Rainfall modelling using backward generalized estimating equations: a case study for Fasa Plain, Iran
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ORIGINAL PAPER
Rainfall modelling using backward generalized estimating equations: a case study for Fasa Plain, Iran Mehdi Bahrami1 · Mohammad Reza Mahmoudi2,3 Received: 7 June 2019 / Accepted: 4 December 2019 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract In recent years, plenty of researches have accomplished to make the relationship between the climatic variables for daily, monthly, and seasonal rainfall occurrence and magnitude around the world. In this study, monthly rainfall modeling was performed using backward generalized estimating equation (GEE). In this regard, monthly average maximum and minimum temperature, sunshine hours, wind speed, and relative humidity data from 1967–2014 for the Fasa Plain at Fars province, Iran were selected as predictors to investigate their effects on response variable of rainfall. Results indicated that in February, March, April, June, August, and October the term of humidity has positive effect (B > 0 and P
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