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This paper highlights the evolution and impact of the SWAP model (Soil – Water – Atmosphere – Plant), which was initiated by R.A. Feddes and colleagues fifty years ago, in 1974. Since then, the SWAP model has played a crucial role in the advancement of agrohydrology. This paper highlights some major advances that have been made, especially focussing on the last fifteen years. The domain of the SWAP model deals with the simulation of the soil water balance in both unsaturated and saturated conditions. The model solves the Richards equation using the water retention and hydraulic conductivity functions as described by the Van Genuchten – Mualem equations. Bimodal extensions of the Van Genuchten - Mualem relationships have been implemented, as well as modifications near saturation and addressing hysteresis. An important sink term in the Richards equation is root water uptake. Crop development plays an important role in a robust simulation of root water uptake. That is why a link has been made with the dynamic crop growth model WOFOST. Instead of using a prescribed crop development, a distinction between potential and actual crop development is calculated by reducing the potential photosynthesis as a result of water or oxygen stress. Since the early days of SWAP, empirical and macroscopic concepts have been used to simulate root water uptake. Recently two process-based concepts of root water uptake and oxygen stress have also been implemented. Another important sink-source term in the Richards equation is the interaction with artificial drains. In SWAP, drainage can be simulated by either using prescribed or simulated drain heads and simulation of controlled drainage with subirrigation is possible. Finally, we briefly elaborate on three studies using SWAP: water stresses in agriculture in the Netherlands, regional water productivity in China, and controlled drainage with subirrigation. We finish discussing promising developments for the near future.

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.

This paper highlights the evolution and impact of the SWAP model (Soil – Water – Atmosphere – Plant), which was initiated by R.A. Feddes and colleagues fifty years ago, in 1974. Since then, the SWAP model has played a crucial role in the advancement of agrohydrology. This paper highlights some major advances that have been made, especially focussing on the last fifteen years. The domain of the SWAP model deals with the simulation of the soil water balance in both unsaturated and saturated conditions. The model solves the Richards equation using the water retention and hydraulic conductivity functions as described by the Van Genuchten – Mualem equations. Bimodal extensions of the Van Genuchten - Mualem relationships have been implemented, as well as modifications near saturation and addressing hysteresis. An important sink term in the Richards equation is root water uptake. Crop development plays an important role in a robust simulation of root water uptake. That is why a link has been made with the dynamic crop growth model WOFOST. Instead of using a prescribed crop development, a distinction between potential and actual crop development is calculated by reducing the potential photosynthesis as a result of water or oxygen stress. Since the early days of SWAP, empirical and macroscopic concepts have been used to simulate root water uptake. Recently two process-based concepts of root water uptake and oxygen stress have also been implemented. Another important sink-source term in the Richards equation is the interaction with artificial drains. In SWAP, drainage can be simulated by either using prescribed or simulated drain heads and simulation of controlled drainage with subirrigation is possible. Finally, we briefly elaborate on three studies using SWAP: water stresses in agriculture in the Netherlands, regional water productivity in China, and controlled drainage with subirrigation. We finish discussing promising developments for the near future. • Advances in soil-vegetation-atmosphere transfer modelling in the SWAP model. • Coupling of soil water dynamics with dynamic crop growth model. • Process-based root water uptake and oxygen uptake functions. • Climate-adaptive drainage with subirrigation. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Spatio-temporal variation of actual evapotranspiration over the central region of Saudi Arabia during 1950–2013 are estimated. • The FAO Penman-Monteith method was used to model the spatial distribution of ETo on a grid-by-grid basis. • Crop coefficients (Kc) were modelled as a function of MODIS normalized difference vegetation index (NDVI). • Actual evapotranspiration (AET) developed in daily, monthly and annual basis, based on soil water balance (SWB) model, Kc maps and ETo. Abstract Spatial and temporal distribution of reference (ETo) and actual evapotranspiration (AET) over the central region of Saudi Arabia during 1950–2013 are estimated using remote sensing and GIS techniques. Firstly, the FAO Penman-Monteith method was used to model the spatial distribution of ETo on a grid-by-grid basis using data collected from meteorological stations and GIS techniques. Then, crop coefficients (Kc) were modeled as a function of 16-day time-series MODIS normalized difference vegetation index (NDVI). Next, using Kc maps and ETo as input, daily AET was simulated by the soil water balance (SWB) model and aggregated to monthly and annual AET. From empirical NDVI-Kc relationships developed and applicable at pixel level, Kc derived from the NDVI-Kc relationships agree well with Kc recommended by FAO over various crop growth stages in the field. The monthly AET maps for 1950–2013 show a gradual increase in AET during the crop-growing season in January to May but a subsequent decline as the season progresses from June to December. The AET estimated for January to June are arranged in descending order, which are May (3.67–44.7 mm/day), April (5.99–36.8 mm/day), March (2.96–32.7 mm/day), February (0.68–20 mm/day), June (2.42–17.7 mm/day) and January (1–11 mm/day), respectively. Statistical analysis shows that statistically significant change point in daily AET generally occurred in 1990, such that the long-term average daily AET of 1950–1990 at 3.6 mm/day increased to about 5.3 mm/day between 1990 and 2016 with a positive trend of 1.5 mm/decade. The annual AET estimated for irrigated cropland in northern and central regions of Riyadh, Al-Qassim province and Hail province range from 1200 to 2900 mm/year. In these regions, low AET values are found in shrubland, grassland, and other natural vegetation. The annual AET estimated by the SWB model are about 9–11% higher than modeled AET in the study area, where the long-term average daily AET estimated for 1950–2013 range from 2 mm/day to 30 mm/day. Representative AET maps derived from applying the NDVI-Kc relationships to the SWB model will be useful to achieve the planning and management of sustainable water use in arid regions of Middle East. [ABSTRACT FROM AUTHOR]

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 • With limited information from farmers, WIDSSLI can tell farmers that when irrigation is needed and how much water is required. • The soil water balance of different layers were simulated. • The model is started from the earliest day of these days while crops are sowed or the cropland is irrigated. • WIDSSLI is deployed in the internet, and its mobile version is also developed. Abstract The increasingly serious water crisis requires all water users to participate in the water saving action. The majority of scattered smallholder farmers are in the disadvantage position of information. It is difficult for them to obtain the guidance of scientific irrigation. In order to satisfy the demands of farmers in North China Plain (NCP), a web-based irrigation decision support system with limited inputs (WIDSSLI) is presented in this paper. WIDSSLI is based on the Brower/Server mode and includes user interfaces (UIs) for farmers and administrators, models, database and a weather data update system (WDUS). FAO-56 dual crop coefficient approach is adopted to simulate the soil water balance of different layers. Without in-field soil moisture monitors, the model is started from the earliest day of these days while crops are sowed or the cropland is irrigated, and soil water depletions of all layers are initialized with 0 at the beginning. Using online weather forecast, future irrigation decision is obtained by the comparison between the field water availability simulated by the system and the lower limit of the soil moisture for irrigation. By which, farmers can obtain the irrigation decision support: when irrigation is needed and how much water is required. Verification results shows that the system initialization method is reasonable, and WIDSSLI can accurately simulate the dynamics of soil water content. WIDSSLI is deployed in the internet, and its mobile version is also developed for ease of use. [ABSTRACT FROM AUTHOR]

Double ridge and furrows with plastic mulching (PM), an effective drought-resistant farming technology, has been widely used in the semi-arid areas of China, and increased crop yields by more than 30%. However, where this technology has been applied in successive years, the annual balance of soil water has been affected and the risk of soil desiccation exacerbated. A 6-year field experiment had been conducted on the semiarid Loess Plateau to find a new mode of ecological security and economic efficiency under PM conditions. The two treatments were (i) PM with continuous maize cropping (PM-C) and (ii) PM with maize–fababean rotation (PM-R). The vertical variation of soil water along profile and the interannual variation of soil water, cumulative water consumption, biomass and yield, benefit and water economic yield were investigated. The results showed that the depth of soil water consumption of PM-C was extended downward by 60 cm from 2009 to 2014, but it did not vary in PM-R; the maximum depth of soil water consumption were 280 cm and 220 cm in PM-C and PM-R, respectively. Compared with the pre-seeding stage in 2009, soil water storage in the 0–300 cm depth in 2014-HA for PM-C decreased by 163.59 mm, comprising 5.21 mm in the 0–140 cm soil layer and 158.37 mm in the 140–300 cm layer. However, in the PM-R treatment, the soil water storage in the 0–300 cm depth in 2014-HA increased by 28.36 mm, resulting from an increase of 47.86 mm in the 0–140 cm soil layer and a decrease of 19.50 mm in the 140–300 cm layer. PM-R significantly improved crop water consumption in the post-flowering period, and the ratio of water consumption in post-flowering to total significantly increased by 19.54–51.09% ( P  < 0.05). The biomass and grain yield for PM-R were significantly lower than for PM-C, by 21.36 and 59.14%, respectively. However, there were no significant differences in benefit, mainly because the price of fababean was higher. The soil water depletion in 6 years of PM-R decreased significantly and therefore water economic yield was significantly higher than for PM-C. This suggested that PM-R alleviated the over-consumption of deep soil water and the water depletion depth, which caused by continuous maize cropping in PM-C, and so achieved significantly higher water economic yield by reducing soil water depletion and provided stable economic benefit. Consequently, PM-R represents a sustainable ecological, economic, secure and replicable planting mode. [ABSTRACT FROM AUTHOR]

