Peach orchard evapotranspiration in a sandy soil: Comparison between eddy covariance measurements and estimates by the FAO 56 approach

The evapotranspiration from a 3 to 4 years old drip irrigated peach orchard, located in central Portugal, was measured using the eddy covariance technique during two irrigation seasons, allowing the determination of crop coefficients. These crop coefficient values differed from those tabled in FAO Irrigation and Drainage Paper 56. In order to improve evapotranspiration estimates obtained from FAO tabled crop coefficients, a dual crop coefficient methodology was adopted, following the same guidelines. This approach includes a separation between the plant and soil components of the crop coefficient as well as an adjustment for the sparse nature of the vegetation. Soil evaporation was measured with microlysimeters and compared with soil evaporation estimates obtained by the FAO 56 approach. The FAO 56 method, using the dual crop coefficient methodology, was also found to overestimate crop evapotranspiration. During 2 consecutive years, measured and estimated crop coefficients were around 0.5 and 0.7, respectively. The estimated and measured soil evaporation components of the crop coefficient were similar. Therefore, the overestimation in evapotranspiration seems to result from an incorrect estimate of the plant transpiration component of the crop coefficient. A modified parameter to estimate plant transpiration for young, yet attaining full production, drip irrigated orchards is proposed based on field measurements. The method decreases the value of basal crop coefficient for fully developed vegetation. As a result, estimates of evapotranspiration were greatly improved. Therefore, the new approach seems adequate to estimate basal crop coefficients for orchards attaining maturity established on sandy soils and possibly for other sparse crops under drip irrigation conditions.     

A rigorous approach of determining FAO56 dual crop coefficient using soil sensor measurements and inverse modeling techniques

Accurate estimation of crop coefficients for evaporation and transpiration is of great importance in optimizing irrigation and modeling water and solute transfers in the soil-crop system. In this study we used inverse modeling techniques on soil sensor measurements at depths from the soil-crop system to estimate crop coefficients. An inverse model was rigorously formulated to infer the crop coefficients and the lengths of growth stages using the measured soil water potential at depths during crop growth. By applying a micro-genetic algorithm to the formulated inverse model, the optimum values of the crop coefficient and the corresponding length of growth stage were successfully deduced. It has been found that the lengths of both the initial and development growth stages of cabbage were 5 d shorter than those from the FAO56 (Irrigation and Drainage Paper by the FAO). The deduced crop coefficient for transpiration at the initial growth stage was 0.11; slightly smaller than 0.15 recommended by the FAO56, while at the mid-season growth stage, the deduced value of 0.95 was identical with the recommended value. Results show that the predictions of soil water potential using the obtained values of crop coefficients agreed well with the measurements throughout the entire growing period, indicating that the deduced crop coefficients were credible and appropriate for cabbage grown under the specific conditions of location and climate. It follows that the strategy presented in the study can enable accurate estimates of crop coefficients to be obtained from soil sensor measurements and inverse modeling techniques.     

Crop coefficients for winter wheat in a sub-humid climate regime

Estimations of evapotranspiration (ET) from natural surfaces are used in a large number of applications such as agricultural water management and water resources planning. Lack of reliable, cheap and easy-to-use instruments, associated with the chaotic and varying nature of the meteorological and plant physiological factors influencing ET cause these estimations to be based on calculated values rather than the measured ones. The two-step approach where ET from a reference crop is calculated and multiplied by empirical crop coefficients to obtain ET from a crop has gained wide acceptance. Daily coefficients for a winter wheat crop growing under standard conditions, i.e. not short of water and growing under optimal agronomic conditions, were estimated for a cold sub-humid climate regime. One of the two methods used to estimate ET from a reference crop required net radiation (R_n) as input. Two sets of coefficients were used for calculating R_n. Weather data from a meteorological station was used to estimate R_n and ET from the reference crop. The winter wheat ET was measured using an eddy covariance system during the main parts of the growing seasons 2004 and 2005. The meteorological data and field measurements were quality controlled and discarded from the analysis if flagged for errors. Daily values of ET from the reference crop and winter wheat calculated from hourly values were used to calculate the crop coefficients. Average daily crop coefficients were in the 1.1–1.15 range during mid-season with standard deviations ranging from 0.13 to 0.23 for both years. These values exceed values used in some sub-humid climate regime studies, but agree well with values from the international literature.     

