Simulation of transpiration, drainage, N uptake, nitrate leaching, and N uptake concentration in tomato grown in open substrate

Free-drainage or “open” substrate system used for vegetable production in greenhouses is associated with appreciable NO₃⁻ leaching losses and drainage volumes. Simulation models of crop N uptake, N leaching, water use and drainage of crops in these systems will be useful for crop and water resource management, and environmental assessment. This work (i) modified the TOMGRO model to simulate N uptake for tomato grown in greenhouses in SE Spain, (ii) modified the PrHo model to simulate transpiration of tomato grown in substrate and (iii) developed an aggregated model combining TOMGRO and PrHo to calculate N uptake concentrations and drainage NO₃⁻ concentration. The component models simulate NO₃⁻-N leached by subtracting simulated N uptake from measured applied N, and drainage by subtracting simulated transpiration from measured irrigation. Three tomato crops grown sequentially in free-draining rock wool in a plastic greenhouse were used for calibration and validation. Measured daily transpiration was determined by the water balance method from daily measurements of irrigation and drainage. Measured N uptake was determined by N balance, using data of volumes and of concentrations of NO₃⁻ and NH₄⁺ in applied nutrient solution and drainage. Accuracy of the two modified component models and aggregated model was assessed by comparing simulated to measured values using linear regression analysis, comparison of slope and intercept values of regression equations, and root mean squared error (RMSE) values. For the three crops, the modified TOMGRO provided accurate simulations of cumulative crop N uptake, (RMSE = 6.4, 1.9 and 2.6% of total N uptake) and NO₃⁻-N leached (RMSE = 11.0, 10.3, and 6.1% of total NO₃⁻-N leached). The modified PrHo provided accurate simulation of cumulative transpiration (RMSE = 4.3, 1.7 and 2.4% of total transpiration) and cumulative drainage (RMSE = 13.8, 6.9, 7.4% of total drainage). For the four cumulative parameters, slopes and intercepts of the linear regressions were mostly not statistically significant (P < 0.05) from one and zero, respectively, and coefficient of determination (r²) values were 0.96-0.98. Simulated values of total drainage volumes for the three crops were +21, +1 and −13% of measured total drainage volumes. The aggregated TOMGRO-PrHo model generally provided accurate simulation of crop N uptake concentration after 30-40 days of transplanting, with an average RMSE of approximately 2 mmol L⁻¹. Simulated values of average NO₃⁻ concentration in drainage, obtained with the aggregated model, were −7, +18 and +31% of measured values.     

Determination of growth-stage-specific crop coefficients (Kc) of cotton and wheat

Development of crop coefficient (Kc), the ratio of crop evapotranspiration (ETc) to reference evapotranspiration (ETo), can enhance ETc estimates in relation to specific crop phenological development. This research was conducted to determine growth-stage-specific Kc and crop water use for cotton (Gossypium hirsutum) and wheat (Triticum aestivum) at the Texas AgriLife Research field at Uvalde, TX, USA from 2005 to 2008. Weighing lysimeters were used to measure crop water use and local weather data were used to determine the reference evapotranspiration (ETo). Seven lysimeters, weighing about 14 Mg, consisted of undisturbed 1.5 m × 2.0 m × 2.2 m deep soil monoliths. Six lysimeters were located in the center of a 1-ha field beneath a linear-move sprinkler system equipped with low energy precision application (LEPA) and a seventh lysimeter was established to measure reference grass ETo. Crop water requirements, Kc determination, and comparison to existing FAO Kc values were determined over a 2-year period on cotton and a 3-year period on wheat. Seasonal total amounts of crop water use ranged from 689 to 830 mm for cotton and from 483 to 505 mm for wheat. The Kc values determined over the growing seasons varied from 0.2 to 1.5 for cotton and 0.1 to 1.7 for wheat. Some of the values corresponded and some did not correspond to those from FAO-56 and from the Texas High Plains and elsewhere in other states. We assume that the development of regionally based and growth-stage-specific Kc helps in irrigation management and provides precise water applications for this region.     

