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The increasing temperatures and changing precipitation patterns have affected both crop yields and water requirements challenging agricultural systems in sustaining high crop yields and ensuring water and food security. In the present study, we evaluated the impact of climate change on the corn production under irrigated and rainfed cropping systems in Nebraska considering four climate zones until 2100 as a case study for the US Corn Belt. Additionally, suggests ways to reduce the impact of climate change on corn yield and water resources. Five global circulation model datasets from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) interconnected to Shared Socioeconomic Pathways (SSPs), were selected. Three future periods: near (2020–2039), mid (2040–2069), and far future (2070–2100) under SSP226, SSP370, and SSP585 scenarios were used to predict the climate changes, crop cycle length, crop yield, and crop water requirement. Additionally, we input annual CO2 concentration scenarios for each SSP scenario to model changes from 2015 to 2100 using the CERES-Maize model. Temperatures are forecasted to rise, precipitation to decline, and crop cycle length to decrease, particularly for SSP370 (up to 49% yield decrease) and SSP585 (up to 67% yield decrease) by 2070–2100. Yields are expected to decline across all scenarios and periods for irrigated and rainfed fields due to the reduction in crop cycle length. Crop water demand is projected to increase, with rainfed systems facing heightened impact due to reduced precipitation. Addressing climate change in Nebraska requires actions like developing new corn varieties to longer the crop season, transitioning to efficient irrigation systems, improving irrigation management for water and food security, and reducing the risk of conflicts over its use. These results open possibilities for discussion about the actions that can be taken to cope with climate change and guarantee water and food security in the US Corn Belt. [ABSTRACT FROM AUTHOR]

Olive groves, often characterized by complex topography and highly variable soils, present challenges for delineating irrigation management zones (MZs). This study addresses this issue by examining the relevance of apparent electrical conductivity (ECa), elevation (Z), topographic wetness index (TWI) and time-series of Sentinel-2 NDVI imagery for delimiting MZs for variable rate irrigation (VRI) in a 40-ha olive grove in southern Spain. Principal Component Analysis (PCA) was employed to disentangle olive and grass cover NDVI patterns. PC1 represented the olive tree development patten and showed little relationship with soil properties, while PC2 was associated with the grass cover growth pattern and considered a proxy for water storage-related soil properties that are relevant for irrigation scheduling. An alternative analysis using NDVI percentiles yielded similar results but favored PCA for distinguishing between grass cover and olive tree development patterns. Correlation between NDVI and ECa varied seasonally (r > 0.60), driven by the grass cover dynamics. To assess also possible non-linear relationships, regression trees were used to estimate NDVI percentiles, emphasizing the importance of ECa, ECaratio, Z, and slope in predicting different NDVI percentiles. Fuzzy k-means zoning using ECa + Z resulted in four classes that best classified variables that are relevant for irrigation scheduling due to their relationship with soil water storage (e.g. clay content, P0.95 and PC2). Zonings based on ECa, ECa + Z + TWI and ECa + Z + TWI + NDVI yielded two zones that classified P0.95 and PC2 well, but not clay content. Therefore, the zoning based on ECa + Z was chosen as optimal in the context of this VRI applications. Our analysis showed how NDVI series can be used in combination with ECa and elevation to evaluate the effectiveness of different zoning approaches for developing VRI prescriptions in olive groves. [ABSTRACT FROM AUTHOR]

In the context of limited resources and a growing demand for food due to an increase in the worldwide population, irrigation plays a vital role, and the efficient use of water is a major objective. In pressurized irrigation systems, water management is linked to high energy requirements, which is especially relevant in sprinkler irrigation. Therefore, decision support models are important for optimizing the design and management of irrigation systems. In this study, a holistic model for solid set irrigation systems (SORA 2024) was developed. This new model integrates hydraulic models at the subunit and plot levels to evaluate the distribution of pressure (EPANET, Rossman in The EPANET programmer's toolkit for analysis of water distribution systems, Tempe, Arizona, 1999), the discharge and water distribution for each emitter (SIRIAS, Carrion et al. in , Irrig Sci 20(2):73–84, 2001) and the distribution of water applied by all the emitters of the subunit (SORA, Carrión et al. in Irrig Sci 20(2): 73–84, 2001). The integrated model also includes crop simulation (AQUACROP, Steduto et al. in Agron J 101(3), 426–437, 2009). to assess the effect of water distribution on crop production. The objective of this holistic model is to assist in decision-making processes for designing, sizing, upgrading, and managing solid set irrigation systems at the sprinkler level. The new integrated model (SORA 2024) was applied to a 2.84 ha commercial plot with 2 irrigation sectors that grow onion crops (Allium cepa L.). It was used to analyse each irrigation event from a real irrigation season, considering the conditions (pressure, irrigation time/periods, environmental conditions, and so on). The analysis is based on the sprinkler–nozzle combination, working pressure and wind direction and intensity during each irrigation event. The model also accounts for the cumulative effect/impact of all irrigation events on the plot. The model was validated through field trials using the "crop as a sensor" approach (Sarig et al. in , Agron 11(3):2021). To demonstrate the effectiveness of the model, the choice of nozzles in each sprinkler of the subunit was optimized. This is a quick and cost-effective way for farmers to improve their irrigation systems. By using this method, farmers can achieve better uniformity of water application and a slight increase in crop yield while maintaining the same irrigation schedule and amount of water used. Furthermore, the model enables farmers to work at the emitter level while integrating the results for the entire plot. This allows for precise irrigation of variable dosages by using different sprinkler–nozzle combinations in the same subunit. Farmers can do this based on the prior zoning of the plot, which is determined by its productive potential. This justifies the use of different irrigation dosages in each zone. [ABSTRACT FROM AUTHOR]

Different canopy resistance (rc) parameterization has been used in land surface models to simulate actual evapotranspiration (ETc) and soil hydraulic variable for crop fields. However, the influence of rc parameterization on evapotranspiration (ET) partitioning and soil water dynamics has not been fully investigated with consideration of the coupled soil water and vapor physics. This study investigated the influential mechanisms of five rc methods (viz., Jarvis, Katerji-Perrier, Massman, Kelliher-Leuning, and Farias) on ET partitioning and soil water contents in an irrigated maize field under a semiarid climate through a soil water and vapor transfer model. The Jarvis method presented the best ET results (R2 = 0.86 and RMSE = 0.71 mm·d-1). Different rc parameterization mainly altered the simulated amount of soil water contents, while not changed the response of soil water dynamics to irrigation events. By the integrated analysis of the ET partitioning and root-zone water budget, different rc methods varied in the choice of the optimum irrigation water use strategies. This study identified the direct and indirect impacts of rc on the ET partitioning and emphasizes the necessity of both the ET partitioning and water supply sources in the decision-making for irrigation water management in semiarid regions. [ABSTRACT FROM AUTHOR]

Irrigation water with high sodicity risk can lead to soil dispersion, poor drainage, and groundwater contamination. The sodium adsorption ratio (SAR) of soil water is influenced by water loss through evaporation. Evaporation concentrates sodium (Na) and magnesium (Mg), and its impact on soluble calcium (Ca) and alkalinity is more intricate. This study presented a refined sodicity hazard assessment that quantifies the influence of evaporative water loss and calcite precipitation on drainage water. Specifically, the initial equivalent concentration of alkalinity and Ca predominantly determines the potential sodicity risk of drainage water. The alternative approach projects two pathways for potential drainage water SAR , which include limiting the sodium adsorption ratio (LSAR) to represent the upper limit boundary and evaporated-based sodium adsorption ratio (ESAR) to represent the lower limit boundary. When irrigation water alkalinity exceeds the soluble Ca concentration, soluble Ca in the drainage water is limited as calcite precipitates and the drainage water is dominated by Na and Mg. The SAR approaches an upper limit (LSAR) determined by the initial relative concentration of Na and Mg. Conversely, if irrigation water alkalinity is less than the soluble Ca concentration, minimal calcite precipitation occurs, and drainage water is dominated by Na, Mg, and Ca. Then, the SAR approaches a lower limit (ESAR) determined by the initial Ca, Mg, and Na concentrations. To validate the accuracy of this new sodicity risk assessment method, this paper analyzed data extracted from previously published lysimeter studies. Water composition boundaries for each source water were plotted, and these boundaries were compared to the recorded drainage water composition in the lysimeter studies. As salinity increased through evaporation, the drainage water followed a distinct salinization path but remained within the LSAR and ESAR boundaries. This information is essential for irrigation managers to quickly assess water sodicity levels and make timely management decisions. Practical Applications: The application of irrigation water with high sodicity risk can lead to soil dispersion. Therefore, an accurate and straightforward approach to assess the sodicity level of the source water is crucial for irrigation management. The practical implementation of the proposed approach for evaluating the sodium (Na) hazard of an irrigation water source begins with source water analysis, considering soluble Na, calcium (Ca), magnesium (Mg), alkalinity, and electrical conductivity (EC). The irrigation water source is then categorized based on its Ca to alkalinity ratio: an alkalinity-rich water source is where the ratio of Alkdw−/Cadw2+≥1 , and an alkalinity-poor water source is where Alkdw−/Cadw2+<1. As soil water salinity or EC increases through evaporation, the alkalinity-rich water is likely to approach the upper boundary, which is the limiting sodium adsorption ratio (LSAR)=Fc·Na+/Mg2+/2 , and Fc=ECdw/ECiw=1/LF , where ECdw represents the EC of irrigation water, ECiw represents the EC of drainage water, and the leaching fraction (LF) represents the leaching fraction. On the other hand, alkalinity-poor water is likely to remain close to the lower boundary, which is the evaporation-adjusted sodium adsorption ratio (ESAR)=Fc×Na+/(Mg2++Ca2+)/2. This information can help managers determine the suitability of a water source or make sodicity management decisions if poor quality irrigation water is used. [ABSTRACT FROM AUTHOR]