Irrigation crop coefficients for lowland rice

Meteorological and lysimetric data for a period of nine years were used to develop crop coefficients for rice grown under lowland conditions in a sub-humid tropical climate in India. The estimated crop coefficients were found to be higher than those values recommended by FAO. A crop coefficient model with basal coefficient, moisture availability coefficient and surface wetness coefficient terms has been proposed and found suitable. On most counts, the moisture availability coefficient was found to be near unity and the wetness coefficient was found to be significant. The basal crop coefficients for lowland rice have also been presented for practical use with the proposed models.     

The dual crop coefficient approach using a density factor to simulate the evapotranspiration of a peach orchard: SIMDualKc model versus eddy covariance measurements

The dual crop coefficient approach accounts separately for plant transpiration and soil evaporation by using the basal crop coefficient and the evaporation coefficient, respectively. The SIMDualKc model, which performs the soil water balance simulation with estimation of the actual crop evapotranspiration (ET) with the dual crop coefficient approach, was applied to a drip-irrigated peach orchard under Mediterranean conditions. Orchard ET was obtained with the eddy covariance technique, which was subsequently correlated with tree transpiration estimated from sap flow measurements and soil evaporation determined with microlysimeters, thus providing ET for the whole irrigation season. Two years of field observations were used for model calibration and validation using those ET measurements and taking into account the fraction of ground covered by trees through a density factor which adjusts the basal crop coefficient. Model fitting relative to ET observations during calibration and validation provided indices of agreement averaging 0.90, coefficients of regression close to 1.0, root mean square errors around 0.41 mm and average absolute errors of 0.32 mm. Model fitting relative to transpiration and to soil evaporation produced similar results, so showing the adequateness of modelling.     

Crop coefficients and water use for cowpea in the San Joaquin Valley of California

To improve irrigation planning and management, a modified soil water balance method was used to determine the crop coefficients and water use for cowpea (Vigna unguiculata (L.) Walp.) in an area with a semi-arid climate. A sandy 0.8-ha field was irrigated with a subsurface drip irrigation system, and the soil moisture was closely monitored for two full seasons. The procedure used was one developed for cotton by DeTar [DeTar, W.R., 2004. Using a subsurface drip irrigation system to measure crop water use. Irrig. Sci. 23, 111-122]. Using a test and validate procedure, we first developed a double sigmoidal model to fit the data from the first season, and then we determined how well the data from the second season fit this model. One of the results of this procedure was that during the early part of the season, the crop coefficients were more closely related to days-after-planting (DAP) than to growing-degree-days (GDDs). For the full season, there was little difference in correlations for the various models using DAP and GDD. When the data from the two seasons were merged, the average value for the crop coefficient during the mid-season plateau was 0.986 for the coefficient used with pan evaporation, and it was 1.211 for the coefficient used with a modified Penman equation for ET₀ from the California Irrigation Management and Information System (CIMIS). For the Penman-Monteith (P-M) equation, the coefficient was 1.223. These coefficients are about 11% higher than for cotton in the same field with the same irrigation system. A model was developed for the merged data, and when it was combined with the normal weather data for this area, it was possible to predict normal water use on a weekly, monthly and seasonal basis. The normal seasonal water use for cowpea in this area was 669 mm. One of the main findings was that the water use by the cowpea was more closely correlated with pan evaporation than it was with the reference ET from CIMIS or P-M.     

