Comparative study of Hargreaves’s and artificial neural network’s methodologies in estimating reference evapotranspiration in a semiarid environment

The Penman–Monteith equation (PM) is widely recommended because of its detailed theoretical base. This method is recommended by FAO as the sole method to calculate reference evapotranspiration (ET_o) and for evaluating other methods. However, the detailed climatological data required by the Penman–Monteith equation are not often available especially in developing nations. Hargreaves equation (HG) has been successfully used in some locations for estimating ET_o where sufficient data were not available to use PM method. The HG equation requires only maximum and minimum air temperature data that are usually available at most weather stations worldwide. Another method used to estimate ET_o is the artificial neural network (ANN). Artificial neural networks (ANNs) are effective tools to model nonlinear systems and require fewer inputs. The objective of this study was to compare HG and ANN methods for estimating ET_o only on the basis of the temperature data. The 12 weather stations selected for this study are located in Khuzestan plain (southwest of Iran). The HG method mostly underestimated or overestimated ET_o obtained by the PM method. The ANN method predicted ET_o better than HG method at all sites.     

Evaluation of estimated weather data for calculating Penman-Monteith reference crop evapotranspiration

Utilizing the weather generator ClimGen, daily solar radiation (R_s) and vapor pressure deficit (VPD) were estimated from temperature data and used to calculate evapotranspiration at five locations, representing tropical, temperate, semi-arid, and arid climates. ClimGen was calibrated for each location using the most recent 2 or 5 years of complete daily weather records. Actual and estimated values were compared on a daily and weekly (7-day running average) basis. Error indices were defined to indicate excellent to poor performance of the estimation methods. Overall in all locations, the ClimGen estimates for both daily R_s and VPD were poor to acceptable. The weekly analyses showed significant improvement in performance for both R_s and VPD estimations in arid and semi-arid locations. Daily reference crop evapotranspiration values using the FAO Penman-Monteith equation (PM ET_o) were calculated using complete daily weather records. These values were compared with (1) ET_o calculated with the PM model, actual temperature data, and ClimGen estimates of daily R_s, VPD, and generated wind speed (PM_Est ET_o), and (2) ET_o calculated solely from actual daily temperature data using a calibrated version of the Hargreaves method (HG_Adj ET_o). The daily PM_Est ET_o results were poor to acceptable in all locations, but analyses for weekly periods showed improved performance to acceptable and good levels for arid and semi-arid locations. The performance of the HG_Adj ET_o method was also poor to acceptable for daily ET estimates in all locations, while weekly analyses showed improvement. A non-calibrated version of the Hargreaves method did not work for either daily or weekly periods. The PM_Est ET_o and HG_adj ET_o methods appeared suitable for weekly periods in arid and semi-arid locations provided that at least 2 years of complete weather records were available to calibrate the parameters required. There was no advantage in using 5 years of weather records for calibration.Communicated by E. Fereres     

Crop coefficients for drip-irrigated processing tomato

Drip irrigation of processing tomato is increasing in the San Joaquin Valley of California (USA), a major tomato production area. Efficient management of these irrigation systems requires reasonable estimates of crop evapotranspiration (ET_c) between irrigations. A common approach for estimating ET_c is to multiply a reference crop evapotranspiration (ET_o) by a crop coefficient. However, a review of literature revealed mid-season crop coefficients for processing tomato to range from 1.05 to 1.25. Because of this variability, uncertainty exists in the crop coefficients appropriate for drip irrigation in the San Joaquin Valley. Thus, a study was initiated to determine the ET_c of processing tomato for drip irrigation in commercial fields and then calculate crop coefficients from the ET_c and ET_o data for the west side of the San Joaquin Valley. Crop ET_c was determined at five locations using the Bowen Ratio Energy Balance Method (BREB). Canopy coverage was also measured using a digital infrared camera. Average crop coefficients ranged from about 0.19 at 10% canopy coverage to 1.08 for canopy coverage exceeding about 90%. A second order regression equation reasonably described a relationship between crop coefficient and canopy coverage. Generic curves describing crop coefficient versus time of year were developed for various planting times.     

