Integrated use of regional weather forecasting and crop modeling for water stress assessment on rice yield
Rajasivaranjan, T.; Anandhi, Aavudai; Patel, N. R.; Irannezhad, Masoud; Srinivas, C. V.; Veluswamy, Kumar; Surendran, U.; Raja, P. (2022-10-10)
Rajasivaranjan, T., Anandhi, A., Patel, N.R. et al. Integrated use of regional weather forecasting and crop modeling for water stress assessment on rice yield. Sci Rep 12, 16985 (2022). https://doi.org/10.1038/s41598-022-19750-z
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https://urn.fi/URN:NBN:fi-fe2023042839312
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Abstract
This study evaluated the effects of water stress on rice yield over Punjab and Haryana across North India by integrating Weather Research Forecasting (WRF) and Decision Support System for Agrotechnology Transfer (DSSAT) models. Indian Remote Sensing Satellite datasets were used to define land use/land cover in WRF. The accuracy of simulated rainfall and temperature over Punjab and Haryana was evaluated against Tropical Rainfall Measuring Mission and automated weather station data of Indian Space Research Organization, respectively. Data from WRF was used as weather input to DSSAT to simulate rice yield in Punjab and Haryana for 2009 and 2014. After simulated yield has been evaluated against district-level observed yield, the water balance components within the DSSAT model were used to analyze the impact of water stress on rice yield. The correlation (R2) between the crop water stress factor and the rice yield anomaly at the vegetative and reproductive stage was 0.64 and 0.52 for Haryana and 0.73 and 0.68 for Punjab, respectively. Severe water stress during the flowering to maturity stage inflicted devastating effects on yield. The study concludes that the regional climate simulations can be potentially used for early water stress prediction and its impact on rice yield.
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