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

Johan Van Tol,George Van Zijl,Stefan Julich

doi:10.3390/hydrology7020034

Johan Van Tol, George Van Zijl + Show 1 more

Open Access

https://doi.org/10.3390/hydrology7020034

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Abstract

Soil information is critical in watershed-scale hydrological modelling; however, it is still debated which level of complexity the soil data should contain. In the present study, we have compared the effect of two levels of soil data on the hydrologic simulation of a mesoscale, urbanised watershed (630 km2) in central South Africa. The first level of soil data, land type (LT) data, is currently the best, readily available soil information that covers the whole of South Africa. In the LT database, the entire study area is covered by only two soil types. The second level of soil data (DSM) was created by means of digital soil mapping based on hydropedological principles. It resulted in six different soil types with different hydrological behaviour (e.g., interflow, recharge, responsive). The two levels of soil data were each included in the revised version of the Soil and Water Assessment Tool (SWAT+). To compare the effects of different complexity of soil information on the simulated water balance, the outputs of the uncalibrated models were compared to the three nested gauging stations of the watershed. For the LT scenario, the simulation efficiencies calculated with the Kling–Gupta efficiency (KGE) for the three nested gauging stations (640 km2, 550 km2, 54 km2) of 0, 0.33 and −0.23 were achieved, respectively. Under the DSM scenario, KGE increased to 0.28, 0.44 and 0.43 indicating an immediate improvement of the simulation by integrating soil data with detailed information on hydrological behaviour. In the LT scenario, actual evapotranspiration (aET) was clearly underestimated compared to MODIS-derived aET, while surface runoff was overestimated. The DSM scenario resulted in higher simulated aET compared to LT and lower surface runoff. The higher simulation efficiency of DSM in the smaller headwater catchments can be attributed to the inclusion of the interflow soil type, which covers the governing runoff generation process better than the LT scenario. Our results indicate that simulations benefit from more detailed soil information, especially in smaller areas where fewer runoff generation processes dominate.

Highlights

Soil is a dominant factor in controlling hydrological flowpaths through partitioning precipitation into different components of the water balance
The number of hydrological soil response units (HRUs) was, twice as high for the digital soil mapping (DSM) simulation when compared to the Land Type (LT) simulation (i.e., 2034 and 1132, respectively)
This is due to the higher level of detail in the DSM soil map compared to the LT soil map (Figure 3)

Summary

Introduction

Soil is a dominant factor in controlling hydrological flowpaths through partitioning precipitation into different components of the water balance. The models rely strongly on calibration against measured data, to optimise simulations and account for the lack of adequate representation of the heterogeneous landscape [6,7,8]. These models tend to be over-parameterised, with many combinations of the model structure or parameters leading to the same final result (i.e., equifinality [9,10]). This limits their value to predicting the impact of climate and land-use change, as well as their extrapolation value to ‘ungauged’ areas

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Discussion

Conclusion