Irrigation is important for the growth of world agriculture, as it enables greater security in agricultural production. The use of center-pivot for irrigation is very common in Brazil. However, there are some information gaps, mainly related to spatial variability in the water application in variable topography. Thus, the present study aimed to apply the geostatistical approach to characterize and evaluate the magnitude of the pressure head (PH) spatial variability in center-pivot lateral lines operating in plots with variable topography. For this analysis, six different points were installed along the lateral line and measured with PH transducers in 18 lateral line angular positions in the study area. Universal kriging (UK) was used to estimate PH across the whole field. The semivariogram was adjusted by the hole effect theoretical model, indicating a strong spatial dependence on PH. A decision support system tool was developed to assist in the analysis of the PH spatial distribution along the center-pivot lateral line using a geostatistical approach (kriging). The proposed tool can be useful for managers of irrigable areas and to identify zones with high energy use (wasted PH) along lateral lines of center-pivot systems. The estimation of PH distribution using geostatistical and UK techniques was satisfactory, allowing the creation of a thematic map. Precision irrigation and monitoring using a thematic map of PH distribution from kriging can help monitor the operating conditions of a center-pivot, as well as improve the decision-making regarding proper management of the whole irrigation system. Practical Applications: Center-pivot irrigation systems are very common in agricultural production areas around the world. Due to the large area irrigated by center-pivots, it is very important to study the reduction in water and energy use in these equipment. Thus, an important point to be studied is the PH distribution along the center-pivot lateral line in areas with undulating topography, where there is a significant PH variation. In this study, we present an analysis of the PH distribution along the lateral line using a geostatistical approach (kriging) to obtain PH values in the entire irrigated area. For this, PH data collected at six different points along the lateral line were used in a decision support system tool, developed to estimate PH in the entire irrigated area using the geostatistical approach. This estimate was satisfactory, allowing the creation of a thematic map. The proposed tool proved to be useful for easily identifying zones with high energy use (wasted PH). In this way, the use of precision irrigation and the analysis of the equipment through thematic mapping can help irrigators in monitoring the operating conditions of a center-pivot. [ABSTRACT FROM AUTHOR]

[Display omitted] • Controlled irrigation reduced net global warming potential (net GWP) by 16–220%. • Hydrochar addition decreased greenhouse gas emission by 10–41% compared to straw addition. • Hydrochar and straw addition increased net ecosystem carbon budget (NECB) by 21–34%. • Hydrochar + controlled irrigation reduced greenhouse gas emission while increased NECB. Hydrochar is proposed as a climate-friendly organic fertilizer, but its potential impact on greenhouse gas (GHG) emissions in paddy cultivation is not fully understood. This two-year study compared the impact of exogenous organic carbon (EOC) application (rice straw and hydrochar) on GHG emissions, the net ecosystem carbon budget (NECB), net global warming potential (net GWP), and GHG emission intensity (GHGI) in a rice pot experiment using either flooding irrigation (FI) or controlled irrigation (CI). Compared with FI, CI increased ecosystem respiration by 23 – 44 % and N 2 O emissions by 85 – 137 % but decreased CH 4 emissions by 30 – 58 % (p < 0.05). Since CH 4 contributed more to net GWP than N 2 O, CI reduced net GWP by 16 – 220 %. EOC amendment increased crop yield by 5 – 9 % (p < 0.05). Compared with CK, hydrochar application increased initial GHG emission, net GWP and GHGI in the first year, while in the second year, there was no significant difference in net GWP and GHGI between CI–hydrochar and CK. Compared with straw addition, hydrochar amendment reduced net GWP and GHGI by 20 – 66 % and 21 – 66 %; and exhibited a lower net CO 2 emission when considering the energy input during the hydrochar production. These findings suggest that integrated CI-hydrochar practices would be a sustainable and eco-friendly way for organic waste management in rice production as it holds potential to enhance the NECB and SOC sequestration of rice production, while also offsetting the extra carbon emissions from organic inputs. [ABSTRACT FROM AUTHOR]

Agriculture’s important role in human survival and its significant impact on the Earth’s ecosystem imply the need for sustainable practices. This study focuses on the critical components of irrigation management and soil remediation, essential for maintaining soil health and productivity. By integrating these components, the study assessed feasible soil remediation practices and explored various irrigation strategies in different contexts. It was observed that integrating soil remediation practices with suitable irrigation techniques and scheduling can improve crop yield, conserve water, and enhance the long-term health of marginal soils, addressing the challenges of climate change, hunger, and environmental sustainability. The study also advocates for incorporating indigenous knowledge with physical, chemical, and biological soil remediation techniques, integrated with irrigation practices. This review serves as a valuable resource for researchers, policymakers, and practitioners, offering insights and paving the way for future research and development in sustainable agriculture. By making the link between irrigation management and soil remediation explicit, this study illustrates practical cases that address the complex challenges faced by marginal lands, global food security, and environmental sustainability. [ABSTRACT FROM AUTHOR]

In arid areas, water shortage has become a major bottleneck limiting the sustainable development of agriculture, necessitating improved water use efficiency and the full development of innovative water-saving irrigation management technologies to improve quality. In the present study, tomato (Solanum lycopersicum cv. Micro Tom) fruits were used as materials, and different irrigation frequencies were set during the fruit expansion stage. The normal treatment (CK) was irrigated every three days, while the water deficit treatments were irrigated at varying frequencies: once every 4 days (T1), 5 days (T2), 6 days (T3), 7 days (T4), and 8 days (T5). These corresponded to 80%, 70%, 60%, 50%, and 40% of the maximum field moisture capacity (FMC), respectively, with CK maintaining full irrigation at 90% of the maximum FMC. The water deficit treatment T3, with less stress damage to plants and the most significant effect on fruit quality improvement, was selected based on plant growth indices, photosynthetic characteristics, chlorophyll fluorescence parameters, and fruit quality indices, and its effects on carotenoids, glycolic acid fractions, and volatile compounds during tomato fruit ripening were further investigated. The outcome indicated that moderate water deficit significantly increased the carotenoid components of the tomato fruits, and their lycopene, lutein, α-carotene, and β-carotene contents increased by 11.85%, 12.28%, 20.87%, and 63.89%, respectively, compared with the control fruits at the ripening stage. The contents of glucose and fructose increased with the development and ripening of the tomato fruits, and reached their maximum at the ripening stage. Compared to the control treatment, the moderate water deficit treatment significantly increased the glucose and fructose levels during ripening by 86.70% and 19.83%, respectively. Compared to the control conditions, water deficit conditions reduced the sucrose content in the tomato fruits by 27.14%, 18.03%, and 18.42% at the mature green, turning, and ripening stages, respectively. The moderate water deficit treatment significantly increased the contents of tartaric acid, malic acid, shikimic acid, alpha ketoglutaric acid, succinic acid, and ascorbic acid, and decreased the contents of oxalic acid and citric acid compared to the control. The contents of total soluble sugar and total organic acid and the sugar–acid ratio were significantly increased by 48.69%, 3.71%, and 43.09%, respectively, compared with the control at the ripening stage. The moderate water deficit treatment increased the fruit response values to each sensor of the electronic nose, especially W5S, which was increased by 28.40% compared to the control at the ripening stage. In conclusion, during the ripening process of tomato fruit, its nutritional quality and flavor quality contents can be significantly improved under moderate (MD) deficit irrigation treatment. The results of this experiment can lay the foundation for the research on the mechanism of water deficit aiming to promote the quality of tomato fruit, and, at the same time, provide a theoretical basis and reference for tomato water conservation and high-quality cultivation. [ABSTRACT FROM AUTHOR]

