@misc{OezgenXianKesserwaniCaviedesVoulliemeetal., author = {{\"O}zgen-Xian, Ilhan and Kesserwani, Georges and Caviedes-Voulli{\`e}me, Daniel and Molins, Sergi and Xu, Zexuan and Dwivedi, Dipankar and Moulton, J. David and Steefel, Carl I.}, title = {Wavelet-based local mesh refinement for rainfall-runoff simulations}, series = {Journal of Hydroinformatics}, volume = {22}, journal = {Journal of Hydroinformatics}, number = {5}, issn = {1464-7141}, doi = {10.2166/hydro.2020.198}, pages = {1059 -- 1077}, abstract = {A wavelet-based local mesh refinement (wLMR) strategy is designed to generate multiresolution and unstructured triangular meshes from real digital elevation model (DEM) data for efficient hydrological simulations at the catchment scale. The wLMR strategy is studied considering slope- and curvature-based refinement criteria to analyze DEM inputs: the slope-based criterion uses bed elevation data as input to the wLMR strategy, whereas the curvature-based criterion feeds the bed slope data into it. The performance of the wLMR meshes generated by these two criteria is compared for hydrological simulations; first, using three analytical tests with the systematic variation in topography types and then by reproducing laboratory- and real-scale case studies. The bed elevation on the wLMR meshes and their simulation results are compared relative to those achieved on the finest uniform mesh. Analytical tests show that the slope- and curvature-based criteria are equally effective with the wLMR strategy, and that it is easier to decide which criterion to take in relation to the (regular) shape of the topography. For the realistic case studies: (i) slope analysis provides a better metric to assess the correlation of a wLMR mesh to the fine uniform mesh and (ii) both criteria predict outlet hydrographs with a close predictive accuracy to that on the uniform mesh, but the curvature-based criterion is found to slightly better capture the channeling patterns of real DEM data.}, language = {en} } @misc{OezgenXianMolinsKesserwanietal., author = {{\"O}zgen-Xian, Ilhan and Molins, Sergi and Kesserwani, Georges and Caviedes-Voullieme, Daniel and Steefel, Carl I.}, title = {Meshing workflows for multiscale hydrological simulations: Wavelet-based approach improves model accuracy.}, series = {AGU 100 : Fall Meeting 2019, San Francisco, CA, 9-13 December2019}, journal = {AGU 100 : Fall Meeting 2019, San Francisco, CA, 9-13 December2019}, address = {San Francisco, California}, pages = {1}, abstract = {The high computational cost of large-scale, process-based hydrological simulations can be approached using variable resolution meshes, where only the region around significant topographic features is refined. However, generating quality variable resolution meshes from digital elevation data is non-trivial. In literature, usually a slope or curvature-based criterion is defined to detect regions of refinement. These techniques often involve a number of free parameters that control the finest and coarsest resolutions, and the transition between fine resolution to coarse resolution. The influence of these parameters on the resulting mesh is usually not well-understood. In order to overcome the large number of free parameters involved, we propose to carry out the Mallat decomposition of the digital elevation data using the Haar wavelet. This gives a nested multilevel representation of the elevation data, split into average coefficients and detail coefficients. Applying hard-thresholding to these detail coefficients assigns a required level of refinement to each data point. This reduces the number of free parameters to exactly one: the acceptable error threshold. In this presentation, we focus on identifying which geomorphometric parameter(s) should be used to steer mesh refinement. We compare zero-inertia model simulation runs on meshes generated by decomposing elevation and slope. We hypothesize that because of the form of the Haar wavelet, the first mesh refinement essentially is using the gradient information, while the latter is using the curvature as refinement criterion. Our results suggest that in high-elevation catchments the curvature of the topography is a far better indicator for refinement than the slope. Using the Mallat decomposition on the tensor of the first derivative of the bed elevation (i.e., bed slope) for mesh refinement yields better agreement in the hydrograph compared to the decomposition of the bed elevation. We present surface runoff results for the Lower Triangle catchment, CO, USA, to illustrate the performance of the wavelet-based local mesh refinement.}, language = {en} }