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Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes.

ABSTRACT: Alternative models for the estimation of reference evapotranspiration (ETo) are typically assessed using traditional error metrics, such as root mean square error (RMSE), which may not be sufficient to select the best model for irrigation scheduling purposes. Thus, this study analyzes the performance of the original and calibrated Hargreaves-Samani (HS), Romanenko (ROM) and Jensen-Haise (JH) equations, initially assessed using traditional error metrics, for use in irrigation scheduling, considering the simulation of different irrigation intervals/time scales. Irrigation scheduling was simulated using meteorological data collected in Viçosa-MG and Mocambinho-MG, Brazil. The Penman-Monteith FAO-56 equation was used as benchmark. In general, the original equations did not perform well to estimate ETo, except the ROM and HS equations used at Viçosa and Mocambinho, respectively. Calibration and the increase in the time scale provided performance gains. When applied in irrigation scheduling, the calibrated HS and JH equations showed the best performances. Even with greater errors in estimating ETo, the calibrated HS equation performed similarly or better than the calibrated JH equation, as it had errors with greater potential to be canceled during the soil water balance. Finally, in addition to using error metrics, the performance of the models throughout the year should be considered in their assessment. Furthermore, simulating the application of ETo models in irrigation scheduling can provide valuable information for choosing the most suitable model.

SUBMITTER: Ferreira LB

PROVIDER: S-EPMC7799801 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes.

Ferreira Lucas Borges LB da Cunha Fernando França FF Zanetti Sidney Sara SS

PloS one 20210111 1

Alternative models for the estimation of reference evapotranspiration (ETo) are typically assessed using traditional error metrics, such as root mean square error (RMSE), which may not be sufficient to select the best model for irrigation scheduling purposes. Thus, this study analyzes the performance of the original and calibrated Hargreaves-Samani (HS), Romanenko (ROM) and Jensen-Haise (JH) equations, initially assessed using traditional error metrics, for use in irrigation scheduling, consider ...[more]

PMID: 33428674

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Project description:Reference evapotranspiration (ETo) is essential for irrigation practices and the management of water resources and plays a vital role in agricultural and hydro-meteorological studies. The FAO-56 Penman-Monteith (PM) equation, recommended as the sole standard method of calculating ETo by the Food and Agriculture Organization of the United Nations (FAO), is the most commonly used and accurate model to determine the ETo and evaluate ETo equations. However, it requires many meteorological variables, often restricting its applicability in regions with poor or missing meteorological observations. Many empirical and semi-empirical equations have been developed to predict the ET0 from numerous meteorological data. The FAO-24 Pan method is commonly used worldwide to estimate ETo because it is simple and requires only pan coefficients. However, pan coefficients (Kpan) should be determined accurately to estimate ET0 using the FAO-24 Pan method. As the accuracy and reliability of the Kpan models can be different from one location to another, they should be tested or calibrated for different climates and surrounding conditions. In this study, the performance of the eight Kpan models was evaluated using 22-year daily climate data for the summer growing season in Adana, which has a Mediterranean climate in Turkey. The results showed that the mean seasonal pan coefficients estimated by all Kpan models differed significantly at a 1% significance level from those observed by FAO-56 PM according to the two-tail z test. In the study, ETo values estimated by Kpan models were compared against those obtained by the FAO-56 PM equation. The seasonal and monthly performance of Kpan models was varied, and the Wahed & Snyder model presented the best performance for ETo estimates at the seasonal scale. (RMSE = 0.550 mm d-1; MAE = 0.425 mm d-1; MBE = -0.378 mm d-1; RE = 0.134). In addition, it showed a good performance in estimating ETo on a monthly scale. The Orang model showed the lowest performance in estimating ETo among all models, with a very high relative error on the seasonal scale. (RMSE = 1.867 mm d-1; MAE = 1.806 mm d-1; MBE = -1.806 mm d-1; RE = 0.455). In addition, it showed the poorest performance on a monthly scale. Hence, the Wahed & Snyder model can be considered to estimate ETo under Adana region conditions after doing the necessary calibration.