In this paper we present PILOTE-N, a crop model devoted to the calculation of crop production from the joint water and nitrogen soil status effects. It is the extension of PILOTE, for contexts in which water might not be the sole limiting factor for crop yield, but the same model structure and credo of parsimonious parameterisation have been kept, assuming simplified descriptions of the physical processes at play. One original aspect of PILOTE-N is the calculation of Leaf Area Index (LAI) and cumulative nitrogen plant demand from similar logistic-type functions. LAI is controlled by specific temperature sums, shape parameters and the occurrence of water and nitrogen stresses, while the time average of LAI values over critical phenological periods also affects the predicted harvest index and crop yield. As specific plant parameters are known from PILOTE, calibration was devoted to nitrogen parameters. Which governing the daily-averaged mineralization rate in a first step, then the two shape parameters of the potential nitrogen plant demand (from the dilution curve) in a second step and, at last, which allowing the link between nitrogen uptake and nitrogen of the soil. Model performance was evaluated using multiple initial soil conditions, irrigation and fertilization strategies for corn, durum wheat and sorghum, over a climatic series of 14 years, at the experimental plot of Lavalette (Montpellier, South-East of France), hence in a Mediterranean context characterized by severe, water stresses during summer, typically exceeding nitrogen stresses. Crop yield as well as the dynamics of nitrogen budget were correctly simulated (R 2  > 0.94 for grain yield, total dry matter and nitrogen in plant). The robustness of such a simple and easy-to-calibrate tool is expected to facilitate its use and implementation in other agro-pedoclimatic contexts, to decipher the effect of abiotic stresses and improve irrigation and fertilization scenarios when included in dedicated tools. [ABSTRACT FROM AUTHOR]

Improvements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRI-NP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as an input. Both 2015 and 2016 had above-average precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 mm, 6 mm, and –12 mm less in separate analyses than for the uniform treatment. Irrigation for the VRI-RS was about 40 mm, 50 mm, and –98 mm greater in separate analyses than the uniform at Mead and about 18 mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates. [ABSTRACT FROM AUTHOR]

The deep percolation and actual evapotranspiration from flood irrigation in tropical floodplains were predicted using a numerical model, Hydrus-1D, and a bucket type water balance model. Field experiments were conducted on onion and maize crops grown from December 2015 to May 2016 in small irrigation schemes found in the Lake Tana floodplains of Ethiopia. Experimental fields were selected along a topographic transect to account for soil and groundwater variability. Irrigation volumes were measured using V-notches and irrigation depths (400–550 mm) were calculated, and daily groundwater levels were monitored manually from piezometers installed in the fields. The soil profiles were described at each field and physical properties (texture, FC , PWP , BD , and OM ) were measured at each horizon which were used to derive model input parameters. Soil hydraulic properties (residual and saturated moisture content, saturated hydraulic conductivity, parameters related to: pore size distribution n, air entry α and pore connectivity l) were derived using KNN pedotransfer functions for tropical soils and fitted using Retention Curve Program for Unsaturated Soils, RETC. The seasonal actual evapotranspiration estimated by Hydrus and water balance models ranged from 320 to 360 mm for onion and from 400 to 470 mm for maize. The seasonal deep percolation estimated from both models was 12–41% of applied irrigation and with this flood irrigation management; the deep percolation is very high. Implementing precise irrigation and water saving practices that minimize deep percolation and unproductive excessive consumptive use are required to achieve the growing food demand with the available water. When less detailed information is available, the water balance model can be an alternative to predict deep percolation and actual evapotranspiration. [ABSTRACT FROM AUTHOR]

Available soil water in the root zone is an essential component of the water balance process since it greatly affects the crop water uptake and crop growth. In this study, a modified soil water deficit index (MSWDI) was established on the basis of the concept of readily available water (RAW), with the accumulated effect considered. This modified index was applied in six agro-meteorological stations in Songnen Plain of China to monitor the agricultural drought. The results showed that: 1) The MSWDI showed similar spatial and temporal agricultural drought patterns as its inherent indices, such as the soil water deficit (SWD), soil moisture deficit index (SMDI) and atmospheric water deficit (AWD), but exhibited a delay between atmospheric and soil water processes; 2) The MSWDI has a better correlation with the crop yield than its inherent indices. For example, its overall correlation coefficient is about 0.6 with the crop yields among six study stations and −0.7 for the number of droughts, while their corresponding values are 0.5 and −0.6, 0.5 and −0.6, and 0.3 and −0.4 for SMDI, SWD and AWD, respectively; 3) The MSWDI could also identify a slightly higher number of reported drought events during the 2000–2012 in comparison with SMDI, SWD and AWD, although it also over-predicts the number of drought events same as other indices. It mainly comes from the uncertainty of reported drought events. The proposed index can be used for agricultural drought monitoring and provides a useful tool for agricultural meteorology and water resource management. [ABSTRACT FROM AUTHOR]

Soil evaporation (E S ) is a major fraction of water loss in dryland farming worldwide. Precise estimation of E S is therefore crucial for improved decision-making in agriculture water management. Ritchie’s two-stage E S algorithm is commonly used in crop models to estimate E S . However, use of different E S input values for the same soil type, and lack of understanding on how different soil types affect E S and crop yield in these models can negatively impact the prediction accuracy. To address these issues, a range of input values for stage 1 and stage 2 E S were collated, and their effects on modelled E S and yield were compared for a dryland wheat crop. The results using APSIM farming system model suggest that while in-crop E S increases and yield decreases with the increase of both stage 1 and stage 2 E S input values, the stage 2 values can have a greater effect, especially under lower rainfall conditions across the soil types. Fallow E S and in-crop E S were higher (by 7 and 12 mm yr −1 respectively) and yield was lower (by 0.27 t ha −1 yr −1 ) under Empirical datasets that used higher stage 2 E S input values than the default datasets. With all the datasets, E S and yield were higher (by 4–51 mm yr −1 and 1.51–1.98 t ha −1 yr −1 respectively) for Black Vertosol than the other soil types. As rainfall and/or E S input values increased, variability in both E S and yield (in turn the modelling error between the datasets) increased, and was higher for Black Vertosol and Red Kandosol soils. These insights will improve the prediction accuracy of E S and dependent factors in the models that apply Ritchie’s algorithm for E S estimation. [ABSTRACT FROM AUTHOR]

Methodologies based on earth observation remote sensing allow for a precise estimation of actual water requirements for irrigated crops across large areas. In spite of the many number of experiments using or analyzing the relationship between the basal crop coefficient (K cb ) and the soil adjusted vegetation index (SAVI) for maize, the development of new maize hybrid varieties with modifications related to canopy architecture suggest a possible change of the leaf area index (LAI) for maximum K cb and its relationship with the SAVI or other vegetation indices. In addition, we noted a lack of analysis of these relationships for cultivated soybean. The objective of this paper is to analyze the K cb , SAVI and LAI relationships in maize and soybean based on the non-linear relationships proposed by Choudhury et al. (1994). In addition, we propose a modification of the Choudhury et al. (1994) approach based on field-based experimental evidence of a minimum K cb greater than 0. For sites with limited field data, we also analyze the utility of a simple linear regression based on the K cb and SAVI values for bare soil and maximum K cb values. The resulting K cb -SAVI relationships are assimilated into a remote sensing based soil water balance model. The results of the model are analyzed in terms of irrigation requirements and crop evapotranspiration (ETa) for 11 growing seasons in two fields cultivated with irrigated and rain-fed maize and soybean in eastern Nebraska. Comparisons of measured and modelled ETa values indicate a good agreement, with RMSE lower than 0.7 mm d −1 for weekly averaged values. The comparison of actual irrigation applied and irrigation requirements indicate the central pivot systems could not supply adequate water in some growing seasons with higher demands. [ABSTRACT FROM AUTHOR]

Irrigation scheduling using remotely sensed surface temperature can result in equal or greater crop yield and crop water use efficiency compared with irrigation scheduling using in-situ soil water profile measurements. Crop evapotranspiration ( ETc ) is useful for irrigation scheduling, and can be calculated using surface temperature. Recent advances in wireless infrared thermometers (IRTs) have made surface temperature measurement a viable alternative to in-situ soil water profile measurements, and wireless IRTs are practical for deployment aboard moving irrigation systems, such as center pivots. However, ETc calculation has not been tested using IRTs aboard center pivots in conjunction with recent advances in a two-source energy balance (TSEB) model. We compared daily ETc calculated by a TSEB model to daily ETc estimated by a simple soil water balance (SSWB), where the SSWB used volumetric soil water measured by a field calibrated neutron probe to the 2.4-m depth. Crops included two seasons each of corn ( Zea mays L.), cotton ( Gossypium hirsutum L.), and grain sorghum ( Sorghum bicolor L.) at Bushland, Texas, USA. Discrepancies of TSEB vs. SSWB daily ETc were similar for each crop and season, and had root mean squared error from 1.5 to 1.8 mm per day, mean absolute error from 1.1 to 1.5 mm per day, and mean bias error from −0.51 to 0.63 mm per day. A sensitivity analysis was conducted for daily evaporation ( E ), daily transpiration ( T ), and ETc calculated by the TSEB model. These were most sensitive to radiometric surface temperature, air temperature, the reference temperature used in time scaling (i.e., to convert instantaneous to daily E , T , and ETc ), and incoming solar irradiance. Because over half of the irrigated area in the USA is now by center pivot, ETc calculated using IRTs aboard center pivots will be useful to maintain or increase crop water productivity. [ABSTRACT FROM AUTHOR]

