FOR 5288: Fast and invisible: Conquering Subsurface Stormflow
through an Interdisciplinary Multi-Site Approach

Abstract:

Environmental tracers have been used to separate streamflow components for many years. They allow us to quantify the contribution of water originating from different sources, such as direct runoff from precipitation, subsurface storm flow, or groundwater to total streamflow at variable flow conditions. Although previous studies have explored the value of incorporating experimentally derived fractions of event and pre-event water into hydrological models, a thorough analysis of the value of incorporating hydrographseparation-derived information on multiple streamflow components at varying flow conditions into model parameter estimation has not yet been performed. This study explores the value of such information to achieve more realistic simulations of catchment discharge. We use a modified version of the process-oriented HBV model that simulates catchment discharge through the interplay of hillslope, riparian-zone discharge, and groundwater discharge at a small forested catchment which is located in the mountainous north of South Korea, subject to a monsoon season between June and August. Applying a Monte-Carlo-based parameter estimation scheme and the Kling–Gupta efficiency (KGE) to compare discharge observations and simulations across two seasons (2013 and 2014), we show that the model is able to provide accurate simulations of catchment discharge (KGE 0.8) but fails to provide robust predictions and realistic estimates of the contribution of the different streamflow components. Using a simple framework that compares simulated and observed contributions of hillslope, riparian zone, and groundwater to total discharge during two sub-periods, we show that the precision of simulated streamflow components can be increased, while remaining with accurate discharge simulations.We further show that the additional information increases the identifiability of all model parameters and results in more robust predictions. Our study shows how tracer-derived information on streamflow contributions can be used to improve the simulation and predictions of streamflow at the catchment scale without adding additional complexity to the model. The complementary use of temporally resolved observations of streamflow components and modeling provides a promising direction to improve discharge prediction by representing model internal dynamics more realistically.

Abstract:

Abstract Environmental DNA (eDNA) has revolutionized ecological research, particularly for biodiversity assessment in various environments, most notably aquatic media. Environmental DNA analysis allows for non-invasive and rapid species detection across multiple taxonomic groups within a single sample, making it especially useful for identifying rare or invasive species. Due to dynamic hydrological processes, eDNA samples from running waters may represent biodiversity from broad contributing areas, which is convenient from a biomonitoring perspective but also challenging, as hydrological knowledge is required for meaningful biological interpretation. Hydrologists could also benefit from eDNA to address unsolved questions, particularly concerning water movement through catchments. While naturally occurring abiotic tracers have advanced our understanding of water age distribution in catchments, for example, current geochemical tracers cannot fully elucidate the timing and flow paths of water through landscapes. Conversely, biological tracers, owing to their immense diversity and interactions with the environment, could offer more detailed information on the sources and flow paths of water to the stream. The informational capacity of eDNA as a tracer, however, is determined by the ability to interpret the complex biological heterogeneity at a study site, which arguably requires both biological and hydrological expertise. As eDNA data has become increasingly available as part of biomonitoring campaigns, we argue that accompanying eDNA surveys with hydrological observations could enhance our understanding of both biological and hydrological processes; we identify opportunities, challenges, and needs for further interdisciplinary collaboration; and we highlight eDNA's potential as a bridge between hydrology and biology, which could foster both domains. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Water and Life > Nature of Freshwater Ecosystems