Time Series Modelling of Pan Evaporation-A Case Study in the Northeast India

In the present study, a monthly time series model was developed for pan evaporation (E_pan) in Jorhat (Assam), northeast India. We assume that the E_pan series can be decomposed into deterministic and stochastic components, and a turning point test was used to identify the presence of a trend component in the series. A trend-free E_pan time series was further obtained by eliminating the trend component from the original E_pan time series, and later used in identifying the periodic component using Fourier series analysis. Results show that the first three harmonics explained the total variance by 88,2 %. Before modelling the stochastic dependent component, the periodic component was removed from the time series. In the stochastic dependent component modelling, the moving average (MA) model of order 2 was found suitable on the basis of minimum value of the Bayesian information criterion (BIC). The independent stochastic component was modelled using the normal distribution function. Overall, a very good agreement is observed between generated and historical records, with the Nash-Sutcliffe coefficient being equal to 0,98.