Quantitative prediction of seasonal rating curve shifts

Abstract

Application of linear multiple regression techniques to discharge measurement and water temperature data collected for selected Missouri River forecast points resulted in development of a successful quantitative technique for prediction of seasonal rating curve shifts. By utilizing 20 yr of discharge measurement and water temperature data for Omaha, Nebraska, and St. Joseph and Kansas City, Missouri, it was found that the addition of the independent variable water temperature (degrees Fahrenheit) to the stage‐discharge relationship increased multiple correlation coefficients significantly. In all cases studied, increased temperature reflected an increase in stage for a constant flow. The maximum effect of water temperature is indicated for low flows. Water temperature is thought to cause the alterations of bed form configuration resulting in seasonal rating curve shifts.