ANALYSIS OF CLIMATE CHANGE IMPACT ON AGRICULTURE IN ZARIA LOCAL GOVERNMENT AREA OF KADUNA STATE
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Department of Arts
Climate change and variability is a global issue that needs to be given proper attention because of
its impacts on the agriculture and other aspects of socio-economies. Annual rainfall and
temperature data of four decades (1971-2010) for Zaria Local Government Area of Kaduna State
located within Latitude 11o081N and Longitude 07o411E were obtained from Nigerian
Meteorological Agency (NIMET), Zaria, and analysed in order to establish climate variability in
the area. Three methods were used to study the climate variability namely: statistical differences
between the two equal-length time scales of 1971-2000 and 1981-2010, respectively, coefficient
of variability (CV); and the Anomaly approach. However, trend analysis using t test, Sen’s
estimator slope and Mann Kendall were also carried out in order to determine the trend in the
climatic variables. On other hand, multiple non linear regression analysis was performed for the
annual maize, millet and sorghum yields on the climatic variables using Sigma plot 11.0. The
three models of the crops developed were evaluated using statistical error measurement. The
result revealed that the differences between the two means of the equal-length time scales
revealed variability of: 7mm, 0.50oC, 0.30oC and 0.40oC for rainfall, maximum, minimum and
mean temperatures, respectively. Similarly, the CVs of rainfall, maximum, minimum and mean
temperatures were: 0.145, 0.026, 0.036 and 0.025, respectively indicating low variability.
However, the anomaly results revealed that 21 years (52.5%) recorded dry; while 19 years
(47.5%) recorded wet; 1983 having the highest dry of 323mm; and 1972 has the lowest dry of
15mm. On the other hand, the highest wet of 340mm occurred in 1978; while the lowest wet of
9mm was recorded in 1971. Moreover, 24 years (60.0%) were warmer than normal; 13 years
(32.5%) less warm than normal; while 3 years (7.5%) had normal mean temperature. The Sen’s
estimator slope revealed downward trend of 94mm/yr in 1971-1980 decades; while it recorded
upward trends of :90mm/yr, 30mm/yr and 118mm/yr, respectively during 1981-1990, 1991-2000
and 2001-2010 decades, but they are not statistically significant. However, the mean temperature
recorded upward trends of 0.2oC/yr, 0.2oC/yr,0.1oC/yr and 0.2oC/yr, respectively in 1971-1980,
1981-1990, 1991-2000 and 2001-2010 decades. The regression analysis revealed that only 28.9%,
45.2% and 24.2%, respectively for maize, millet and sorghum yields variation can be accounted
for by the rainfall and mean temperature. However, out of the three developed models, the millet
model was the most fitted and valid as it recorded the lowest total and mean square errors of:
0.335 and 0.030, respectively. It was followed by the sorghum model with total and mean square
errors of: 0.349 and 0.032, respectively; while the maize model was the least as it recorded
highest total and mean square errors of: 1.457 and 0.132, respectively. Additionally, 1000
questionnaires were self- administered in order to study the perceptions of residents of the area on
climate change. It was coupled with some Focus Group Discussions with farmers and Key
Informant Interviews. The results revealed that climate change affect agricultural activities
because the planting dates as well as harvesting dates are affected. Finally, it was concluded that
climatic variables affect agriculture and some mitigation measures and adaptation options were
proposed in order to control the climate change impacts.
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