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.

Predicting runoff source areas and how they change through time is a challenge in hydrology. Topographically induced lateral water redistribution and water removal through evapotranspiration lead to spatially and temporally variable patterns of watershed water storage. These dynamic storage patterns combined with threshold mediation of saturated subsurface throughflow lead to runoff source areas that are dynamic through time. To investigate these processes and their manifestation in watershed runoff, we developed and applied a parsimonious but spatially distributed model (WECOH—Watershed ECOHydrology). Evapotranspiration was measured via an eddy‐covariance tower located within the catchment and disaggregated as a function of vegetation structure. This modeling approach reproduced the stream hydrograph well and was internally consistent with observed watershed runoff patterns and behavior. We further examined the spatial patterns of water storage and their evolution through time by building on past research focused on landscape hydrologic connectivity. The percentage of landscape area connected to the stream network ranged from less than 1% during the fall and winter base flow period to 71% during snowmelt. Over the course of the 2 year study period, 90% of the watershed areas were connected to the stream network for at least 1 day, leaving 10% of area that never became connected. Runoff source areas during the event shifted from riparian dominated runoff to areas at greater distances from the stream network when hillslopes became connected. Our modeling approach elucidates and enables quantification and prediction of watershed active areas and those active areas connected to the stream network through time.

The exposure of freshwater-dependent coastal ecosystems to saltwater is a present-day impact of climate and land-use changes in many coastal regions, with the potential to harm freshwater and terrestrial biota, alter biogeochemical cycles and reduce agricultural yields. Land-use activities associated with artificial drainage infrastructure (canals, ditches, and drains) could exacerbate saltwater exposure. However, studies assessing the effects of artificial drainage on the vulnerability of coastal landscapes to saltwater exposure are lacking. We examined the extent to which artificial drainage infrastructure has altered the potential for saltwater intrusion in the coastal plain of eastern North Carolina. Regional spatial analyses demonstrate that artificial drainages not only lower the overall elevation in coastal landscapes, but they also alter the routing and concentration of hydrological flows. Together, these factors have the potential to increase the total proportion of the landscape vulnerable to saltwater intrusion, not only in areas adjacent to drainage infrastructure but also in places where no artificial drainages exist due to large scale effects of flow rerouting. Among all land cover types in eastern North Carolina, wetlands are most vulnerable to saltwater exposure. Droughts and coastal storms associated with climate change potentially exacerbate vulnerability to saltwater facilitated by artificial drainage.

Changes in streamflow are an important area of ongoing research in the hydrologic sciences. To better understand spatial patterns in past changes in streamflow, we examined relationships between watershed‐scale spatial characteristics and trends in streamflow. Trends in streamflow were identified by analyzing mean daily flow observations between 1940 and 2009 from 967 U.S. Geological Survey stream gages. Results indicated that streamflow across the continental U.S., as a whole, increased while becoming less extreme between 1940 and 2009. However, substantial departures from the continental U.S. (CONUS) scale pattern occurred at the regional scale, including increased annual maxima, decreased annual minima, overall drying trends, and changes in streamflow variability. A subset of watersheds belonging to a reference data set exhibited significantly smaller trend magnitudes than those observed in nonreference watersheds. Boosted regression tree models were applied to examine the influence of watershed characteristics on streamflow trend magnitudes at both the CONUS and regional scale. Geographic location was found to be of particular importance at the CONUS scale while local variability in hydroclimate and topography tended to have a strong influence on regional‐scale patterns in streamflow trends. This methodology facilitates detailed, data‐driven analyses of how the characteristics of individual watersheds interact with large‐scale hydroclimate forces to influence how changes in streamflow manifest.