Estimation of Annual Runoff in Indravati Sub Basin of Godavari River using Statistical Approach

Abstract

Prediction of runoff from known rainfall is one of the major problems confronted by hydrologists. There is lack of availability of long period runoff records in large number of catchments in India. Investigators have proposed many empirical relationships for runoff estimation in different catchments based on limited data of parameters affecting runoff. These regional relationships are useful in planning of water resource projects. This study was carried out to obtain simple yet effective relationship for estimation of annual runoff in Indravati sub basin of Godavari river. Regression analysis was carried out using annual rainfall, annual runoff and average annual temperature data to develop empirical models for annual runoff estimation. GIS software was used for preparing maps for the study area and to extract the precipitation and temperature data available in grid format from IMD. The best suited empirical model is then selected as per statistical criteria with lower values of standard error, standard deviation, mean absolute deviation (MAD), root mean square error (RMSE) and higher values of R square and correlation coefficient. Statistical significance of selected empirical model was evaluated by paired t test, F test and P value at 95 % confidence level. The developed relationship is then compared with the existing Khosla and Inglis and DeSouza relationships. Outcome of this comparison produces encouraging inferences to suggest an effective regional relationship for annual runoff estimation in the Indravati sub basin of Godavari river in India.

Authors and Affiliations

Dahe P. D. , Deshmukh B. B.

Keywords

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  • EP ID EP177968
  • DOI -
  • Views 174
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How To Cite

Dahe P. D. , Deshmukh B. B. (2016). Estimation of Annual Runoff in Indravati Sub Basin of Godavari River using Statistical Approach. International Journal of Innovative Research in Advanced Engineering, 0(0), 1-8. https://europub.co.uk/articles/-A-177968