Crop Evapotranspiration Model Research Articles

Estimation of Crop-coefficients and Evapotranspiration of Field Pea (Pisum sativum L.) Using Lysimeter and Empirical Models under Temperate Climate

During Rabi 2020-21, a field experiment was conducted at SKUAST-K, Shalimar, India, focusing on field Pea (Pisum sativum L.). The aim of this study was to determine the water requirement and single crop coefficient (Kc) of pea using a lysimeter setup. Four empirical models were employed to calculate the reference evapotranspiration and were then compared with the actual crop evapotranspiration at different growth stages. The Kc values for field pea were 0.50, 0.80, 1.15, and 1.10 during the initial, development, mid-season and late season stages, respectively. The water requirement was found as 239.9 mm for the whole cropping period of the pea. Among the models, the Penman Montieth crop evapotranspiration model exhibited the closest agreement with the corresponding values obtained in the field through water balance study, yielding RMSE, RSR, and NSE values of 0.97, 9.5, and 11.6, respectively. These findings highlight the significance of using Penman Monteith crop evapotranspiration model for estimating crop evapotranspiration in temperate regions.

Comparative assessment of reference crop evapotranspiration models and its sensitivity to meteorological variables in Peninsular Malaysia

Comparative assessment of reference crop evapotranspiration models and its sensitivity to meteorological variables in Peninsular Malaysia

Decision Support System for Variable Rate Irrigation Based on UAV Multispectral Remote Sensing.

Rational utilization of water resources is one of the major methods of water conservation. There are significant differences in the irrigation needs of different agricultural fields because of their spatial variability. Therefore, a decision support system for variable rate irrigation (DSS-VRI) by center pivot was developed. This system can process multi-spectral images taken by unmanned aerial vehicles (UAVs) and obtain the vegetation index (VI). The crop evapotranspiration model (ETc) and crop water stress index (CWSI) were obtained from their established relationships with the VIs. The inputs to the fuzzy inference system were constituted with ETc, CWSI and precipitation. To provide guidance for users, the duty-cycle control map was outputted using ambiguity resolution. The control command contained in the map adjusted the duty cycle of the solenoid valve, and then changed the irrigation amount. A water stress experiment was designed to verify the rationality of the DSS-VRI. The results showed that the more severe water stress is, the more irrigation is obtained, consistent with the expected results. Meanwhile, a user-friendly software interface was developed to implement the DSS-VRI function.

Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ψstem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an R2 ≥ 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm·day−1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

典型半干旱区干旱胁迫作用对春小麦蒸散及其作物系数的影响特征

An understanding of evapotranspiration, which is an important component of the surface water cycle, is critical in water resource management and planning, and in meeting the water requirements of agriculture and ecological systems. Although the methods for calculating crop evapotranspiration are advanced in humid areas, the understanding of evapotranspiration in semi-arid areas is developing because evapotranspiration is significantly affected by drought. The classic crop evapotranspiration model and crop coefficients cannot be applied to estimations of actual evapotranspiration, which is rarely studied now. In this study, we analyzed differences between lysimeter evapotranspiration and evapotranspiration that was estimated with Food and Agriculture Organization (FAO)-recommended crop coefficients. In addition, changes in evapotranspiration according to the degree of drought stress were analyzed with lysimeters, evaporating dishes, ultrasonic and eddy instruments, and conventional meteorological data in spring wheat fields in typical semi-arid zones of the Dingxi arid ecological environment comprehensive scientific experiment station, which is located in the Loess Plateau. The variations in spring wheat reference evapotranspiration/pan evaporation and actual evapotranspiration/pan evaporation according to the degree of drought stress and the effects of drought stress on the spring wheat crop coefficients in this area were studied. Because crop evapotranspiration is significantly affected by drought stress in semi-arid areas, the differences between lysimeter evapotranspiration and evaporation that was estimated with FAO-recommended crop coefficients were very significant. Crop coefficients were highly dependent on drought stress, and this dependence increased according to the reduction in the degree of drought stress. In addition, its sensitivity was significantly lower after the drought stress reached about 0.7. In this study, crop coefficients that were modified during the crop development and exuberant period were far below the FAO-recommended values and the Kumar correction values. The modified crop coefficients were obviously closer to the actual observed values than the spring wheat evapotranspiration values that were estimated using other crop coefficient. The coefficient of linear fitting of the modified crop coefficient and the observations was 0.98. The coefficient of determinationwas 0.45, and the standard error was 0.85. Therefore, the modified crop coefficient was effective for estimating crop evapotranspiration in semi-arid areas.