Optimization of furrow irrigation schedules,designs and net return to water

A seasonal furrow irrigation model consisting of irrigation scheduling and kinematic-wave-based hydraulic submodels was modified to incorporate an economic optimization submodel. The model used a systematic simulation technique to optimize furrow irrigation schedules and designs assuming 80% irrigation adequacy at cutoff time. The irrigation schedules and designs were optimized for the homogeneous and heterogeneous infiltration under the mean and observed ET_o (grass reference crop ET) conditions. The optimal management allowable depletion (MAD) level changed with the variation in ET_o condition, and with the consideration of spatial and temporal (seasonal) variability in infiltration characteristics. Irrigation design changed with both infiltration conditions and MAD level. Infiltration variability did not influence the bean yield. However, the return to water decreased when spatial variability in infiltration conditions was considered. Using mean ET_o resulted in slightly higher yield and net return to water as compared to using observed ET_o. A small variation in daily mean ET_o values with respect to daily observed ET_o values caused a change in both irrigation schedules and designs. Therefore, mean ET_o cannot be used to forecast irrigation schedules and designs at the beginning of crop season. The net return to water increased (1.7 to 3.6%), and the seasonal inflow, losses, and bean yield decreased in the case of variable interval scheduling (holding MAD constant) as compared to the fixed interval scheduling (MAD varies).     

An evaluation of two hourly reference evapotranspiration equations for semiarid conditions

The methodology proposed by the Food and Agriculture Organization (FAO) (Doorenbos, J., Pruitt, W.O., 1977. Crop water requirements. FAO irrigation and drainage. Paper No. 24. FAO, Rome) and updated by Allen et al. (Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. FAO irrigation and drainage. Paper No. 56. FAO, Rome) for calculating crop water requirements is the most extended and accepted method worldwide. This method requires the prior calculation of reference evapotranspiration (ET_o). This study evaluates the FAO-56 and American Society of Civil Engineers (ASCE) Penman–Monteith (PM) equations for estimation of hourly ET_o under the semiarid conditions of the province of Albacete (Spain). The FAO-56 and ASCE equations (hourly time step) were compared against measured lysimeter ET_o values at Albacete for 13 days during the period of April–October 2002 and 16 days during April–October 2003. The average of estimated FAO-56 Penman–Monteith ET_o values was equal to the average of measured values. However, the average of estimated ASCE Penman–Monteith values was 4% higher than the average of measured lysimeter ET_o values. This method overestimated measured lysimeter ET_o values by 0.45 mm h⁻¹.Simple linear regression and error analysis statistics suggest that agreement between both estimation methods and the lysimeter was quite good for the province of Albacete.In this paper, the FAO-56 Penman–Monteith equation for calculating hourly ET_o values was more accurate than the ASCE Penman–Monteith method under semiarid weather conditions in Albacete.     

Evaluation of FAO-56 methodology for estimating reference evapotranspiration using limited climatic data: Application to Tunisia

The Food and Agriculture Organization of the United Nations had improved the version of the Penman–Monteith method (FAO-56 PM) which has recently been proposed as the standard for estimating reference evapotranspiration (ET_o). Unfortunately, some weather variables, especially solar radiation, relative humidity and wind speed, are often missing which could impede the estimation of ET_o with the FAO-56 PM method. To overcome the problem of the availability of climatic parameters, procedures to estimate ET_o with missing climate data are proposed as part of the FAO methodology. Therefore, assessing the accuracy of these procedures for different Tunisian locations is important. The comparison of ET_o estimates using limited data to those computed with full data set revealed that the difference between ET_o obtained from full and limited data set is small considering the 8 locations studied. Both the Mean Bias Error (MBE) and the Root Mean Square Error (RMSE) of the comparison were less than 0.6 and 0.8 with a minimum of −0.4 and 0.2 mm day⁻¹, respectively, leading to small errors in the ET_o estimates. The higher deviations occur when the only available information is minimum and maximum air temperature. These deviations were significantly higher when using the Hargreaves equation to calculate ET_o.     

