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

Abstract:

Headwater streams account for 70% or more of total stream length in most catchments, making it crucial to better understand the processes and controlling factors governing streamflow generation as well as water quality. In this context, stream water chemistry longitudinal profiles can provide valuable insights. This study examines longitudinal stream chemistry profiles across six headwater catchments in three mid-mountain ranges in Germany: The Ore Mountains (catchments OM 1 and OM 2), Black Forest (BF 1 and BF 2), and Sauerland (SL 1 and SL 2). Three to four snapshot sampling campaigns were conducted per catchment across different seasons and catchment wetness conditions. During the campaigns, water samples were collected from 22 stream monitoring points in the Ore Mountains catchments, 14 in the Black Forest, and 14 in Sauerland, and the samples were analyzed for major cations, anions, and dissolved organic carbon. Subsequently, the longitudinal profiles observed were grouped into spatial and temporal patterns. In the Ore Mountains, solute concentrations were generally stable over time. However, the spatial patterns varied between the two neighbouring catchments (OM 1 and OM 2). OM 2 exhibited chemostatic longitudinal profiles for most solutes, while OM 1 showed pronounced spatial variability in solutes such as nitrate, dissolved organic carbon (DOC), chloride, and sodium. This variability is usually linked to monitoring points located near springs, tributaries, and drainage systems. However, some spikes in ion concentrations along the stream were not linked to these obvious inflows, thus potentially indicating hotspots for groundwater inflow. The Sauerland catchments showed elevated concentrations of DOC, magnesium, calcium, and sodium in July 2023, a period associated with lower streamflow. An increase in concentration from upstream to downstream was here seen in both streams for solutes like calcium and sodium, during all snapshot campaigns. However, other solutes, like nitrate and sulfate, showed different longitudinal patterns and notable shifts in solute concentration during the snapshot campaigns in SL 2. The shifts in patterns indicate a dependency on time-variant factors like seasonal changes in water input, and land use practices. BF 1 catchment in the Black Forest showed a decreasing pattern in DOC, from upstream to downstream, while the neighbouring catchment BF 2 showed a chemostatic trend. These trends could be influenced by the land use changes within the catchments. Notable increased nitrate concentrations were seen along reaches adjacent to grassland areas and at sampling points near tile drains in OM 1, BF 1, SL 1, and SL 2. Overall, solute spatial and temporal patterns were stream-specific, with no universal behaviour observed across all catchments. This variability likely results from the interplay of factors such as geology, soils, land use, stream morphology, and climate. High-resolution spatial sampling enabled the identification of point sources and hotspots of groundwater inflow which could be missed by sparse sampling. These findings enhance our understanding of the processes regulating water quality and flow in headwater systems, providing a basis for better management of these systems.

Abstract:

Subsurface stormflow (SSF) generated on hillslopes is an important hydrological process in headwater catchments. Tracing SSF flow paths and ultimately quantifying its contribution to streamflow is challenging as the signal can undergo various transformations from the hillslope. The riparian zone specifically, can act as a mixing and storage zone and may change strongly the physical and chemical signals of hillslope SSF before it reaches the stream. As a consequence, SSF may not be recognized as streamflow contribution. Thus, the relevance of this process for streamflow generation is currently not fully understood. In addition, studies often focus on quantifying SSF generation at the hillslope scale. Therefore, there is a lack of data to fully understand SSF characteristics at the catchment scale. The aim of this study is to characterize the hillslope-stream connectivity at the reach to catchment scale, using physical as well as chemical information. To deal with the challenges associated with measuring the SSF signal, this study implements a novel multi-method experimental design that will create a unique along-stream data set of hillslope contributions to streamflow in four test catchments in Germany and Austria. A combination of extensive salt dilution gauging along streams, water level measurements in-stream and in near-stream groundwater, longitudinal Radon profiles in streamwater and regular sampling of near-stream groundwater and streamwater for hydrochemical analyses will allow to evaluate the spatial variability of SSF inputs to the stream and to quantify the along-stream attenuation of the SSF signal. Here, we present the study outline as well as first data of water chemistry in near-stream groundwater and streamwater and will characterize the longitudinal patterns of a range of hydrochemical tracers along the streams in the four test catchments. The data set we will collect will be used to simplify and minimize future experimental effort and to identify simple proxies for regionalization. Ultimately, we aim to develop a framework to determine the likelihood of hillslope-stream connectivity at the catchment scale, as influenced by landscape and climate characteristics.

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:

Hydrologic connectivity is the linkage of separate regions of a catchment via water flow. Knowledge of hillslope–stream connectivity (both at the surface and in the subsurface) is essential for understanding and predicting runoff responses and streamwater quality. Connectivity can be very dynamic: hillslopes may connect to the stream only during certain events or seasons. While surface connectivity is often discussed, particularly in the context of sediment transport, subsurface connectivity is more difficult to describe and assess. This difficulty has led to a wide variety in methodologies that are used in various contexts. Field approaches have focused on intensive monitoring of processes on the hillslope or the fingerprint of connectivity in the stream. Combining experimental studies with modeling allows for testing of hypotheses with respect to thresholds and controls on connectivity, and extrapolation from the hillslope scale to the catchment scale. However, as most modeling approaches are based on datasets from a few intensively studied hillslopes, this carries the inherent risk of oversimplification because it assumes that the observed hillslope responses are representative for the catchment or even the region. Focussed efforts on catchment scale assessment of hillslope–stream connectivity, as well as site intercomparisons and the search for similarity measures may allow us to capture the wider picture of the mechanisms and factors that control hillslope–stream connectivity, and its effects on flow and transport at the catchment scale. This overview focuses on how hillslope–stream connectivity has been studied and describes the advantages, disadvantages, and challenges of the different methods. WIREs Water 2015, 2:177–198. doi: 10.1002/wat2.1071 This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Quality