Thompson, S.*, Sanni, I.M., Abubakar, U.A. and Sani, B.S.
Department of Water Resources and Environmental Engineering, Ahmadu Bello University, Zaria
*Corresponding Author: firstname.lastname@example.org
A 35-year annual rainfall was collected from NIMET to determine the Standard Precipitation Index (SPI) and also to study the trend of rainfall parameter in the Kano State, Northern Nigeria. The paper captures the average rainfall (normal rainfall) data for thirty-five years period which implies a rainfall of about 1081.56mm. The positive values (above zero) signify rainfalls that were higher than normal (wet); while the negative values (below zero) imply rainfalls that were lower than normal (dry). From the rainfall anomaly, 18 years (52.9%) recorded wet due to the fact that rainfall occurred in those years were greater than the normal rainfall of 1081.56; while 16 years (47.1%) recorded dry because the rainfalls that occurred in those years were below normal rainfall. In the study, Weilbul method was used to determine the return period in order to predict the year of occurrence of maximum rainfall. In addition, Standard Precipitation Index was used to determine periods of dry, normal or wet temperatures. September 1991 recorded the minimum SPI value of -0.86 (moderately dry), while October 2011 recorded the maximum SPI value of 1.88 (moderately wet). This study is carried out because of the importance of agriculture in the region and to Nigeria at large. Kano state is well known to support food production in the country. Also, the presence of dams further buttresses this study. Dams have many purposes; one is agriculture during dry and wet season. It is observed that the rainfall in the basin has no definite pattern.
Keywords: Standard Precipitation Index (SPI), Statistical Analysis, Rainfall, Anomaly, Return period
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Cite this article as:
Thompson, S., Sanni, I.M., Abubakar, U.A. and Sani, B.S., 2022. Preliminary Analysis of Daily Rainfall Data from Kano State using Statistical Techniques. Nigerian Journal of Environmental Sciences and Technology, 6(2), pp. 317-324. https://doi.org/10.36263/nijest.2022.02.0366