Predicting Model Uncertainty at River Junctions due to Drainage Network Structure

Abstract

The mixing of water, solutes, and sediments from two or more tributaries produces streamflow possessing unique biogeochemical, ecological, hydrological, and morphological signatures. To understand and predict these signatures, confluence locations within river networks are commonly used to divide a watershed into individual modeling units, within these units hydrologic characteristics are spatially averaged and used to parameterize process models. In this context, model parameters from an individual unit directly influence the simulated hydrograph at its corresponding downstream junction and reach. Previous researchers have shown complex changes in flow hydraulics, stream geometry, and channel morphology in the downstream direction of a drainage network. However, the uncertainty of model predictions at and between junction locations due to parameter variability within individual modeling units is poorly understood. This paper presents a methodology for identifying stream junctions and reaches that are potentially vulnerable to increased model uncertainty due to the structural arrangement of their upstream drainage network and model parameter variability. A case study, using coastal southern California, is presented to illustrate the concepts and explore the relationships between changes in simulated peak discharge at junctions and along reaches due to expected model parameter variability for varying drainage network characteristics. Based on simulation results for 300 different drainage network configurations, eight model parameter scenarios, and three design storms (7,200 simulations), the uncertainty in simulated peak discharge within a reach is related to the drainage network characteristics. In the study region, 18% of the reaches are shown to be especially vulnerable to model parameter uncertainty, with 32% of those researches crossed by a major road and/or railroad. This approach is intended to improve risk assessment in sensitive hydrologic applications, such as the design of bridges, culverts, and channels to convey flood flows.