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Subsurface water flows play a key role in the distribution of water and solutes and thereby in the water availability for plants. However, the characterization of different flow processes (i.e.matrix and preferential flow), the frequency and factors that cause them, is relatively rare. This characterization enables a better understanding of spatio-temporal variability of water resources and allows for the design of models to be improved. Using a method based on the time derivative of soil moisture variation known as maximum wetting slope, types of soil wetting processes were classified and quantified. For this, capacitance sensors, which registered the volumetric water content at high temporal resolution (30min) for more than two hydrological years, were installed at different depths and placed in soil moisture stations with different vegetation covers, lithology and topographic position. Results indicated that there is a general behaviour or pattern of soil moisture dynamics in the catchment with a dominant occurrence of slower soil wetting processes (>50%), caused by matrix flows, and a low occurrence of those faster processes (<30%), originated by preferential flows. Nevertheless, when the total volume of water is considered, preferential flow becomes the dominant process, so that the ecological role of both flow types becomes prominent in water-limited environments. Statistical multivariate analyses based on data-mining techniques proved that although both flow types depend on variables associated with precipitation and antecedent soil moisture conditions, faster soil wetting processes are mainly related to variables such as rainfall intensity and topography, while slower soil wetting processes are related to flow velocity, soils or vegetation. Copyright (c) 2015 John Wiley & Sons, Ltd.
Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However, in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here, we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapunos catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (>13.3mm30min(-1)) however show large differences between the versions with and without macropores. These model results compared with measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore, preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events. Copyright (c) 2013 John Wiley & Sons, Ltd.