FAO AquaCrop model for determining optimum wheat sowing date in Tarai region of Uttarakhand
DOI:
https://doi.org/10.54302/mausam.v73i1.5092Keywords:
Aquacrop, Calibration, Validation, Wheat, , Sowing date, Simulation &Tarai regionAbstract
The ideal sowing period is critical for maximizing the crop's yield potential under specific agroclimatic conditions (Nain, 2016; Patra et al., 2017). It influences the phenological stages of the crop's development and, as a result, the efficient conversion of biomass into economic yield. During rabi 2013-14, a field research was done at GBPUA&T's Borlaug Crop Research Centre to determine the best sowing dates for wheat crops employing Aquacrop model. Aquacrop model has been calibrated against vegetative and economic yield forthree sowing dates, viz., 3rd December, 18th December and 3rd January (Pareek et al., 2017). After calibrating the Aquacrop model, a set of conservative variables was obtained (Pareek et al., 2017). Afterward, the calibrated Aquacrop model was used to validate wheat yield and biomass for three years in a row, namely 2010-11, 2011-12 and 2012-13. The model subsequently used to simulate yield under different sowing dates. For all of the tested years, the simulation findings of the Aquacrop model reflected the observed crop yields and biomass of wheat. The model was used to simulate the optimum sowing week based on varying sowing dates and produced grain yield for a period of 10 years (Malik et al., 2013). The average and assured yield of wheat was worked out based on probability analysis (60, 75 and 90%). The optimum sowing time for Tarai region of Uttarakhand was suggested as first week of November followed by second week of November (Nain, 2016). In no case wheat should be sown during third week of November and beyond due to poor assured yield and average yield (Nain, 2016). The finding of the studies will help to increase productivity and production of wheat crop in Tarai region of Uttarakhand.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 MAUSAM
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published by MAUSAM are licensed under the Creative Commons Attribution 4.0 International License. This permits anyone.
Anyone is free:
- To Share - to copy, distribute and transmit the work
- To Remix - to adapt the work.
Under the following conditions:
- Share - copy and redistribute the material in any medium or format
- Adapt - remix, transform, and build upon the material for any purpose, even
commercially.