Journal
HYDROLOGICAL PROCESSES
Volume 18, Issue 5, Pages 1009-1026Publisher
WILEY
DOI: 10.1002/hyp.1455
Keywords
air permeability; saturated hydraulic conductivity; spatial variability; surface runoff; modelling
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The time required at a field site to obtain a few measurements of saturated hydraulic conductivity (K-s) will allow for many measurements of soil air permeability (k(a)). This study investigates if k(a) measured in situ (k(a,in) (situ)) can be a substitute for measurement of K-s in relation to infiltration and surface runoff modelling. Measurements of k(a,in situ) were carried out in two small agricultural catchments. A spatial correlation of the log-transformed values existed having a range of approximately 100 m. A predictive relationship between K-s and k(a) measured on 100-cm(3) soil samples in the laboratory was derived for one of the field slopes and showed good agreement with an earlier suggested predictive K-s-k(a) relationship. In situ measurements of K-s and k(a) suggested that the predictive relationships also could be used at larger scale. The K-s-k(a) relationships together with the k(a,in situ) data were applied in a distributed surface runoff (DSR) model, simulating a high-intensity rainfall event. The DSR simulation results were highly dependent on whether the geometric average of k(a,in situ) or kriged values of k(a,in situ) was used as model input. When increasing the resolution of K, in the DSR model, a limit of 30-40 m was found for both field slopes. Below this limit, the simulated runoff and hydrograph peaks were independent of resolution scale. If only a few randomly chosen values of K-s were used to represent the spatial variation within the field slope, very large deviations in repeated DSR simulation results were obtained, both with respect to peak height and hydrograph shape. In contrast, when using many predicted K-s values based on a K-s-k(a) relationship and measured k(a,in situ) data, the DSR model generally captured the correct hydrograph shape although simulations were sensitive to the chosen K-s-k(a) relationship. As massive measurement efforts normally will be required to obtain a satisfactory representation of the spatial variability in K-s, the use of k(a,in situ) to assess spatial variability in K-s appears a promising alternative. Copyright (C) 2004 John Wiley Sons, Ltd.
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