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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]

The success of an irrigation decision support system (DSS) much depends on the reliability of the information provided to farmers. Remote sensing data can expectably help validate that information at the field scale. In this study, the MOHID-Land model, the core engine of the IrrigaSys DSS, was used to simulate the soil water balance in an irrigated vineyard located in southern Portugal during three growing seasons. Modeled actual basal crop coefficients and transpiration rates were then compared with the corresponding estimates derived from the normalized difference vegetation index (NDVI) computed from Sentinel-2 imagery. On one hand, the hydrological model was able to successfully estimate the soil water balance during the monitored seasons, exposing the need for improved irrigation schedules to minimize percolation losses. On the other hand, remote sensing products found correspondence with model outputs despite the conceptual differences between both approaches. With the necessary precautions, those products can be used to complement the information provided to farmers for irrigation of vine crop, further contributing to the regular validation of model estimates in the absence of field datasets. [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]

• Salinity impacts on soils, crops and the environment. • Modelling salinity and leaching requirements. • The FAO56 approach to assess crop ET and its partition when affected by salinity. • Appropriate water and irrigation management issues to cope with salinity in agriculture. Soil and water salinity and associated problems are a major challenge for global food production. Strategies to cope with salinity include a better understanding of the impacts of temporal and spatial dynamics of salinity on soil water balances vis-à-vis evapotranspiration (ET) and devising optimal irrigation schedules and efficient methods. Both steady state and transient models are now available for predicting salinity effects on reduction of crop growth and means for its optimization. This paper presents a brief review on the different approaches available, focusing on the FAO56 framework for coping with the effects of soil salinity on crop ET and yields. The FAO56 approach, applied widely in soil water balance models, is commonly used to compute water requirements, including leaching needs. It adopts a daily stress coefficient (K s) representing both water and salt stresses to adjust the crop coefficient (K c) when it is multiplied by the grass reference ET o to obtain the actual crop ET values for saline environments (ET c act = K s K c ET o). The same concept is also applied to the dual K c approach, with K s used to adjust the basal crop coefficient (K cb). A review on applications of K s is presented showing that the FAO56 approach may play an interesting role in water balance computations aimed at supporting irrigation scheduling. Transient state models, through alternative formulations, provide additional solutions for quantification of the salinity build-up in the root zone. These include irrigation-induced salinity, upward movement of salts from saline ground water-table, and sodification processes. Regardless of the approach, these models are now very much capable of supporting irrigation water management in saline stress conditions. For maintaining crop growth under salinity environments, soil-crop-water management interventions consistent with site-specific conditions are then discussed. Adequateness of irrigation methods, cyclic uses of multi-salinity waters and proper irrigation scheduling are further analyzed as examples of efficient means to obviate the effects of salinity. [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]

Water-saving irrigation is becoming more important in the upper Yellow River basin (YRB) due to reduced water allocation and growing water scarcity. However, drip irrigation as an efficient irrigation method, has not gained as much acceptance as one might expect. In this study, integrated approaches involving field experiments, agro-ecosystem modeling, and financial analysis were proposed to evaluate the multiple benefits of two irrigation methods. Field experiments on maize irrigated with border irrigation and drip irrigation under plastic mulching (i.e., BI-M and DI-M) were conducted in the Hetao Irrigation District (Hetao) of the upper YRB during 2021 and 2022. The AHC model was calibrated and validated using two-year experimental data, performing well in simulations of soil water-salt-nitrogen (N) dynamics and crop growth. An irrigation scheduling module was newly incorporated into AHC. Then the model was applied to analyze scenarios consisting of three classes of groundwater depth (GWD) and five N application levels. Optimal irrigation and N-fertilization strategies were suggested; and DI-M showed significant advantages over BI-M in terms of water-saving (56–66 mm), labor-saving, environmental benefits (50 kg ha−1 less N fertilizer and 19–25 kg ha−1 less N loss), and crop yields (<4%), both in experimental and scenario cases. However, the financial analysis revealed that the current smallholder BI-M could achieve higher net returns (about 12%) compared to DI-M, since the family labor is often not counted as a cost in smallholder farming. Additionally, the widespread adoption of BI-M is also partly attributed to its easy operation. Lastly, results indicated a trend where the advantages of drip irrigation would become more significant in the future, with the increasing agricultural population aging and rising labor costs in the YRB. • Experiments, surveys and AHC model were combinedly used for irrigation evaluation. • Water-salt-nitrogen fate and economic benefits were evaluated under various scenarios. • Optimal water-nitrogen strategies were suggested for border and drip irrigation. • Smallholder BI-M achieves higher net returns due to exclusion of family labor cost. • Drip irrigation has clear advantages in water, labor and eco-environmental benefits. [ABSTRACT FROM AUTHOR]

The occurrence of shallow saline water tables in arid zones provides for groundwater-fed natural vegetation and for a substantial amount of irrigated crops' water needs. This is the case of the Hetao plain, upper Yellow River Basin, Inner Mongolia, China, where one of the major irrigation systems of China and the World is installed. As reviewed, numerous irrigation and water management studies have been developed in Hetao and the upstream irrigated plain of Yinchuan, Ningxia. These studies have demonstrated the need for controlling salts through the autumn irrigation and the appropriate irrigation methods and scheduling. Moreover, studies evidenced the need for adopting irrigation schedules that consider groundwater contribution during the crop cycle but most of these studies were empirical, resulting difficult to transfer results. When models adopted were mechanistic, they are difficult to use for irrigation scheduling purposes comparatively with soil water balance (SWB) models. Thus, the current study used two sets of five static water table lysimeters cropped with maize and having water table depths (WTD) fixed between 0.85 and 2.25 m. It was therefore possible to observe the daily capillary rise fluxes from the water table, the dynamics of water and salts and to calibrate the SWB model SIMDualKc. Results show that the average electrical conductivity of the saturated extract of the soil ranged from 3.10 to 4.69 dS m−1 with the higher values observed when WTD was smaller, while the electrical conductivity of irrigation water ranged 1.73–1.87 dS m−1. Results also show that shallower WTD required less irrigation water but caused higher salinity impacts on crop growth and yields. Thus, the best WTD were around 1.75–2.00 m when basin irrigation was adopted in 2017 and 2018. In these crop seasons, the simulated groundwater contribution to actual crop evapotranspiration (ET c act) was up to 37% in the lysimeters having a shallow WTD (1.25 m), while in the lysimeters with deeper WTD (2.00–2.25 m) it was about 11% of the ET c act. Contrastingly, in 2019, when maize was not irrigated, the average groundwater contribution represented 73% and 49% of ET c act in the lysimeters with shallow and deep WTD, respectively. Results were obtained when a large leaching autumn irrigation (200 mm) was performed. Those experiments showed that, solutions for using basin flooding irrigation are ready but still require that irrigation scheduling is adjusted to provide for appropriate use of the saline groundwater contribution, which may be performed with the model SIMDualKc, as demonstrated by the high goodness-of-fit indicators used to evaluate the referred simulations. • Soil water contents and capillary rise from a saline shallow water table (WT) were measured using static WT lysimeters. • Observations were used to calibrate/validate the SIMDualKc model. • Impacts of WT depth on crop ET, soil salinity, maize growth and yield were assessed. • Best results for crop transpiration and yield were obtained for the WT depth at 2 m. • Groundwater contribution with shallower WT promoted salinity build-up in the rootzone. [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]

• 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]