Maximum entropy-based conditional probability distribution runoff model

The principle of maximum entropy was applied to develop a minimally prejudiced, conditional probability distribution model to estimate runoff on weekly and monthly basis for the catchment of Matatila dam comprising an area of 20 720 km(2) on Betwa river in India. The hydrological data of rainfall and runoff for the active monsoon weeks (23rd to 43rd weeks) and active months (June-October) from year 1971 to 1985 were considered for the development of model. The model parameters were determined on the basis of the prior information such as means of rainfall and runoff and their covariance. The developed model has been applied for estimation of weekly and monthly runoff for different values of runoff coefficient a and return period Tat different probability levels of rainfall for the study area. It is observed that the developed model is applicable in the study area as it predicts runoff subject to the selected constraints reasonably well in response to a given rainfall. (C) 2004 Silsoe Research Institute. All rights reserved Published by Elsevier Ltd.