Uncertainty on Travel Time in Kinematic Wave Channel Routing

Channel flow routing provides information on the movement of flood wave as it travels downstream. From the flood forecast viewpoint, it is desirable to have some knowledge about the expected arrival time of peak flow. However, many parameters involved in the flow routing model, in reality, can not be quantified with certainty. In this paper, a probabilistic analysis using the Mellin transform is performed to assess the uncertainty in computing the travel time of flood wave based on the kinematic wave model. Information about the uncertainty of the arrival time of flood peak may have a potential impact on decision making relating to various contingency plans in attempting to alleviate the potential flood damage. INTRODUCTION Channel flood routing is an important hydraulic engineering practice because it deals with the modeling of movement of flow along the channel over time. Results of channel flow routing provide information regarding to the temporal and spatial distributions of flood wave which is essential f o r flood warning and protection. Mathematical models used in channel flood routing range from very sophisticated 3D distributed-parameter models such as the St. Venant full dynamic wave equation to the simple lumpparameter Muskingum model (Chow et al., 1988). Intuitively, a sophisticated model not only is expansive and difficult to use, but a l s o it requires a large amount of data with reasonable accuracy in order to produce reliable results. The selection of an appropriate model to use would generally be dictated by a number of factors such as objectives of the study, accuracy requirements, data availability, budget and time constraints, and others. The solution to a channel flood routing model is a function of hydrologic characteristics of the channel such as roughness, slope, channel geometry and boundary conditions. Deterministic analysis of channel flood routing would assume that a l l model parameters, boundary conditions and initial conditions are known with certainty. Such idealizations, in