Project description:The reference evapotranspiration (ETo) is considered one of the primary variables for water resource management, irrigation practices, agricultural and hydro-meteorological studies, and modeling different hydrological processes. Therefore, an accurate prediction of ETo is essential. A large number of empirical methods have been developed by numerous scientists and specialists worldwide to estimate ETo from different climatic variables. The FAO56 Penman-Monteith (PM) is the most accepted and accurate model to estimate ETo in various environments and climatic conditions. However, the FAO56-PM method requires radiation, air temperature, air humidity, and wind speed data. In this study in Adana Plain, which has a Mediterranean climate for the summer growing season, using 22-year daily climatic data, the performance of the FAO56-PM method was evaluated with different combinations of climatic variables when climatic data were missing. Additionally, the performances of Hargreaves-Samani (HS) and HS (A&G) equations were assessed, and multiple linear regression models (MLR) were developed using different combinations of climatic variables. The FAO56-PM method could accurately estimate daily ETo when wind speed (U) and relative humidity (RH) data were unavailable, using the procedures suggested by FAO56 Paper (RMSEs were smaller than 0.4 mm d-1, and percent relative errors (REs) were smaller than 9%). Hargreaves-Samani (A&G) and HS equations could not estimate daily ETo accurately according to the statistical indices (RMSEs = 0.772-0.957 mm d-1; REs (%) = 18.2-22.6; R2 = 0.604-0.686, respectively). On the other hand, MLR models' performance varied according to a combination of different climatic variables. According to t-stat and p values of independent variables for MLR models, solar radiation (Rs) and sunshine hours (n) variables had more effect on estimating ETo than other variables. Therefore, the models that used Rs and n data estimated daily ETo more accurately than the others. RMSE values of the models that used Rs were between 0.288 to 0.529 mm d-1; RE(%) values were between 6.2%-11.5% in the validation process. RMSE values of the models that used n were between 0.457 to 0.750 mm d-1; RE(%) values were between 9.9%-16.3% in the validation process. The models based only on air temperature had the worst performance (RMSE = 1.117 mm d-1; RE(%) = 24.2; R2 = 0.423).

Project description:Precision irrigation technologies using sensor feedback can provide dynamic decision support to help farmers implement DI strategies. However, few studies have reported on the use of these systems for DI management. This two-year study was conducted in Bushland, Texas to investigate the performance of the geographic information (GIS) based irrigation scheduling supervisory control and data acquisition (ISSCADA) system as a tool to manage deficit irrigation scheduling for cotton (Gossypim hirsutum L). Two different irrigation scheduling methods automated by the ISSCADA system - (1) a plant feedback (designated C) - based on integrated crop water stress index (iCWSI) thresholds, and (2) a hybrid (designated H) method, created to combine soil water depletion and the iCWSI thresholds, were compared with a benchmark manual irrigation scheduling (M) that used weekly neutron probe readings. Each method applied irrigation at levels designed to be equivalent to 25%, 50% and 75% replenishment of soil water depletion to near field capacity (designated I25, I50 and I75) using the pre-established thresholds stored in the ISSCADA system or the designated percent replenishment of soil water depletion to field capacity in the M method. Fully irrigated and extremely deficit irrigated plots were also established. Relative to the fully irrigated plots, deficit irrigated plots at the I75 level for all irrigation scheduling methods-maintained seed cotton yield, while saving water. In 2021, the irrigation savings was a minimum of 20%, while in 2022, the minimum savings was 16%. Comparing the performance of deficit irrigation scheduling between the ISSCADA system and the manual method showed that crop response for all three methods were statistically similar at each irrigation level. Because the M method requires labor intensive and expensive use of the highly regulated neutron probe, the automated decision support provided by the ISSCADA system could simplify deficit irrigation management of cotton in a semi-arid region.

Project description:The electrical response of plants to environmental stimuli can be measured and quantitatively related to the intensity of several stimulating sources, like temperature, solar radiation, soil water content, evapotranspiration rates, sap flow and dendrometric cycles. These relations can be used to assess the influence of different environmental situations on soil water availability to plants, defined as a steady state condition between leaf transpirative flow and soil water flow to plant roots. A restricted soil water flow due to soil dryness can trigger water stress in plants, if the atmospheric evaporative demand is high, causing partial stomata closure as a physiological response to avoid plant dehydration; water stressed and unstressed plants manifest a differential electrical response. Real time plant electrical response measurements can anticipate actions that prevent the plant reaching actual stress conditions, optimizing stomata gas exchange and photosynthetic rates. An electrophysiological sensor developed in this work, allows remote real-time recording information on plant electrical potential (EP) in the field, which is highly related to EP measurements obtained with a laboratory Keithley voltmeter sensor used in an highly controlled experimental setup. Our electrophysiological sensor is a wireless, autonomous devise, which transmits EP information via Internet to a data server. Using both types of sensors (EP electrodes with a Keithley voltmeter and the electrophysiological sensor), we measured in real time the electrical responses of Persea americana and Prunus domestica plants, to induced water deficits. The differential response for 2 scenarios: irrigation and water restriction is identified by a progressive change in slope on the daily maximal and minimal electric signal values in stressed plants, and a zero-slope for similar signals for well-watered plants. Results show a correspondence between measured signals obtained by our electrophysiological sensor and the EP electrodes connected to the Keithley voltmeter in each irrigation stage. Also, both sensors show a daily cyclical signal (circadian cycle).

Dataset Information

Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes.

Publications

Selecting models for the estimation of reference evapotranspiration for irrigation scheduling purposes.

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