Comparative analysis of 31 reference evapotranspiration methods under humid conditions

Evaluation of simple reference evapotranspiration (ET_o) methods has received considerable attention in developing countries where the weather data needed to estimate ET_o by the Penman–Monteith FAO 56 (PMF-56) model are often incomplete and/or not available. In this study, eight pan evaporation-based, seven temperature-based, four radiation-based and ten mass transfer-based methods were evaluated against the PMF-56 model in the humid climate of Iran, and the best and worst methods were selected from each group. In addition, two radiation-based methods for estimating ET_o were derived using air temperature and solar radiation data based on the PMF-56 model as a reference. Among pan evaporation-based and temperature-based methods, the Snyder and Blaney–Criddle methods yielded the best ET_o estimates. The ET_o values obtained from the radiation-based equations developed here were better than those estimated by existing radiation-based methods. The Romanenko equation was the best model in estimating ET_o among the mass transfer-based methods. Cross-comparison of the 31 tested methods showed that the five best methods as compared with the PMF-56 model were: the two radiation-based equations developed here, the temperature-based Blaney–Criddle and Hargreves-M4 equations and the Snyder pan evaporation-based equation.     

Crop coefficient and evaptranspiration of onion at Awash Melkassa, Central Rift Valley of Ethiopia

Improved water management through precise crop water requirement determination is needed to improve the efficiency of water use in agricultural production. As a result, appropriate irrigation scheduling which can lead to water saving, improvements in the yield and income can be designed. In this study, three non-weighing lysimeters having dimensions of 2 m × 1 m × 2 m were used to determine water requirement (ET_c) and crop coefficient (Kc) of onion (Bombay Red cultivar). Reference crop evapotranspiration (ET_o) was determined using weather data recorded at the site. The measured ET_c values were 51.3 mm, 140.5 mm, 144.8 mm, and 53.9 mm during the initial, development, mid-season and late season growth stages respectively. Crop coefficient (K_c) values, calculated as ratio of ET_c to ET_o, were 0.47, 0.99, and 0.46 during the initial and mid-season stages and end of late season. Furthermore, third-order polynomials were fitted well to predict the crop coefficient values as functions of growing degree-days (GDD).     

An analysis of the tendency of reference evapotranspiration estimates and other climate variables during the last 45 years in Southern Spain

Climate change will have important implications in the agriculture of semi-arid regions, such as Southern Spain, where the expected warmer and drier conditions might augment crop water demand. To evaluate these effects, a data set consisting of observed daily values of air temperature, relative humidity, sunshine duration and wind speed from eight weather stations in Andalusia and covering the period 1960-2005 was used for estimating reference evapotranspiration (ET_o). ET_o was calculated using five methods: the more complex Penman-Monteith FAO-56 (PM) equation, considered as a reference in this study, and four alternative methods with fewer data requirements, Hargreaves, Blaney-Criddle, Radiation and Priestley-Taylor. These methods were compared to PM with respect to ET_o average values and trends. The non-parametric Mann-Kendall test was used to evaluate annual and seasonal trends in the main climate variables and ET_o.Due to increases in air temperature and solar radiation, and decreases in relative humidity, statistically significant increases in PM-ET_o were detected (up to 3.5 mm year⁻¹). Although the Hargreaves equation provided the closest average values to PM, this method did not detect any ET_o trend. On the other hand, trends found from Blaney-Criddle and Radiation ET_o values were similar to those obtained from PM. In addition, after a local adjustment, these two methods gave accurate ET_o average values. Therefore, Blaney-Criddle and Radiation methods have shown themselves to be the most accurate approaches for ET_o determination in climate change studies, when available data provided by climate models are limited.     

