Seasonal climate forecasts (SCFs) based risk management strategies: A case study of rainfed rice cultivation in India

Seasonal climate forecasts (SCFs) have gained popularity in agriculture for risk management studies. The available forms of SCFs are not conducive to decision making because a mismatch scales over space and time. In this study, were disaggregated using the FResampler1 technique simulate rice yield (cultivar PR 114) under different nitrogen levels planting dates DSSAT (Decision Support System Agrotechnology Transfer) Sitamarhi district, Bihar, India. Results showed that late predicted highest (3800 kg ha-1) with high variability SCF (wet) 200 ha-1 application fertilizer. Similarly, (dry), simulated (3100 attributes However, climatology (3450 was more than (dry) ha-1). Planting on 15th June 2019 (normal) low uncertainty mean yields as compared mid (05th July 2019), (25th 2019) planting. present study by applying SCF, we can better understanding “relative” changes fertilizer doses dates, which may be adopted adviser offset without compromising productivity.