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Soil salinization problems are widespread in the Hetao plain, Inner Mongolia, resulting from arid climate conditions, a shallow saline water table, poor irrigation water management, and insufficient drainage. This study follows previous research aimed at evaluating crop water use and controlling the salinity build-up in the region, namely using weighing and static water table lysimeters to parameterize a water balance model aimed at the development of appropriate irrigation scheduling. Two sets of five static water table lysimeters, which fixed depths ranged from 1.25 to 2.25 m, were used over two maize crop seasons. The mechanistic HYDRUS-1D model was further used to daily predict measured data on soil water contents, boundary fluxes in the interface between the saturated and unsaturated zones, the electrical conductivity of the soil saturation paste extract (EC e), and the actual crop evapotranspiration (ET c act). The soil water balance helped quantify the combined effect of water and salinity stresses on root water uptake as well as groundwater fluxes into the rootzone. The salt balance showed that the salinity build-up was much related to irrigation and capillary fluxes, and that the autumn irrigation carried out during the non-growing season was essential for controlling soil salinity. The efficiency of the autumn irrigation much depended on groundwater depth and the amount of water applied for salt leaching, with the best results found for the lysimeters with water table depths at 2.0 and 2.25 m (85–100%) for irrigation depths ≥ 220 mm. The lysimeters with shallower water tables never showed a leaching efficiency higher than 88%. This research shows that the sustainability of irrigation in Hetao depends on finding adequate solutions for controlling the depth of the saline groundwater, minimizing capillary fluxes to the rootzone, and developing consequent approaches for autumn irrigation leaching. • Soil water contents and fluxes, EC e , and ET c act were measured using water table lysimeters. • The HYDRUS-1D model successfully simulated lysimeter data during two seasons. • The water table depth influenced the effectiveness of autumn irrigation leaching. • The leaching efficiency only increased by improving soil drainage conditions. • Reducing autumn irrigation depth (<200 mm) promoted soil salinization. [ABSTRACT FROM AUTHOR]

Citrus is one of the most valuable crops in Syria, with the largest production areas being in the coastal provinces of Tartus and Latakia, where this study was performed. A companion paper reported on the basal crop coefficients derived from the field water balance and on the performance assessment of various irrigation methods used in a citrus orchard located in the same region. That study evidenced the need for the improved management of irrigation water, mainly reducing water applications and increasing productivity, thus leading to the current research. The main objectives consisted of (i) providing a set of reliable basal (Kcb) and average (Kc) crop coefficients to be used in practice in the citrus orchards of the Syrian coastal area, while accounting for the diversity of characteristics observed; (ii) to estimate the seasonal consumptive use of typical orchards under different climate-demand and deficit-irrigation scenarios; and (iii) to assess possible water savings and related yield reductions. The previously calibrated water balance model SIMDualKc was used for these purposes. The computed Kcb values for the mid-season and average demand for water ranged from 0.52, when the plant density was low, to 0.84, when plant density was very high. The corresponding Kc values, which further reflected the impact of drip irrigation on controlling soil evaporation, were 0.72 and 0.97, respectively. Overall, the consumptive use of water was estimated to range from 867 to 1573 mm. The assessed water-saving scenarios consisted of adopting increased management-allowed depletion (MAD) thresholds relative to the p depletion fraction for no stress: MAD = 1.05, 1.10, 1.20, and 1.30 p. For trees under a very high climatic demand, water savings ranged from 12 to 34%, but the yield losses induced by the water deficits ranged from 8 to 48%. Although the selection of optimal strategies should be based upon economic terms, these may only be used when the Syrian economy recovers from civil war and the current crisis. The present results show the feasibility of adopting such MAD thresholds for building an irrigation management platform. The data provided by the current study are valuable because they can be efficiently used to support of the irrigation management of Syrian citrus production systems. [ABSTRACT FROM AUTHOR]

