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On the effects of improved cross-section representation in one-dimensional flow routing models applied to ephemeral rivers

Hutton, Christopher J., Brazier, Richard E., Nicholas, Andrew P., Nearing, Mark
Water resources research 2012 v.48 no.4
floods, groundwater recharge, hydrologic cycle, hydrologic models, lidar, prediction, rivers, runoff, watershed hydrology, watersheds, United States
Flash floods are an important component of the semiarid hydrological cycle, and provide the potential for groundwater recharge as well as posing a dangerous natural hazard. A number of catchment models have been applied to flash flood prediction; however, in general they perform poorly. This study has investigated whether the incorporation of light detection and ranging (lidar) derived data into the structure of a 1-D flow routing model can improve the prediction of flash floods in ephemeral channels. Two versions of this model, one based on an existing trapezoidal representation of cross-section morphology (K-Tr), and one that uses lidar data (K-Li) were applied to 5 discrete runoff events measured at two locations on the main channel of The Walnut Gulch Experimental Watershed, United States. In general, K-Li showed improved performance in comparison to K-Tr, both when each model was calibrated to individual events and during an evaluation phase when the models (and parameter sets) were applied across events. Sensitivity analysis identified that the K-Li model also had more consistency in behavioral parameter sets across runoff events. In contrast, parameter interaction within K-Tr resulted in poorly constrained behavioral parameter sets across the multidimensional parameter space. These results, revealed with a modeling focus on the structure of a particular element of a distributed catchment model, suggest that lidar derived cross-section morphology can lead to improved, and more robust flash flood prediction.