Soil Moisture Responses to Rainfall: Implications for Runoff Generation

Abstract

Soil moisture is a key control on runoff generation and biogeochemical processes on hillslopes. Precipitation events can evoke different soil moisture responses with depth through the soil profile, and responses can differ among landscape positions along a hillslope. We sought to elucidate the nature of these responses by estimating changes in water content, response time between peak precipitation and peak soil moisture, and wetting front velocities for 43 storms at 45 locations on three adjacent hillslopes within a headwater catchment of the southern Appalachian Mountains (NC, USA). We used a multivariate modeling approach to quantify the relative influences and the predictability of soil moisture responses by a combination of landscape and storm characteristics. We quantified the lag correlations between hillslope mean soil moisture and catchment runoff to demonstrate how storm properties and hillslope‐scale characteristics may influence runoff at the catchment outlet. Soil moisture responses varied widely, and no consistent patterns were observed among response metrics laterally or vertically along hillslopes. In contrast to other studies, we found that the relative influence of hillslope properties and storm characteristics varied with soil moisture responses and during storms. Antecedent conditions and storm depths influenced the strength of lag correlations between soil moisture and runoff, whereas storm mean intensity was correlated with the lag times. These results highlight the utility of intensive observations for characterizing heterogeneity in soil moisture responses, suggesting, among other things, a need for better representation of the subsurface processes in rainfall‐runoff models. Identifying the relative importance of drivers can be beneficial in building parsimonious hydrological models.

Dynamic Hillslope Soil Moisture in a Mediterranean Montane Watershed

“…(2009) found similar spatial heterogeneity following precipitation events in sandy volcanic soils, attributing much of the variability across space to preferential flow pathways. Similarly, a large analysis of storm events across watersheds in the southern Appalachian mountains also found that soil moisture responses varied widely depending on hillslope properties, storm characteristics, and antecedent conditions (Singh et al., 2021).…”

Effect of soil thickness on rainfall infiltration and runoff generation from karst hillslopes during rainstorms

“…We calculated three different rainfall event response metrics for each soil moisture, perched water tables at the soil-epikarst interface, and runoff flow on a storm-by-storm basis (Figure 3). We defined a minimum threshold for soil moisture response as a generated change of 0.01 cm 3 cm À3 in 30 min (Singh et al, 2021). The peak value time was defined as the time difference between the time of maximum rainfall intensity at 30 min intervals and the time of peak soil moisture, water table, and runoff flow (Singh et al, 2021).…”

“…We defined a minimum threshold for soil moisture response as a generated change of 0.01 cm 3 cm À3 in 30 min (Singh et al, 2021). The peak value time was defined as the time difference between the time of maximum rainfall intensity at 30 min intervals and the time of peak soil moisture, water table, and runoff flow (Singh et al, 2021). Residual time was defined as the maximum value time minus the change in values in the first 30 min.…”

The Coupling of Soil Water and Leaf Phenology Observed by Satellite During Australian Bushfires in 2019–2020

“…In Australia, the amount of rainfall and the timing of the beginning of the wet season vary from regions hence affects the time of year when soil moisture peaks in different regions. When the wet season arrives, SSM would rise significantly in a short period of time (Li et al., 2015; Singh et al., 2021). By contrast, the growth of vegetation leaves is a relatively slower process, so there might be a time lag between the two. Regarding the impact on SSM from plants.…”

“…For example, woody vegetation covers large areas in the southeast and eastern regions, the northeast and northern areas are mainly covered with savannas and grasslands, and the southwest areas are covered with shrublands and forests. The time lag might vary from different regions of Australia. Rainfall is one of the most important sources of SSM in some regions (Singh et al., 2021), and SSM shares an obvious and strong physical connection with rainfall (Koster Randal et al., 2004; Taylor, 2001). On the one hand, on a regional scale, antecedent SSM has a significant impact on the rainfall‐triggering mechanism.…”