learning models for providing high spatiotemporal accuracy in predicting groundwater depletion, while also highlighting how anthropogenic activity impacts groundwater in India, with consequent implications for productivity and well-being.

Soil Moisture Detector

Abstract: Soil Moisture is directly related to the amount of irrigation in agriculture and influences the yield of crops. Accordingly, a soil moisture sensor is an important tool for measuring soil moisture content. In this study, the previous research conducted in recent 2-3 decades on soil moisture sensors was reviewed and the principles of commonly used soil moisture sensors and their various applications were summarized. Furthermore, the advantages, disadvantages, and influencing factors of various measurement methods employed were compared and analyzed. The improvements presented by several scholars have established the major applications and performance levels of soil moisture sensors, thereby setting the course for future development. These studies indicated that soil moisture sensors in the future should be developed to achieve high-precision, lowcost, non-destructive, automated, and highly integrated systems. Also, it was indicated that future studies should involve the development of specialized sensors for different applications and scenarios. This review research aimed to provide a certain reference for application departments and scientific researchers in the process of selecting soil moisture sensor products and measuring soil moisture.

Validation of farmers’ on-farm irrigation scheduling for optimal water utilization in Tigray Region, Ethiopia

Unwise use of irrigation water in water-scarce areas exacerbates water scarcity, diminishes crop yield, and leads to resource wastage. In the Tigray region of Ethiopia, where water is scarce and a determinant resource, no regional-level validation of on-farm irrigation scheduling had been conducted until now. The objectives of this study were to (i) validate farmers’ irrigation scheduling practices and (ii) optimize water consumption for increased irrigated area and number of farmers. Eight different irrigation schemes were purposively selected from the Tigray region. Primary data, acquired through field measurements, observations, and discussions, were supplemented with secondary data. Farmers' irrigation scheduling practices were predominantly of the "Fixed" type, characterized by constant irrigation intervals and amounts. Unfortunately, these practices were non-optimal, with 55% over-irrigation and 45% under-irrigation. Over-irrigation instances ranged from 1350 m3in a garlic plot within the Mesima scheme to a maximum of 1,327,067 m3in a maize plot within the Serenta scheme. The excess water could potentially be utilized to irrigate an additional area of 2 to 148 hectares, thereby benefiting 7 to 296 more farmers, respectively. Conversely, instances of under-irrigation in the Fre Lekatit scheme resulted in yield reductions of 10,445 kg for potatoes and 138,499 kg for maize. In the Tigray region, most of the schemes are semi-arid, emphasizing the imperative need for water conservation. Renovating regional-level irrigation scheduling by integrating performance assessment and enhancing water productivity at the field level, and establishing a remote-sensing-based 'Real-Time Irrigation Scheduling System' is deemed necessary to sustain dryland irrigated agriculture.

PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts

Efficient water management strategies are of utmost importance in drought-prone regions, given the fundamental role irrigation plays in avoiding yield losses and food shortages. Traditional methodologies for estimating irrigation amounts face limitations in terms of overall precision and operational scalability. This study proposes to estimate irrigation amounts from soil moisture (SM) data by adapting the PrISM (Precipitation Inferred from Soil Moisture) methodology. The PrISM assimilates SM into a simple Antecedent Precipitation Index (API) model using a particle filter approach, which allows the creation and estimation of irrigation events. The methodology is applied in a semi-arid region in the Ebro basin, located in the north-east of Spain (Catalonia), from 2016 to 2023. Multi-year drought, which started in 2020, particularly affected the region starting from the spring of 2023, which led to significant reductions in irrigation district water allocations in some of the areas of the region. This study demonstrates that the PrISM approach can correctly identify areas where water restrictions were adopted in 2023, and monitor the water usage with good performances and reliable results. When compared with in situ data for 8 consecutive years, PrISM showed a significant person’s correlation between 0.58 and 0.76 and a cumulative weekly root mean squared error (rmse) between 7 and 11 mm. Additionally, PrISM was applied to three irrigation districts with different levels of modernization, due to the different predominant irrigation systems: flood, sprinkler, and drip. This analysis underlined the strengths and limitations of PrISM depending on the irrigation techniques monitored. PrISM has good performances in areas irrigated by sprinkler and flood systems, while difficulties are present over drip irrigated areas, where the very localized and limited irrigation amounts could not be detected from SM observations.

