PERFORMANCE EVALUATION OF COMPUTER-BASED SUITABLE FIELD WORKDAYS MODEL

Publication Date : 01/02/2017


Author(s) :

Abdulsalam, M., Isiaka, M., Dalha, I.B., Dalhat, M.K..


Volume/Issue :
Volume 12
,
Issue 1
(02 - 2017)



Abstract :

Maximum utilization of power and machinery requirement for farm production system depends on the accurate information on suitable field workdays. This study focused on determining the accuracy and performance of the computer based suitable workdays model developed for estimating the available workdays for tillage operations in the selected locations in Northern part of Nigeria. Normally, amount of moisture stored in the soil and rainfall amount were the criteria used for segregating the good and bad tillage workdays. Based on these criteria, field soil moisture monitoring was conducted for period of 30 days during rainy season and recorded as the field measured soil moisture data. Also, five (5) years (2008-2012) rainfall data were collected from the IAR meteorological station and used as the field measured rainfall data. The simulated soil moisture and rainfall values using the computer based suitable workday’s model and the field measured soil moisture and rainfall data were subjected to statistical analysis. Field measurements of soil moisture were conducted and the results were used to evaluate the performance of the SFWD computer model developed. The results were subjected statistical analysis and results show that the R2, RMSE, CRM, and EF were 0.9297, 0.138, 0.031 and 0.797 or 79.7% respectively for the comparison of the simulated and observed soil moisture. The result of the paired t-test shows that the differences were not significant at 5% probability level. The simulated rainfall amount fit best with the 2010 rainfall data with R2, RMSE, CRM and EF value of 0.8699, 0.3411, 0.0005 and 0.7125 respectively. Generally, the differences in the simulated and measured rainfall of year 2008 to 2012 were not significant at 5% level of probability. The study guides farm machinery managers in making wise decisions with respect to when, where and how to perform desired operations.


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