A new expression of the time derivative of predawn leaf water potential was proposed by equalizing two expressions of the grapevine transpiration. This expression was established when transpiration is the only driver of the vineyard water balance. Under Mediterranean climate, this condition is met for long periods of drought i.e. most of the summer time under the hypothesis that there is no water movement (capillary rise) from the deep layers of the soil. The proposed approach showed that changes in predawn leaf water potential (Ψ pd ) values are in inverse relation with the Total Transpirable Soil Water (TTSW) which characterizes the maximal water stock of the soil and in direct relation with reference evapotranspiration (ET o ) and the basal crop coefficient (k cb ) of the vine. The relation between Ψ pd changes and cumulated ET o is linear with a slope related to the ratio of “k cb to TTSW”. This ratio can be therefore estimated from field measurements and climatic data. This approach was tested on two year observations performed by Acevedo-Opazo et al. (2010) in vineyards cultivated with cv. Shiraz and Mourvedre, without any irrigation. Analysis of the data obtained in 49 sites per vineyard for several dates in the very dry summers of 2003 (Shiraz) and 2005 (Mourvedre) showed strong and significant adjustments of the model. These results proved the linear relationship between the sum of ET o and Ψ pd . For each site of the vineyard, the approach demonstrated the possibility to provide site-specific estimates of the ratio of k cb to TTSW. This theoretical and practical development could have applications for water management and soil studies in Mediterranean vineyards. [ABSTRACT FROM AUTHOR]

A series of mobile irrigation apps have been developed on the basis that irrigation schedules can be estimated using an average of the previous five days of crop evapotranspiration (ET c ). The application of this average ET c methodology for developing an irrigation schedule has not been fully evaluated for the suite of apps, including the avocado app. Thus, an irrigation testing model was developed and is presented here that simulates irrigation depths based on the Smartirrigation avocado app operation technique and uses a soil water balance to simulate drainage, soil water content, runoff and plant water stress. The objectives were to identify an optimum number of previous days average ET c needed for estimating of an app irrigation schedule and to evaluate seasonal influences (wet and dry seasons) on the irrigation schedule through development and application of an irrigation testing model. Four different methods (3, 4, 6 and 7 previous days ET c ) were tested and compared to the current methodology (that uses the average of the previous 5 days ET c ) for developing irrigation schedules for five years from 2010 to 2014. In general, no significant differences ( p ≤ 0.05 ) were observed for irrigation depths, drainage depths, runoff and soil water content simulated among the app scheduling methods. Sixty two to 67% water savings were predicted with the app irrigation scheduling methods compared to a time based irrigation method (38 mm week −1 ). Average irrigation and drainage depths simulated were 15 to 41% and 160 to 512% greater in wet seasons compared to dry seasons, respectively. Ninety seven to 100% of the drainage was simulated during rainfall events. The current app methodology (previous 5 days ET c ) was found to capture weather variability for irrigation schedule development. Use of previous 6 and 7 days ET c was also sufficient. Addition of a wireless connection allowing users to modify the irrigation schedule using the smartphone app is recommended to reduce water losses during wet seasons and/or when rainfall events are predicted or occur. [ABSTRACT FROM AUTHOR]

Irrigation management has become a critical concern in the face of increasing water scarcity and food demand, particularly in the arid and semi-arid regions of the world. However, the effects of climate and soil texture on irrigation schedules remain unclear. In the present study, a two-year trial (2019–2020) was conducted in three greenhouses with different climates and soil textures under drip irrigation. The irrigation schedules were based on the cumulative evaporation (CE) of a 20 cm pan. Three treatments with different amounts of irrigation (I) were set in 2019. Three irrigation frequencies (IF) in combination with three irrigation amounts were set in 2020. A numerical model (HYDRUS-2D) was applied to simulate the soil water balance of greenhouse tomatoes. Tomato yield and irrigation water use efficiency (IWUE) were measured, and the responses of photosynthetic indices to soil water availability (SWA) were quantified. The results indicated that the soil water content (SWC) simulated by HYDRUS-2D was in accordance with the observed data, with average root mean square error (RMSE), mean bias error (MBE), and index agreement (IA) reaching 0.0127 cm3 cm−3, −0.0010 cm3 cm−3, and 0.9275, respectively. Among the four photosynthetic indices, the normalized photosynthetic rate exhibited the highest degree of fit (R2 =0.9678) with SWA (0–20 cm). Increased irrigation frequency (high IF) reduced the deep drainage by 24.6%, 10.5%, and 3.0% in sandy loam, loam, and silty clay soils, respectively. It was concluded that frequent irrigation with low amount can be applied to sandy loamy soil, whereas a lower irrigation frequency and larger single irrigation amount are recommended for silty clay soil. Our study provides theoretical support for irrigation management in semiarid regions with similar climates and soil textures. • HYDRUS-2D was used to simulate soil water dynamics in greenhouse tomato under drip irrigation. • The response of photosynthetic indices to simulated soil water availability in different soil layers was quantified. • Frequent irrigation lowered deep drainage and lateral diffusion, while maintaining higher soil water availability. • Higher frequent irrigation with smaller single amounts were recommended for sandy loam soil than that in silty clay. [ABSTRACT FROM AUTHOR]

The concept of available water holding capacity (AWHC) is important to many aspects of soil water management, particularly those involving a soil water balance calculation. In New Zealand AWHC estimates are commonly based directly or indirectly on laboratory measured pressure plate data. Such retentivity based values for AWHC are relatively similar across a range of soil types. Less often, AWHC values have been measured under rye grass/white clover pasture in the field. We critically discuss an important earlier New Zealand study. It noted that field-measured values are commonly about twice the laboratory-based estimates. We conclude that variable rooting depth, due to the presence or absence of compacted soil at depth and/or variable pasture vigour or species composition, usually has a greater effect on the AWHC than does the soil properties in the top 760 mm depth. Finally, it is claimed that this uncertainty around the exact size of AWHC need not undermine its utility. The one exemption to this assurance is where reliable predictions of drainage (and leaching) below the root zone are required: in this case there is the likelihood that use of the often quoted values for AWHC in the water balance will result in a significant overestimation of drainage (and leaching). [ABSTRACT FROM AUTHOR]

Accumulated daily crop evapotranspiration (ET c ) generally provides good estimates of cumulative soil water depletion between irrigation of well drained soils. If the canopy is wet due to fog, dew, or light rainfall, however, energy contribution to surface evaporation will reduce transpiration and hence soil water losses. When surface evaporation occurs, the ET c overestimates the soil water depletion by an amount approximately equal to the surface water evaporation. Moratiel et al. (2013) proposed a method to estimate the contribution of surface water to ET c based on the time of canopy drying. The first method assessment was done with California data, and this evaluation was conducted in the Ebro basin, Spain, to appraise the method in a higher latitude in area with a somewhat different climate. Differences between the California and Spain corrected models were less than 10% and depended mainly on the time of canopy drying. The comparison showed that the model is robust and useful to estimate the fraction ( F ) of ET c coming from the soil under dew, light rainfall, and fog conditions. [ABSTRACT FROM AUTHOR]

Mobile infrared thermometers (IRTs) mounted on moving platforms provide one-time-of-day radiometric measurements (T r), which can be used to calculate instantaneous actual evapotranspiration (ET a) using the two-source energy balance (TSEB) model. However, irrigation scheduling decisions utilize daily ET a estimates, hence the need for time scaling. This study evaluated different upscaling methods to calculate daily maize ET a using one-time-of day T r under varying water stress conditions. Mobile IRTs were mounted on a high clearance mobile sensing platform and collected T r in remote locations under full, deficit and rainfed conditions. Seven scaling methods via two pathways were employed to obtain daily ET a. First pathway was scaling one-time-of-day T r (SC) whereas the second pathway involved use of six upscaling methods of instantaneous ET a including: original and modified evaporative factor ((EF) o , (EF) m) as well as crop coefficient ((K c) o , (K c) m), direct canopy resistance (Direct- r c), and solar radiation ratio (R n /R s); and all were compared to a neutron-based soil water balance (SWB) determined ET a. From the results, SC outperformed other methods in comparison to SWB ET a across all the selected treatments with smaller discrepancies and lower RMSE (0.9–1.7 mm d−1 vs. 0.7–4.3 mm d−1 for other methods). Furthermore, methods including SC, (EF) o , (EF) m , and R n /R s had their daily average ET a values in close agreement to SWB ET a with mean ET a differences ranging between 0.2 and 1.6 mm d−1. Overall, SC method performed better in fully irrigated maize (r2 = 0.52, RMSE = 0.9 mm d−1) than in deficit irrigated maize (r2 = 0.48, RMSE = 1.4 mm d−1) but worst in rainfed maize (r2 = 0.16, RMSE = 1.7 mm d−1). This implies that SC is more suited for irrigated rather than rainfed settings. Importantly, the choice of any method depends on data requirements, irrigation water management strategy, and ET a estimation accuracy. • Infrared thermometers (IRTs) mounted on a mobile platform provide one-time-of-day radiometric temperatures (T r). • Two source energy balance (TSEB) with T r measurements provide estimates of actual evapotranspiration (ET a). • Different scaling approaches provide daily ET a via two pathways (scaling T r vs. instantaneous ET a); and all were compared to daily soil water balance ET a. • Water stress impacts the accuracy of daily ET a estimation and better results achieved in irrigated treatments more so with T r time scaling method. • Preference of scaling method entirely depend on data requirements and accuracy. [ABSTRACT FROM AUTHOR]