Optimization of irrigation and fertilization of apples under magnetoelectric water irrigation in extremely arid areas.

Apple (Malus pumila Mill.) is one of the important economic crops in the arid areas of Xinjiang, China. For a long time, there has been a problem of high consumption but low yield in water and fertilizer management, prevent improvements in apple quality and yield. In this study, 5-year-old 'Royal Gala' apple trees in extremely arid areas of Xinjiang were used as experimental materials to carry out field experiments. considering 5 irrigation levels (W1, 30 mm; W2, 425 mm; W3, 550 mm; W4, 675 mm; W5, 800 mm) and 5 fertilization levels (F1, 280 kg·ha-1; F2, 360 kg·ha-1; F3, 440 kg·ha-1; F4, 520 kg·ha-1; F5, 600 kg·ha-1) under magnetoelectric water irrigation conditions. The results demonstrated that magnetoelectric water combined with the application of 675 mm irrigation amount and 520 kg·ha-1 fertilization amount was the most effective combination. These results occurred by increasing net photosynthetic rate of apple leaves, improved the quality of apples, increased apple yield, and promoted the improvement of water and fertilizer use efficiency. Additionally, the quadratic regression model was used to fit the response process of yield, IWUE and PFP to irrigation amount and fertilization amount, and the accuracy was greater than 0.8, indicating good fitting effects. The synergistic effect of water and fertilizer has a positive effect on optimizing apple water and fertilizer management. Principal component analysis showed that the magnetoelectric treatment combined water and fertilizer mainly affected apple yield, water and fertilizer use efficiency and vitamin C content related to quality. This study provides valuable guidance for improving water and fertilizer productivity, crop yield and quality in extreme arid areas of Xinjiang by using Magnetoelectric water irrigation.

SolarET: A generalizable machine learning approach to estimate reference evapotranspiration from solar radiation

Irrigation is the most significant consumer of freshwater worldwide. Deciding on the right amount of irrigation is crucial for sustainable water management and food production. The Penman-Monteith (P-M) reference crop evapotranspiration (ETO) is the gold standard in irrigation management and scheduling; however, its calculation requires measurements from multiple sensors over an extended reference grass surface. The cost of land, sensors, maintenance, and water to keep the grass surface green impedes having a dense network of ETO stations. To solve this challenge, this research aims to develop an input-limited ETO estimation approach based on historical weather data and machine learning (ML) algorithms to relax the need for a reference grass surface. This approach, called "SolarET," takes solar radiation (RS) data as its sole input. RS is the only meteorological driving factor of ETO that does not rely on the measuring surface. To test the generalizability of SolarET, we test its performance over unseen arbitrary locations across California. California is chosen as the case study since it is one of the world's most hydrologically altered and agriculturally productive regions. In total, 19,088,736 hourly data samples from 131 automated weather stations have been used in this study. The ML models have been trained over 114 stations and tested over 17 unseen stations, each representing a California climatic zone. Our findings point to the superiority of decision tree-based algorithms versus neural networks. SolarET works best in irrigation-oriented regions of California (e.g., Central Valley) and is less accurate in coastal and desert zones. Our results demonstrate the higher accuracy of SolarET using hourly (RMSE = 0.93 mm/day) and daily (RMSE = 0.97 mm/day) RS data in comparison to well-known empirical alternatives like Priestley-Taylor (PT) (RMSE = 1.35 mm/day) and Hargreaves-Samani (HS) (RMSE = 2.69 mm/day).

Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2

Abstract. Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities.