Influence of soil depth and spatial resolution on the performance of the DHSVM hydrological model in basins with low input data availability

The DHSVM model has been applied in several regions and with different objectives such as to simulate the hydrological behavior of watersheds, and to study the impact of climate change and land use on watershed hydrology. Modeling efficiency requires the use of consistent data on topography, soil types, vegetation types, and meteorological data. In this paper, we present studies on the influence of pixel size and the maximum soil depth on the efficiency of the DHSVM model. The study was elaborated considering the sub-basin of Rio Pardo, in the Brazilian Atlantic Forest, under a tropical climate. The results indicate that a reasonable adjustment to the soil depth and the spatial resolution (pixel size) can significantly improve the modeling efficiency. In particular, the results for the Rio Pardo sub-basin show that the maximum soil depth should be close to 30 m and the pixel size should be 100 m considering a daily time step.