Exploring crop spatial organizations within landscapes is a promising solution for agroecological transitions and climate change adaptation in Mediterranean rainfed hilly agrosystems. A prerequisite is to ensure that crop models can simulate a range of agrohydrological processes in such agrosystems. The current study deepened the evaluation of the AquaCrop model by conducting a multicriteria evaluation (canopy cover CC, dry aboveground biomass AGB, actual evapotranspiration ET a , runoff R, soil water content SWC) for a range of crop and soil combinations, and for contrasted hydroclimatic years in northeastern Tunisia. The data were collected in the Kamech catchment (OMERE Observatory) during nine measurement campaigns on predominant soils and crops. AquaCrop simulations were based on field observations and parameters from the literature. AquaCrop could simulate plant dynamics and water fluxes for contrasted hydroclimatic years, with a slight dependence on soil class and a significant dependence on crop type. Model simulations were of moderate quality for CC (R2 of 0.45, RMSE of 0.24 on average) and of acceptable quality for AGB (R2 of 0.81, RMSE of 0.85 ton ha−1 on average). AquaCrop acceptably simulated water transfer across the soil–plant continuum (R2 of 0.62, RMSE of 0.77 mm day−1 on average for ET a ; R2 of 0.68, RMSE of 0.75 mm day−1 on average for R; R2 of 0.86, RMSE of 27.4 mm on average for SWC). The model performances were satisfactory for most cases, with p values larger than 5 % for the Student's t test on linear regressions of validation. Our results were similar to those reported in previous studies over flat terrain, including delayed senescence by model simulations with subsequent overestimation of CC and AGB observations. Additionally, soil cracks likely altered the AquaCrop ability to simulate runoff. Despite these limitations, our results support the application of AquaCrop to evaluate water productivity in hilly agrosystems. • Multicriteria evaluation of AquaCrop for rainfed hilly agrosystems. • Various combinations of Mediterranean crops and soils. • AquaCrop performance strongly depends on crop type and slightly on soil class. • The results are similar to those reported in previous studies over flat terrains. • AquaCrop can be used to characterize crop functioning and related water fluxes. [ABSTRACT FROM AUTHOR]

Crop growth simulation models of varying complexity have been developed to predict the effects of soil, water, nutrients and climate on biomass and grain yields and water use efficiency of different crops. In this study, the AquaCrop model was calibrated and validated for rice crop growth modeling under different irrigation water regimes at the Bangladesh Rice Research Institute, Gazipur, Bangladesh during the 2008–09 and 2009–10 winter (dry) seasons. Three irrigation water regimes were examined: irrigation with continuous standing water (CSW), and irrigation at 3 or 5 days after water disappearance (3 or 5 DAWD) from the field as potential water saving adaptations. Model performance was evaluated in terms of prediction error ( P e ), coefficient of determination ( R 2 ), the normalized root mean squared error (NRSME), the Nash–Sutcliffe model efficiency coefficient (EF) and Willmott’s index of agreement ( d ). The model calibration yielded 0.94 < R 2 < 0.99, 14.5 < NRMSE < 21.6, 0.83 < EF < 0.95 and 0.97 < d < 0.99 in simulating canopy cover (CC) percentage and above-ground biomass. Model validation yielded 0.98 < R 2 < 0.99, 8.6 < NRMSE < 12.9, 0.94 < EF < 0.97 and d = 0.99 in simulating CC percentage and above-ground biomass. In calibration and validation, respectively, the prediction errors for grain yield varied from 5.55 to 7.70% and 8.22 to 11.54%, and for biomass production from 2.62 to 5.19% and 7.95 to 11.15%, indicating good model performances. Based on crop yield, water use and its use efficiency, the IR69515-KKN-4-UBN-4-2-1-1 genotype showed better productivity in the dry season under the 3 DAWD irrigation water regime compared to the other examined treatments, which was shown by both the experimental data and the model simulations using FAO recommended conservative model parameters. The FAO AquaCrop model was able to predict rice growth and yield with acceptable accuracy under different water regimes, making this model a suitable candidate to facilitate local scenario studies related to irrigation scheduling, yield prediction or studies related to climate change and adaptation. [ABSTRACT FROM AUTHOR]

Two contrasting rainfall barley seasons, dry (2012) and wet (2013), were used to parameterize and assess the performance of the SIMDualKc and AquaCrop models. Field data were obtained from malt barley cropped in a farmer’s field in Ribatejo, Portugal. SIMDualKc applies the dual crop coefficient approach for computing and partitioning crop evapotranspiration (ET), while AquaCrop uses an empirical approach to estimate potential crop transpiration (T c ) and soil evaporation (E s ) depending upon the canopy cover (CC). The calibration and validation of both models was performed through comparing observed and predicted soil water content (SWC) for both seasons. The goodness-of-fit indicators were very good for SIMDualKc, with low errors of estimate (RMSE < 0.015 cm 3 cm −3 ). AquaCrop was first parameterized for the CC curves of both years using LAI observations. When tested for SWC, indicators have shown less accuracy than SIMDualKc. The analysis focused the partition of ET into T c and E s by both models through the analysis of the daily basal crop coefficients (K cb ) and evaporation coefficients (K e ), and the actual crop transpiration (T a ) and E s values cumulated to each crop growth stage and the season. Differences between the dry and wet year were evident, also in terms of model behavior when simulating SWC. Differences were also notable relative to the water balance terms, namely T a and E s . Problems with estimating K cb and K e with AquaCrop were identified, which likely cause its less good performance in simulating SWC and impacted yield estimation. Results of assessing both models led to conclude that computation procedures used in AquaCrop for T c , T a and E s lead to inaccuracies that make AquaCrop less appropriate to support irrigation scheduling. [ABSTRACT FROM AUTHOR]

Irrigation scheduling tools are critical to allow producers to effectively manage water resources for crop production. To be useful, these tools need to be accurate, complete, and relatively reliable. The current work presents an uncertainty analysis and its results for the Mississippi Irrigation Scheduling Tool (MIST) model, showing the margin of error (uncertainty) of the resulting irrigation advice arising solely from the propagation of measurement uncertainty through the MIST calculations. The final relative uncertainty in the water balance value from MIST was shown to be around 9% of that value, which is in the normal range of the margin of error and acceptable for agronomic systems. The results of this research also indicate that accurate measurements of irrigation and rainfall are critical to minimizing errors when using MIST and similar scheduling tools. While developed with data from Mississippi, the results of this uncertainty analysis are relevant to similar tool development efforts across the southern and southeastern United States and other high-rainfall areas, especially for locations lacking high-quality co-located weather stations. [ABSTRACT FROM AUTHOR]

Four years of soybean experimental data observed at Daxing, North China Plain, were used to assess the ability of the AquaCrop model to predict soybean final biomass and yield. The model was parameterized and calibrated using field data on leaf area index (LAI), available soil water, soil evaporation, biomass and final yield data. The model was assessed using calibrated and default parameters. Data on LAI were used to derive the fraction of ground cover and to calibrate the green canopy cover (CC) curve. An accurate calibration of the CC curve was performed, with low root mean square errors (RMSE < 7.3%). Results relative to soil water balance simulations show a high variability of the predictions, thus a bias of the estimation, with R 2 ranging 0.22–0.86 and low Nash-Sutcliffe efficiency EF, ranging between −0.47 and 0.82. The estimation errors were relatively high, with RMSE not exceeding 22.9 mm. AquaCrop was compared with the soil water balance model SIMDualKc, that has shown better performance with R 2 ≥ 0.83, EF generally greater than 0.75 and RMSE smaller than 12.5 mm. The soil evaporation ( E s ) simulations were compared with the observations performed using microlysimeters; results for Aquacrop have shown a clear trend for under-estimation of E s , with “goodness-of-fit” results worse than for SIMDualKc ( Wei et al., 2015 ). In general, AquaCrop has shown serious limitations to estimate crop transpiration or soil evaporation, which is likely due to abandoning the FAO dual K c approach. However, the model performed well relative to biomass and yield predictions, with a yield RMSE of 302 kg ha −1 . Overall, results show the adequacy of AquaCrop for estimating soybean biomass and yield when the model is appropriately parameterized. However, AquaCrop is not appropriate to support irrigation scheduling. [ABSTRACT FROM AUTHOR]

