This research explores the efficiency of kinematic wave and Soil Conservation Service (SCS) flow models at a watershed scale in a semi-arid environment. The scope of this research is based on the hypothesis that flow models based on the simplest approximation of the full dynamic equations (kinematic wave, hydraulic) produce output variables that are representative of the watershed system compared to flow models that rely only on the continuity equation (SCS, hydrologic). The overall objective of this research study is to provide an improved understanding of kinematic wave and SCS flow models and compare their efficiencies to the observe flow data. Physical data such as precipitation, runoff, soils, and topography was derived from the Walnut Gulch Experimental Watershed (WGEW) in the southwest United States. Several important conclusions have emerged from this study that can prove useful to a practicing engineer/hydrologist. First, the kinematic-wave model proved to be a satisfactory tool to predict surface runoff in semi-arid watersheds, where transmission losses are a significant factor besides initial abstraction in the overall water budget computations. Analysis of the "Peak-Weighted Root Mean Squared Error" (PRMSE) values between the computed models (kinematic wave and SCS flow) and observed flow data for the three study watersheds show that the kinematic wave flow model has lower values of objective function compared to SCS flow model. Since PRMSE function is an implicit measure of comparison of the magnitudes of the peaks, volumes, and times of peak of the two hydrographs, it means that the kinematic wave flow model is more accurate than the SCS flow model. Second, the percent difference in peak flows between the observed data and computed flow results indicates that the kinematic wave model is no more likely to over-predict than to under-predict. On the other hand, the majority of the percent difference in peak flows between the observed and the SCS flow model indicates that the SCS model has a strong tendency to under predicted peak flows. Finally, the kinematic wave accuracy is demonstrated with data encompassing a relatively wide range of field conditions, where the kinematic wave flow model proved advantageous in that it can process spatial and/or temporal rainfall and overland and channel roughness variations, which the SCS model, by virtue of it being a lumped model, cannot.
Read
