Precipitation is very
important for both the environment and its inhabitants. Agricultural activities
mostly depend on precipitation and its availability. Therefore, the ability to
predict future precipitation values at specific stations is key for environmental
and agricultural decision making. This research developed Autoregressive
Integrated Moving Average (ARIMA) models for selected stations with Integrated
component and Autoregressive Moving Average (ARMA) for selected stations
without Integrated component at Louisiana State. The ARIMA module is
represented as ARIMA(p, d, q)(P,D,Q). The selected lag order for the
Autoregressive (AR) component is represented with p and P for seasonal AR
component, while the integrated form (number of times data were differenced) is
d and D for seasonal differencing, and the Moving Average (MA) lag order is q
and Q for seasonal MA component. Data from 1950 to 2020 were employed in this
research. Results of the analysis indicated that Baton Rouge (ARIMA (0,1,1)
(0,0,2)12), Abbeville (ARMA (0,0,1) (0,0,2)12), Monroe
Regional (ARMA (0,0,1) (0,0,0)12), New Orleans Airport (ARMA (1,0,0)
(0,0,2)12), Alexandria (ARMA (1,0,1) (0,0,0)12),
Logansport (ARIMA (0,1,2) (0,0,0)12), New Orleans Audubon (ARMA
(1,0,0) (0,0,0)12), Lake Charles Airport (ARMA (2,0,2) (0,0,0)12)
are the best ARIMA models for predicting precipitation in Louisiana. The models
were used to predict the average monthly rainfall at each station. The highest
precipitation observed in Louisiana was recorded in 1991. The Precipitation in
Louisiana fluctuated over the years but has adopted a decreasing trend from the
year 2000 to 2020. It was recommended that the government, researchers, and
individuals take note of these models to make future plans to help increase the
production of
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