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.
[1] Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfallrunoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.
The rainfall-runoff response of watersheds is affected by the legacy of past hydroclimatic conditions. We examined how variability in precipitation affected streamflow using 21 years of daily streamflow and precipitation data from five watersheds at the Coweeta Hydrologic Laboratory in southwestern North Carolina, USA. The gauged watersheds contained both coniferous and deciduous vegetation, dominant north and south aspects, and differing precipitation magnitudes. Lag-correlations between precipitation and runoff ratios across a range of temporal resolutions indicated strong influence of past precipitation (i.e., watershed memory). At all time-scales, runoff ratios strongly depended on the precipitation of previous time steps. At monthly time scales, the influence of past precipitation was detectable for up to 7 months. At seasonal time scales, the previous season had a greater effect on a season's runoff ratio than the same season's precipitation. At annual time scales, the previous year was equally important for a year's runoff ratio than the same year's precipitation. Estimated watershed storage through time and specifically the previous year's storage state was strongly correlated with the residuals of a regression between annual precipitation and annual runoff, partially explaining observed variability in annual runoff in watersheds with deep soils. This effect was less pronounced in the steepest watershed that also contained shallow soils. We suggest that the location of a watershed on a nonlinear watershed-scale storage-release curve can explain differences in runoff during growing and dormant season between watersheds with different annual evapotranspiration.
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