Guidance for parameterizing post-fire hydrologic models with in situ infiltration measurements

Wildfire can alter soil-hydraulic properties, often resulting in an increased prevalence of infiltration-excess overland flow and greater potential for debris-flow hazards. Mini disk tension infiltrometers (MDIs) can be used to estimate soil hydraulic properties, such as field-saturated hydraulic conductivity (K_fs) and wetting front potential (H_f), and their spatial variability following wildfire. However, the small (point-scale) footprint of MDI measurements makes it challenging to use these data to parameterize hydrologic models at the hillslope and watershed scales where hydrologic hazards, such as debris flows, initiate. Here, we designed numerical experiments to estimate spatially constant or watershed-scale effective hydrologic parameters (EHPs) that approximate the response of spatially variable hydrologic parameters with distributions derived from MDI measurements at five sites in the southwestern United States. We found that it is possible to define EHPs for both K_fs and H_f based on the MDI measurements that lead to reasonable approximations of run-off hydrographs at the outlets of small watersheds (<1 km²). We found that watershed EHPs are functions of rainfall characteristics, although they are most sensitive to rainfall intensity and relatively less sensitive to the temporal distribution of rainfall. EHPs are lower than the arithmetic mean of the MDI measurements and are better approximated by the median or geometric mean of the MDI measurements, particularly for storms with recurrence intervals of approximately 1 year or less that commonly initiate post-fire debris flows. This work demonstrated that using the proposed upscaling method to estimate watershed-scale EHPs, as opposed to approximating EHPs based on the arithmetic mean of the MDI measurements, improved the ability of a hydrologic model to identify storms that are likely to produce debris flows. Results improved our ability to link point-scale MDI measurements and watershed-scale EHPs in post-fire settings and helped guide our ability to use MDI data to parameterize post-fire hydrologic models.