Field and model study of rainfall pattern and its impact on wheat (Triticum aestivum) productivity in Uttarakhand

The rainfall pattern aberrations during winter (rabi) season (December to March) in north India are a cause of concern to administrators and researchers. A field experiment was carried out during 2013–14 and 2014–15 at Roorkee, Uttarakhand, to study the effect of rainfall pattern on productivity of wheat (Triticum aestivum L.). It was laid down in factorial design with treatment combinations including 4 wheat varieties (‘PBW 292’, ‘HD 2967’, ‘PBW 154’ and ‘PBW 550’) and 3 sowing dates (20 November, 5 December and 20 December), replicated thrice. Soil was sandy loam, moderate in fertility. Crop was grown under best management practices. Weather data were re-corded from Automated Weather Station installed at the farm. Observations were recorded on growth, development, yield and yield attributes of the crop. The results showed that the total rainfall during the growing season was similar, i.e. 222.2 mm in 2013–14 and 227.1 mm in 2014–15 but the pattern was totally different. During the winter (rabi) season 2013–14, a very high rainfall occurred in January (98 mm) and February (52 mm) that coincided with the grand growth phase of wheat, resulting in to bumper harvest. On the contrary, during the winter (rabi) season 2014–15 higher rainfall was received in March (115 mm) and April (62 mm) which coincided with flowering and grain-setting stages, resulting in reduced productivity due to lodging. The average productivity of wheat during 2013–14 was 4.37 t/ha, whereas during 2014–15 it was 3.78 t/ha. Productivity during 2014–15 was reduced by 13.6% in comparison to 2013–14. Loss in productivity was more (ranging from 11.4% to 42.1%) in timely sown crop. The late-sown (20 December) treatment did not reveal much productivity loss and remained within 5% during 2014–15. Normal-sown varieties (‘PBW 292’, ‘HD 2967’, ‘PBW 154’) suffered serious productivity loss as compared to late-sown variety (‘PBW 550’). DSSAT model simulated result compared well during 2013–14. However, during 2014–15 the heavy rainfall in March and April caused severe lodging and the model perhaps could not detect it.