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We developed a novel Bayesian Hierarchical Network Model (BHNM) for daily streamflow, which uses the spatial dependence induced by the river network topology, and average daily precipitation from the upstream contributing area between station gauges. In this, daily streamflow at each station is assumed to be distributed as Gamma distribution with temporal non-stationary parameters. The mean and standard deviation of the Gamma distribution for each day are modeled as a linear function of suitable covariates. The covariates include daily streamflow from upstream gauges or from the gauge above of the upstream gauges depending on the travel times, and daily, 2-day, or 3-day precipitation from the area between two stations that attempts to reflect the antecedent land conditions. Intercepts and slopes of the mean and standard deviation parameters are modeled as a Multivariate Normal distribution (MVN) to …