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Knowledge of the soil water balance is fundamental for improving crop water use in agricultural fields. Estimates are normally for representative and homogeneous areas where the variability of soil properties is neglected. However, this variability significantly impacts soil water dynamics at the field scale. In this study, the MOHID-Land distributed process-based model was used to compute the spatially explicit soil water dynamics in a 22.6-ha almond field located in southern Portugal. An electromagnetic induction survey was first performed to obtain electromagnetic images of the real soil conductivity in depth, which were related to soil texture. Then, pedotransfer functions were used to convert soil texture into soil hydraulic data. MOHID-Land results included maps of the spatial distribution of soil water contents, actual crop transpiration, actual soil evaporation, percolation below the rootzone, and surface runoff. These allowed identifying preferential flow pathways as well as the main control factors influencing soil water dynamics at the field scale. Some development needs were identified, and overcoming them would enhance the significance of contributions such as this study to the field of precision agriculture. • The spatial variability of the soil water balance was assessed in an almond field. • Soil properties were inferred from an electromagnetic induction (EMI) survey. • Distributed modeling identified crop growth areas and preferred flow paths at the field scale. • Limitations of the modeling approach were identified and discussed. • The development of approaches combining distributed modeling and EMI sensing is of interest to precision agriculture. [ABSTRACT FROM AUTHOR]

Highlights • Very-high density olive orchards have been expanding rapidly in the Alentejo region (Portugal). • The long-term impact of irrigation practices on soil salinization/sodification was assessed using HYDRUS-1D. • Soil salinization/sodification risks from current monitored practices were found to be low. • Modeled scenarios further considered waters with lower quality, maize as an alternative crop, and climate change. • The variability and uncertainty of model predictions recommend the close monitoring of the problem at the local scale. Abstract Deficit irrigation practices carried out in very high-density olive orchards grown in the Alentejo region of southern Portugal can bring important economic benefits in terms of water savings, yields, and oils. They can also result in serious salinization/sodification problems without proper management of soil and water resources. The main objective of this study was to evaluate the long-term (30 years) impact of those irrigation practices on local soil resources using a multicomponent transport modeling approach embedded in the HYDRUS-1D model. Soil salinization and sodification risks were quantified for 160 soil profiles by considering eight different scenarios: current monitored irrigation practices (S1), using waters of variable quality (S2-S6), planting maize as an alternative crop (S7), and using climate change projections for the region (S8). Despite the large observed variability, simulations that considered current irrigation practices (S1) produced average values of the electrical conductivity of the soil solution (EC sw) at the end of the leaching seasons always below the threshold limit for crops moderately tolerant to soil salinity. In this scenario, the average values of the sodium adsorption ratio (SAR) were also kept within the same magnitude of those determined at the beginning of the simulation period (initial conditions). Irrigations with worse quality waters (S2-S6) led to higher EC sw and SAR values. Although annual rainfall amounts influenced the salinity build-up, the SAR evolution depended mainly on water quality. In maize soil profiles (S7), the simulated EC sw and SAR values were lower than in olive soil profiles, with irrigation practices contributing to salt removal during the seasons. Conversely, the climate change scenario (S8) resulted in slightly higher EC sw and SAR values than those simulated for current conditions, indicating a potentially greater risk of soil degradation in the near future. Although current irrigation practices seem to present relatively low soil salinization/sodification risks, the variability of results and the uncertainty associated with model predictions indicate that close monitoring to prevent further degradation of soil and water resources in the region should be recommended. [ABSTRACT FROM AUTHOR]

Secondary salinization has long been reported in the Roxo irrigation district (RID), southern Portugal, due to the use of saline-prone irrigation water and the existence of poorly structured soils. This study assessed the soil water and salt budgets in nine commercial orchards located in the RID using the multiple ion chemistry module available in the HYDRUS-1D model during the 2019 and 2020 growing seasons. The studied crops were almond, olive, citrus (orange, mandarin, and clementine), and pomegranate. The model successfully simulated soil water contents measured in the different fields but there was a clear underestimation of the electrical conductivity of the soil saturation paste extract (EC e) in some locations, while simulations of the sodium adsorption ratio (SAR) were generally acceptable. Modeling errors were mostly associated with missing information on fertigation events rather than related to the effects of irrigation water quality. The water and salt balances were also computed for the 1979–2020 period. Considering the probability of non-exceedance of salt accumulation during this period, the risk of salinity build-up was high to very high for the very dry years in most fields, except in the citrus sites. The factors influencing the salt accumulation were the irrigation strategy, the seasonal irrigation and rainfall depths, the duration of the crop growth period, the rainfall distribution in the late and non-growing stages, the soil drainage conditions, and the irrigation water quality. For the current climate conditions and irrigation water quality, the risk of soil salinity levels affecting crop development and yields was found to be minor. This means that, despite salts tended to accumulate in the rootzone over a season, under current conditions the salinity stress did not reach harmful levels for plants. Only in two of the study sites, there was a need to promote salt leaching. Hence, this study shows that soil salinization risks in the study area are low but, for given locations during drier seasons, there is a need for tailored irrigation solutions aimed at the conservation of soil and water resources. • Soil salinization risks in nine commercial orchards were assessed with HYDRUS-1D. • The probability of non-exceedance of salt accumulation was computed for 1979–2020. • The risk of salinity build-up was high to very high for the very dry years in most fields. • For current conditions, the risk of soil salinity levels affecting crop development was minor. • Tailored irrigation solutions should be considered in some cases in dry and very-dry years. [ABSTRACT FROM AUTHOR]

