Application of hydropedological insights in hydrological modelling of the Stevenson-Hamilton Research Supersite, Kruger National Park, South Africa

Abstract

Soil information is increasingly sought after for hydrological modelling, as the importance of soil in the hydrological cycle is understood better. In this paper the output of a digital soil mapping exercise was used as the soil input into a distributed hydrological model (ACRU) for a test site within the Stevenson-Hamilton Research Supersite, Kruger National Park (South Africa). The aim was to determine the effect of parameterising a hydrological model with increased levels of soil information, at different scales. To accommodate this aim, ACRU was run in 3 different modes, each with increasing levels of input, on 3 catchments, including a 1 st , 2 nd and 3 rd order catchment. The outputs evaluated included both streamflow and soil water content at selected soil profiles. Simulation accuracy increased with higher levels of soil input, as well as with increasing catchment size. The improved accuracy with increased soil input underscores the value of detailed soil information in modelling, while the improved results with increased catchment size show that the optimal scale for including soil information has not yet been reached.

Importance of Detailed Soil Information for Hydrological Modelling in an Urbanized Environment

“…Total discharge is underestimated by 18% for the DSM simulation (compared to >38% for the same soil dataset in the lager catchments), whereas the LT simulations overestimate streamflow by 30%. From our simulations, it appears that detailed soil information becomes more important in smaller areas, where fewer runoff generation processes dominate, a notion supported by [14]. It is also important to recognize that land-use change, such as urbanisation or open-cast mining, is site-specific.…”

“…The advances in digital soil mapping (DSM; [12]) have paved the way for providing detailed soil information in an adequate scale and format for hydrological modelling studies (e.g., [7,[13][14][15][16][17]). But does this enhanced soil information translate into more efficient modelling?…”

“…Several studies found that there is improved accuracy in modelling results when compared to measured streamflow or at least reduced parameter uncertainty during calibration [14,16,[18][19][20]. For example, the inclusion of more detailed soil descriptions and representation in the Agriculture Catchments Research Unit (ACRU) model led to an increase in Nash-Sutcliffe efficiency (NSE) of between 9% and 52% in semi-arid catchments in South Africa [14]. DSM using the Soil Land Inference Model (SoLIM) yielded a more detailed soil map for a data-scarce area in Portugal [16].…”

Combining Historical Remote Sensing, Digital Soil Mapping and Hydrological Modelling to Produce Solutions for Infrastructure Damage in Cosmo City, South Africa

“…To capture the spatial distribution of soil properties, hydropedological studies generally use soil maps [14,15]. However, in urban areas that are already developed, conventional soil maps are impossible to create due to the limited access to undisturbed soil observation positions.…”

Improved Hydrological Understanding of a Semi-Arid Subtropical Transboundary Basin Using Multiple Techniques – The Incomati River Basin

“…Several studies (e.g. Van Tol et al, 2015;van Zijl et al, 2016) have used digital soil mapping to derive parameters for hydrological models. However, detailed soils map information at the level of transboundary river basins, such as the Incomati basin is not available.…”