Agricultural water management in a humid region: sensitivity to climate,soil and crop parameters

A sensitivity analysis of irrigation water requirements at the regional scale was conducted for the humid southeastern United States. The GIS-based water resources and agricultural permitting and planning system (GWRAPPS), a regional scale, GIS-based, crop water requirement model, was used to simulate the effect of climate, soil, and crop parameters on crop irrigation requirements. The effects of reference evapotranspiration (ET_o) methods, available soil water holding capacities (ASWHC), crop coefficients (K_c), and crop root zone depths (z) were quantified for 203 ferneries and 152 potato farms. The irrigation demand exhibited a positive relationship with K_c and z, a negative relationship with ASWHC, and seasonal variations depending on the choice of ET_o methods. The average irrigation demand was most sensitive to the choice of K_c with a 10% shift in K_c values resulting in approximately 15% change in irrigation requirements. Most ET_o methods performed reasonably well in estimating annual irrigation requirements as compared to the FAO-56 PM method. However, large differences in monthly irrigation estimates were observed due to the effect of the seasonal variability exhibited by the methods. Our results suggested that the selection of ET_o method is more critical when modeling irrigation requirements at a shorter temporal scale (daily or monthly) as necessary for many applications, such as daily irrigation scheduling, than at a longer temporal scale (seasonal or annual). The irrigation requirements were more sensitive to z when the resultant timing of irrigation coincided with rainfall events. When compared with the overall average of the irrigation requirements differences, the site-to-site variability was low for K_c values and high for the other variables. In particular, soil properties had considerable average regional differences and variability among sites. Thus, the extrapolation of site-specific sensitivity studies may not be appropriate for the determination of regional responses crop water demand.     

Corn yield responses under crop evapotranspiration-based irrigation management

Improving irrigation water management is becoming important to produce a profitable crop in South Texas as the water supplies shrink. This study was conducted to investigate grain yield responses of corn (Zea mays) under irrigation management based on crop evapotranspiration (ET_C) as well as a possibility to monitor plant water deficiencies using some of physiological and environmental factors. Three commercial corn cultivars were grown in a center-pivot-irrigated field with low energy precision application (LEPA) at Texas AgriLife Research Center in Uvalde, TX from 2002 to 2004. The field was treated with conventional and reduced tillage practices and irrigation regimes of 100%, 75%, and 50% ET_C. Grain yield was increased as irrigation increased. There were significant differences between 100% and 50% ET_C in volumetric water content (θ), leaf relative water content (RWC), and canopy temperature (T_C). It is considered that irrigation management of corn at 75% ET_C is feasible with 10% reduction of grain yield and with increased water use efficiency (WUE). The greatest WUE (1.6 g m⁻² mm⁻¹) achieved at 456 mm of water input while grain yield plateaued at less than 600 mm. The result demonstrates that ET_C-based irrigation can be one of the efficient water delivery schemes. The results also demonstrate that grain yield reduction of corn is qualitatively describable using the variables of RWC and T_C. Therefore, it appears that water status can be monitored with measurement of the variables, promising future development of real-time irrigation scheduling.     

Spatially distributed monthly reference evapotranspiration derived from the calibration of Thornthwaite equation: a case study, South of Iran

The Penman-Monteith equation is the most common method for estimating reference crop evapotranspiration (ET_o). Using this method reqiures many different meteorological data, yet few stations with adequate meteorological data may exist in a region. Setting up a station that records the required data for Penman-Monteith equation is expensive. Alternatively, the Thornthwaite equation is a simpler method for estimating ET_o since it is a temperature-based method. In this study, the Thornthwaite equation was spatially calibrated based on the Penman-Monteith method (as the standard and reference method to compute ET_o) for every month of the year, using the meteorologica data of seven synoptic weather stations in Fars province, and seven synoptic stations outside the Fars province. The Thornthwaite equation using effective temperature that has been introduced recently in other studies was used (Camargo et al. in Revista Brasileira de Agrometeorologica 7:251–257, 1999). For this purpose a calibration coefficient k must be determined. The results of the spatial and temporal calibration of the new approach using the Thornthwaite equation showed that for each station different k values should be used monthly. Generally, the k values fluctuated between 0.55 and 1.12, and the mean RMSE for all stations was less than 1 mm day⁻¹, which showed good and reliable agreement between the ET_o estimations obtained from the Penman-Monteith and calibrated Thornthwaite equations. Depending on the geographical location of each station, spatial distribution maps of monthly k values were created for the study area using the inverse distance weighting (IDW) interpolation method. It is therefore possible to estimate monthly ET_o using the appropriate k map and the Thornthwaite equation for different regions of study area instead of using the Penman-Monteith method. This case study showed that the same analysis might be used for the other parts of the country or any part of the world and would result in efficient scheduling of water resources for agriculture.     