The main objectives of this study were to assess and partition soybean evapotranspiration and modelling to predict yields. The SIMDualKc water balance model, that adopts the dual crop coefficient approach, was used to evaluate the transpiration and soil evaporation components. Transpiration estimates were then used with the Stewart's water-yield model to predict soybean yields. SIMDualKc was calibrated and validated using soil water observations relative to four crop seasons and six treatments. In addition, the adopted soil evaporation approach using the Ritchie's model was validated against microlysimeter observations, also for the four years of study. The calibrated K cb was 1.05 for the mid-season and 0.35 at harvesting. Model results show a good agreement between available soil water data observed and predicted by the model, with root mean square errors of estimates (RMSE) smaller than 5% of the total available soil water. Testing the soil evaporation approach also produced good fitting results, with RMSE averaging 0.50 mm d −1 , hence confirming the appropriateness of the Ritchie's model to estimate soil evaporation of a cropped soil. The yield prediction through combining SIMDualKc and the Stewart's model was successful for all treatments, leading to a small RMSE of 381 kg ha −1 representing less than 11.5% of the maximum observed yield. These results indicate that yield may be predicted with that simple empirical approach provided that transpiration is accurately estimated and the water yield factor K y is adequately calibrated. Consumptive water productivity WP ET were high, ranging 0.95–1.46 kg m −3 , showing that both the crop variety and the agronomic practices may be extended in North China Plain. [ABSTRACT FROM AUTHOR]

Winter wheat ( Triticum aestivum L.) production in the North China Plain (NCP) is threatened by insufficient water supply. Interest in microirrigation is increasing in the NCP, while data and guidance for microirrigation scheduling are lacking. An accurate estimation of actual crop evapotranspiration ( ET a ) is critical for appropriate water management. In this study, therefore, the SIMDualKc model was calibrated with the data from a three-season experiment, and ET a of winter wheat with subsurface drip irrigation (SDI) was estimated with the dual crop coefficient approach and stress adjustments described in the FAO-56 using the data of the other two treatments. The mean value of basal crop coefficient ( K cb ) for the winter wheat at the initial-, mid-, and late-season growth stages over the three seasons was 0.25, 1.06, and 0.34, respectively. Over the three growing seasons, the ET a for subsurface drip-irrigated wheat with three irrigation treatments ranged from 393 to 449 mm. The K c-local ( ET a / ET o ) values for the winter wheat with SDI were 0.34–0.80, 0.91–1.11, and 0.41–0.98, respectively, at the initial-, mid-, and late-season growth stages. Results indicated that the procedure of the dual K c approach and stress adjustments simulated ET a of the winter wheat reasonably well, with the average absolute error ( AAE ) of 0.36 mm d −1 , the root mean square error ( RMSE ) of 0.43 mm d −1 ,the index of agreement ( d ) of 0.98, the Nash–Sutcliffe efficiency ( NSE ) of 0.91, and the RMSE -observations standard deviation ratio ( RSR ) of 0.31. Discrepancy between the simulated and measured data was mainly attributed to the assumption of a uniform distribution of soil water around an emitter. Irrigation rates have significant effects on ET a , grain yield and WUE . Based on effects of irrigation rates on grain yield and WUE , irrigation schedule for optimum yield and WUE was developed for winter wheat. It was estimated that grain yield and WUE of winter wheat with the optimum irrigation schedule was 7780 kg ha −1 and 1.83 kg m −3 , respectively. The simulated results can be used as a reference for irrigation schedule and water management for winter wheat in the NCP. [ABSTRACT FROM AUTHOR]

The development of a method to estimate the seasonal crop coefficient ( K c ) would be of great benefit to irrigated agriculture. We examined the simulation capacities of CropSyst for determining crop water use of Japanese plum under varying growing conditions. These conditions involved weather changes occurring during a period of three years (2010–2012), different pruning intensities, and the use of two cultivars having different vigor and maturity time ( Prunus salicina Lindl. ‘Angeleno’ and ‘Red Beaut’). Crop evapotranspiration (ET c ) was determined using the soil water balance method. Midday stem water potential ( Ψ stem ) was determined using a pressure chamber. Two parameters of the CropSyst crop model: crop coefficient at full canopy ( K c,fc ) and maximum plant hydraulic conductance ( C max ) were parameterized in 2010 season to predict K c , while 2011 and 2012 were used for validation. In 2011 and 2012, ‘Angeleno’ trees were subjected to severe summer pruning so that tree size would be smaller than in 2010. The influence of the high vigor and early harvest of ‘Red Beaut’ was tested in 2011. The results of 2010 parameterization revealed that K c,fc and C max had a distinctive seasonal pattern. This parameterization was adequate to simulate K c and Ψ stem for ‘Angeleno’ in other seasons and smaller trees than in 2010. The parameters adjusted in 2010 were not adequate to simulate the behavior of the more vigorous cultivar of ‘Red Beaut’. In ‘Red Beaut’, the factor that best explained the need to adapt CropSyst parameters was the difference in vigor but not the time of the removal of fruit sinks. To accurately simulate K c and Ψ stem in ‘Red Beaut’ it was required to use slightly higher values of K c,fc and C max during a specific midsummer period. [ABSTRACT FROM AUTHOR]

Uncertainty analysis can provide useful insights into the sources and effects of uncertainty for decision makers to achieve the goals of reliability and sustainability in water management. This study presents parameters uncertainty of a physically based soil–water–atmosphere–plant (SWAP) model and its effect on model prediction within the generalized likelihood uncertainty estimation (GLUE) framework for two irrigated agricultural fields in a dry region of Iran. To simulate soil water dynamics of the two fields, the SWAP model is calibrated using soil moisture observation data. The results demonstrate that predictive uncertainty in soil moisture during the growing season in both fields is relatively small and a good model performance is achieved. Parameter uncertainty analysis of soil hydraulic parameters showed that in spite of similarity of soil texture in both the fields, the estimated parameters (i.e. posterior distribution) exhibit different behaviors. This was because of the dynamics of soil structure which varies considerably within cultivated fields during the growing season. Moreover, the simulated water balance fluxes (actual evapotranspiration and deep percolation) indicate that in irrigated agricultural fields in dry regions, the precision of actual evapotranspiration predicted by the SWAP model is high (i.e. a high degree of model reliability is achieved). However, deep percolation fluxes show higher variation (lower precision) and are more sensitive to soil hydraulic conductivity parameterization. Finally, this study reveals the importance of uncertainty analysis to estimate the degree of reliability associated with model predictions as an important first step for providing decision makers with realistic information about the models outputs. [ABSTRACT FROM AUTHOR]

The temporal stability of soil moisture in irrigated cropland may have profound implications for precision agriculture in arid regions. This study evaluated the temporal variation of components of the soil water balance in irrigated cropland in northwestern China and identified representative locations to reliably estimate the profiles (0-1 and 1-2m) of spatial mean soil water storage (SWS) and deep percolation below a depth of 2m. Soil water storages were determined with a neutron probe at 48 locations (31 and 17 in the northern and southern croplands, respectively) on a total of 18 occasions in 2011 and 2012. Crop evapotranspiration, SWS variations and deep percolation were analyzed during the maize growing seasons. Soil water storages in the northern and southern croplands were temporally stable. The location with the lowest standard deviation of relative differences could accurately estimate the spatial mean SWS with a high coefficient of determination (R²>0.91, P<0.001) and prediction accuracy (PE>0.76) and near-zero mean absolute relative error (MARE=0). The most representative locations were different for the 0-1 and 1-2m soil layers, but the location for the 0-1m layer could also generally represent SWS in the 1-2m layer in the northern and southern croplands. From 21 May to late September in both years, approximately 39 and 22% of the irrigation and rainwater were lost as deep percolation in the northern and southern croplands, respectively. Deep percolation at the most representative locations of spatial mean SWS for the 0-1m layers could generally estimate the spatial mean deep percolation below a depth of 2m. This study provides an alternative approach for estimating spatial mean SWS and deep percolation, which is essential for the rational management of scarce resources of irrigation water in a large arid region of northwestern China. [ABSTRACT FROM AUTHOR]

Highlights: [•] Current irrigation efficiency is 76% and water deficit is 13%. [•] Corn was over-irrigated and alfalfa is under-irrigated. [•] The irrigation drainage fraction represents the 12% of the water applied. [•] A proposed change on the irrigation scheduling would increase the efficiency to 83%. [Copyright &y& Elsevier]