A Study on Variation of Priestley-Taylor Model Parameter in Rain Fed Spring Maize Field

The study of Priestley-Taylor (PT) reference crop evapotranspiration model coefficient (α) in local is of great significance in semi-arid agricultural water resources efficient use and precision irrigation in corn. Here, based on the FAO (1998)-recommended Penman-Monteith (PM) reference crop evapotranspiration as a standard method, water and heat exchange and its estimated parameters were determined by eddy covariance technique and Priestley-Taylor model under local climatic conditions. The results indicated that the estimated values of reference crop evapotranspiration (ET0-PT 1.26) in gained by PT mode-recommended coefficient (α = 1.26) lowed by 21.2% during non-growth stages (from November to April next year), and reached an average of 5.5% above PM model reference crop evapotranspiration (ET0-PM) during May to September. The local PT model coefficient α value was 1.15 ± 0.06. The gained average PT mode coefficient at noon during growth stages showed a peak trend with the highest value 0.67 ± 0.08 at tasseling to flowering stage and with the lowest value 0.26 ± 0.13 at seedling stage. In conclusion, the reference crop evapotranspiration estimated accurately by PT mode in the semi-arid climate area, a local PT parameter is required to gain firstly.

Variation of Priestley-Taylor Model Parameter in Rain Fed Spring Maize Field

The study on Priestley-Taylor (PT) reference crop evapotranspiration model coefficient (α) in local area is of great significance in semi-arid agricultural water resources efficient use and precision irrigation in corn. Here, based on the FAO (1998)-recommended Penman-Monteith (PM) reference crop evapotranspiration as a standard method, we determined the water and heat exchange and its estimated parameters by the eddy covariance technique and Priestley-Taylor model under local climatic conditions. The results indicated that the estimated values of reference crop evapotranspiration (ET 0-PT 1.26 ) gained from PT model-recommended coefficient (α = 1.26) lowed by 21.2% on an average during non-growth stages (from November to April next year), and reached an average of 5.5% higher than those from PM model reference crop evapotranspiration (ET 0-PM ) from May to September. The local PT model coefficient α value was 1.15 ± 0.06. The average PT model coefficient at noon during growth stages showed a single peak changing trend with the highest value of 0.67 ± 0.08 from tasseling to flowering stage and with the lowest value of 0.26 ± 0.13 at seedling stage. In conclusion, if the reference crop evapotranspiration is necissery to be estimated accurately by PT model in the semiarid climate area, the local PT parameters should be studied firstly.

Corrected surface energy balance to measure and model the evapotranspiration of irrigated orange orchards in semi-arid Mediterranean conditions

In this paper, based on the analysis of a long-term energy balance monitoring programme, a Bowen ratio-based method (BR) was proposed to resolve the lack of closure of the eddy covariance technique to obtain reliable sensible (H) and latent heat fluxes (λE). Evapotranspiration (ET) values determined from the BR method (ETc,corr) were compared with the upscaled transpiration data determined by the sap flow heat pulse (HP) technique, evidencing the degree of correspondence between instantaneous transpirational flux at tree level and the micrometeorological measurement of ET at orchard level. Using the BR-corrected λE fluxes, a crop ET model implementing the Penman–Monteith approach, where the canopy surface resistance was determined from standard microclimatic variables, was applied to determine the crop coefficient values. The performance of the model was evaluated by comparing it with the sap flow HP data. The results of the comparison were satisfactory, and therefore, the proposed methodology may be considered valid for characterizing the ET process for orange orchards grown in a Mediterranean climate. By contrast to reports in the FAO 56 paper, the crop growth coefficient of the orange orchard being studied was not constant throughout the growing season.