The model HYDRUS-1D was used to simulate soil water dynamics of full and deficit irrigated maize grown under a rainout shelter during two crop seasons. Four irrigation treatments were established based on the amount of water applied to fulfil crop water requirements. Treatment D1 was irrigated to fully satisfy crop water requirements, while treatments D2 (mild deficit), D3 (moderate deficit), and D4 (severe deficit) were for increased controlled water stress conditions. The computation and partitioning of evapotranspiration data into soil evaporation and crop transpiration was carried out with the SIMDualKc model, and then used with HYDRUS-1D. The soil hydraulic properties were determined from numerical inversion of field water content data. The compensated root water uptake mechanism was used to describe water removal by plants. The HYDRUS-1D model successfully simulated the temporal variability of soil water dynamics in treatments irrigated with full and deficit irrigation, producing RMSE values that varied between 0.014 and 0.025 cm 3 cm −3 when comparing model simulations with field measurements. Actual transpiration varied between 224 and 483 mm. Potential transpiration reductions varied from 0.4 to 48.8% due to water stress, but plants were able to compensate for the water deficits in the surface layers by removing more water from the deeper, less stressed layers. HYDRUS-1D water balance estimates were also comparable with the corresponding ones determined with the SIMDualKc water balance model. Both modelling approaches should contribute to improve the web-based IRRIGA system, used to support farm irrigation scheduling in Brazil. [ABSTRACT FROM AUTHOR]

• The database, the core engine, and the graphical interface of IrrigaSys are described. • Details on its implementation in an irrigation district in southern Portugal are also given. • The major strengths and weaknesses are discussed based a 5-years' support to farmers. IrrigaSys is a decision support system (DSS) for irrigation water management based on online, open source tools. The aim of this paper is to describe the structure of IrrigaSys and how it is implementation at the plot scale. The DSS includes remote access to local meteorological stations for weather conditions, a meteorological model for weather forecast, the MOHID-Land model for the computation of the soil water balance and irrigation scheduling, and a database for data repository. Despite its complexity, the data necessary to run IrrigaSys is minimal, and include as mandatory input information on the location of field plots, crop type, sowing and harvest dates, soil texture, irrigation method, and daily/weekly applied irrigation depths. Based on this information, the system automatically downloads the weather data from the meteorological station located closest to the agricultural plot, as well as the weather forecast for the seven incoming days. The soil water balance is then computed from sowing to the present date (updating always the system with newly acquired information) as well as the recommended irrigation schedule for the incoming week. Results are made available via a web interface, a mobile app, a SMS, and email. The IrrigaSys further provides the Normalized Difference Vegetation Index (NDVI) computed from the most recent Sentinel-2 imagery available with a resolution of 10 m. The IrrigaSys was developed in close cooperation with the Water Board from the Sorraia Valley irrigation district, southern Portugal, supporting 103 plots of 30 farmers over the last 5 years. This stakeholder has been fundamental for successfully running the system. This paper further discusses the main strengths and limitations of IrrigaSys, with the latter being naturally associated to difficulties in providing reliable estimates for all field plots based on limited data. [ABSTRACT FROM AUTHOR]

The IrrigaSys decision support system (DSS) has supported farmers' decision-making regarding irrigation scheduling in the Sorraia Valley irrigation district in Southern Portugal over a span of six years (2017–2022). This study aims to conduct a postevaluation of farmers' adherence to the DSS, employing a multicriteria analysis (MCA) approach with data from the 2019 (driest year) and 2020 (average year) growing seasons. Two distinct scenarios were taken into consideration: the first focused on water conservation, and the second centered on farmers' economic returns. The outcomes of the first scenario revealed that farmers exhibited a reasonable level of expertise, particularly during the driest season. They achieved water-saving indicators comparable to those obtained when adhering to optimized irrigation schedules generated weekly by the DSS. In the wetter season, discrepancies emerged between farmers' and model indicators, primarily attributed to challenges in integrating reliable information from precipitation forecasts into the decision-making process. In the second scenario, both farmers' and model results exhibited close economic indicators throughout both seasons. While IrrigaSys requires further developments, these results show that the DSS has effectively contributed to supporting irrigation water management in the study region. [ABSTRACT FROM AUTHOR]