Enhancing the Simplified Surface Energy Balance (SSEB) approach for estimating landscape ET: Validation with the METRIC model

Evapotranspiration (ET) can be derived from satellite data using surface energy balance principles. METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) is one of the most widely used models available in the literature to estimate ET from satellite imagery. The Simplified Surface Energy Balance (SSEB) model is much easier and less expensive to implement. The main purpose of this research was to present an enhanced version of the Simplified Surface Energy Balance (SSEB) model and to evaluate its performance using the established METRIC model. In this study, SSEB and METRIC ET fractions were compared using 7 Landsat images acquired for south central Idaho during the 2003 growing season. The enhanced SSEB model compared well with the METRIC model output exhibiting an r² improvement from 0.83 to 0.90 in less complex topography (elevation less than 2000 m) and with an improvement of r² from 0.27 to 0.38 in more complex (mountain) areas with elevation greater than 2000 m. Independent evaluation showed that both models exhibited higher variation in complex topographic regions, although more with SSEB than with METRIC. The higher ET fraction variation in the complex mountainous regions highlighted the difficulty of capturing the radiation and heat transfer physics on steep slopes having variable aspect with the simple index model, and the need to conduct more research. However, the temporal consistency of the results suggests that the SSEB model can be used on a wide range of elevation (more successfully up 2000 m) to detect anomalies in space and time for water resources management and monitoring such as for drought early warning systems in data scarce regions. SSEB has a potential for operational agro-hydrologic applications to estimate ET with inputs of surface temperature, NDVI, DEM and reference ET.     

Considering sink strength to model crop production under elevated atmospheric CO2

Climatic changes and elevated atmospheric CO₂ concentrations will affect crop growth and production in the near future. Rising CO₂ concentration is a novel environmental aspect that should be considered when projections for future agricultural productivity are made. In addition to a reducing effect on stomatal conductance and crop transpiration, elevated CO₂ concentration can stimulate crop production. The magnitude of this stimulatory effect (‘CO₂ fertilization’) is subject of discussion. In this study, different calculation procedures of the generic crop model AquaCrop based on a foregoing theoretical framework and a meta-analysis of field responses, respectively, were evaluated against experimental data of free air CO₂ enrichment (FACE) environments. A flexible response of the water productivity parameter of the model to CO₂ concentration was introduced as the best option to consider crop sink strength and responsiveness to CO₂. By varying the response factor, differences in crop sink capacity and trends in breeding and management, which alter crop responsiveness, can be addressed. Projections of maize (Zea mays L.) and potato (Solanum tuberosum L.) production reflecting the differences in responsiveness were simulated for future time horizons when elevated CO₂ concentrations and climatic changes are expected. Variation in future yield potential associated with sink strength could be as high as 27% of the total production. Thus, taking into account crop sink strength and variation in responsiveness is equally relevant to considering climatic changes and elevated CO₂ concentration when assessing future crop production. Indicative values representing the crop responsiveness to elevated CO₂ concentration were proposed for all crops currently available in the database of AquaCrop as a first step in reducing part of the uncertainty involved in modeling future agricultural production.     

基于双线性理论的参考作物蒸发蒸腾量估算

利用成都、乐山、内江和雅安在1951--2000年的气象资料和地理参数,用Penman-Monteith公式计算蒸发蒸腾量（ETo）,将双线性理论用于EL的计算,建立了多个计算ETo的双线性模型,进一步利用双线性模型计算的E丁0再建立双线性模型,在已建立的双线性模型基础上,又建立了简化双线性模型。各双线性模型与P-M计...     

Characterizing leaf gas exchange responses of cotton to full and limited irrigation conditions

Plant responses to water deficit need to be monitored for producing a profitable crop as water deficit is a major constraint on crop yield. The objective of this study was to evaluate physiological responses of cotton (Gossypium hirsutum) to various environmental conditions under limited water availability using commercially available varieties grown in South Texas. Soil moisture and variables of leaf gas exchange were measured to monitor water deficit for various varieties under different irrigation treatments. Lint yield and growth variables were also measured and correlations among growth parameters of interest were investigated. Significant differences were found in soil moisture, leaf net assimilation (A_n), stomatal conductance (g), transpiration rate (T_r), and instantaneous water use efficiency (WUE_i) among irrigation treatments in 2006 while no significant differences were found in these parameters in 2007. Some leaf gas exchange parameters, e.g., T_r, and leaf temperature (T_L) have strong correlations with A_n and g. A_n and WUE were increased by 30–35% and 30–40%, respectively, at 600 μmol (CO₂) m⁻² s⁻¹ in comparison with 400 μmol (CO₂) m⁻² s⁻¹. Lint yield was strongly correlated with g, T_r, WUE, and soil moisture at 60 cm depth. Relative A_n, T_r, and T_L started to decrease from FTSW 0.3 at 60 cm and FTSW 0.2 at 40 cm. The results demonstrate that plant water status under limited irrigation management can be qualitatively monitored using the measures of soil moisture as well as leaf gas exchange, which in turn can be useful for describing yield reduction due to water deficit. We found that using normalized A_n, T_r, and T_L is feasible to quantify plant water deficit.     