WATER REQUIREMENT OF POMEGRANATE (PUNICA GRANATUM L.) FOR SOLAPUR DISTRICT OF MAHARASHTRA STATE

The study was carried out to select a best reference crop evapotranspiration model (ET(r)), developed crop coefficient (K(c)) and actual evapotranspiration of pomegranate (ET(c)) for Solapur (North latitude 17°10” to 18°32” and East longitude 74°42” to 76°15”) at 483.5 m asl in the semi-arid zone of Maharashtra. Six most commonly used reference crop evapotranspiration models were selected for testing their validity under the climatic conditions. The important reference evapotranspiration models are: (i) Penman-Monteith FAO-56 model, (ii) Modified Penman FAO-24 model, (iii) Hargreaves Samani model, (iv) FAO-24 Pan Evaporation model (v) Blaney Criddle model, and (vi) FAO Radiation model. For the estimation of shaded area at solar noon hour, a plywood board of 3.5×3.5 m size with grid marking of size 10×10 cm was used. Actual pomegranate evapotranspiration was determined by the crop coefficient approach where the effects of various weather conditions were incorporated into reference crop evapotranspiration and crop characteristics into crop coefficient. Testing of these models was done on the basis of the least root mean square error and regression analysis. Radiation method are higher followed by modified Penman method, Blanney Criddle, pan evaporation, Hargreaves-Samani and Penman Monteith. Out of six models the Hargreaves Samani method was found to least root mean square error under climatic conditions of Solapur region. The measured shaded area at solar noon increased from new leaf initiation to maturity of crop ranging from 0.68 to 10.80 m2 and decreased from harvesting period 10.80 to 7.43 m2. The water requirement of crop development and maturity period ranges from 32.85 to 65.75 L/tree/day. The crop coefficient values increased ranging from 0.15 to 1.20 from new leaf initiation to maturity period of the crop and the seasonal water requirement for the pomegranate crop during the kharif season varies from 9.6 to 65.75 L/tree/day. The present study is based on analysis of long term (25 years) climatic data and measured shaded area at solar noon of 5th year pomegranate orchards.

Development and Validation of GANN Model for Evapotranspiration Estimation

The present study was carried out to develop generalized artificial neural network (GANN) based reference crop evapotranspiration models corresponding to FAO-56 PM, FAO-24 Radiation, Turc, and FAO-24 Blaney–Criddle methods. The generalized ANN models were developed using the data from four California Irrigation Management Information System (CIMIS) stations, namely, Davis, Castroville, Mulberry, and West Side Field Station. The average weighted standard error of estimate (WSEE) for the developed models, namely, GANN (4-5-1), GANN (3-4-1), GANN (5-6-1), and GANN (6-7-1) corresponding to the FAO-24 Blaney–Criddle, FAO-24 Radiation, Turc, and FAO-56PM was 0.72, 0.85, 0.63, and 0.48mmday−1, respectively. The developed ANN models were applied at 2 CIMIS stations namely, Lodhi and Fresno, without any local training. The average WSEE for models GANN (4-5-1), GANN (3-4-1), GANN (5-6-1), and GANN (6-7-1) was 0.68, 0.71, 0.65, and 0.46mmday−1, respectively In addition, the GANN (4-5-1) model corresponding to FAO-24 Blaney–Criddle was directly applied to four Indian locations, namely, Hoshangabad, Gwalior, Jabalapur, and Pendra. The model gave the average WSEE of 0.57mmday−1. Based on the results it was concluded that the GANN models can be used directly to predict evapotranspiration (ETo) under the arid conditions, since they performed better than the conventional evapotranspiration (ETo) estimation method.