An optimal nutrient prescription along with favorable water management through mulching is key to high horticultural productivity, efficient water use, and minimizing soil nutrient loss. A field experiment was conducted in the Balindi Research Complex, Bidhan Chandra Krishi Viswavidyalaya in the Indo-Gangetic Plains of India, to evaluate the impact of mulching and balanced fertilization on actual evapotranspiration (ETa), crop coefficients (Kc), yield and yield attributes of cabbage (Brassica oleracea var. capitata L. cv. Green Express) during the winter seasons of 2018–2019 and 2019–2020 in the cabbage-fallow upland system under surface irrigated conditions. The experiment was laid out in a factorial strip plot design where no mulch (M1), live mulch [M2, Egyptian clover (Trifolium alexandrinum L.)], and paddy straw mulch (M3) were in strips with cabbage. Each treatment contained nutrient levels of 75% (N1), 100% (N2), and 125% (N3) of the recommended dose of an NPK fertilizer (RDF) with 200 N:100 P 2 O 5 :100 K 2 O. Higher soil water conservation under M3 incited 60% and 46% lower profile water change than M1 and M2 treatments, respectively. Paddy straw mulch produced 10.1% and 22.3% more yield and achieved 29.5% and 15.1% higher water productivity (WP) as compared to M1 and M2, respectively. Treatment N3 produced the highest yield and the least partial factor productivity of fertilizer (PFP f) compared to N2 and N1 treatments. Maximum ETa loss was from the M1N3 treatment (226.30 mm) and the highest yield (25,695 kg ha−1), yield attributes, and WP (120.1 kg ha−1 mm−1) were obtained from the M3N3 combination. The average estimated Kc values were 0.5 for initial, 1.0 for crop development, and 1.2 for mid-season, and 0.6 for maturity stages. The results suggest that the application of straw mulch with 125% RDF of chemical fertilizer under surface irrigated conditions improved cabbage yield, water productivity and soil fertility, however, living mulch achieved a higher economic return to the Indo-Gangetic alluvial clay loam Inceptisol of India. • Soil moisture storage under different mulched materials (straw and living) were different. • No mulch obtained higher ETa of cabbage irrespective of nutrient doses. • Higher doses of NPK and paddy straw produced higher yield and water use efficiency. • Nutrient management and mulch in finer soils affected soil moisture-nutrient retention and release. • Crop coefficients obtained from field water balance are comparable to FAO-56 due to soil and climatic variability. [ABSTRACT FROM AUTHOR]

Highlights: [•] We study the impacts of various soil matric potential thresholds (SMP) on tomato crop. [•] Tomato yields, fruit quality and water productivity (WP) were evaluated. [•] Crop coefficients of tomato were determined from crop density and plant height. [•] Mild to moderate water stress may benefit the tomato fruit quality. [•] The recommend SMP threshold for tomato irrigation in the study area is −40kPa [ABSTRACT FROM AUTHOR]

Highlights: [•] Intense monitoring campaign with HDP-sensors in a soil profile under rainfed maize. [•] Calibration and validation of a numerical model to simulate the soil–plant–atmosphere domain over 4 years. [•] Proper description of the crop phenological dynamics implemented in the numerical model. [•] Impact of climate forcing and soil water storage on root water uptake stress. [•] Effects of drought events on the water balance of the modeled soil domain. [ABSTRACT FROM AUTHOR]

Highlights: [•] A new root zone model was proposed to quantify drainage out of root zone by simplification of the unsaturated flow equation. [•] The model could satisfactorily simulate field water balance of winter wheat–summer maize crop rotation. [•] The cumulated drainage accounted for −27% to 19% of the applied irrigation and precipitation. [•] The optimal irrigation schedules of three typical hydrologic years were obtained by the model. [•] The developed model is useful for irrigation scheduling and reasonable utilization of groundwater resources in semi-arid region. [Copyright &y& Elsevier]

Abstract: The dual crop coefficient (K c) approach to estimate crop evapotranspiration (ETc) separately considers soil evaporation (E) and plant transpiration (T) by computing a soil evaporation coefficient (K e) and a basal crop coefficient (K cb), respectively, with K c = K e + K cb. This approach may be more precise than the single K c approach particularly when the crops incompletely cover the ground. The SIMDualKc model, which is adopted in this study, is an irrigation scheduling simulation model that uses a daily time-step for performing two separate soil water balances, one for the soil evaporation layer from which K e is computed, and the other for the entire root zone, thus allowing to compute the actual K cb adjusted to the soil moisture conditions (K cbadj). The standard K cb is corrected to the climate, crop density and height. Two years of field experimental data relative to winter wheat and summer maize were used for model calibration and validation using soil water content data observed with time-domain reflectometry (TDR) in a silt loam soil. Field data also include E measured with microlysimeters placed along the crop rows. The calibration procedure consisted in adjusting the basal crop coefficients, the soil evaporation parameters used to compute K e, and the soil water depletion fraction for no stress (p) to achieve the best fit of the observed soil water content data. The calibrated K cb values for winter wheat were 0.25 for the initial and the soil frozen period, 1.15 for the mid-season and 0.30 at harvesting. For the summer maize, the initial, mid season and end season K cb were respectively 0.2, 1.10 and 0.45. Model results have shown a good agreement between model predictions and field observations of the soil water content of both crops, with root mean square errors of estimates (RMSE) of about 0.01m3 m−3 for both the calibration and validation. The modelling efficiency EF and the index of agreement d IA were larger than 0.96 and 0.99, respectively, thus indicating good performance of modelling with SIMDualKc. Model estimates of E using Ritchie''s approach were compared with microlysimeter data; for winter wheat a RMSE=0.37mmd−1 was obtained, while for maize RMSE of 0.45 and 0.49mmd−1 were obtained for both years of observations. Results for soil evaporation allow confirming the appropriateness of using Ritchie''s model to estimate soil evaporation of a cropped soil. E averaged 124mm for wheat, representing 29% of ETc, and 146mm for summer maize, i.e. 41% of ETc. In conclusion, results show that the model is appropriate to simulate the soil water balance adopting the dual K c approach and may be further used to develop improved irrigation schedules for the winter wheat–summer maize crop sequence in North China. [Copyright &y& Elsevier]

Abstract: This paper is the second of a two-part series, with the first part describing the SIMDualKc model, an irrigation scheduling simulation tool that employs the dual crop coefficient approach for calculating daily crop ET and then performs a water balance for a cropped soil. The model was applied, calibrated and validated for rainfed and basin irrigated maize (Coruche, Portugal), rainfed and surface irrigated wheat (Aleppo, Syria), and furrow irrigated cotton (Fergana, Central Asia). Results show good agreement between available soil water content observed in the field and that predicted by the model. Results indicate that the calibrated model does not tend to over- or underestimate available soil water over the course of a season, and that the model, prior to calibration, and using standard values for many parameters, also performed relatively well. After calibration, the average growing season maximum estimation errors were 10mm for maize, 8mm for winter wheat and 9mm for cotton, i.e., respectively 3.6, 2.9 and 5.0% of total available water. Results indicate that the separation between evaporation and transpiration and the water balance calculation procedures are accurate enough for use in operational water management. The indicators used for assessing model performance show the model to accurately simulate the water balance of several crops subjected to a variety of irrigation management practices and various climate conditions. In addition, the model was applied to alternative irrigation management scenarios and related results are discussed aiming at assessing the model''s ability to support the development of alternative active water management strategies. [Copyright &y& Elsevier]

Abstract: Irrigation planning and scheduling require the availability of modeling tools that are accurate, quick and easy to use. The crop coefficient (K c )-reference evapotranspiration (ET) method is a traditional method for estimating ET, but has become relatively complicated with the introduction of the dual K c procedure. The dual crop coefficient approach (K cb + K e ) gives a better estimation of daily crop evapotranspiration because it separately considers soil evaporation and crop transpiration. This approach allows one to plan irrigation schedules properly, especially in the case of crops that do not completely cover the soil, where evaporation from the soil surface may be substantial. The SIMDualKc software application was developed with the purpose of simplifying implementation of the computation of the crop coefficient and crop evapotranspiration using the dual crop coefficient approach over a range of cultural practices and to provide ET information for use in irrigation scheduling and hydrologic water balances. The model performs a soil water balance at the field level using a daily time step. It estimates crop transpiration and soil evaporation as well as soil water dynamics to support irrigation scheduling for full and incomplete cover crops. This paper is the first part of a two-part series, where the second part describes model testing and application for various crops, locations and irrigation management issues. [Copyright &y& Elsevier]

Abstract: Automated residential irrigation systems tend to result in higher water use than non-automated systems. Increasing the scheduling efficiency of an automated irrigation system provides the opportunity to conserve water resources while maintaining good landscape quality. Control technologies available for reducing over-irrigation include evapotranspiration (ET) based controllers, soil moisture sensor (SMS) controllers, and rain sensors (RS). The purpose of this research was to evaluate the capability of these control technologies to schedule irrigation compared to a soil water balance model based on the Irrigation Association (IA) Smart Water Application Technologies (SWAT) testing protocol. Irrigation adequacy and scheduling efficiency were calculated in 30-day running totals to determine the amount of over- or under-irrigation for each control technology based on the IA SWAT testing protocol. A time-based treatment with irrigation 2 days/week and no rain sensor (NRS) was established as a comparison. In general, the irrigation adequacy ratings (measure of under-irrigation) for the treatments were higher during the fall months of testing than the spring months due to lower ET resulting in lower irrigation demand. Scheduling efficiency values (measure of over-irrigation) decreased for all treatments when rainfall increased. During the rainy period of this testing, total rainfall was almost double reference evapotranspiration (ETo) while in the remaining three testing periods the opposite was true. The 30-day irrigation adequacy values, considering all treatments, varied during the testing periods by 0–68 percentile points. Looking at only one 30-day testing period, as is done in the IA SWAT testing protocol, will not fully capture the performance of an irrigation controller. Scheduling efficiency alone was not a good indicator of controller performance. The amount of water applied and the timing of application were both important to maintaining acceptable turfgrass quality and receiving good irrigation adequacy and scheduling efficiency scores. [Copyright &y& Elsevier]

