Measurements of the initiation of post‐wildfire runoff during rainstorms using in situ overland flow detectors

Overland flow detectors (OFDs) were deployed in 2012 on a hillslope burned by the 2010 Fourmile Canyon fire near Boulder, Colorado, USA. These detectors were simple, electrical resistor‐type instruments that output a voltage (0–2·5 V) and were designed to measure and record the time of runoff initiation, a signal proportional to water depth, and the runoff hydrograph during natural convective rainstorms. Initiation of runoff was found to be spatially complex and began at different times in different locations on the hillslope. Runoff started first at upstream detectors 56% of the time, at the mid‐stream detectors 6%, and at the downstream detectors 38% of the time. Initiation of post‐wildfire runoff depended on the time‐to‐ponding, travel time between points, and the time to fill surface depression storage. These times ranged from 0·5–54, 0·4–1·1, and 0·2–14 minutes, respectively, indicating the importance of the ponding process in controlling the initiation of runoff at this site. Time‐to‐ponding was modeled as a function of the rainfall acceleration (i.e. the rate of change of rainfall intensity) and either the cumulative rainfall at the start of runoff or the soil–water deficit. Measurements made by the OFDs provided physical insight into the spatial and temporal initiation of post‐wildfire runoff during unsteady flow in response to time varying natural rainfall. They also provided data that can be telemetered and used to determine critical input parameters for hydrologic rainfall–runoff models. Copyright © 2015 John Wiley & Sons, Ltd.     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

A finite element model for simulating surface run‐off and unsaturated seepage flow in the shallow subsurface

This work introduces water–air two‐phase flow into integrated surface–subsurface flow by simulating rainfall infiltration and run‐off production on a soil slope with the finite element method. The numerical model is formulated by partial differential equations for hydrostatic shallow flow and water–air two‐phase flow in the shallow subsurface. Finite element computing formats and solution strategies are presented to obtain a numerical solution for the coupled model. An unsaturated seepage flow process is first simulated by water–air two‐phase flow under the atmospheric pressure boundary condition to obtain the rainfall infiltration rate. Then, the rainfall infiltration rate is used as an input parameter to solve the surface run‐off equations and determine the value of the surface run‐off depth. In the next iteration, the pressure boundary condition of unsaturated seepage flow is adjusted by the surface run‐off depth. The coupling process is achieved by updating the rainfall infiltration rate and surface run‐off depth sequentially until the convergence criteria are reached in a time step. A well‐conducted surface run‐off experiment and traditional surface–subsurface model are used to validate the new model. Comparisons with the traditional surface–subsurface model show that the initiation time of surface run‐off calculated by the proposed model is earlier and that the water depth is larger, thus providing values that are closer to the experimental results.     

Comparing Beerkan infiltration tests with rainfall simulation experiments for hydraulic characterization of a sandy‐loam soil

Saturated soil hydraulic conductivity, K _s , data collected by ponding infiltrometer methods and usual experimental procedures could be unusable for interpreting field hydrological processes and particularly rainfall infiltration. The K _s values determined by an infiltrometer experiment carried out by applying water at a relatively large distance from the soil surface could however be more appropriate to explain surface runoff generation phenomena during intense rainfall events. In this study, a link between rainfall simulation and ponding infiltrometer experiments was established for a sandy‐loam soil. The height of water pouring for the infiltrometer run was chosen, establishing a similarity between the gravitational potential energy of the applied water, E _p , and the rainfall kinetic energy, E _k . To test the soundness of this procedure, the soil was sampled with the Beerkan estimation of soil transfer parameters procedure of soil hydraulic characterization and two heights of water pouring (0.03 m, i.e., usual procedure, and 0.34 m, yielding E _p  = E _k ). Then, a comparison between experimental steady‐state infiltration rates, i _sR , measured with rainfall simulation experiments determining runoff production and K _s values for the two water pouring heights was carried out in order to discriminate between theoretically possible (i _sR  ≥ K _s ) and impossible (i _sR  < K _s ) situations. Physically possible K _s values were only obtained by applying water at a relatively large distance from the soil surface, because i _sR was equal to 20.0 mm h^?1 and K _s values were 146.2–163.9 and 15.2–18.7 mm h^?1 for a height of water pouring of 0.03 and 0.34 m, respectively. This result suggested the consistency between Beerkan runs with a high height of water pouring and rainfall simulator experiments. Soil compaction and mechanical aggregate breakdown were the most plausible physical mechanisms determining reduction of K _s with height. This study demonstrated that the height from which water is poured onto the soil surface is a key parameter in infiltrometer experiments and can be adapted to mimic the effect of high intensity rain on soil hydraulic properties.