Effect of Nitrogen on Yield and Oil Quality of Sunflower (<i>Helianthus Annuus</i>L.) Hybrids under Sub Humid Conditions of Pakistan

Sunflower (Helianthus annuus L.) has emerged as an economically important crop in Pakistan due to its significant share in vegetable oil production. The plant metabolic processes require protein to increase the vegetative, reproductive growth and yield of the crop. The protein is wholly dependent upon the amount of nitrogen fertilization available for plant use. A two-year field study was conducted in 2008 and 2009. The objective was to determine the effect of different nitrogen (N) levels (N1 = 0 kg·ha–1, N2 = 60 kg·ha–1, N3 = 120 kg·ha–1, N4 = 180 kg·ha–1 and N5 = 240 kg·ha–1) on three sunflower hybrids (Hysun-33, Hysun-38 and Poineer-64A93) in agro-climatic conditions of Gujranwala, a sub-humid region in the centre of the Punjab province of Pakistan. A randomized complete block design split plot experiment was set-up with cultivars in the main plots and N levels in the subplots. Results showed that Hysun-38 gave maximum TDM (15815 kg·ha–1) and maximum grain yield (3389 kg·ha–1), while minimum TDM (14640 kg·ha–1) and grain yield (3125 kg·ha–1) was observed in Hysun-33. Among different N rates evaluated, N4 gave maximum TDM (17890 kg·ha–1) and grain yield (3809 kg·ha–1) compared to the other N rates. The maximum oil content (46.2%) was observed in Hysun-38 without application of N fertilizer (N1), while the minimum oil content (40.6%) was observed from N5 treatment. In conclusion, the application of 180 kg·ha–1 N to Hysun-38 provided the best combination for good yield in sunflower crop under the prevailing sub-humid conditions of Pakistan.

Evaluation of SWAT Model performance on glaciated and non-glaciated subbasins of Nam Co Lake, Southern Tibetan Plateau, China

This paper presents an assessment of the Soil and Water Assessment Tool(SWAT) on a glaciated(Qugaqie) and a non-glaciated(Niyaqu) subbasin of the Nam Co Lake. The Nam Co Lake is located in the southern Tibetan Plateau, two subbasins having catchment areas of 59 km^2 and 388 km^2, respectively. The scores of examined evaluation indices(i.e., R^2, NSE, and PBIAS) established that the performance of the SWAT model was better on the monthly scale compared to the daily scale. The respective monthly values of R^2, NSE, and PBIAS were 0.94, 0.97, and 0.50 for the calibration period while 0.92, 0.88, and -8.80 for the validation period. Glacier melt contribution in the study domain was simulated by using the SWAT model in conjunction with the Degree Day Melt(DDM) approach. The conjunction of DDM with the SWAT Model ensued improved results during both calibration(R^2=0.96, NSE=0.95, and PBIAS=-13.49) and validation (R^2=0.97, NSE=0.96, and PBIAS=-2.87) periods on the monthly time scale. Average contribution(in percentage) of water balance components to the total streamflow of Niyaqu and Qugaqie subbasins was evaluated. We found that the major portion(99.45%) of the streamflow in the Niyaqu subbasin was generated by snowmelt or rainfall surface runoff(SURF_Q), followed by groundwater(GW_Q, 0.47%), and lateral(LAT_Q, 0.06%) flows. Conversely, in the Qugaqie subbasin, major contributor to the streamflow(79.63%) was glacier melt(GLC_Q), followed by SURF_Q(20.14%), GW_Q(0.13%), and LAT_Q(0.089%). The contribution of GLC_Q was the highest(86.79%) in July and lowest(69.95%) in September. This study concludes that the performance of the SWAT model in glaciated catchment is weak without considering glacier component in modeling; however, it performs reasonably well in non-glaciated catchment. Furthermore, the temperature index approach with elevation bands is viable in those catchments where streamflows are driven by snowmelt. Therefore, it is recommended to use the SWAT Model in conjunction with DDM or energy base model to simulate the glacier melt contribution to the total streamflow. This study might be helpful in quantification and better management of water resources in data scarce glaciated regions.