Cover crop evapotranspiration under semi-arid conditions using FAO dual crop coefficient method with water stress compensation

Cover cropping is a common agro-environmental tool for soil and groundwater protection. In water limited environments, knowledge about additional water extraction by cover crop plants compared to a bare soil is required for a sustainable management strategy. Estimates obtained by the FAO dual crop coefficient method, compared to water balance-based data of actual evapotranspiration, were used to assess the risk of soil water depletion by four cover crop species (phacelia, hairy vetch, rye, mustard) compared to a fallow control. A water stress compensation function was developed for this model to account for additional water uptake from deeper soil layers under dry conditions. The average deviation of modelled cumulative evapotranspiration from the measured values was 1.4% under wet conditions in 2004 and 6.7% under dry conditions in 2005. Water stress compensation was suggested for rye and mustard, improving substantially the model estimates. Dry conditions during full cover crop growth resulted in water losses exceeding fallow by a maximum of +15.8% for rye, while no substantially higher water losses to the atmosphere were found in case of evenly distributed rainfall during the plant vegetation period with evaporation and transpiration concentrated in the upper soil layer. Generally the potential of cover crop induced water storage depletion was limited due to the low evaporative demand when plants achieved maximum growth. These results in a transpiration efficiency being highest for phacelia (5.1 g m⁻² mm⁻¹) and vetch (5.4 g m⁻² mm⁻¹) and substantially lower for rye (2.9 g m⁻² mm⁻¹) and mustard (2.8 g m⁻² mm⁻¹). Taking into account total evapotranspiration losses, mustard performed substantially better. The integration of stress compensation into the FAO crop coefficient approach provided reliable estimates of water losses under dry conditions. Cover crop species reducing the high evaporation potential from a bare soil surface in late summer by a fast canopy coverage during early development stages were considered most suitable in a sustainable cover crop management for water limited environments.     

Designing crop technology for a future climate: An example using response surface methodology and the CERES-Wheat model

Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO₂ environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO₂ conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m⁻² than the check cultivar under normal CO₂ conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.     

不同地下水埋深时甜椒需水量及作物系数试验研究

采用排水式蒸渗仪试验,研究了不同地下水埋深时,甜椒需水量和地下水利用量的变化规律及与外界环境因子的关系。分析和模拟了甜椒作物系数,并与FAO-56推荐作物系数值进行了比较。结果表明,地下水埋深为0.6~0.9m时,地下水与降雨利用量占需水量的40%~50%,灌溉量较低。地下水埋深较浅时,需水量与地下水利用量与蒸发量、气温和地温具有显著的线性关系。地下水埋深较深时,需水量主要受降雨的影响,与环境因子的相关性较小;地下水利用量与蒸发量、气温、地温及饱和水气压差仍具有显著的线性关系。甜椒全生育期作物系数为1.35,与移栽后旬数、地温和需水系数分别表现出3次、2次和3次多项式的关系。生长中期和后期,作物系数分别为1.25和1.25~1.1,高于FAO-56推荐值。研究结果为蔬菜类作物节水灌溉制度的制定和高效灌溉管理提供参考。     

Evaluation of the RZWQM-CERES-Maize hybrid model for maize production

The root zone water quality model (RZWQM) was developed primarily for water quality research with a generic plant growth module primarily serving as a sink for plant nitrogen and water uptake. In this study, we coupled the CERES-Maize Version 3.5 crop growth model with RZWQM to provide RZWQM users with the option for selecting a more comprehensive plant growth model. In the hybrid model, RZWQM supplied CERES with daily soil water and nitrogen contents, soil temperature, and potential evapotranspiration, in addition to daily weather data. CERES-Maize supplied RZWQM with daily water and nitrogen uptake, and other plant growth variables (e.g., root distribution and leaf area index). The RZWQM-CERES hybrid model was evaluated with two well-documented experimental datasets distributed with DSSAT (Decision Support System for Agrotechnology Transfer) Version 3.5, which had various nitrogen and irrigation treatments. Simulation results were compared to the original DSSAT-CERES-Maize model. Both models used the same plant cultivar coefficients and the same soil parameters as distributed with DSSAT Version 3.5. The hybrid model provided similar maize prediction in terms of yield, biomass and leaf area index, as the DSSAT-CERES model when the same soil and crop parameters were used. No overall differences were found between the two models based on the paired t test, suggesting successful coupling of the two models. The hybrid model offers RZWQM users access to a rigorous new plant growth model and provides CERES-Maize users with a tool to address soil and water quality issues under different cropping systems.