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Rainfall runoff models using linear regression-a case study of an intermittent river

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Title Rainfall runoff models using linear regression-a case study of an intermittent river
 
Creator Jothiprakash, V
Magar, R
Sunil, K.
 
Subject rainfall runoff modelling
intermittent reservoir
kanand watershed
linear regression
 
Description This study presents the use of an intermittent river rainfall-runoff time series data in developing a deterministic linear regression rainfall-runoff models. An intermittent runoff river system, Kanand in Maharashtra state is taken as the case study. After finding the cross correlations between the rain gauge stations, eleven regression models were developed. Regression analysis is a statistical tool for the investigation of relationships between variables and is the first type of model to be developed before going in for more sophisticated models and is very useful to field engineers. The goal of regression analysis is to determine the values of parameters for a function that cause the function to best fit a set of observational data. Out of twenty three years of monthly historical data 16 years of data is used for building the model parameters and 7 years of data is used for validating the model. In the present study a regression model which considered four previous months rainfall data as input has resulted in a better relationship with runoff, with correlation coefficient of (0.89) as well as with better statistical performances.
 
Publisher Indian Association for Environmental Management
 
Date 2012-09-12T11:05:01Z
2012-09-12T11:05:01Z
2007
 
Type Article
 
Identifier Journal of Indian Association for Environmental Management, 34(3) 125-131
0970-8480
http://dspace.library.iitb.ac.in/jspui/handle/100/14407
 
Language English