Ancillary data supply strategies for improvement of temperature-based ETo ANN models

The development of new and more precise models for reference evapotranspiration (ET_o) estimation from minimum climatic data is mandatory, since the application of existing methods that provide acceptable results is limited to those places where large amounts of reliable climatic data are available. The performance quality of empirical equations and their local calibrations is to be questioned in a large variety of climatic contexts. As an alternative to traditional techniques, artificial neural networks (ANNs) are highly appropriate for the modelling of non-linear processes, which is the case of evapotranspiration. Nevertheless, temperature-based ANN models do not always provide accurate enough ET_o estimations and their performance depends highly on the specific relationships temperature-ET_o of the studied continental context. This paper describes the performance improvement of temperature-based ANN models through the consideration of exogenous ET_o records as ancillary inputs in different continental contexts of the autonomous Valencia region, on the Spanish Mediterranean coast. The influence on the model performance of the number of considered ancillary stations and the corresponding number of training patterns is also analysed. Finally, this performance is compared with existing empirical and ANN temperature-based models. The proposed models can be used with high accuracy not only for infilling purposes, but also for estimating ET_o outside the training station. Concerning models which demand scant climatic inputs, the proposed model provides performances with lower associated errors than the currently existing temperature-based models, which only consider local data. The local performance of the model presents 0.084 of average absolute relative error (AARE). The external performance of the model presents 0.1072 of AARE.     

Bahiagrass crop coefficients from eddy correlation measurements in central Florida

Bahiagrass (Paspalum notatum) is a warm-season grass used primarily in pastures and along highways and other low maintenance public areas in Florida. It is also used in landscapes to some extent because of its drought tolerance. Bahiagrass can survive under a range of moisture conditions from no irrigation to very wet conditions. Its well-watered consumptive use has not been reported previously. In this study, bahiagrass crop coefficients (K _c) for an irrigated pasture were determined for July 2003 through December 2006 in central Florida. The eddy correlation method was used to estimate crop evapotranspiration (ET_c) rates. The standardized reference evapotranspiration (ET_o) equation (ASCE-EWRI standardization of reference evapotranspiration task committee report, 2005) was applied to calculate ET_o values using on site weather data. Daily K _c values were estimated from the ratio of the measured ET_c and the calculated ET_o. The recommended K _c values for bahiagrass are 0.35 for January–February, 0.55 for March, 0.80 for April, 0.90 for May, 0.75 for June, 0.70 for July–August, 0.75 for September, 0.70 for October, 0.60 for November, and 0.45 for December in central Florida. The highest K _c value of 0.9 in May corresponded with maximum vapor pressure deficit conditions as well as cloud free conditions and the highest incoming solar radiation as compared to the rest of the year. During the summer (June to August), frequent precipitation events increased the cloud cover and reduced grass water use. The K _c annual trend was similar to estimated K _c values from another well-watered warm-season grass study in Florida.     