Abstract: Straightforward guidelines for deficit irrigation (DI) can help in increasing crop water productivity in agriculture. To elaborate such guidelines, crop models assist in assessing the conjunctive effect of different environmental stresses on crop yield. We use the AquaCrop model to simulate crop development for long series of historical climate data. Subsequently we carry out a frequency analysis on the simulated intermediate biomass levels at the start of the critical growth stage, during which irrigation will be applied. From the start of the critical growth stage onwards, we simulate dry weather conditions and derive optimal frequencies (time interval of a fixed net application depth) of irrigation to avoid drought stress during the sensitive growth stages and to guarantee maximum water productivity. By summarizing these results in easy readable charts, they become appropriate for policy, extension and farmer level use. We illustrate the procedure to derive DI schedules with an example of quinoa in Bolivia. If applied to other crops and regions, the presented methodology can be an illustrative decision support tool for sustainable agriculture based on DI. [ABSTRACT FROM AUTHOR]

Abstract: Micro-catchment water harvesting (MCWH) requires development of small structures across mild land slopes, which capture overland flow and store it in soil profile for subsequent plant uses. Water availability to plants depends on the micro-catchment runoff yield and water storage capacity of both the plant basin and the soil profile in the plant root zone. This study assessed the MCWH potential of a Mediterranean arid environment by using runoff micro-catchment and soil water balance approaches. Average annual rainfall and evapotranspiration of the studied environment were estimated as 111 and 1671mm, respectively. This environment hardly supports vegetation without supplementary water. During the study period, the annual rain was 158mm in year 2004/2005, 45mm in year 2005/2006 and 127mm in year 2006/2007. About 5000 MCWH basins were developed for shrub raising on a land slope between 2 and 5% by using three different techniques. Runoff at the outlets of 26 micro-catchments with catchment areas between 13 and 50m2 was measured. Also the runoff was indirectly assessed for another 40 micro-catchments by using soil water balance in the micro-catchments and the plant basins. Results show that runoff yield varied between 5 and 187m3 ha−1 for various rainfall events. It was between 5 and 85% of the incidental rainfall with an average value of 30%. The rainfall threshold for runoff generation was estimated about 4mm. Overall; the soil water balance approach predicted 38–57% less water than micro-catchment runoff approach. This difference was due to the reason that the micro-catchment runoff approach accounted for entire event runoff in the tanks; thus showed a maximum water harvesting potential of the micro-catchments. Soil water balance approach estimated water storage in soil profile and did not incorporate water losses through spillage from plant basins and deep percolation. Therefore, this method depicted water storage capacity of the plant basins and the root zone soil profile. The different between maximum water harvesting potential and soil-water storage capacity is surplus runoff that can be better utilized through appropriate MCWH planning. [Copyright &y& Elsevier]

Abstract: Evapotranspiration-based irrigation controllers, also known as ET controllers, use ET information or estimation to schedule irrigation. Previous research has shown that ET controllers could reduce irrigation as much as 42% when compared to a time-based irrigation schedule. The objective of this study was to determine the capability of three brands of ET-based irrigation controllers to schedule irrigation compared to a theoretically derived soil water balance model based on the Irrigation Association Smart Water Application Technologies (SWAT) protocol to determine the effectiveness of irrigation scheduling. Five treatments were established, T1–T5, replicated four times for a total of twenty field plots in a completely randomized block design. The irrigation treatments were as follows: T1, Weathermatic SL1600 with SLW15 weather monitor; T2, Toro Intelli-sense; T3, ETwater Smart Controller 100; T4, a time-based treatment determined by local recommendations; and T5, a reduced time-based treatment 60% of T4. All treatments utilized rain sensors set at a 6mm threshold. A daily soil water balance model was used to calculate the theoretical irrigation requirements for comparison with actual irrigation water applied. Calculated in 30-day running totals, irrigation adequacy and scheduling efficiency were used to quantify under- and over-irrigation, respectively. The study period, 25 May 2006 through 27 November 2007, was drier than the historical average with a total of 1326mm of rainfall compared to 1979mm for the same historical period. It was found that all treatments applied less irrigation than required for all seasons. Additionally, the ET controllers applied only half of the irrigation calculated for the theoretical requirement for each irrigation event, on average. Irrigation adequacy decreased when the ET controllers were allowed to irrigate any day of the week. All treatments had decreased scheduling efficiency averages in the rainy season with the largest decrease of 29 percentile points with a timer and rain sensor (T4) and an average decrease of 20 percentile points for the ET controllers, indicating that site specific rainfall has a significant effect on scheduling efficiency results. Rainfall did not drastically impact the average irrigation adequacy results. For this study, there were two controller program settings that impacted the results. The first setting was the crop coefficients where specific values were chosen for the location of the study when calculating the theoretical requirement whereas the controllers used default values. The second setting was the soil type that defines the soil water holding capacity of the soil. The ET controllers were able to regularly adjust to real-time weather, unlike the conventional irrigation timers. However, the incorporation of site specific rainfall measurements is extremely important to their success at managing landscape water needs and at a minimum a rain sensor should be used. [Copyright &y& Elsevier]

Abstract: The objective of this paper is to analyse the impact of temperature increases and irregular rainfall distribution, associated with climate change, on water availability for rainfed vineyards cultivated in a Mediterranean climate area. The study includes the analysis of the interrelations between precipitation distribution, temperature, evapotranspiration and runoff rates, and the resulting water storage in vineyards soils of the Penedès region (NE Spain). A hierarchical cluster analysis was applied to classify the years according to water availability. The influence of water stored into the soil on yield for some one of the main vine varieties cultivated in the area is analysed. A vineyard, representative of the land management practices in this area, was selected for soil moisture monitoring and runoff evaluations, as well as for grape yield, which was compared with yields recorded in other plots. According to rainfall distribution and water availability, the 12 analysed years represent five different situations: wet years with positive and negative water balance; dry years; years with average annual rainfall but irregularly distributed throughout the year leading to a negative water balance; and extreme situations. Significant water deficits were observed in years in which total rainfall amount was above the annual average in the area, being similar to those observed in dry years: in 8 of the 12 analysed years deficits higher than 100mm (up to 309mm) during the growing period (budbreak–harvest) were recorded. At annual scale, 42% of the analysed years recorded deficits ranging between 27.7 and 191.4mm. In the driest years, and those with more irregular rainfall distribution, soil moisture contents below the wilting point were reached. The high intensity rainfalls, producing important runoff losses (in many cases out of the periods in which crop water needs are higher), together with the increasing temperature trends, which give rise to significant evapotranspiration increases (values up to 32% higher than the average were recorded during the study period), are the main responsible factors for the water deficits recorded during grape development. Winegrape yield was influenced by the water stored into the soil, bloom–veraison or during budbreak–bloom depending on the variety. [Copyright &y& Elsevier]

Abstract: The development of accurate methodologies for monitoring drainage and evaluating nitrogen leaching from agricultural land is an absolute necessity, particularly considering the growing problem of nitrogen pollution of groundwater throughout the world. In this context, the Gee Passive Capillary Lysimeter appears to be an innovative tool that allows direct and continuous measurement of drainage and enables drainage water to be sampled for chemical analysis. The main objective of this study was to evaluate how the Gee Passive Capillary Lysimeter works in alluvial soils. The study was conducted at two agricultural field stations: Site 1 (central Spain), with a non-gravelly soil, and Site 2 (north of Spain), with a gravelly soil. An installation procedure that leaves part of the soil profile undisturbed was selected for the soil without gravel, whereas a procedure that may alter the soil physical properties was used for the gravelly soil. The experiment was carried out over two consecutive crop cycles at both field stations. Soil water balances were obtained through two different methods: a direct method based on direct measurements of drainage using the Gee Passive Capillary Lysimeter, and an indirect method based on the calculation of daily crop evapotranspiration. A statistical comparison of results obtained by the two methods showed no significant differences in estimates of drainage or crop evapotranspiration from both the non-gravelly and the gravelly soil. The efficiency of leachate collection with the Gee Passive Capillary Lysimeter in the non-gravelly soil was 101±1% (mean±standard deviation), while in the gravelly soil, it was 142±52%. Drainage and nitrogen leaching below the root zone were determined to be primarily triggered by excessive irrigation. This study helps to validate the use of the Gee Passive Capillary Lysimeter in gravelly and non-gravelly alluvial soils under irrigated agriculture. [Copyright &y& Elsevier]

Abstract: The average yield of sugar beet has almost doubled within the last 30 years. With the raise in average yields and the increase in sensitivity to water stress of sugar beets, the yield response factor (Ky) derived by needs an update. In this article, the soil water balance model BUDGET () was calibrated and validated to obtain correct estimations of the evapotranspiration deficit (1−ETa/ETc, where ETa=actual crop evapotranspiration and ETc=maximum crop evapotranspiration under standard conditions) of sugar beets in two locations in France. Datasets of observed soil water contents of several years and different irrigation treatments were used. The simulated evapotranspiration deficits and observed yields were used to derive a seasonal Ky. The obtained linear and polynomial yield response relation between observed yield decline and evapotranspiration deficit showed a high goodness-of-fit. The coefficient of determination (R 2)=0.83, the Nash–Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.26 for linear; the coefficient of determination (R 2)=0.85, the Nash–Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.25 for polynomial). The results suggested a more pronounced response of sugar beet to water stress in Europe as compared to the values previously reported by . The comparison between the observed and simulated yields (with the updated Ky) for another site in France confirmed the findings. [Copyright &y& Elsevier]

