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Disentangling event-scale hydrologic flow partitioning in mountains of the Korean Peninsula under extreme precipitation

Shope, Christopher L.
Journal of hydrology 2016 v.538 pp. 399-415
altitude, base flow, forests, groundwater, isotope labeling, landscapes, mountains, pollution load, runoff, sediment yield, spatial variation, stable isotopes, subsurface flow, temporal variation, watersheds, South Korea
Mountainous headwaters include a variety of spatial landscape units; however, the flow contribution from different hydrologic components is complex and often unclear. In addition to complex landscape controls, temporal meteorological drivers play an important role in the distribution between surface runoff and subsurface storage changes. This spatiotemporal variability in partitioning can influence catchment-wide flow accumulation and nutrient and sediment loading. We use a multi-year, multi-method analysis of stable isotopes, geochemical indicators, and discharge distributed throughout the Haean catchment in South Korea to identify temporal variability in hydrologic flow partitioning from surface runoff, springs, shallow interflow, and groundwater under monsoonal conditions. By combining a weighted, multi-method discharge approach, high frequency, synoptic, catchment-wide isotopic and geochemical sampling, and baseflow analysis, we characterize watershed-scale spatiotemporal hydrologic flow partitioning. Meteorological drivers are spatially variable throughout the catchment and temporally between individual events. Baseflow contributions in the high elevation, forested areas are up to 50%, while the majority of the catchment is approximately 20%. Our study builds on previously reported seasonality of isotopic signatures by quantifying trends in distributed event-based partitioning of isotopic tracers. We demonstrate that high frequency flow partitioning can accurately be determined in mountainous topography with high precipitation and that there is a need for multiple method characterizations. Our results further show the benefit of spatially distributed synoptic sampling for process understanding of hydrologic partitioning throughout the watersheds.