Introduction: Actinidia is highly susceptible to water stress, both excess and shortage, and is therefore a model fruit crop for irrigation management, requiring precise water application. The present study was carried out in a mature kiwifruit orchard in southern Italy to investigate the physiology of a yellow-fleshed kiwifruit cultivar under non-limiting soil water conditions and in response to a progressive decrease in soil water content in a Mediterranean environment, with the aim of defining soil moisture thresholds to guide irrigation management. Methods: The progressive lowering in soil moisture was monitored using multi-profile probes, taking into account a 60 cm layer. Plant water status and physiological parameters were measured throughout the experiment and were significantly correlated with soil water status, suggesting that the level of soil water deficit affects plant physiological performance. Results: Reference minimum values of stem water potential reached during the day under non-limiting soil water conditions ranged from -0.4 to -0.7 MPa, with a value of -0.8 MPa identifying the threshold below which stomatal conductance began to decrease significantly. Soil moisture thresholds were defined according to the spatio-temporal dynamics of available water (AW) reduction, which decreased by approx. 10% and 1% before the onset of water stress and 16% and 2% at the onset of water stress, considered in the 0-30 cm and 30-60 cm soil layers, respectively, compared to the AW content of the whole soil profile. Discussion: Results confirmed that root uptake was mainly concentrated in the first 30 cm of soil depth, which should be properly managed by irrigation, as reduced soil water availability could easily lead to plant water stress. An integrated approach, combining plant measurements and soil water content monitoring, together with an assessment of root water uptake dynamics, is essential to identify soil water thresholds and develop precision irrigation, especially for high water-demanding crops and environments. [ABSTRACT FROM AUTHOR]

The impact of climate change on methane (CH4) emissions from rice production systems in the Coimbatore region (Tamil Nadu, India) was studied by leveraging field experiments across two main treatments and four sub-treatments in a split-plot design. Utilizing the closed-chamber method for gas collection and gas chromatography analysis, this study identified significant differences in CH4 emissions between conventional cultivation methods and the system of rice intensification (henceforth SRI). Over two growing seasons, conventional cultivation methods reported higher CH4 emissions (range: from 36.9 to 59.3 kg CH4 ha−1 season−1) compared with SRI (range: from 2.2 to 12.8 kg CH4 ha−1 season−1). Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R2 (0.92). The validated model was then used to develop future CH4 emissions projections under various shared socio-economic pathways (henceforth SSPs) for the mid- (2021–2050) and late (2051–2080) century. The analysis revealed a potential increase in CH4 emissions for the simulated scenarios, which was dependent on specific soil and irrigation management practices. Conventional cultivation produced the highest CH4 emissions, but it was shown that they could be reduced if the current practice was replaced by minimal flooding or through irrigation with alternating wetting and drying cycles. Emissions were predicted to rise until SSP 370, with a marginal increase in SSP 585 thereafter. The findings of this work underscored an urgency to develop climate-smart location-specific mitigation strategies focused on simultaneously improving current water and nutrient management practices. The use of methanotrophs to reduce CH4 production from rice systems should be considered in future work. This research also highlighted the critical interaction that exists between agricultural practices and climate change, and emphasized the need to implement adaptive crop management strategies that can sustain productivity and mitigate the environmental impacts of rice-based systems in southern India. [ABSTRACT FROM AUTHOR]

Assessing maize yield is critical, as it is directly influenced by the crop's growth conditions. Therefore, real-time monitoring of maize growth is necessary. Regular monitoring of maize growth indicators is essential for optimizing irrigation management and evaluating agricultural yield. However, quantifying the physical aspects of regional crop development using time-series data is a challenging task. This research was conducted at the Dengkou Experimental Station in the Hetao irrigation area, Northwest China, to develop a monitoring tool for regional maize growth parameters. The tool aimed to establish a correlation between satellite-based physical data and actual crop growth on the ground. This study utilized dual-polarization Sentinel-1A GRD SAR data, accessible via the Google Earth Engine (GEE) cloud platform. Three polarization descriptors were introduced: θc (pseudo-scattering type parameter), Hc (pseudo-scattering entropy parameter), and mc (co-polar purity parameter). Using an unsupervised clustering framework, the maize-growing area was classified into several scattering mechanism groups, and the growth characteristics of the maize crop were analyzed. The results showed that throughout the maize development cycle, the parameters θc, Hc, and mc varied within the ranges of 26.82° to 42.13°, 0.48 to 0.89, and 0.32 to 0.85, respectively. During the leaf development stage, approximately 80% of the maize sampling points were concentrated in the low-to-moderate entropy scattering zone. As the plants reached the big trumpet stage, the entire cluster shifted to the high-entropy vegetation scattering zone. Finally, at maturity, over 60% of the sampling points were located in the high-entropy distribution scattering zone. This study presents an advanced analytical tool for crop management and yield estimation by utilizing precise and high-resolution spatial and temporal data on crop growth dynamics. The tool enhances the accuracy of crop growth management across different spatial and temporal conditions. [ABSTRACT FROM AUTHOR]

Because of the importance of the Central Valley of California, USA, to shorebirds along the Pacific Flyway, conservation investments have been made in the area's agricultural fields and managed wetlands. Increasingly, landowner incentive programs are being used to deliver shorebird habitat, presenting opportunities to answer remaining questions about which implementation strategies and field management practices are most effective at attracting birds. To provide management guidance for these investments, we collected and analyzed 5 years of data (2014–2018) on shorebird abundance in flooded rice fields enrolled in a dynamic habitat incentive program. The program incentivized flooding in fallow and post‐harvest rice fields in seasons when habitat is relatively sparse, specifically the early fall and late spring. Across nearly 9,000 field observations over 5 years, we explored the relationship between abundance and density (birds/ha) of shorebirds and vegetation cover, soil clay, landscape‐level flooding, and local flood timing, duration, and depth. We observed more shorebirds in fields that were approximately 50% flooded, had water depths of 5–10 cm, and had minimal rice straw or stubble cover, with strong or very strong evidence for each of these relationships. We found that the timing of habitat provisioning was important, with moderate evidence that earlier fall flooding and strong evidence that the duration of fall flooding was associated with higher shorebird density. We observed lower shorebird densities in locations with ample flooded rice habitat in surrounding areas, potentially because shorebirds spread out across the landscape. We found very strong evidence that flooding consistency, either at a site that was continually flooded over many months or a site that had been flooded in previous years, was associated with higher shorebird density. Soil clay content was associated with decreased observed shorebird density, potentially through its influence on the ability of shorebirds to forage for invertebrate prey. These results suggest best practices for shorebird habitat creation in agricultural landscapes, providing important information for conservation and population recovery. [ABSTRACT FROM AUTHOR]

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Irrigation management is essential for addressing global food security challenges under changing climate. This review discusses the integration of advanced irrigation technologies and their roles in enhancing water use efficiency and managing energy demands within agricultural systems. High-efficiency irrigation systems, such as drip and sprinkler systems, have significant potential to reduce water use and increase crop yields. However, their adoption varies worldwide, and the efficiency of existing irrigation practices often remains inadequate, resulting in substantial water losses due to outdated management practices. Emerging technologies and innovative irrigation strategies, including precision agriculture and advanced crop models, provide promising pathways for improving irrigation efficiency. Nonetheless, the widespread integration of these technologies is hindered by high costs, the need for technical expertise, and challenges in adapting existing agricultural systems to new methodologies. Irrigation systems can have substantial energy requirements, particularly those dependent on groundwater. The exploration of the water-environment-energy-food (WEEF) nexus illustrates the importance of a balanced approach to resource management, which is crucial for achieving sustainable agricultural outcomes. Future research should include lowering barriers to technology adoption, enhancing data utilization for precision irrigation, promoting integrated management strategies within the WEEF framework, and strengthening policy support for sustainable practices. This review proposes a multidisciplinary approach to irrigation management that includes technological innovation, strategic policy development, and global cooperation to secure sustainable agricultural practices and ensure global food supply resilience in the face of climate change. [ABSTRACT FROM AUTHOR]

Daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote-sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, and so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies used to retrieve Td in almond trees with different production systems and water statuses. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th –TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo), and potential evapotranspiration (ETp). These approaches were first evaluated with in situ sap flow (T –SF) data and were then applied to the Th –TSEB. Daily T –SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T –SF and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water-stressed trees. However, the daily upscaling approaches applied in the TSEB (Td –TSEB) failed to detect differences between production systems. The lack of sensibility of Th –TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The use of ETp as a reference variable could address this issue as it incorporates various aerodynamic and radiative properties associated with different canopy architectures that influence the daily Th –SF pattern. However, more accurate ETp estimates or more advanced ETp models are needed. [ABSTRACT FROM AUTHOR]

The depth and width of drip infiltration play a critical role in designing effective irrigation strategies. However, existing models primarily focus on continuous irrigation and fail to predict wetting patterns under intermittent drip irrigation. This study developed an infiltration model to estimate soil moisture depth and width under intermittent drip irrigation and identified strategies that enhance effective water storage. Indoor soil box simulations were conducted, with continuous drip irrigation as the control. Results showed that intermittent irrigation increased infiltration width and reduced depth, maximizing water storage efficiency. We recommend adopting an intermittent irrigation system with 1.5 h of irrigation followed by a 0.5 h interval, repeated four times. This system increased effective water storage by up to 16.23% compared to continuous irrigation. The proposed method is suitable for sandy loam farmland in southern Xinjiang and can significantly improve water use efficiency in arid regions. [ABSTRACT FROM AUTHOR]

