PM Equation Research Articles

Testing hourly reference evapotranspiration approaches using lysimeter measurements in a semiarid climate

Numerous approaches have been developed for estimating hourly reference evapotranspiration ET0, most of which require numerous meteorological data. In many areas, the necessary data are lacking and new techniques are required. The objectives of this study are: (1) to develop artificial neural networks for estimating hourly reference evapotranspiration from limited weather data; (2) to evaluate the reliability of obtained artificial neural networks (ANNs) and Food and Agricultural Organization—56 Penman Monteith (FAO-56 PM) equation compared to the lysimeter measurements; (3) to test the performance of the FAO-56 PM equation for hourly daytime periods using rc=70 s m−1 (PM70) and using a lower rc=50 s m−1 (PM50); and (4) to evaluate the reliability of obtained ANNs compared to the FAO-56 PM equation using an hourly dataset from a variety of locations. The accuracy of two reduced-set artificial neural networks (ANNTR and ANNTHR) and two FAO-56 Penman-Monteith equations with different canopy resistance values (PM50 and PM70) was assessed using hourly lysimeter data from Davis, California. The ANNTR required only two parameters (temperature and radiation) as inputs. Temperature, humidity and (Rn−G) term were used as inputs in the ANNTHR. The ANNTR and PM50 were best at estimating hourly grass ET0. The ANNTR approach was additionally tested using hourly FAO-56 PM ET0 data from California Irrigation Management Information System (CIMIS) dataset. The overall results recommended Radial Basis Function (RBF) network for estimating hourly ET0 from limited weather data. Also, the results support the introduction of new value for canopy resistance (rc=50 s m−1) in the hourly FAO-56 PM equation.

Prediction of annual reference evapotranspiration using climatic data

Abstract It is important to determine how well ETo can be estimated from easily observed Epan (free water evaporation measured by a pan) measurements and the other climatic data. Our objectives are to predict annual ETo with Epan data (with a calibrated kp (=ETo/Epan)) and with a 4-variable regression function method. The significance of the trends of Epan, ETo and kp series were detected. The whole data series (ETo, Epan, mean temperature, sunlight hours, relative humidity and wind speed) were divided into the early (L-5) years for calibrating kp and coefficients of a 4-variable function and the last 5 years for predicting ETo. From the results, significance of series trends decreased when using the modified Mann–Kendall (MMK) test compared to the Mann–Kendall (MK) method. For ETo, five out of six sites showed significant trends according to the MK statistic Z, and two sites were significant in trend combining with the MMK statistic Z*(j). For Epan, two sites were significant in trends according to Z, and zero sites were significant in trends combining with Z*(j). For kp, two sites were significant in trends according to Z, and no sites were significant in trends combining with Z*(j). Thus the calibrated kp can be treated as a constant when using the Epan method. The predicted annual ETo using the Epan and the multi-variable methods showed generally good agreements with the estimated annual ETo (based on monthly PM equation) with low relative errors (RE). Mean ETo values were well predicted by both methods. When using Epan method, RE ranged from −14.7 to −3.3% for Urumqi, from 17.6 to 21.7% for Xning, from 1.8 to 10.7% for Lanzhou, from 4.7 to 17.0% for Huhehaote, from −7.4 to 9.1% for Beijing, and from −8.6 to 2.3% for Changchun. RE of predicting annual ETo with 4-variable regression function were even lower compared to Epan method. The main error source of the predictions came from the deviation between calibrated kp and the actual kp of the predicted years when using Epan method and from random fluctuations of climatic data when using the 4-varible regression function. In conclusion, the MMK test was a robust method for trend detection because it considered serial time dependence. Insignificant trend of the kp series supports the choice of a mean value as the calibrated kp and for ETo predictions. The Epan method is recommended for prediction of annual ETo.

Evaluation of an open portable chamber system for measuring cover crop water use in a vineyard and comparison with a mini-lysimeter approach

Cover crops are largely used in viticultural areas because of the many positive agronomic and environmental benefits they provide. However, there is insufficient data describing the amount of water they use. A portable chamber used as an open measurement system and its suitability to measure the cover crop evapotranspiration ( E) in a vineyard are described in this study. The performance of the chamber was tested by a calibration experiment ( R 2 = 0.97). The lowest air flow rate used (9.2 l s −1) was found to be suitable to limit the chamber from overheating beyond 3.1 K above the outside temperature. Furthermore, an experiment was designed to compare the daily cover crop ( Festuca arundinacea var. barfelix) water use measured by the chamber system with measurements using a mini-lysimeter (ML) method and with estimates using the FAO-56 PM equation (Eo). The experiment was carried out in one inter row of a vineyard over the course of 4 days following an irrigation event. Although the field experiment was limited to 4 days, the results obtained together with the calibration trials support the possibility of the chamber being a useful tool for measuring the cover crop E. The ability of the MLs to represent the water use of the cover crop in the rest of the vineyard was limited to the first two days of the experiment, after which time the soil water content inside the containers was significantly ( p = 0.007, p = 0.03) lower than in the surrounding field.

CROP-CLIMATE COUPLING IN GREENHOUSES. CHARACTERIZATION AND ANALYSIS

CROP-CLIMATE COUPLING IN GREENHOUSES. CHARACTERIZATION AND ANALYSIS