Performance of AquaCrop model for predicting yield and biomass of okra (Abelmoschus esculentus) crop

Abstract

The present study was carried out at Technology Park of College of Technology and Engineering, Udaipur, Rajasthan for two years (2019 and 2020) with 6 irrigation treatments and four replications in RBD. Among all the treatments, the treatment T2 (Irrigation at 85% field capacity of soil, based on soil moisture sensor based drip irrigation system) was found best in selected areas for growing okra [Abelmoschus esculentus (L.) Moench] crop under sensor based drip irrigation with maximum crop yield and biomass. In other water scarce regions of Rajasthan, the use of a simulation model can be a better option to predict the crop yield and biomass with respect to different irrigation levels. Therefore, calibration and validation of the AquaCrop model was done with the help of various data which were collected from field experiments during the study period (2019–20). The cut off temperature and base temperaturewere set as 32.5–100C, respectively. The model was successfully calibrated and validated with minimum prediction error, mean absolute error (MAE: 0.34–0.56), root mean square error (RMSE: 0.38–0.60) and maximum model efficiency (E ranges 0.8–0.95) and coefficient of correlation (R2 > 0.9). The overall result indicate good performance of the model and can help in decision making as well as for irrigation water management for okra crop under the given conditions of Udaipur district of Rajasthan. It can be used to assess the influence of various environmental factors and management practices on okra crop growth.