As water scarcity is worsened by drought and climate change, there is more interest in efficient management of urban irrigation, requiring understanding of the drivers of evapotranspiration (ET) and the role of irrigation inputs. We developed and validated a method to accurately measure ET of turfgrass lawns in contrasting climates using portable static chambers. We made in situ measurements of ET and irrigation inputs in lawns across three metropolitan areas in the United States with varying climatic conditions, water availability, and water conservation policies: Salt Lake Valley, Utah; San Fernando Valley, California; and Tallahassee, Florida. In full sun, mean daily ET estimates (ETsun) were 0.7 ± 0.4 mm day−1 in Tallahassee, 1.6 ± 0.8 mm day−1 in Los Angeles, and 3.3 ± 1.1 mm day−1 in Salt Lake Valley. In the shade, daily ET estimates (ETshade) were two to three times lower. In all three regions, ET was primarily driven by solar radiation (I0) and atmospheric vapor pressure deficit (D). Across the cities, irrigation rates were a key driver of ET, along with I0 and D. Daily irrigation ranged from 0 mm day−1 in Tallahassee (most were unirrigated) to 1.9 ± 1.2 mm day−1 in Los Angeles and 5.1 ± 2.9 mm day−1 in Salt Lake Valley. ET increased linearly with irrigation up to ~3 mm day−1, after which ET remained relatively constant despite irrigation increases. Our results highlight the importance of accounting for nonlinear responses and shading effects on ET in developing accurate irrigation recommendations. [ABSTRACT FROM AUTHOR]

A multi-season research trial entitled 'crop residue management effects on yield and water productivity of summer mung bean (Vigna radiata L.) under different irrigation regimes in Indian Punjab' was conducted at Punjab Agricultural University (PAU), Regional Research Station (RRS), Bathinda, during rabi 2020 and 2021. The field experiment was conducted in a split-plot layout with nine treatment combinations and replicated thrice. The treatments consisted of T1 (no wheat residue along with tillage), T2 (leftover wheat residue with zero tillage), and T3 (incorporated wheat residue along with tillage) in main plots and irrigation regimes viz., I1 (vegetative growth and flowering stage), I2 (vegetative growth, flowering, and pod filling stage) and I3 (vegetative growth, flowering, pod formation and pod filling stage) in sub-plots, respectively. The growth and yield attributing characters were significantly higher under T3 than T1 but statistically at par with T2 during both years. An increase of 24.1% and 19.0% in grain yield was found in residue incorporation (T3) and residue retention (T2) over residue removal (T1), respectively. Maximum crop and irrigation water productivity was observed under T3 due to reduced water use and increased yield. Among the irrigation regimes, the I3 recorded significantly higher grain yield (0.70 and 0.79 t ha− 1) than I1. It was at par with I2 during both years due to higher irrigation frequency at the pod formation and pod filling stage. Crop water productivity (CWP) was higher under I3, whereas irrigation water productivity (IWP) was higher under I1 during both years. Additional irrigation at the pod-filling stage increased the grain yield by 36.5%, and two additional irrigations at the pod-formation and pod-filling stage further increased yield by 46.2% compared to only two irrigations at the vegetative and flowering stages. The treatment combinations of T2I2 and T3I2 outperformed T1I3 in terms of growth and yield attributing characters viz. plant height, dry matter accumulation (DMA), leaf area index (LAI), pods plant− 1, seeds pod− 1, and 1000-seed weight, which resulted in higher grain yield in these treatment combinations over T1I3. Applying crop residue can help minimize water use and increase crop water productivity. So, retaining crop residue in summer mung bean resulted in saving irrigation water due to lesser evapotranspiration from the soil surface. [ABSTRACT FROM AUTHOR]

Numericalmodels of crop response to irrigation and weather forecasts with internet access should be fully utilized in modern irrigation management. In this respect, we developed a new numerical scheme to optimize irrigation depth that maximizes net income over each irrigation interval. The scheme applies volumetric water prices to inspire farmers to save water, and it provides growers with real-time estimates of irrigation depth and net income over the growing season. To evaluate this scheme, we carried out a field experiment for groundnut (Arachis hypogaea L.) grown in a sandy field of the Arid Land Research Center (ALRC), Tottori University, Japan. Two treatments were established to compare the net income of the proposed scheme with that of an automated irrigation system. Results showed that although the proposed scheme gave a larger amount of seasonal irrigation water 28%, it achieved 2.18 times of net income owing to 51% higher yield compared to results of the automated irrigation system. The accuracy of rainfall forecast had little effect on the scheme outputs, where the root mean square error (RMSE) between observed and forecasted rainfall was 4.63 mm. By utilizing numerical simulation information of the soil-plant-atmosphere system into the proposed scheme, it would be a more costeffective tool for optimizing irrigation depths than automated irrigation systems. [ABSTRACT FROM AUTHOR]

In the context of global warming, rising air temperatures are increasing evapotranspiration ( ET c ) in all agricultural crops, including rice, a staple food worldwide. Simultaneously, the occurrence of droughts is reducing water availability, affecting traditional irrigation methods for rice cultivation (flood irrigation). The objective of this study was to determine ET c (water use) and yield performance in rice crop under different irrigation regimes: treatments with continuous flood irrigation (CF) and irrigations with alternating wetting and drying ( A W D 5 , A W D 10 , and A W D 20 ) in an experimental area in INIA–Vista Florida. Water balance, rice physiological data, and yield were measured in the field, and local weather data and thermal and multispectral images were collected with a meteorological station and a UAV (a total of 13 flights). ET c values obtained by applying the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) energy balance model ranged from 2.4 to 8.9 mm d−1 for the AWD and CF irrigation regimes. In addition, ET c was estimated by a water balance using the AquaCrop model, previously parameterized with RGB image data and field weather data, soil, irrigation water, and crops, obtaining values between 4.3 and 7.1 mm d−1 for the AWD and CF irrigation regimes. The results indicated that AWD irrigation allows for water savings of 27 to 28%, although it entails a yield reduction of from 2 to 15%, which translates into an increase in water use efficiency (WUE) of from 18 to 36%, allowing for optimizing water use and improving irrigation management. [ABSTRACT FROM AUTHOR]

Groundwater recharge can greatly contribute to the crop growth in farmland for the sustainable development of regional production in modern agriculture. It is crucial to precisely quantify the rational utilization of groundwater sources. Among them, groundwater recharge can be broadly classified into empirical and mechanistic models in recent years. However, some limitations are still remained in practical application, due to the complexity and highly nonlinear of groundwater recharge. In this study, a series of experiments were conducted on the winter wheat under different groundwater levels and irrigation treatments using 24 clustered large-scale lysimeters. The AquaCrop model was calibrated and validated using the soil moisture content, canopy coverage, biomass, and grain yield of winter wheat as evaluation indicators. The calibrated AquaCrop model was then utilized to simulate the growth and development of winter wheat, as well as the soil water dynamics under varying irrigation treatments and groundwater depths. An estimation model was proposed for the groundwater recharge in the period of winter wheat growth. Thereby, the critical groundwater levels were determined for the different growth stages, and the threshold depth of water table suitable for winter wheat growth. Results showed that: 1) The AquaCrop model was performed best on the growth and development of winter wheat under different irrigation treatments and groundwater levels. Simultaneously, the better performance was achieved in the statistical parameters between the simulated and measured values of soil water content, canopy coverage, biomass, and grain yield during the growth period, with the determination coefficient (R²)≥0.8, the relative error (RE) and the normalized root mean square error (NRMSE) are both＜16%. 2) The validated AquaCrop model was employed to simulate the growth of winter wheat under 52 scenarios of groundwater depth and irrigation treatments. Subsequently, the nonlinear regressions of soil water storage - groundwater recharge intensity and groundwater depth - soil water storage were fitted during the growth period of winter wheat. The groundwater recharge intensity was calculated to compare with the measured values for verification. The statistical parameters fell well within the acceptable error range of the model, such as R²≥0.873, RE≤9.22%, RMSE≤0.316 mm/d and NRMSE≤11.89%. 3) The critical tables of groundwater were calculated in different growth stages of winter wheat under various irrigation treatments. The critical tables of groundwater were 3.28, 3.36 and 3.54m, respectively, for the winter wheat during the seedling, frozen and reviving-jointing stages under irrigation. Furthermore, the critical table of groundwater was 3.38 m under the sufficient irrigation treatment in the whole growth period. There was the various behavior in the different growth periods of winter wheat under the insufficient irrigation treatments. In general, the critical table of groundwater decreased with the increasing irrigation amount. The optimal threshold water table was ranged from 2.0 to 2.5 m for the winter wheat, according to the relationship between grain yields and groundwater levels under 52 simulated scenarios. Therefore, the yield and water use efficiency (WUE) of winter wheat were simultaneously reached their optimal levels under the insufficient irrigation treatment (at reviving and filling stages), which were 8.848 t/hm² and 2.17 to 2.43 kg/m³, respectively. The findings can also provide the technical support for the accurate assessments of groundwater contribution for the precision irrigation and decision-making management. making management. [ABSTRACT FROM AUTHOR]

