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In-season crop production forecasts at the regional or sub-regional scale are essential to aid in food security through early warning of harvest shortfall/surplus, tailoring crop management decisions and addressing climatic shock. Considering the efforts to establish a framework towards quantifying the crop yield prediction at regional scales are limited, we investigated the utility of combining crop model with the regional weather prediction model to forecast winter wheat yields over space. The exercise was performed for various lead-times in the regions of Punjab and Haryana for the years 2008–2009. A numerical weather prediction (NWP) model was used to generate micro-meteorological variables at different lead times (1-week, 2-weeks, 3-weeks and 5-weeks) ahead of crop harvest and used within the CERES-Wheat crop simulation model gridded framework at a spatial resolution of 10 km. Various scenarios of the yield forecasts were verified with district-wide reported yield values. Average deviations of −12 to 3% from the actual district-wise wheat yields were observed across the lead times. The 3-weeks-ahead yield forecasts yielded a maximum agreement index of 0.86 with a root mean squared error (RMSE) of 327.75 kg/ha and a relative deviation of −5.35%. The critical crop growth stages were found to be highly sensitive to the errors in the weather forecast, and thus made a huge impact on the predicted crop yields. The 5-weeks-ahead weather forecasts generated anomalous meteorological data during flowering and grain-filling crop growth stages, and thus had the highest negative impact on the simulated yields. The agreement index of the 5-week-ahead forecasts was 0.41 with an RMSE of 415.15 kg ha−1 and relative deviation of −2.77 ± 5.01. The proposed methodology showed significant forecast skill for extended space and time scale crop yield forecasting, offering scope for further research and practical applicability. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]