Estimation of a reliable evapotranspiration model and crop coefficient in red gram ( Cajanus cajan L .) for semi-arid environments in India

The study aims to compute the reference evapotranspiration (ETo) by six standard methods such as Penman Monteith, Modified Penman, Hargreaves, Radiation Balance, Blaney Criddle and Pan Evaporation by using the meteorological data of the All India Coordinated Research Project on Water Management at Rahuri, India (long. 74° 18′, lat. 19° 45′). These methods were compared with lysimeter crop evapotranspiration (ETc) by statistical tools. The results revealed that the total lysimeter ETc of red gram in 132 days' growing period (sowing to harvest) was 494?mm and the ETo in the above-mentioned models were 485.2, 486.9, 544.6, 547.6, 563.9 and 485.2?mm, respectively. Out of six models, ETo of Modified Penman and Pan Evaporation methods were very much close to lysimeter ETc, but the coefficient of variation was very high, i.e., 43.05% and 23.91%, respectively. But in the Hargreaves and Blaney Criddle methods, the coefficient of variation was low, i.e., 15.97% and 12.6%, respectively. Besides low coefficient of variation, these two methods require limited meteorological parameters such as minimum and maximum temperature, radiation. For generating these parameters even at regional level, minimum expenditure is involved. The crop coefficient (Kc) estimated by Hargreaves (Kc 0.90) and the Blaney Criddle (0.87) model for the entire growing season was very much close to the Food and Agricultural Organization (FAO) 56 model, and this can be used for estimating the irrigation requirement of red gram.     

单、双作物系数法计算夏玉米需水量对比研究

采用FAO-56推荐计算作物需水量的单作物系数和双作物系数方法,计算豫北安阳地区夏玉米需水量,并与实测值进行对比,分析其差异及原因。结果表明,采取单、双作物系数法计算的夏玉米需水总量与实测值相对误差分别为14．8％、11．7％,双作物系数法更接近实测值;采取单.双作物系数法2种方法计算的夏玉米逐日及月均需水量具有较好的一致性,相关系数（r）为O．78、0．85。     

宁夏近59年参考作物腾发量时空变化特征分析

依据1951-2009年宁夏回族自治区10个气象站气象资料,运用Penman-Monteith方程计算参考作物腾发量（ET0）月值系列。利用克里金插值、Mann-Kendall突变检验及气候趋势系数等方法分析了宁夏E瓦的时空变化特征。结果表明,宁夏地区ETo自北向南逐渐减小,全区多年平均值为982．90mm／a 16月...     

Comparison of artificial neural network models and empirical and semi-empirical equations for daily reference evapotranspiration estimation in the Basque Country (Northern Spain)

Reference evapotranspiration (ETo) determination is a key factor for water balance and irrigation scheduling. Evapotranspiration can be measured directly by high-cost micrometeorological techniques, or estimated by mathematical models. The combination equation of Penman–Monteith, modified 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] (PM56), is the reference equation for ETo estimation. This method is also appropriate for the calibration of other ETo estimation equations. The utilization of these calibrated ETo equations is recommended in the absence of data of any of the meteorological parameters necessary for the application of PM56. In addition to the use of classic ETo equations, the adoption of artificial neural network (ANN) models for the estimation of daily ETo has been evaluated in this study. ANNs are mathematical models, whose architecture has been inspired by biological neural networks. They are highly appropriate for the modelling of non-linear processes, which is the case of the evapotranspiration process. Seven ANNs (with different input combinations) have been implemented and compared with ten locally calibrated empirical and semi-empirical ETo equations and variants of these equations (with estimated meteorological parameters as inputs). The comparisons have been based on statistical error techniques, using PM56 daily ETo values as a reference. ANNs have obtained better results than the locally calibrated ETo equations in the three groups of evaluated methods: temperature and/or relative humidity-based methods (0.385 mm d⁻¹ of root mean square error (RMSE)), solar radiation-based methods (0.238 mm d⁻¹ of RMSE), and methods based on similar requirements to those of PM56 except for the estimation of solar radiation and/or relative humidity (0.285 mm d⁻¹ of RMSE).