In general, young plants in the establishment phase demonstrate sensitivity to changes in environmental conditions, especially regarding water availability. The effects of the seasonality of biophysical processes on plant physiology can trigger differential responses, even within the same region, making it necessary to conduct studies that characterize the physiological performance of the species at different spatial and temporal scales, making it possible to understand their needs and growth limits under water stress conditions. This paper aimed to evaluate the growth, gas exchange and Chl a fluorescence in ipê-rosa seedlings subjected to levels of water replacement (LWRs) of 100, 75, 50 and 25% in a greenhouse. The morphometric variables of plant height, diameter at stem height, numbers of leaves and leaflets, root length and volume, plant dry mass and leaf area were evaluated. The potential evapotranspiration of seedlings (ETc) was obtained using direct weighing, considering the water replacement of 100% of the mass variation between subsequent days as a reference; the cultivation coefficients (kc) were obtained using the ratio between ETc and the reference evapotranspiration (ETo) obtained by the Penman–Monteith FAO-56 method. Biomass and evapotranspiration data were combined to determine water sensitivity. Diurnal fluxes of gas exchange (net photosynthesis rate, transpiration rate, stomatal conductance, internal and atmospheric carbon ratio, water use efficiency and leaf temperature) and Chl a fluorescence (Fv/Fm, ΦPSII, ETR, Fv′/Fm′, NPQ and qL) were evaluated. Water restriction caused reductions of 90.9 and 84.7% in the increase in height and diameter of seedlings subjected to 25% water replacement when compared to seedlings with 100% water replacement. In comparison, biomass accumulation was reduced by 96.9%. The kc values increased throughout the seedling production cycle, ranging from 0.59 to 2.86. Maximum water sensitivity occurred at 50% water replacement, with Ky = 1.62. Maximum carbon assimilation rates occurred in the morning, ranging from 6.11 to 12.50 µmol m−2 s−1. Ipê-rosa seedlings regulate the physiology of growth, gas exchange and Chl a fluorescence depending on the amount of water available, and only 25% of the water replacement in the substrate allows the seedlings to survive. [ABSTRACT FROM AUTHOR]

To address the complexity and high computational burden in the design of drip irrigation networks, the Jaya algorithm is utilized to study factors affecting project costs, including equipment and pipeline depreciation and the operation and management costs of the irrigation area. A mathematical model of synchronization optimal design of pipe layout and pipe diameter selection in a drip irrigation network system with constraints on pipe diameter, flow velocity, and pipe pressure is established. Using an irrigation district in Xinjiang, China, as an example, the Jaya algorithm optimization design program was run independently 50 times, and the relative deviation of each optimization result from the optimal solution was calculated. The results show that the annual cost per unit area o is reduced to 635.99 RMB/hm2, a 25.34% reduction compared to the original engineering program, and the investment-saving effect is obvious. The relative deviation is controlled within 3%, which shows that the algorithm has stable convergence performance and can meet the requirements of actual engineering design. The Jaya algorithm eliminates the need for parameter tuning, and it excels in cost savings, algorithm stability, and computational accuracy, making it an effective method for the single-objective optimization design of drip irrigation networks. [ABSTRACT FROM AUTHOR]

Super high-density (SHD) planting systems are very efficient in terms of production and water use. In these orchards, water-saving irrigation strategies are used precisely to keep the best sustainability compared to traditional orchards. With agro-climatic and eco-physiological parameter monitoring, the SHD planting system has become even more efficient. SHD orchards, however, could also be more so affected by other pests and diseases than traditional systems, but field responses are still unknown when olive trees are grown in SHD groves. The goal of this two-year field research was to investigate the seasonal changes of the phytosanitary status of 'Arbosana' grown in an SHD orchard under both regulated deficit (RDI) and full irrigation regimes (FI). This study investigated the influence of the two different irrigation regimes on the infections of three olive tree key diseases: cercosporiosis (Pseudocercospora cladosporioides), cycloconium (Fusicladium oleagineum), and olive knot (Pseudomonas savastanoi pv. savastanoi). RDI significantly reduced the severity of cercosporiosis in 2020 compared to FI but not in 2021. Cycloconium was observed only as a latent infection during the two studied years and olive knot was not influenced by irrigation but only by weather conditions. These findings suggest that irrigation management can play a key role in controlling cercosporiosis effectively in SHD olive orchards, but also that weather conditions have an even higher impact on the tree key diseases. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is an important component of surface energy balance and a key process of hydrological cycle. Continuous and accurate estimation of regional ET is meaningful for water management, agricultural production, and climate change adaptation. Remote sensing (RS) technique is of important meaning for estimating ET on regional scale. In this study, a new method is developed to integrate the RS information and meteorological data based on the decouple model which is deduced from Penman–Monteith (PM) model. Firstly, a parameterization method for decoupling factor (Ω) which is key parameter in the decouple model and could reflect the coupling relationship between the land surface and atmosphere systems is introduced. Subsequently, the decouple model is applied to inverse regional ET in Beijing City and nearby region, from 1st, May, 2013 to 31th, October, 2020. Thirdly, the inversed daily ET values are evaluated based on the measured data at Huailai station and in Badaling Forest Farm. The results show that the changing trend of estimated ET and measured ET are basically the similar. The bias value is −0.12 mm d−1, the RSME value is 0.66 mm d−1, and the correlation coefficient is 0.52. Finally, the spatiotemporal trend of water consumption in study area is analysed based on the ET estimation results. The month with the largest water consumption in 2013 is July with the quantity of 0.92 billion m3, accounting for about 22% of the regional total water consumption in growing season. The regions with high ET values agree well with the regions of high soil moisture and high air humidity as well as high biomass. These results suggest that the decouple model is with great potential to generate regional daily ET products and to support irrigation management. [ABSTRACT FROM AUTHOR]

The increase in crop yield can be primarily attributed to the combined effect of genetic advancements, as well as increased contributions from nitrogen (N) and water. The accumulation of dry matter plays a crucial role in determining grain yield in winter wheat. The current study aimed to better understand the source‐sink dynamics, analyse the dry matter transport (DMT) before and after anthesis and calculate its ratio to grain yield. In this experiment, eight main cultivars of winter wheat that have been widely cultivated in Shaanxi Province since the 1940s were selected as planting material. Field examinations were conducted using three levels of both irrigation and N. The yield‐related parameters, dry matter accumulation, dry matter distribution, DMT and DMT efficiency were measured. The results showed that irrigation prolonged the time of dry matter accumulation, and the application of N fertiliser increased the rate of dry matter accumulation. The analysis of the dynamic characteristic parameters of dry matter in winter wheat showed that irrigation and N had a significant impact on rate of dry matter accumulation. The proportion of stems, leaves and spikes of new varieties increased significantly (p < 0.05), which increased by 56.67%–69.7%, 13.26%–18.07% and 15.78%–28.26%, respectively, with the varietal improvement. The DMT efficiency increased with varietal improvement and also with increased irrigation and N application. The response of irrigation treatment to DMT and dry matter was more significant. In addition, the irrigation treatment had a higher effect on the DMT efficiency of vegetative organs after anthesis. The logistic equation analysis revealed that water stress accelerated the fulfilment of maximum daily temperature (Tmax), while both the maximum growth rate (Gmax) and dry matter weight (Wmax) decreased as water stress increased. There was a positive linear relationship between dry matter accumulation after anthesis and grain yield. The structural equation model showed that varieties, N application and irrigation had significant positive effects on DMT, post‐anthesis dry matter and grain yield, while irrigation had significant negative effects on DMT efficiency. The accumulation of dry matter in winter wheat after anthesis showed a significant increase with the succession of varieties. The combination of moderate deficit irrigation and fertilisation improved transportation and dry matter accumulation after anthesis in winter wheat, thereby enhancing its production capacity. [ABSTRACT FROM AUTHOR]