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]

Orchards consist of complex agricultural systems, with a variety of characteristics (planting density, tree height, training system, canopy cover, irrigation method, interrow management) influencing crop evapotranspiration (ET c). Thus, irrigation water management requires finding crop coefficients (K c) that represent the characteristics of local orchards, evidencing the need for site specific data. The main objective of this study was to derive the K c of almond, olive, citrus, and pomegranate orchards in Alentejo, southern Portugal, wherein they became dominant over the last decade. Monitoring was carried out in nine orchards, which management decisions were performed by the farmers. The ET c was estimated from the soil water balance computed for each orchard using the FAO56 dual-K c approach with the SIMDualKc model. The model successfully simulated the soil water contents measured in the various fields along two growing seasons, with root mean square error values lower than 0.005 m3 m−3 and modeling efficiencies from 0.363 to 0.782. The estimated basal crop coefficients (K cb) for the initial, mid- and end-seasons were respectively 0.22, 0.58, and 0.50 for almond; 0.32–0.33, 0.35–0.36, and 0.33–0.34 for olive; 0.40, 0.40–41, and 0.40–0.41 for citrus; and 0.24, 0.60, and 0.52 for pomegranate. Small variations in olive and citrus K cb values were found to be related to differences in the fraction of the ground covered by trees' canopies and tree height. The single K c values, which included the component relative to soil evaporation, were also estimated. Furthermore, evaluation of the soil water balance in the nine case studies showed salinity effects in one almond orchard, mild irrigation water deficits in olive systems, and large non-consumptive water use in citrus and pomegranate orchards. These results evidence the need for better management of orchards irrigation water in the region, and the current study provides for reliable information on the K c of tree crops to support improving the management of local orchard systems and the preservation of soil and water resources. Aimed at these resources and the sustainability of their use, simulated alternative irrigation schedules were performed, which identified possible water savings of 20 mm in case of olives, up to 855 mm for citrus. • Irrigation management in nine commercial orchards was assessed with SIMDualKc. • Large non-consumptive water use was found in almond, citrus and pomegranate orchards. • Olive systems registered mild irrigation water deficits. • K c values are provided for improving irrigation water management in the Alentejo region. • Better training of orchardists is needed with support of computational tools. [ABSTRACT FROM AUTHOR]

• Regression models were developed for soil salinity assessment in Lezíria Grande, Portugal; • Multi-year maxima of 9 vegetation indices were correlated to rootzone salinity; • The CRSI, vegetation cover and soil type were the inputs selected by stepwise regression; • Remote assessment of soil salinity is a viable option in future soil monitoring programs. Lezíria Grande is an important agricultural area in Portugal, prone to waterlogging and salinity problems due to the influence of estuarine tides on groundwater dynamics. Simple, non-invasive, practical approaches are need for monitoring soil salinity in the region and preventing further degradation of soil resources. The objective of this study was to develop regression models for soil salinity assessment in Lezíria Grande based on the relationship between multi-year crop reflectance data derived from Sentinel-2 multispectral imagery and rootzone salinity. Nine vegetation indices (VI), computed from the annual averages of the spectral bands, were tested between 2017 and 2019. The multi-year maximum from each pixel was then used for correlating the VI with the ground-truth dataset. This dataset was composed of average values of the electrical conductivity of the soil saturation paste extract (EC e mean) measured in 80 sampling sites (0–1.5 m depth) located in four agricultural fields representative of the salinity gradient in the region. The Canopy Response Salinity Index (CRSI), which uses the blue (490 nm), green (560 nm), red (665 nm), and infrared (842 nm) bands, provided the strongest correlation with measured data (r=−0.787). Regression models further considered vegetation cover and soil type as explanatory variables, with predictions resulting in a coefficient of determination (R2) ranging from 0.63 to 0.91 and a root mean square error (RMSE) varying from 1.63 to 3.26 dS m−1. The use of remote sensing data for soil salinity assessment showed to be an interesting option to consider in future soil monitoring programs. Nevertheless, more detailed covariates are needed for improving salinity assessment models at the regional scale. [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 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]

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]

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]

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]

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]