Validation of soil water balance models for crop assessment and yield prediction under Tanzanian conditions
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Date
1998
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Sokoine University of Agriculture
Abstract
The information gathering for early warning and crop assessment in Tanzania is still based on physical inspection of standing crops in fields. The physical inspection is based on sown area, the state of crop development towards maturity, the prevailing and anticipated weather conditions (during and after) at the time of inspection and the extent of crop attack by pests and diseases. The process is subject to human error and it is also time consuming. Developments in computer simulation models may provide an efficient method for analysis of data for early warning and crop assessment. This study was aimed at validating Irrigation Scheduling Information System (IRSIS) and Crop Growth and Irrigation Scheduling Model (CRPSMW) which are soil water balance simulation models for crop assessment and prediction of grain yields. Five stations viz. Ilonga Agricultural Research and Training Center, Msimba Foundation Seed Farm, Selian Agricultural Research Institute, Arusha Foundation Seed Farm, and Tanzania Pesticides Research Institute were selected for this study. Input data for the models comprised of weather, crop and soil data. Weather data was of a 10 year duration where as for the crop data the record length varied from 3 to 10 years. The [RSIS mode appeared to over predict grain yield of maize, sorghum, and wheat. This could be attributed to the inadequacy of the model to accurately account for the runoff, a fact that was depicted in the model output whereby a portion of the excess rainfall was utilized by the crop for evapotranspiration purposes. On the other hand, the CRPSMW model results were not significantly different (P<0.05) from the actual grain yields simulated yields of maize, sorghum, wheat, and beans. The simulated grain yields for the different planting dates falling on or after the probable date for start of the growing season during the long rains for both Morogoro and Arusha were not significantly different (P<0.05) from the actual grain yield. Although there was a good agreement between the actual and the CRPSMW model simulated grain yields, it was observed that, mean values for predicted grain
yields were consistently smaller than for actual grain yields. This could be attributed o lack of representative location specific input parameters required by the model. These results indicate that the subroutine in the ERSIS model that considers runoff is inadequate and needs to be reformulated and/or allowance should be given for calibration of the model with respect to the runoff component. From the results it can be concluded, that a subroutine which considers factors such as hill slope, rainfall, and catchment area in estimating surface runoff should be incorporated into the IRSIS model to take account of the effects of excessive water on crop yields. There is also a need to determine more representative location specific parameters required by the CRPSMW model and the influence of moisture stress on different growth stages and hence yields under tropical conditions in order to increase its accuracy in predicting grain yields.
Description
Dissertation
Keywords
Soil water balance, Crop assessent, Grain yield prediction, Maize, Sorghum, Wheat