Water shortages in arid regions present challenges in administering water and requires robust water accounting. In southeast Idaho, the Eastern Snake Plain Aquifer (ESPA) supports an important agricultural sector. Due to connectivity between surface and groundwater in the ESPA, quantifying aquifer recharge is also important. Historically, leaching from excess surface irrigation supported incidental recharge to the ESPA, but more efficient irrigation techniques reduced incidental recharge. This paper outlines a deep infiltration (DI) model developed to evaluate infiltration losses from different irrigation practices and soil types. Twelve scenarios were created to simulate an alfalfa growing season under varying climatic and soil conditions. Under some scenarios, modeled infiltration losses increased by 10%–20% coincident with increased application efficiency. The concept of consumptive use efficiency (CUE) is introduced to quantify the proportion of irrigation beneficially used by crops. The model results show that CUE decreased with increasing application efficiency and suggest CUE could be improved 8%–10% for well-drained loamy soils; clay loam soils showed little opportunity for improvement. The results indicate that more efficient irrigation application techniques may increase DI loss if irrigation schedules do not explicitly include soil water storage for the entire rooting zone. These results indicate that in conditions where losses from DI can be reduced, improving water use efficiency depends on precision irrigation scheduling linked to infiltration rates. This model provides a practical method by which infiltration losses from irrigated lands can be estimated. Considering site-specific infiltration would facilitate and prioritize investments meant to improve water use efficiency. Practical Applications: Irrigation in arid regions usually entails some degree of inefficiency, partly due to water lost through deep percolation. Although some drainage loss occurs under most real-world conditions, it is difficult to measure actual loss. A lack of real information hampers precise estimates and increases uncertainty about actual conveyance and irrigation efficiency. On the other hand, soil infiltration models can utilize existing soil survey maps and guide prioritization and incentives to encourage best practices. This study demonstrates a straightforward application of a soil water drainage model combined with regional soil maps, as could be implemented by water managers. The model was calibrated using observations of crop water use, irrigation application, and soil water content from an irrigated alfalfa field. The calibrated model was then used to describe potential drainage rates from common soil types and weather conditions in southeastern Idaho. The model results indicate that efficient irrigation practices may be best suited to well drained soils, and fewer benefits were observed in poorly drained soils. Even a relatively simple application of this model highlights conditions that are best suited to particular efficiency strategies and help prioritize limited resources for developing best practices for water conservation. [ABSTRACT FROM AUTHOR]

qdOne of the most important limitations of cultivation in the Sistan plain is soil salinity. To investigate the salinity status using remote sensing in Sistan Plain, Landsat 8 (LC08- LOI/TIRS) satellite images were used in April, August and November of 2017 and April 2018. To convert radiance data, the initial correction related to voltage change to digital number (DN) to convert radiance data was done by sensor calibration file as well as data radiometric correction using flat area method in ENVI 5.1 software. To determine the soil sampling points, first draw a 2x2 km grid and then by referring to the area and checking the sampling location, 312 soil samples were taken and the values of Electrical Conductivity (EC), Sodium Adsorption ratio (SAR) and texture in them were measured. By secondary processing, extracting the spectral features of satellite images and using several algorithms and indices, a salinity map was prepared for the surface soils of the region in four periods. The results of the remote sensing investigation showed that surface soil salinity in the region is a dynamic phenomenon and has significant changes with the changes of season, rainfall, irrigation and land management. The results obtained from the interpretation of satellite images showed that time, rainfall events of the planting season and water and soil management have a significant effect on soil salinity and the areas of lands with different salinity. The extent of soils with high salinity increased in the summer season, but in April 2018 (MBE=0.98, NRMSE=17.56%, R²=0.69) which coincided with the sampling due to the occurrence of rains and floods in these areas, this extent decreased. [ABSTRACT FROM AUTHOR]

With the advancement of agricultural technology, most crop cultivation adopts water-saving techniques to improve nutrient utilization efficiency. However, limited research has been carried out on the applicability of water-saving techniques for summer maize in the Shandong Province, and it is necessary to assess the risk of nutrient loss in farmland when applying these technologies. This study investigated the distribution of nitrogen and phosphorus under different irrigation methods and planting patterns through soil and water samples. It included sprinkler irrigation (SI), drip irrigation (DI), and subsurface irrigation (SUBI). Different planting patterns, i.e., monoculture (MP) and intercropping pattern (IP), were also selected in the SI zones. The results show variations in soil nitrogen distribution within the layers between 0.9 and 4.5 m, with a pronounced trend of NO 3 − -N accumulating in deeper layers in the SI zone. Under SI conditions, the IP effectively reduces the nutrient accumulation around the shallow root zone while controlling the accumulation of nitrogen in deep layers. The Olsen-P accumulation in each zone would increase after the accumulation ratio decreased. Compared with MP, the depth interval of the accumulation ratio mutation was shallower in the IP. The trend of NO 3 − -N accumulation in deep layers is consistent with that of nitrogen concentration in groundwater. Phosphorus that is accumulated in the deep layers is not easily leached into groundwater. In conclusion, these findings can provide basic information for irrigation management in existing cropping systems. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: The study explored the relationship between irrigation practices, water availability, and soil fertility in relation to crop yield. The investigation analyzed three distinct irrigation scenarios, namely full irrigation, deficit irrigation, and rain fed agriculture. The primary objective of the study was to evaluate the correlation between irrigation practices and soil fertility. To achieve this, the study incorporated different soil fertility levels, with high levels representing unlimited fertility for both full and deficit irrigation, and low levels corresponding to rain fed conditions. This design is primarily used to isolate the effects of irrigation practices on crop yields under a variety of fertility scenarios. The study also looks into how to achieve sustainable water management in the agricultural sector. METHODS: Aqua-crop, a computerized model, was utilized mimic real-life crop harvests. The aqua crop model was used to simulate crop yield in response to water availability. The calibration of the model involved utilizing data on various crop growth parameters, including soil fertility, crop canopy cover, evapotranspiration, soil water movement, crop yield and harvest index percentage. This innovative study utilizes aqua-crop to analyze the impact of irrigation methods on crop yields under controlled settings, effectively isolating irrigation influences from soil discrepancies. This approach is well-suited for studying sustainable water management strategies in agriculture, a pressing concern in light of worldwide water water scarcity. FINDINGS: Aqua-crop simulations revealed that consistent irrigation with a full irrigation system and high efficiency (70 percent) resulted in high yields. The simulated yields (8.48 to 10.04 tons per hectare) were significantly higher than farmers' actual yields (3.86 to 4.74 tons per hectare). Discrepancies between farmer irrigation methods and the model's assumption of uniform water application are the probable cause of the variation, underscoring the significance of considering real-world intricacies in the interpretation of model outcomes. The observed yield differences despite similar irrigation systems indicate the potential impact of unaccounted for factors such as soil type variations and real-world farmer practices (e.g., fertilization). Nevertheless, a substantial R-squared value of 0.85 suggests a robust association between simulated and observed yields, suggesting that aqua-crop can be valuable in comprehending overall irrigation-yield connections. Emphasis is placed on considering real-world complexities to achieve optimal crop yield. Aqua-crop simulations analyzed the correlation between irrigation and water use efficiency. Although full irrigation resulted in the highest simulated yields, deficit irrigation enhanced evapotranspiration water productivity. This seemingly contradictory finding can be explained by diminishing returns: deficit irrigation may result in slightly lower yields but higher water efficiency, highlighting the importance of considering both yield and water use efficiency when making long-term irrigation decisions. has highlighted the disparity between projected and actual crop yields, underscoring the significance of incorporating practical factors into the simulation of irrigation techniques. This finding holds particular relevance in areas where water resources are limited. CONCLUSION: The Food Agriculture Organization's aqua-crop is a useful tool for farmers who have limited access to water. Aqua-crop is a computer-based model that replicates the growth of crops in different irrigation scenarios. It provides farmers with the opportunity to explore the correlation between water usage and crop yield. By doing so, they can determine the most effective irrigation strategies that optimize harvest while minimizing water consumption. This aspect holds particular significance in regions facing water scarcity. [ABSTRACT FROM AUTHOR]

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The Crop Water Stress Index (CWSI), a pivotal indicator derived from canopy temperature, plays a crucial role in irrigation scheduling for water conservation in agriculture. This study focuses on determining CWSI (by empirical method) for wheat crops in the semi-arid region of western Uttar Pradesh, India, subjected to varying irrigation treatments across two cropping seasons (2021–2022 and 2022–2023). The aim is to investigate further the potential of four machine learning (ML) models—support vector regression (SVR), random forest regression (RFR), artificial neural network (ANN), and multiple linear regression (MLR) to predict CWSI. The ML models were assessed based on determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE) under diverse scenarios created from eight distinct input combinations of six variables: air temperature (Ta), canopy temperature (Tc), vapor pressure deficit (VPD), net solar radiation (Rn), wind speed (U), and soil moisture depletion (SD). SVR emerges as the top-performing model, showcasing superior results over ANN, RFR, and MLR. The most effective input combination for SVR includes Tc, Ta, VPD, Rn, and U (R2 = 0.997, MAE = 0.901%, RMSE = 2.223%). Meanwhile, both ANN and MLR achieve optimal results with input combinations involving Tc, Ta, VPD, Rn, U, and SD (R2 = 0.992, MAE = 2.031%, RMSE = 3.705%; R2 = 0.759, MAE = 13.95%, RMSE = 19.98%, respectively). For RFR, the ideal input combination comprises Tc, Ta, VPD, and U (R2 = 0.951, MAE = 5.023%, RMSE = 9.012%). The study highlights the considerable promise of ML models in predicting CWSI, proposing their future application in integration into an irrigation decision support system (IDSS) for crop stress mitigation and efficient water management in agriculture. [ABSTRACT FROM AUTHOR]

