Strategies to Improve and Evaluate Physics‐Based Hyperresolution Hydrologic Simulations at Regional Basin Scales

Abstract The application of physics‐based distributed hydrologic models (DHMs) at hyperresolutions (~100 m) is expected to support several water‐related applications but is still prevented by critical data, model validation, and computational challenges. In this study, we address some of these challenges by applying the TIN‐based Real‐time Integrated Basin Simulator DHM at a nominal resolution of ~88 m in the Río Sonora basin, a regional watershed of ~21,000 km2 in northwest Mexico. First, we generate reliable high‐resolution (1‐km) hydrometeorological forcings by bias correcting reanalysis products with ground observations and applying downscaling routines that use terrain information at high resolution, which is available globally. Second, we develop a strategy to obtain high‐resolution (250‐m) grids of soil parameters by integrating a coarse‐resolution soil map based on the Food and Agriculture Organization classification with recently released high‐resolution global data sets. Third, we apply the model over a decadal period (2004–2013) and use a set of complementary tools, including Taylor diagrams, connectivity analysis, and empirical orthogonal function analysis, to assess its ability to simulate spatial patterns of land surface temperature through comparison with daily remotely sensed products. We find that (i) the hyperresolution‐simulated patterns capture the spatial variability of land surface temperature quite well and (ii) vegetation properties are the major physical factors controlling the discrepancies between simulated and remotely sensed products. The strategies presented here are based on global data sets and robust statistical techniques that can be utilized in different settings with other DHMs, and thus, they provide valuable support for the scientific community focused on hyperresolution hydrologic modeling.