Estimation of dwarf green bean water use under semi-arid climate conditions through ground-based remote sensing techniques

Determination of temporal and spatial distribution of water use (WU) within agricultural land is critical for irrigation management and could be achieved by remotely sensed data. The aim of this study was to estimate WU of dwarf green beans under excessive and limited irrigation water application conditions through indicators based on remotely sensed data. For this purpose, field experiments were conducted comprising of six different irrigation water levels. Soil water content, climatic parameters, canopy temperature and spectral reflectance were all monitored. Reference evapotranspiration (ET₀), crop coefficient K_c and potential crop evapotraspiration (ET_c) were calculated by means of methods described in FAO-56. In addition, WU values were determined by using soil water balance residual and various indexes were calculated. Water use fraction (WUF), which represents both excessive and limited irrigation applications, was defined through WU, ET₀ and K_c. Based on the relationships between WUF and remotely sensed indexes, WU of each irrigation treatments were then estimated. According to comparisons between estimated and measured WU, in general crop water stress index (CWSI) can be offered for monitoring of irrigated land. At the same time, under water stress, correlation between measured WU and estimated WU based on CWSI was the highest too. However, canopy-air temperature difference (T_c − T_a) is more reliable than others for excessive water use conditions. Where there is no data related to canopy temperature, some of spectral vegetation indexes could be preferable in the estimation of WU.     

Water use and the development of seasonal crop coefficients for Superior Seedless grapevines trained to an open-gable trellis system

Water consumption of table grapevines (Vitis vinifera cv. Superior Seedless) trained to a large open-canopy gable system was measured during six growing seasons (1999, 2001–2005) using 12 drainage lysimeters. The lysimeters (1.3 m³ each) were installed as part of a one-hectare vineyard in a semi-arid region in southern Israel. Water consumption of the lysimeter-grown vines (ET_c) was used as the basis for the calculation of irrigation applications in the vineyard. Three irrigation treatments, 80% (high), 60% (medium) and 40% (low) of ET_c of the lysimeter-grown vines, were applied in the vineyard. Reference evapotranspiration (ET_o) was calculated from regional meteorological data according to the Penman–Monteith equation. Seasonal curves for the crop coefficient (K _c) were calculated as K _c = ET_c/ET_o. Maximum ET_c values in different seasons ranged from 7.26 to 8.59 mm day⁻¹ and seasonal ET_c (from DOY 91 through DOY 304) ranged from 1,087 to 1,348 mm over the six growing seasons. Leaf area index (LAI) was measured monthly using the SunScan Canopy Analysis System. Maximum LAI ranged from 4.2 to 6.2 m² m⁻² for the 2002–2005 seasons. A second-order polynomial curve relating K _c to LAI (R² = 0.907, P < 0.0001) is proposed as the basis for efficient irrigation management. The effects of the irrigation treatments on canopy growth and yield are presented. The high ET_c and K _c values that were observed are explained by the wide canopy layout that characterize the large open-gable trellis system.     

Applicability of support vector machines and adaptive neurofuzzy inference system for modeling potato crop evapotranspiration

Estimation of crop evapotranspiration (ET_C) for certain crops such as potato is very important for irrigation planning, irrigation scheduling and irrigation systems management. The primary focus of this study was to investigate the accuracy of the adaptive neurofuzzy inference system (ANFIS) and support vector machines (SVM) for potato ET_C estimation when lysimeter measurements or the complete weather data for applying the FAO method are not available. The estimates of the ANFIS and SVM models were compared with the empirical equations of Blaney–Criddle, Makkink, Turc, Priestley–Taylor, Hargreaves and Ritchie. The performances of the different SVM and ANFIS models were evaluated by comparing the corresponding values of root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (r). The drawn conclusions confirmed that the SVM and ANFIS models could provide more accurate ET_C estimates than the empirical equations. Overall, the minimum RMSE (0.042 mm/day) and MAE (0.031 mm/day) values and the maximum r value (0.98) were obtained using the SVM model with mean air temperature, relative humidity, solar radiation, sunshine hours and wind speed as inputs.     