Comparative study of conventional and artificial neural network-based ETo estimation models

Accurate estimation of reference crop evapotranspiration (ETo) is required for several hydrological studies and thus, in the past, a number of ETo estimation methods have been developed with different degree of complexity and data requirement. The present study was carried out to develop artificial neural network (ANN) based reference crop evapotranspiration models corresponding to the ASCE’s best ranking conventional ETo estimation methods (Jensen et al. ASCE Manual and Rep. on Engrg. Pract. no. 70, 1990). Among the radiation methods, FAO-24 radiation (or Rad) method for arid and Turc method for humid region, and among the temperature methods, FAO-24 Blaney–Criddle (or BC) method were studied. The ANN architectures corresponding to the above three less data-intensive methods were developed for four CIMIS (California Irrigation Management Information System) stations, namely, Davis, Castroville, Mulberry, and West Side Field station. The comprehensive ANN architecture developed by Kumar et al. (J Irrig Drain Eng 128(4):224–233, 2002) corresponding to Penman–Monteith (PM) ETo for Davis was also tried for the other three stations. Daily meteorological data for a period of more than 10 years (01 January 1990 to 30 June 2000) were collected from these stations and were used to train, test, and validate the ANN models. Two learning schemes, namely, standard back-propagation with learning rate of 0.2 and standard back-propagation with momentum having learning rate of 0.2 and momentum term of 0.95 were considered. ETo estimation performance of the ANN models was compared with the FAO-56 PM method. It was found that the ANN models gave better closeness to FAO-56 PM ETo than the best ranking method in each category (radiation and temperature). Thus these models can be used for ETo estimation in agreement with climatic data availability, when not all required climatic variables are observed.

A water balance model for rainfed lowland rice fields emphasising lateral water movement within a toposequence

In the Mekong region, most rice paddies lie in gently sloping lowlands. An accurate estimate of paddy water availability is crucial for modelling rice ( Oryza sativa L.) productivity in such environments. However, modelling of water balance in the sloping lowlands can be difficult due to problems in estimating lateral water movement from high to low positions in the toposequence. This paper describes a semi-empirical model for estimating net lateral water flow along a toposequence of rice fields. Net lateral water flow is separated into three sub-components: (i) lateral seepage through the bunds from field to field; (ii) surface runoff over the bunds from field to field; (iii) water run-on from the catchment above the toposequence. The lateral seepage is estimated using the Dupuit equation for steady unconfined flow. Surface runoff over the bund is calculated as excess water depth above the bund height, while run-on from the catchment is calculated using a rainfall–runoff relationship. The other water balance components used in the model are rainfall (measured), paddy evapotranspiration (ET), and downward water flow (within the field and under the bund). Paddy ET is estimated using the FAO crop ET model. The downward water flow is empirically determined for soil texture groups. Simulation results showed that field water levels computed by the model varied between the bund height (maximum) and the hardpan level (minimum). The daily change in the water level was satisfactorily validated using data collected from a field experiment in a toposequence in Cambodia. The component governing the water balance in the higher toposequence positions was the downward water flow (45% of seasonal rainfall at the top of the toposequence). However, the water balance in the lower positions was affected largely by the net lateral water flow (21% of seasonal rainfall at the bottom of the toposequence). Seasonal ET was 67–69% of seasonal rainfall.

A microcomputer scheduling program for supplementary irrigation

Abstract A real-time irrigation scheduling computer package for use on farms is described. The package comprises four models; a reference crop evapotranspiration model, an actual evapotranspiration model, a soil water balance model and an irrigation forecast model. The models used have been shown to produce reliable estimates of the soil water balance, however, the predictions are sensitive to the accuracy of the input data measured on the farm. This paper summarises the experience of applying such a program to supplementary irrigation in the UK.