An Alternative Approach for Improving Prediction of Integrated Hydrologic-Hydraulic Models by Assessing the Impact of Intrinsic Spatial Scales


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The effect of spatial scale and resolution has been quantified individually for different hydrologic and hydraulic processes. However, the model structure and intrinsic resolution are seldom modified to accurately capture scale-dependent physical processes. Although automated calibration methods exist for computationally expensive integrated models, an alternate approach reliant on improving the model structure is proposed here. This study advocates for a better representation of the intrinsic spatial scales of physical processes and their submodels by quantifying the impact of different types of spatial scaling on the overall watershed response. First, the effect of spatial extent scaling is quantified by evaluating the change in the basin response (e.g., streamflow and inundation extent) across a small and large subwatershed for the same region. Second, the effect of modifying the relative intrinsic spatial scales of surface-groundwater (SW-GW) submodels is quantified. Finally, the results are used to implement a better model structure for improving prediction across two watersheds with distinct physical characteristics. The findings suggest that the relative intrinsic scales of SW-GW submodels may be different for different hydrogeological systems depending on the ratio of the characteristic length scales of hydrologic-hydraulic processes. Conducting a scaling analysis can help identify how different physical processes can be best represented in integrated models for a range of climatological and physiographic conditions which can potentially serve as an alternative to extensive calibration in distributed models. Therefore, it is recommended that this analysis should be included as a prerequisite to extensive parameter calibration for large-scale-integrated models.



riverine modeling and prediction, watershed hydrology, integrated flood modeling, intrinsic spatial scale, physically based distributed modeling, surface-groundwater model