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Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND AND OBJECTIVES: The study explored the relationship between irrigation practices, water availability, and soil fertility in relation to crop yield. The investigation analyzed three distinct irrigation scenarios, namely full irrigation, deficit irrigation, and rain fed agriculture. The primary objective of the study was to evaluate the correlation between irrigation practices and soil fertility. To achieve this, the study incorporated different soil fertility levels, with high levels representing unlimited fertility for both full and deficit irrigation, and low levels corresponding to rain fed conditions. This design is primarily used to isolate the effects of irrigation practices on crop yields under a variety of fertility scenarios. The study also looks into how to achieve sustainable water management in the agricultural sector.METHODS: Aqua-crop, a computerized model, was utilized mimic real-life crop harvests. The aqua crop model was used to simulate crop yield in response to water availability. The calibration of the model involved utilizing data on various crop growth parameters, including soil fertility, crop canopy cover, evapotranspiration, soil water movement, crop yield and harvest index percentage. This innovative study utilizes aqua-crop to analyze the impact of irrigation methods on crop yields under controlled settings, effectively isolating irrigation influences from soil discrepancies. This approach is well-suited for studying sustainable water management strategies in agriculture, a pressing concern in light of worldwide water water scarcity.FINDING: Aqua-crop simulations revealed that consistent irrigation with a full irrigation system and high efficiency (70 percent) resulted in high yields. The simulated yields (8.48 to 10.04 tons per hectare) were significantly higher than farmers' actual yields (3.86 to 4.74 tons per hectare). Discrepancies between farmer irrigation methods and the model's assumption of uniform water application are the probable cause of the variation, underscoring the significance of considering real-world intricacies in the interpretation of model outcomes. The observed yield differences despite similar irrigation systems indicate the potential impact of unaccounted for factors such as soil type variations and real-world farmer practices (e.g., fertilization). Nevertheless, a substantial R-squared value of 0.85 suggests a robust association between simulated and observed yields, suggesting that aqua-crop can be valuable in comprehending overall irrigation-yield connections. Emphasis is placed on considering real-world complexities to achieve optimal crop yield. Aqua-crop simulations analyzed the correlation between irrigation and water use efficiency. Although full irrigation resulted in the highest simulated yields, deficit irrigation enhanced evapotranspiration water productivity. This seemingly contradictory finding can be explained by diminishing returns: deficit irrigation may result in slightly lower yields but higher water efficiency, highlighting the importance of considering both yield and water use efficiency when making long-term irrigation decisions. has highlighted the disparity between projected and actual crop yields, underscoring the significance of incorporating practical factors into the simulation of irrigation techniques. This finding holds particular relevance in areas where water resources are limited.CONCLUSION: The Food Agriculture Organization’s aqua-crop is a useful tool for farmers who have limited access to water. Aqua-crop is a computer-based model that replicates the growth of crops in different irrigation scenarios. It provides farmers with the opportunity to explore the correlation between water usage and crop yield. By doing so, they can determine the most effective irrigation strategies that optimize harvest while minimizing water consumption. This aspect holds particular significance in regions facing water scarcity.

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Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND: This study explored the mechanism of irrigation and nitrogen (N) coupling on spring maize yield and soil greenhouse gas (GHG) emissions, with the objective of achieving water saving, high yield and emission reduction. Field experiments were conducted to analyze the effects of multiple irrigation and N management strategies on GHG emissions and to determine the optimal balance between GHG, water conservation and grain yield. The experiments were conducted on spring maize with three irrigation levels (low, IL; medium, IM; and high, IH) and 4 N application levels (N40, N80, N120 and N160 kg N ha−1). RESULTS: The IL treatment exhibited the lowest N2O and CO2 emission fluxes and the lowest CH4 uptake fluxes. The N40 treatment exhibited the lowest N2O and CO2 emission fluxes and the highest CH4 uptake flux. Significant positive correlations were observed among N2O and CO2 emission fluxes, CH4 uptake fluxes, and soil moisture and inorganic N content. Maize yield initially increased and then decreased with rising levels of irrigation and N management. By employing the TOPSIS method to assess yield and greenhouse effects, we identified the IMN120 treatment as optimal given that this treatment achieved the highest yield (14 686.26 kg ha−1) and water use efficiency (3.51 kg m−3) while maintaining relatively low global warming potential (573.30 kg CO2 eq ∙ ha−1) and GHG intensity (0.0390 kg CO2 eq ∙ kg−1). CONCLUSION: Irrigation optimization and N management are key to reducing GHG emissions, enhancing yield, and promoting both the sustainable development of agriculture and environmental protection. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Farmers in North Carolina are turning to irrigation to reduce the impacts of droughts and rainfall variability on agricultural production. Droughts, rainfall variability, and the increasing demand for food, feed, fiber, and fuel necessitate the urgent need to provide North Carolina farmers with tools to improve irrigation management and maximize water productivity. This is only possible by understanding the current status of irrigated agriculture in the state and investigating its potential weaknesses and opportunities. Thus, the objective of this study was to perform a comprehensive analysis of the current state of irrigation management in North Carolina based on 15-year data from the Irrigation and Water Management Survey by the United States Department of Agriculture–National Agricultural Statistics Service (USDA-NASS). The results indicated a reduction in irrigation acres in the state. Also, most farms in the state have shifted to efficient sprinkler irrigation systems from gravity-fed surface irrigation systems. However, many farms in North Carolina still rely on traditional irrigation scheduling methods, such as examining crop conditions and the feel of soil in deciding when to irrigate. Hence, there are opportunities for enhancing the adoption of advanced technologies like soil moisture sensors and weather data to optimize irrigation schedules for improving water efficiency and crop production. Precision techniques and data-based solutions empower farmers to make informed, real-time decisions, optimizing water use and resource allocation to match the changing environmental conditions. The insights from this study provide valuable information for policymakers, extension services, and farmers to make informed decisions to optimize agricultural productivity and conserve water resources.

The injudicious use of water and fertilizer to maximize crop yield not only leads to environmental pollution, but also causes enormous economic losses. For this reason, we investigated the effect of nitrogen (N) (N0 (0), N60 (60 kg ha−1), and N120 (120 kg ha−1)) at different irrigation levels (I0 (0), I1200 (budding 600 m3 ha−1 + kernel 600 m3 ha−1), and I1800 (budding 900 m3 ha−1 + kernel 900 m3 ha−1)) on oilseed flax in the Loess Plateau of China in 2019 and 2020. The objective was to establish appropriate irrigation and fertilizer management strategies that enhance the grain yield (GY) of oilseed flax and maximize water and N productivity. The results demonstrated that irrigation and N application and their coupling effects promoted dry matter accumulation (DMA) and non-structural carbohydrate (NSC) synthesis, and increased the GY of oilseed flax. The contents of NSC in various organs of flax were closely related to grain yield and yield components. Higher NSC in stems was conducive to increased sink capacity (effective capsule number per plant (EC) and thousand kernel weight (TKW)), and the coupling of irrigation and N affected GY by promoting NSC synthesis. Higher GY was obtained by the interaction of irrigation and N fertilizer, with the increase rate ranging from 15.84% to 35.40%. Additionally, in the increased yield of oilseed flax, 39.70–78.06%, 14.49–54.11%, and −10.6–24.93% were contributed by the application of irrigation and nitrogen and the interaction of irrigation and nitrogen (I × N), respectively. Irrigation was the main factor for increasing the GY of oilseed flax. In addition, different climatic conditions changed the contribution of irrigation and N and their interaction to yield increase in oilseed flax. Drought and low temperature induced soluble sugar (SS) and starch (ST) synthesis to resist an unfavorable environment, respectively. The structural equation model showed that the key factors to increasing the GY of oilseed flax by irrigation and nitrogen fertilization were the differential increases in DMA, EC, and TKW. The increases in EC and TKW were attributed to the promotion of DMA and NSC synthesis in oilseed flax organs by irrigation, nitrogen fertilization, and their coupling effects. The I1200N60 treatment obtained higher water use efficiency (WUE) and N partial factor productivity (NPFP) due to lower actual evapotranspiration (ETa) and lower N application rate. Therefore, the strategy of 1200 m3 ha−1 irrigation and 60 kg ha−1 N application is recommended for oilseed flax in semi-arid and similar areas to achieve high grain yield and efficient use of resources. [ABSTRACT FROM AUTHOR]

