Digital Soil Mapping Across Paradigms, Scales, and Boundaries: A Review

Abstract

Digital soil mapping approaches can play a role in providing soil information in a format useful to hydrological modellers, thus filling a void in the current state of hydrology. In this paper, it is shown how an expert knowledge-based digital soil mapping approach was used to provide the soil-related input needed for a process-based hydrological model (ACRU) of the Stevenson Hamilton Research Supersite (SHRS) in the Kruger National Park, South Africa. First, a soil map was created for the entire 4001 ha study area. This soil map had a validation point accuracy of 73 %. Thereafter, the study area was divided into hillslopes. The hillslopes combined with the soil map were used to create a map showing the size and position of the hillslope-specific conceptual hydrological response models (CHRMs). The CHRM map was then used to configure ACRU and to model stream flow in a first-, second- and third-order catchment within the larger area. The stream flow modelling proved successful for the second- and third-order catchments, with Nash–Sutcliffe model efficiency coefficients (NS) of 0.79 and 0.73 for the two catchments, respectively. That the first-order catchment did not model well was explained by the level of detail of the soil mapping which was too coarse to model such a small catchment successfully. All configurations of ACRU modelled the third-order catchment very well (NS between 0.75 and 0.79), but failed to map single rain events consistently. This work showed that digital soil mapping can provide the soil information necessary to configure a process-based stream flow model successfully, provided that the scale of the mapping corresponds with the scale of the first-order controls of the process being modelled. It was indicated that the optimal time frame for this form of hydrological modelling is a hydrological season.