Abstract: Crop models are useful tools for integrating knowledge of biophysical processes governing the plant–soil–atmosphere system. But few of them are easily usable for water and yield management especially under specific cropping systems such as direct seeding. Direct seeding into mulch (DSM) is an alternative for conventional tillage (CT). DSM modifies soil properties and creates a different microclimate from CT. So that, we should consequently consider these new conditions to develop or to adapt models. The aim of this study was to calibrate and validate the PILOTE [Mailhol, J.C., Olufayo, A.A., Ruelle, P., 1997. Sorghum and sunflower evapotranspiration and yield from simulated leaf area index. Agric. Water Manag. 35, 167–182; Mailhol, J.C., Zaïri A., Slatni A., Ben Nouma, B., El Amami, H., 2004. Analysis of irrigation systems and irrigation strategies for durum wheat in Tunisia. Agric. Water Manag. 70, 19–37], an operative crop model based on the leaf area index (LAI) simulation, for corn and durum wheat in both DSM and CT systems in Mediterranean climate. In DSM case, simple model modifications were proposed. This modified PILOTE version accounts for mulch and its impact on soil evaporation. In addition root progression was modified to account for lower soil temperatures in DSM for winter crops. PILOTE was calibrated and validated against field data collected from a 7-year trial at the experimental station of Lavalette (SE of France). Results indicated that PILOTE satisfactorily simulates LAI, soil water reserve (SWR), grain yield, and dry matter yield in both systems. The minimum coefficient of efficiency for SWR was 0.90. This new version of PILOTE can thus be used to manage water and yield under CT and DSM systems in Mediterranean climate. [Copyright &y& Elsevier]

Drought has been a major limiting factor affecting agricultural production in the world. Accurately quantitative analysis of the dynamic changes of evapotranspiration and soil water balance is very important for effectively managing water resources and improving water use efficiency under water scarcity. Soil water balance for perennial forage is more complex than the annuals due to stronger roots and periodic evapotranspiration. The objective was to explore the evapotranspiration characteristics and soil water balance of alfalfa (Medicago sativa L.) grasslands under border irrigation at different stand ages and irrigation treatments. A 3-yr field experiment with a full irrigation and 6 regulated deficit irrigation treatments was conducted, and growth-related indicators, soil evaporation and soil water dynamics were observed regularly. Daily evapotranspiration and soil water balance were computed using a modified dual-Kc model which is able to simulate evaporation and transpiration separately. The results showed that soil water simulated by the model and the measured value were in good agreement, and regression coefficients were higher than 0.6 and close to 1.0 in most cuts. The change trend of root zone water under deficit irrigation at single growth stages was similar to that under full irrigation. Under irrigation, the transpiration was the main water loss of alfalfa grasslands. The daily actual evapotranspiration of alfalfa in the 1st cut was higher than 8.0 mm d−1 and even over 15.0 mm d−1 at the middle and later growth stages. In contrast, in the 2nd and 3rd cut, it was always less than 10.0 mm d−1. The daily actual evapotranspiration decreased significantly and immediately after cutting, and daily actual transpiration was reduced to less than 1.0 mm d−1. The change trend of daily actual evapotranspiration under deficit irrigation at single growth stages was also similar to that under full irrigation. The seasonal evapotranspiration could reach 800 mm and was reduced by deficit irrigation. The average proportion of soil evaporation to total evapotranspiration was 18%. With the decrease of irrigation amount, the evapotranspiration, transpiration and irrigation water compensation decreased, while evaporation remained relatively stable and the ratio of evaporation to evapotranspiration increased. A lower relative evapotranspiration deficit (0.041) was obtained under moderate deficit irrigation at the budding stage than those in other deficit cases (0.086 or over). In conclusion, in the arid and semi-arid areas, deficit irrigation could be applied to alfalfa grassland at the budding stage in alfalfa production. • The dual-Kc model can well simulate the change of soil water content in the root zone of alfalfa. • Change trends under different irrigation treatment varied between alfalfa transpiration and soil evaporation. • Transpiration was the main water loss, which is more than 70% of the evapotranspiration. • Moderate deficit irrigation at the budding stage did not cause obvious water stress. [ABSTRACT FROM AUTHOR]

Plastic mulching (PM) is regarded as a promising way to increase crop production. However, its reported that plastic mulching may decrease soil organic carbon content and been unfavorable for sustainable agricultural production. Confirmation of the effects of plastic mulching on soil water and organic carbon balances in a long term, including finding efficient ways to improve these balances, is crucial for the sustainability of agricultural production in semiarid rain-fed areas. We conducted field experiment (2010–2019), with spring maize and wheat as tested crops, using four treatments of plastic mulching (PM), plastic mulching with supplementary irrigation (PMI), plastic mulching with organic fertilizer application (PMO) and without mulching (CK). The results of this 10-year field experiment showed that PM with supplementary irrigation and organic fertilizer application not only significantly increased yield and Water productivity (WP) of wheat and maize, but also had a positive effect on soil water budget. The soil water budget of PMI, PMO and PM significantly increased by 120.4%, 96.1% and 105.8% in wheat and by 149.7%, 28.2% and 53.6% in maize, compared with CK, respectively. The improved soil water condition resulted in a significant increment of yield, PMI, PMO and PM increased yield by 122.8%, 89.7% and 67.0% for wheat, by 237.8%, 183.0% and 148.4% for maize, respectively, compared with CK. The 10 years of continuous PM significantly decreased soil organic carbon content (SOC) in 0–10, 10–20, 30–50 and 50–70 cm profiles by 22.5%, 19.1%, 15.6% and 15.3% for wheat, but had no significant effect for maize. The PMO significantly increased soil organic carbon content in 0–30 cm profiles for both wheat and maize, but the soil organic carbon budgets were negative for all four treatments, the PMO accelerated soil organic carbon loss for maize but had little effect for wheat compared with PM and CK. However, PMI, PMO and PM significantly increases crop bio-carbon production, resulted in the positive total carbon budget and significantly increased by 25.0, 15.0, 11.5 Mg ha−1 in wheat and 105.1, 74.1, 74.0 Mg ha−1 in maize, respectively, as compared with CK. These results suggested that the soil organic carbon budget differed for the two crops, also affected by water or organic carbon supplementation. A more appropriate crop rotation system with organic fertilizer application should be developed, to increase crop production and soil quality under plastic mulched condition in such semiarid rain-fed areas. • Plastic mulching sustains soil water balance, decreased soil carbon content in wheat field. • Plastic mulching significantly improved carbon accumulation of soil–crop system. • Water and carbon addition strengthened carbon accumulation in both maize and wheat field. • Optimized crop rotation with carbon addition may ameliorate soil organic carbon budget. [ABSTRACT FROM AUTHOR]

Intercropping planting pattern under plastic film mulching (PFM) has been widely adopted in the arid regions to reduce soil evaporation (E), improve land-use efficiency, and increase crop yield. However, water competition between intercropping components in the soil-plant-atmosphere continuum remains largely unexplored. The evaporation and radiation interception using the neighboring species model (ERIN) can effectively estimate evapotranspiration (ET) in a different intercropping ecosystem. However, the effects of soil surface resistance in the mulching area on ET are not considered in the ERIN model. Thus, the existing ET models do not accurately estimate ET in the intercropping ecosystem with PFM. In this study, we proposed a modified ERIN model (MERIN). In the MERIN model, soil surface resistance in the mulching area was taken into account, and its performance was compared to ERIN and Penman-Monteith (PM) models. These models were validated against observed ET and E using the water balance method and micro-lysimeters in a corn intercropped tomato experiment under high (HI: 30 mm for corn and 22.5 mm for tomato, a locally recommended irrigation depth), medium (MI: 22.5 mm for corn and 16.9 mm for tomato, 25% of HI), and low irrigation depth (LI: 15 mm for corn and 11.25 mm for tomato, 50% of HI) during 2018-2019, respectively. The outcomes of this study showed that the MERIN model could accurately estimate ET and E variation for a corn-tomato intercropping ecosystem under PFM during the entire crop growth season compared to the other examined models. The most intense water competition between corn and tomato was observed in stage II (the elongation and tasseling stages for corn; the flowering and fruiting stages for tomato). T of corn generally was higher than tomato, but an opposite result was also observed in stage II. Additionally, the variation of water competition under different irrigation levels was similar in the intercropping ecosystem. When irrigation depth decreased to 22.5 and 15 mm from 30 mm, average T for corn decreased by 10.7% and 16.3%, respectively, and by 12.9% and 22.4% for tomato, respectively, in both years. • A modified ET model (MERIN) for intercropping ecosystem was proposed. • The accuracy performance of the MERIN model was better than other ET models. • Water competition between crops mainly occurred in elongation and tasseling stages. • The variation of water competition under different irrigation levels was similar. [ABSTRACT FROM AUTHOR]