This study uses a triple-sensor collocation approach to evaluate the performance of small-holder irrigation schemes in the Zamra catchment of Northern Ethiopia. Crop water productivity (CWP), as an integrator of biomass production and water use, was used to compare the overall efficiencies of three types of irrigation systems: traditional and modern diversions, and dam-based irrigation water supply. Farmer-reported data often rely on observations, which can introduce human estimation and measurement errors. As a result, the evaluation of irrigation scheme performance has frequently been insufficient to fully explain crop water productivity. To overcome the challenges of using one single estimation method, we used a triple-sensor collocation approach to evaluate the efficiency of three small-scale irrigation schemes, using water productivity as an indicator. It employed three independent methods: remotely sensed data, a model-based approach, and farmer in-situ estimates to assess crop yields and water consumption. To implement the triple collocation appraisal, we first applied three independent evaluation methods, i.e., remotely sensed, model-based, and farmer in-situ estimates of crop yields and water consumption, to assess the crop water productivities of the systems. Triple-sensor collocation allows for the appraisal and comparison of estimation errors of measurement sensor systems, and enables the ranking of the estimators by their quality to represent the de-facto unknown true value, in our case: crop yields, water use, and its ratio CWP, in small-holder irrigated agriculture. The study entailed four main components: (1) collecting in-situ information and data from small-holder farmers on crop yields and water use; (2) derivation of remote sensing-based CWP from the FAO WaPOR open database and time series; (3) evaluation of biomass, crop yields and water use (evapotranspiration) using the AquaCrop model, integrating climate, soil data, and irrigation management practices; (4) performing and analysis of a categorical triple collocation analysis of the independent estimator data and performance ranking of the three sensing and small-holder irrigation systems. Maize and vegetables were used as main crops during three consecutive irrigation seasons (2017/18, 2018/19, 2019/20). Civil war prevented further field surveying, in-situ research, and data collection. The results indicate that remote sensing products are performed best in the modern and dam irrigation schemes for maize. For vegetables, AquaCrop performed best in the dam irrigation scheme. [ABSTRACT FROM AUTHOR]

Introduction: To examine the impacts of varied water and nitroge combinations on wheat yield and quality under drip irrigation in the Huang-Huai-Hai area, a field experiment was conducted over two growing seasons of winter wheat from 2019 to 2021. Methods: Traditional irrigation and fertilization methods served as the control (CK), with two nitrogen application rates set: N1 (180 kg/ha) and N2 (210 kg/ha). The irrigation schedules were differentiated by growth stages: jointing, anthesis (S2); jointing, anthesis, and filling (S3); and jointing, booting, anthesis, and filling (S4), at soil depths of 0-10 cm (M1) and 0-20 cm (M2). Results: Results indicated that compared toCK, the 3 and 4 times irrigation treatments comprehensively improved grain yield (GY) by 8.0% and 13.6% respectively, increased the average plant partial factor productivity of nitrogen fertilizer (PFPN) and irrigation use efficiency (IUE) by 57.5% and 38.2%, and 62.2% and 35.8%, respectively. The gluten content (GC) of 3 irrigationswas 1.6% higher than CK, and othermetrics such as dough tenacity (DT), softness (ST), water absorption (WAS), and gluten hardness (GH) also showed improvements. Furthermore, the contents of amylose, amylopectin, and total starch under 3 irrigations significantly increased by 9.4%, 11.4%, and 9.8%, respectively, with higher than 4 irrigations. The crude protein content and soluble sugar content in 3 irrigations rose by 6.5% and 9.8% respectively over two years. These irrigation treatments also optimized gelatinization characteristics of grains, such as breakdown viscosity (BDV), consistency peak viscosity (CPV), consistency setback viscosity (CSV), pasting temperature (PeT), and pasting time (PaT). Discussion: The study demonstrated that appropriate drip irrigation can effectively synchronize water and nitrogen supply during critical growth stages in winter wheat, ensuring robust late-stage development and efficient transfer of photosynthetic products into the grains, thus enhancing grain mass and yield. This also led to improved utilization of water and fertilizer and enhanced the nutritional and processing quality of the grain. However, excessive irrigation did not further improve grain quality. In conclusion, given the goals of saving water and fertilizer, achieving excellent yield, and ensuring high quality, the N1S3M1 treatment is recommended as an effective production management strategy in the Huang-Huai Hai area; N1S3M2 could be considered in years of water scarcity. [ABSTRACT FROM AUTHOR]

In arid regions, water scarcity, land degradation and groundwater pollution caused by excessive fertilization are the main constraints to sustainable agricultural production. Optimizing irrigation and fertilizer management regime is an effective means of improving crop water and fertilizer productivity as well as reducing negative impacts on the ecosystem. In order to investigate the effects of different irrigation and nitrogen (N) fertilizer rates on sunflower growth, yield, and water and N use efficiency, and to determine the optimal water and N management strategy, a two-year (2021 and 2022) field experiment with under-mulched drip irrigation was conducted in the Hexi Oasis area of Northwest China. The experiment design comprised three irrigation levels (W1, 55%-65% FC, where FC represents field water capacity; W2, 65%-75% FC; W3, 75% -85% FC) and three N application levels (N1, 120 kg ha-1; N2, 180 kg ha-1; N3, 240 kg ha-1), resulting in a total of nine treatments. The findings indicated that increasing irrigation and N application rates led to improvements in leaf area index (15.39%-66.14%), dry matter accumulation (11.43%-53.15%), water consumption (ET, 1.63%-42.90%) and sunflower yield (6.85%-36.42%), in comparison to the moderate water deficit and low N application (W1N1) treatment. However, excess water and N inputs did not produce greater yield gains and significantly decreased both water use efficiency (WUE) and nitrogen partial factor productivity (NPFP). Additionally, a multiple regression model was developed with ET and N application as explanatory variables and yield, WUE and NPFP as response variables. The results based on the regression model combined with spatial analysis showed that an ET range of 334.3-348.7 mm and N application rate of 160.9-175.3 kg ha-1 achieved an optimal balance between the multiple production objectives: yield, WUE and NPFP. Among the different irrigation and N management strategies we evaluated, we found that W2N2 (65%-75% FC and 180 kg N ha-1) was the most fruitful considering yield, resource use efficiency, etc. This result can serve as a theoretical reference for developing appropriate irrigation and N fertilization regimes for sunflower cultivation in the oasis agricultural area of northwest China. [ABSTRACT FROM AUTHOR]

Utilizing new irrigation techniques to introduce cultivars into paddy fields experiencing water scarcity is one way to combat water shortage and increase water productivity. To this end, this experiment was conducted as a strip plot in a randomized complete block design with three independent replications over two years (2016 and 2017) at the Rice Research Institute of Iran, Amol, Iran. Ten rice genotypes (V1 to V10) were subjected to three types of irrigation systems, including conventional Flood Irrigation (FI) and Alternate Wetting and Drying (AWD) at 10 (AWD10) and 20 (AWD20) cm below the soil surface. These results demonstrate that AWD10 and AWD20 methods reduced water consumption by 20 and 17%, respectively, compared to the conventional methods. This decreased water usage resulted in 1.4 and 0.2% yield losses compared to the conventional flood irrigation system. Moreover, milling recovery in flood irrigation (68.7%) was lower than AWD10 and AWD20 methods (69.6 and 69.8%, respectively). In conclusion, Neda, Shiroodi, and 8611 rice genotypes showed a better response to AWD irrigation, and may be considered as suitable genotypes for increasing water productivity in paddy fields. [ABSTRACT FROM AUTHOR]

This research explores the relationship between hydrological drought and agricultural drought in the Corong River Basin, focusing on the Gondang Reservoir Irrigation Area, Indonesia. By employing a Causal Time Series Regression Model, the study uncovers that agricultural drought twelve months prior has a significant impact on current agricultural drought and is influenced by current hydrological drought. Time series regression analysis reveals that 45.86% of agricultural drought is influenced by hydrological drought, with 54.14% influenced by other factors besides rainfall. Further research is needed to investigate these additional factors. These findings have practical implications, serving as a valuable index for assessing drought severity and planning mitigation actions, especially in the irrigation areas of interest. They emphasize the importance of effective irrigation management, appropriate cropping patterns, and a comprehensive understanding of the complex characteristics of drought in agricultural regions through comprehensive monitoring efforts in agricultural drought mitigation. [ABSTRACT FROM AUTHOR]

Crop growth simulation models relate the soil–water-plant-atmosphere components to estimate the development and yield of plants in different scenarios, enabling the identification of efficient irrigation strategies. The aim of this study was to calibrate crop coefficients for a common bean cultivar (IAPAR 57) and assess the AquaCrop model's efficacy in simulating crop growth under different irrigation regimes (T0 – non-irrigated, T1—fully irrigated, and T2—deficit irrigated) and sowing dates (S1—March 21, S2—April 24, and S3—August 23). Successful calibration was achieved for crop seasons with suitable temperatures to crop growth (S1 and S3). However, during periods with suboptimal temperatures (April 24 season), coupled with reduced irrigation supply (T0 and T2), the AquaCrop model did not appropriately account for the combined effects of thermal and water stresses. Despite adjustments to stress coefficients, this led to an overestimation of crop growth and yield. In long-term simulations, the model successfully replicated the variability of crop water availability over cropping seasons, reflecting the impact of precipitation variations. It recommended irrigation strategies for the study region (irrigate at depletion of 120 and 170% of readily available water for sowing on March 21 and August 24, respectively) to achieve high crop yield (> 2,769 kg ha−1) and water productivity (1,050 to 1,445 kg m−3) with minimal application depths (< 150 mm). While acknowledging the need for improvements in thermal stress calculations, the AquaCrop model demonstrates promising utility in studies and applications where water availability significantly influences crop production. [ABSTRACT FROM AUTHOR]