Crop-coefficients of tomato as derived using monolithic weighing type lysimeter in mid hill region of Meghalaya

Crop coefficients (kc) was determined for tomato (Lycopersicon esculentum Mill.) with the help of UMS-GmBH cylindrical field lysimeter of 30 cm diameter and 120 cm deep and Penman-Monteith FAO-56 model. Eight other models viz. Modified Penman Method, Hargreaves equation, Samani-Hargreaves equation, Thornthwaite equation, Solar Radiation Method, Net Radiation Method, Blaney-Criddle Method and Radiation Method were also used for estimation of ET0­ and compared with Penman-Monteith model to find out the accuracy of prediction with limited weather parameters. Scatter plot and paired t-test were used for comparison. Out of all these models, Blaney-Criddle method, Solar and Net Radiation method were found to yield similar results as given by Penman-Monteith model. The values of crop evapo-transpiration (ETc) were varying from 2.54 mm d-1 to 6.70 mm d-1. The crop-coefficients (kc) for three growth stages of tomato viz., initial, mid and maturity were found to be 0.55, 1.07 and 0.78, respectively.

Variations and Sensitivity Analysis of Reference Evapotranspiration During 2010-2019 in the Zhangye Farmland Oasis, Northwest China

Reference evapotranspiration (ET0) is an important parameter for agricultural water management in the arid Zhangye farmland oasis. However, the ET0 variations in this oasis over the last decade and meteorological forcings of these variations are unknown. This study investigated the ET0 variations during 2010-2019 in this oasis using the FAO-56 Penman-Monteith (PM) and Hargreaves equations. Results showed that the ET0 features daily and monthly variations with peak values in mid-July and an annual cycle. Although the estimated ET0 series based on the two equations have high correlations in the time domain, the Hargreaves equation always underestimates the ET0 compared to the PM equation. The yearly ET0 showed statistically significant increasing trends (90% significance level) during 2010-2019, while statistically significant increasing trends in monthly ET0 are found only in March and November. Increasing trends reflected in monthly and yearly ET0 are mainly attributed to the increasing maximum temperature and sunshine duration and decreasing relative humidity. Sensitivity analysis demonstrated that the meteorological factor to which the ET0 is most sensitive varies with time scale and equation. Moreover, regression equations used to correct the underestimation associated with the Hargreaves equation for estimating ET0 in the Zhangye farmland oasis also were constructed.

Generalized calibration of the Hargreaves equation for evapotranspiration under different climate conditions

Accurate estimation of evapotranspiration (ETo) is a key factor in weather-based irrigation scheduling methods. To estimate ETo using the Hargreaves equation, just the data on the minimum and maximum temperature and solar radiation are required. However, this procedure cannot offer consistent accuracy for different climate conditions. To attain the accuracy, calibration of the equation constants (C_Hand E_H) for different climate conditions have successfully been attempted by many researchers. Because these calibration procedures are lengthy and location-specific, there is a need of a generalized calibration method to make the Hargreaves equation more pertinent and effective. In this paper, fuzzy logic based calibration method for the Hargreaves equation is proposed and validated. The fuzzy inference system is developed to compute appropriate values of the constants C_Hand E_H on the basis of past data on humidity and wind velocity of a selected location. The underlying relationship between weather conditions and the best values of the constants C_Hand E_H are used to establish a fuzzy rule base. The performance of the method is checked at eight geographically different locations of India with diverse climate conditions. The Mean Absolute Error (MAE) in ETovalues estimated by the calibrated modified Hargreaves equation and the Penman-Monteith (PM) equation is in the range of 0.3220–1.0325. It is far more lower than if the error is calculated using the original Hargreaves equation. It confirms the correctness of the calibration method for different climate conditions.