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Comparing Maize Potential yields Predicted using Actual and Interpolated Weather data in Uganda

Author Affiliations

  • 1Dept. of Environmental management, Makerere University, Kampala, UGANDA
  • 2 Dept. of Agricultural and Bio-systems Engineering, Makerere University, Kampala, UGANDA

Int. Res. J. Environment Sci., Volume 2, Issue (10), Pages 63-70, October,22 (2013)

Abstract

Acquisition of measured weather data in Uganda for crop growth modeling is a challenge due to the low number of weather stations. Often, rainfall, maximum and minimum temperatures are measured. Total solar radiation is only measured at few weather stations due to shortage of sunshine duration recorders, the time graded paper strips or the newer automated weather stations (AWOS). A number of agencies do fill this void and provide on-line interpolated daily weather data to enable long-term simulations. A dynamic crop growth model CERES within the DSSAT modeling suite was used in order to evaluate simulation results obtained using actual and interpolated weather data from Kawanda, Central and Mbarara, south-western Uganda. Generic coefficients for very short, short, medium and long season maize varieties with in DSSAT were used. Farmer planting dates for the two cropping seasons were used to start the simulation. Results showed that at Kawanda, the average actual and interpolated maximum temperature were comparable, while at Mbarara, maximum temperatures were underestimated with a deviation of 3°C. At both sites, actual and interpolated minimum temperatures were comparable. The average actual total solar radiation at Kawanda was lower, probably indicating a shift in the AWOS radiation sensors. At Mbarara, the interpolated and measured values are comparable, indicating that the solarimeter method is still very reliable. RMSEs between actual and predicted potential yields at Kawanda were larger; very short (942 kg ha 1), short (1176 kg ha 1), medium (1864 kg ha 1) and long season maize (3055 kg ha 1). Actual radiation measurements at this site were lower, which emphasizes the importance of re-calibrating radiation sensors at least every two years. At Mbarara, the RMSEs for very short (418 kg ha 1), short (618 kg ha 1), medium (1056 kg ha 1) and long season (1896 kg ha 1) were low and acceptable. Interpolated data from the NASA can be used to predict potential yields and for long-term simulations in absence of measured weather data.

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