Temporal and spatial variations of evapotranspiration for spring wheat in the Shiyang river basin in northwest China

The methods for estimating temporal and spatial variation of crop evapotranspiration are useful tools for irrigation scheduling and regional water allocation. The purpose of this study was to develop a method for mapping spatial distribution of crop evapotranspiration and analyze the temporal and spatial variation of spring wheat evapotranspiration in the Shiyang river basin in Northwest China in the last 50 years. DEM-based methods were employed to estimate the spatial distribution of spring wheat evapotranspiration (ET_c). Reference crop evapotranspiration (ET₀) was calculated with the Penman–Monteith equation using meteorological data measured from eight stations in the basin. Crop coefficient (K_c) was determined from measured evapotranspiration in spring wheat season in the region. The results showed that ET_c gradually increased in the upper reaches of the basin in the last 50 years, while the middle reaches showed a significant decreasing trend, and in other regions, no significant trend was found. These changes can be attributed to expansion of irrigation areas and climate change. The multiple regression analysis between ET_c and altitude, latitude, and aspect were carried out for eight weather stations and the relationships were used to map ET_c for the basin. The spatial variations of ET_c were analyzed for three typical growing seasons based their precipitation. Results showed that long-term average ET_c over cultivated land was increasing from 270 mm in southwest mountainous area to 591 mm in northeast oasis of the basin, and the relative error between the estimated ET_c in spring wheat growing season by reference evapotranspiration (ET₀) and crop coefficient (K_c), and the interpolated ET_c was within 11.1%.     

Irrigation scheduling of plastic greenhouse vegetable crops based on historical weather data

Irrigation scheduling based on the daily historical crop evapotranspiration (ET_h) data was theoretically and experimentally assessed for the major soil-grown greenhouse horticultural crops on the Almería coast in order to improve irrigation efficiency. Overall, the simulated seasonal ET_h values for different crop cycles from 41 greenhouses were not significantly different from the corresponding values of real-time crop evapotranspiration (ET_c). Additionally, for the main greenhouse crops on the Almería coast, the simulated values of the maximum cumulative soil water deficit in each of the 15 consecutive growth cycles (1988–2002) were determined using simple soil-water balances comparing daily ET_h and ET_c values to schedule irrigation. In most cases, no soil-water deficits affecting greenhouse crop productivity were detected, but the few cases found led us to also assess experimentally the use of ET_h for irrigation scheduling of greenhouse horticultural crops. The response of five greenhouse crops to water applications scheduled with daily estimates of ET_h and ET_c was evaluated in a typical enarenado soil. In tomato, fruit yield did not differ statistically between irrigation treatments, but the spring green bean irrigated using the ET_h data presented lower yield than that irrigated using the ET_c data. In the remaining experiments, the irrigation-management method based on ET_h data was modified to consider the standard deviation of the inter-annual greenhouse reference ET. No differences between irrigation treatments were found for productivity of pepper, zucchini and melon crops.     

VegSyst, a simulation model of daily crop growth, nitrogen uptake and evapotranspiration for pepper crops for use in an on-farm decision support system

The VegSyst simulation model was developed to assist with N and irrigation management of sweet pepper grown in plastic greenhouses in the Mediterranean Basin. The model was developed for use in an on-farm decision support system with the requirement for readily available input data. Dry matter production (DMP), crop N uptake and crop evapotranspiration (ET_c) are simulated on a daily basis. DMP is calculated from daily fraction of intercepted photosynthetically active radiation (PAR), PAR radiation, and radiation-use efficiency. Fraction of intercepted PAR is calculated from relative thermal time. Crop N uptake is calculated as the product of DMP and N content which is described by a power function of DMP. ET_c is the product of daily reference evapotranspiration (ET_o) using an adapted Penman–Monteith equation, and a daily simulated crop coefficient value. The VegSyst model for soil-grown, greenhouse pepper was calibrated in one crop and validated in three different crops. In the validation, the model accurately simulated crop growth, N uptake and ET_c. Relative to measured values, simulated DMP at final harvest was 0.89–1.06, and crop N uptake was 0.97–1.13. Simulated cumulative ET_c for complete crops was 0.95–1.05 of measured values.