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Facta universitatis - series: Working and Living Environmental Protection
2013, vol. 10, iss. 1, pp. 79-91
article language: English
document type: unclassified
published on: 23/01/2014
Precipitation forecast using statistical approaches
aUniversity of Belgrade, Faculty of Physics, Institute of Meteorology
bEmergency Management Sector, Ministry of Interior of the RS, Belgrade
cUniveristy of Niš, Faculty of Occupational Safety



A statistical approach is often used in the analysis of time series in climatology and hydrology. One of its advantages is the possibility to predict future time series. This can be applied in many circumstances, such as temperature, precipitation, solar radiation and other studies of climate elements. Several models to determine the time series analysis of rainfall were used in this paper. The goal is to find an appropriate model for predicting the trend forecasting of rainfall series. Trend forecasting is one of the important methods of time series analysis (TSA). The simulation shows that the list of 50 data of elapsed values will produce optimal results. The procedures of model selection and evaluation were applied to a series of annual precipitation in the period 1961-2011 in the weather forecast station in Negotin. The obtained results show a decrease in the trend of the total annual precipitation in the period 1961-2011. The results of the analysis and rainfall forecast in the years to follow, in comparison to 2011, show an annual increase of rainfall.


meteorological time series; the ARIMA model; trend method; the Mann-Kendall test; precipitation


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