Vol. 8 (6) : November-December 2017 issue
Green Farming Vol. 8 (6) : 1351-1355 ; November-December, 2017
Development of stochastic time series model for prediction of rainfall in upper Bhima catchment of Western Maharashtra
PRADIP DALAVIa1*, S.R. BHAKARa2, P.K. SINGHa3, MAHESH KOTHARIa4 and H.K. JAINb5
aDepartment Soil and Water Engineering, College of Technology and Engineering, bDepartment of Statistics, Raj. College of Agriculture, Maharana Pratap University of Agriculture & Technology, Udaipur - 313 001 (Rajasthan)
Designation : 1Research Scholar *(pradipdalavi@gmail.com), 2,3,5Professor, 4Associate Professor
Subject : Water and Natural Resource Management, Water Conservation Engg., Water Harvesting, Farm Pond, Sewage Water, Irrigation
Paper No. : P-7053
Total Pages : 5
Received : 02 November 2017
Revised accepted : 30 November 2017
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Citation :
PRADIP DALAVI, S.R. BHAKAR, P.K. SINGH, MAHESH KOTHARI and H.K. JAIN. 2017. Development of stochastic time series model for prediction of rainfall in upper Bhima catchment of Western Maharashtra. Green Farming Vol. 8 (6) : 1351-1355 ; November-December, 2017
ABSTRACT
A study was conducted to develop a stochastic time series model for prediction of monthly rainfall in Bhima catchment of Bhima river catchment. The developed model is based on 12 years data from 2000 to 2011. The statistical tests indicated that the series of the rainfall data was trend free. The stochastic components of the monthly rainfall followed first order autoregressive model. By comparing generated and historic series validation of generated monthly rainfall series was done. The correlation coefficient between generated and historic rainfall series was found to be 0.99. Based on the results, it was concluded that AR(1) model can be effectively used for prediction of monthly rainfall in Bhima catchment.
Key words :
Autoregressive model, Bhima catchment, Rainfall, Stochastic model, Time series analysis, Trend.