The evaluation of the role of different agronomic strategies in achieving sustainable wheat yields under variable Mediterranean climate conditions may involve the use of resource-use indicators that combine productivity and environmental impact. A two-seasons field experiment was conducted in South Portugal to study the effect of water regimes and nitrogen fertilization on wheat yield, grain quality and water use evaluated with water productivity and water footprint indicators. The water regime treatments were full irrigation, supplemental irrigation, and rainfed. Nitrogen fertilizer treatments, including conventional and enhanced efficiency fertilizers (EEF) were distinguished by N splitting and timing over the crop cycle. Contrasting meteorological variables in the two years caused distinct wheat productive responses. Although leading to lower grain yields, supplemental irrigation guaranteed a water productivity similar to full irrigation. The use of EEFs in which 50% of the total nitrogen was applied at the booting phase had a positive significant effect on grain protein content and on dough rheologic properties, indicating that late nitrogen applications benefit the technological quality of wheat. The average total water footprints estimated for the two seasons showed no relevant differences but the partition of the green, blue and grey components in irrigated wheat varied, with an increased importance of blue water consumptive use in the second year of the experiment. In fact, the ratio blue water footprint/green water footprint increased from 0.40 to 2.00 due to higher irrigation requirements. High grey water footprint in rainfed wheat was mostly influenced by lower yields in 2018–2019, and by an advantageous rainfall distribution during the 2017–2018 season. No significant reduction in grey water footprint was observed when using EEFs. A multivariate statistical approach through factor analysis (FA) and multivariate linear regression (MLR) was used to examine the data structure and correlation. FA resulted in three-factor models of yield and water use, yield components and wheat quality, in the first season. In the second, drier, season, variables most related with irrigation water use were clustered in one detached factor. The stepwise MLR pointed to a good prediction capability of water footprints from NDVI measured with proximal sensors at booting, anthesis, maturation and/or tillering. [Display omitted] • Water regimes and nitrogen fertilization of wheat evaluation through water footprint. • Supplemental irrigation guaranteed wheat water productivity similar to full irrigation. • Increased ratio blue/green water footprint with drier Mediterranean conditions. • Enhanced efficiency N fertilizers did not reduce wheat grey water footprint. • Good prediction of wheat water footprints using multiple linear regressions with proximal NDVI. [ABSTRACT FROM AUTHOR]

Jute mallow (Corchorus olitorius L.) is an annual crop grown for human consumption of its nutritious leaves in many regions of the world. Despite its importance for household food security and farmers' income, reliable information on the crop's water requirements is still quite scarce. To overcome this knowledge gap, the irrigation needs of jute mallow grown in the Akkar region in Syria were investigated. The analysis focused on a three-year period (2017–2019) where the SIMDualKc model was calibrated and validated for simulating soil water contents and computing the soil water balance in jute mallow plots irrigated with basin and drip methods. The model was further used to determine the probabilities of the demand for irrigation water in scenarios considering different crop season lengths, irrigation methods, and application depths over a longer period of 23 years (1998–2020). The SIMDualKc model was able to simulate soil water contents measured in the field plots, returning root mean square error values lower than 0.001 m3 m-3 and modeling efficiencies ranging from 0.358 to 0.812. The calibrated basal (non-stressed) crop coefficients (K cb) were 0.15, 0.95, and 0.95 for the initial (K cb ini), mid-season (K cb mid), and end-season (K cb end) stages, respectively. The crop was harvested twice per season, with the drip treatments presenting the highest water productivity and economic indicators. In contrast, the basin treatment resulted in substantial percolation losses, which affected yields and indicators. Although net irrigation requirements showed a large variation for the extremes of the long-term weather time series, differences between the years representing average water demand and those representing very high water demand were only found for the drip irrigation scenarios. This study contributes to improving irrigation water management of jute mallow in the Syrian Akkar region, and for the sustainability of local production systems. • SIMDualKc computed the soil water balance of jute mallow irrigated with basin and drip methods. • The model simulated soil water contents with model efficiency from 0.36 to 0.81. • After model calibration, standard K cb values were derived for the first and second cut cycles. • Drip irrigation resulted in higher yields, water productivity and water saving. • Drip irrigation allowed optimizing NIR considering interannual seasonal variability. [ABSTRACT FROM AUTHOR]

