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

Highlights

• Multi-year and -method discharge, baseflow, geochemistry and isotope analysis.

• High elevation baseflow near 50%, while low elevation is approximately 20%.

• Build upon reported isotopic seasonality with event-based characterization in Korea.

• Event-based characterization defines spatiotemporal structure and storm evolution.

• Explicitly describe a need for multiple method analysis for hydrologic partitioning.

Summary

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.

Introduction

Not only does spatial variability of heterogeneous soil, geology, topography, and land use have an impact on flow partitioning (Boluwade and Madramootoo, 2013), temporal meteorological forcing conditions play an important role by inducing rapid surface runoff and seasonal-scale subsurface storage changes (Radatz et al., 2013). Hydrologic flow partitioning is defined as the separation of precipitation into different storage components and their resulting fluxes in the catchment including; surface runoff, baseflow, shallow interflow, and shallow and deep groundwater recharge. In areas with extreme monsoonal precipitation conditions, accurate estimation of both flow volume and the distribution of that flow are needed to assess the quantity and timing of discharge at discreet monitoring locations (Wulf et al., 2010, Zhai et al., 2005). The variability in topography, soil, and land use distribution throughout a catchment can have significant effects on recharge contributions and partitioning over a range of elevations. Differences in process-based hydrologic partitioning can further affect local-scale loading, increasing the vulnerability of streams to legacy nitrate issues and source lag times (Tesoriero et al., 2013). Surface water discharge has also been shown to be highly variable and dependent on not only the meteorological drivers but also agricultural management activities, crop development, urbanization, and anthropogenic engineering (Shope et al., 2014, Shope et al., 2013).

A variety of methods have been used to assess the spatial characterization of hydrologic partitioning including field-based techniques (Béziat et al., 2013, Shope et al., 2013), tracer approaches (Christophersen and Hooper, 1992, Fischer et al., 2015, Inamdar et al., 2013, Lu, 2014, Penna et al., 2014), remote sensing (Renzullo et al., 2008), and modeling simulations (Boluwade and Madramootoo, 2013, Yu et al., 2013). Llorens and Domingo (2007) provide an extensive review of rainfall at 83 sites in the Mediterranean area of Europe and the importance of using standard measurement protocols to better assess this critical process in ecosystem functioning. Utilizing remotely sensed data to inform a hydrodynamic model in the Lake Eyre Basin, Australia, Jarihani et al. (2015) showed that the catchment water balance could be constrained in data sparse locations. Using a different approach, controls on metrics of hydrologic partitioning in Tenderfoot Creek, Montana were modeled by Kelleher et al. (2015). The authors found that using this comparative hydrology approach across watersheds limits the need for observational analysis in lieu of comparative similarities and differences in the perceptual model. Six northern catchments in Sweden, Canada, Scotland, and the USA were examined using conceptual rainfall–runoff models and the stable isotopes to better understand the relationship between hydrologic partitioning and ecohydrologic influences (Tetzlaff et al., 2015). The authors argue that stable isotope studies are crucial in quantifying hydrologic partitioning and functioning in northern environments. Troch et al. (2013) found that a strong co-evolution of catchment vegetation and soil properties with climate leads to specific hydrologic partitioning at the catchment scale.

Much of the border along North and South Korea is relatively ungauged due to the inability to install a sufficient monitoring network and these monitoring sites are typically constrained to areas adjacent to roads, bridges, and engineered structures. Due to longstanding geopolitical differences, a lack of remotely sensed geographic information is prevalent throughout the demilitarized zone between North and South Korea. Often, the observational time series is typically constrained by the length of the investigation period, which generally lacks annual variability in meteorological conditions. However, quantification of observed hydrologic sources can assist in the characterization of watershed-scale distributed nutrient and sediment loading that is typically integrated at the catchment outlet. The Haean watershed is an area of intensive soil erosion in South Korea, and a number of studies have quantified the catchment sediment rate (Arnhold et al., 2013, Ruidisch et al., 2013), point source nutrient loading (Jeong et al., 2012, Jung et al., 2012, Kettering et al., 2012), and the development of best management practices (Arnhold et al., 2013). Kim et al. (2011) found a correlation between increased agricultural production in the watershed in recent years and increased nutrient and fertilizer additions to the shallow soil. These local nutrient additions as well as regional increases in atmospheric deposition contribute both point and nonpoint sources, which impact water quality (Bartsch et al., 2013, Jeong et al., 2012, Jung et al., 2012, Kettering et al., 2013, Kettering et al., 2012).

We aimed to identify how hydrologic flow partitioned between different hydrologic components across a steep elevation gradient and how this partitioning changes over different events. We present a distributed multi-method analysis to identify which sources of water contribute to streamflow and how they vary in time. We conducted 3 synoptic sampling campaigns from 2009–2011 over the course of up to 72 h. We use a robust field data set for source identification including; (1) weighted, multi-method discharge; (2) multi-method baseflow estimates; (3) stable isotope analysis for source apportionment; and (4) modeled source contributions. Further, we incorporate event-based variability in these indicators that to our knowledge, has not been introduced in the literature. Our study demonstrates the need for multiple methods in the characterization of spatiotemporal baseflow and groundwater contributions throughout a topographically complex catchment under extreme monsoonal conditions.