Water scarcity and saline stress are primary threats for water use and agricultural production in arid and semi-arid regions, such as the Hetao Irrigation District, China. The current study, using irrigation with saline water, developed through three seasons (2017–2019) of field experimental surveillance of mulched maize water use in two cropped weighing lysimeters. Measurements included crop characteristics (height, LAI, dates of development stages), soil and water salinity, and daily actual crop evapotranspiration (ET c act). Deficit surface irrigation was scheduled in 2017 and 2018 seasons, while in 2019 drip irrigation was used aimed at satisfying crop water requirements. Both approaches aimed at improving irrigation management while controlling impacts of salinity. The collected information was used to parameterize and calibrate the soil water balance model SIMDualKc. The model uses the FAO56 dual crop coefficient approach and considers the combined effect of water and salinity stresses due to salinity of both soil and irrigation water. Results show that the SIMDualKc model adequately simulates the dynamics of the observed ET c act throughout the three growing seasons. The goodness-of-fit indicators show highly appropriate model fitting of observed ET c act with low RMSE of 0.42 mm d-1 for the calibration and 0.53 mm d-1 for validation. The calibrated standard basal crop coefficients (K cb) of maize for the initial, mid, and end stages were respectively 0.15, 1.15 and 0.25, which agree with those recently proposed by Pereira et al. (2021). Due to the impacts of both water and salt stress in 2017 and 2018, ET c act was much below the potential value ET c , ranging 64–83%, while in 2019 that percentage increased to 92% due to avoiding water stress by then. The average K cb mid act range 0.58–1.06, therefore lower than K cb mid , with the lower values occuring in the lysimeter that was irrigated with a large deficit. The irrigation scheduling practiced was assessed using water use and productivity indicators, which have shown the advantage in using drip irrigation with small time intervals between irrigations. Moreover, the current study and the calibrated model provide for adopting irrigation management practices that may save water and control salinity. • Weighing lysimeters provide for accurate measurement of evapotranspiration fluxes. • A couple of them were used to follow daily crop ET as affected by soil and water salinity. • Observations were used to calibrate and validate the model SIMDualKc for maize. • Results for deficit basin irrigation show ET and yields decreased by water and salt stress. • When drip irrigation was used without water deficit water productivity increased. [ABSTRACT FROM AUTHOR]

Highlights: [•] Changes of soil water, salinity and yield were simulated using SWAP for wheat. [•] SWAP was modified by adopting EPIC crop model and osmotic head-dependent function. [•] Model was well calibrated and validated using experimental data in 2007 and 2008. [•] Fifteen treatments with different irrigation and GWD were predicted and evaluated. [•] A target GWD of 1.0–1.5m was suggested to be optimal for wheat's growth. [Copyright &y& Elsevier]

• SIMDualKc computed the soil water balance of Zucchini squash irrigated with furrow and drip methods. • The model simulated soil water contents with RMSE ≤ 0.002 m3 m−3 and NSE from 0.166 to 0.732. • Calibrated basal K c for the initial, mid- and end-season varied from 0.18 to 0.22, 0.85 to 0.98, and 0.56 to 0.71. • Furrow irrigated plots presented substantial percolation losses and reduced yields. • Drip plots resulted in higher water productivity values and yields. The coastal area of the Syrian Akkar region is particularly suitable for intensive vegetable production, and Zucchini squash (Curcubita pepo L.) is one of the most profitable crops grown there. Local agricultural policies have been especially concerned at improving irrigation water management in the region by rationalizing water and nutrient use, modernizing irrigation methods, and minimizing the associated environmental risks. The objective of this study was to compute the soil water balance in Zucchini squash plots irrigated with furrow and drip methods using the SIMDualKc model during four growing seasons (2012–2015). The furrow plots (treatment T0) represented the traditional irrigation practices in the study area while the drip plots (treatments T1 and T2) followed alternative irrigation schemes. The SIMDualKc model was able to simulate soil water contents measured in the field plots, returning root mean square error values lower than 0.002 m3 m−3 and modelling efficiencies ranging from 0.166 to 0.732. The basal (non-stressed) crop coefficients (K cb) varied from 0.18 to 0.22, 0.85 to 0.98, and 0.56 to 0.71 during the initial, mid-season, and end-season stages, respectively, with the actual values (K cb act) often matching the potential ones. The evaporation coefficients (K e) varied according to irrigation schedules and methods during the early crop stages, but were minimized with full canopy development. Drip T1 presented always the highest water productivity (WP) indicators due to the higher frequency of irrigation events, with less water applied per event. In contrast, furrow T0 resulted in substantial percolation losses, which affected yields and WP. Hence, model results evidenced the benefits of precise irrigation for Zucchini squash production in the Syrian Akkar region, further enhancing the need for sustainable water management practices in local production systems. [ABSTRACT FROM AUTHOR]