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

Abstract:

Subsurface stormflow (SSF) is a streamflow generation process that is difficult to observe. It has therefore been challenging to evaluate the relevance and magnitude of SSF contributions to streamflow quantity and quality. However, some earlier studies have shown that it can deliver substantial amounts of water to the stream at the time scale of an event. One possible approach for detecting SSF in streamflow has been to sample SSF on hillslopes, characterize it by analyzing various tracers and search for this SSF fingerprint in stream water samples. In this study, we ask the following questions: Does subsurface stormflow generated on hillslopes and moving downslope towards the stream have a typical chemical fingerprint or signature by which we could recognize it in the stream? And does this signature vary over time? Here, we present data from a headwater catchment near Freiburg, Germany, where we installed three trenches to measure SSF flow rates and to obtain SSF samples for chemical analysis. We collected SSF samples from the three trenches over multiple events during spring 2023, fall 2023 and spring 2024 and analyzed them for dissolved organic carbon and major ions. We compared chemical SSF signatures through the events, across seasons and between the three trenches. Preliminary analyses indicate that the SSF signature changed during events, with SSF signatures at the beginning and at the end of events being remarkably similar to each other. Results also hint at a seasonal stability of SSF signatures. In our presentation, we are going to present a detailed analysis of the dynamics of the chemical SSF signature. This dataset provides a unique opportunity to evaluate the chemical composition of subsurface stormflow in sub-daily resolution at three different hillslopes and to improve our capability to recognize contributions of SSF to streamflow.

Abstract:

Extreme rainfall events are likely to increase in intensity and frequency due to climatic changes and therefore the forecast of flooding events will become more important in the following decades. The flow properties of rainwater in the subsurface play a critical role in the flood formation process, but the underlying mechanism of this subsurface stormflow (SSF) formation has not been fully understood so far. Here, we explore the viability of environmental DNA (eDNA) as an indicator for small-scale flow pathway reconstruction. eDNA comprises genetic signatures from organisms across the Tree of Life (ToL), from whole microorganisms to molecular traces of higher taxa, such as plants or animals. The degree of similarity of biodiversity patterns indicates biological and therefore, in principle, also hydrological connectivity. As part of the SSF Research Unit we characterised 3 trenched hillslopes in 4 catchment areas in Germany and Austria through eDNA ToL-metabarcoding. With this broad-range approach, we aim to understand whether and how eDNA diversity patterns can inform subsurface flow pathways. We found three-dimensional connectivity patterns of biodiversity indicating systematic barriers as well as pathways of hydrological connectivity within each hillslope. Variation between catchments reflects their geographic differences as well as geological peculiarities. Although our results support the potential of eDNA to identify flow pathways and enhance our understanding of SSF, we are still at the beginning of understanding the viability of eDNA as a tracer in hydrological research. Nonetheless, making use of such natural occurring tracers can extend our understanding of hydrological phenomena and can contribute to a more accurate flood prediction.

Abstract:

Rainfall runoff contributes to a large proportion of the discharge in streams and therefore, heavily influences stream water quality but also flood generation. Rainfall runoff generation is usually a combination of overland and subsurface flow processes, the latter of which being especially difficult to trace. Here, we explored the viability of environmental DNA (eDNA) for subsurface water flow pathway reconstruction and simultaneous biodiversity assessment. The degree of similarity of community patterns indicates biological and therefore, in principle, also hydrological connectivity. We applied eDNA metabarcoding to characterise 10 drilling cores (0.7-3.2 m depth) on 3 hillslopes (10x50 m) in 4 catchment areas in Germany and Austria. In total, more than 2000 species across taxonomic groups could be identified down to species level. Analysis of alpha and beta diversity in the different catchments showed significant differences in spatial clustering patterns between taxonomic groups, but also between geomorphological and geochemical properties, such as the composition of dissolved organic carbon, of the respective catchment. We could assign indicator species sets in all taxonomic groups to various depth layers and identify habitat-specific communities that can be used as hydrological tracers. Although our results support the potential of eDNA to identify flow pathways and enhance our understanding of subsurface flow processes, we are still at the beginning of understanding the viability of eDNA as a tracer in hydrological research. However, our results show that making use of such naturally occurring tracers can expand our understanding of hydrological phenomena, especially those hidden in the subsurface.

Abstract:

In addition to overland flow, subsurface stormflow (SSF) can play a major role for runoff generation during certain events. Even though SSF is a well-recognised process, there is a lack of systematic studies on SSF, partly because it is very difficult to quantify. In hydrological modelling, this can lead to an unclear distinction of SSF from other processes. If parameters that describe SSF processes or thresholds are implemented in hydrological models, they are often used as fitting parameters and can contribute to overall model uncertainty. So far, there has been no systematic benchmarking of SSF routines in hydrological models. This presentation discusses how we plan to address this research gap. In order to address the inconsistency of SSF representation in hydrological models, different existing lumped hydrological models will be set up for four study sites located in the Alps, Ore Mountains, Black Forest and Sauerland. In a first step, different models will be calibrated using only basic data like discharge observations, climate data and readily available geodata. Differences in SSF simulations will be detected and quantified and the models will be benchmarked regarding the simulation of SSF dynamics and associated uncertainties. In a next step, we will include new experimental data on SSF derived at the four study sites in the calibration of the lumped hydrological models by a multi-objective calibration and evaluation framework. In order to consider SSF observations collected at scales different than the scale of model application, new SSF metrics will be developed. Testing different combinations of these metrics for model calibration it will be possible to state which SSF proxies can lead to the most productive improvement of SSF simulations. Identifying current weaknesses in SSF representation of current models, and providing directions for improving them by including the most beneficial SSF metrics, this project will show potential for the improvement of SSF simulations through SSF data collection. In a final application of the most reliable SSF simulations to all study sites, we will show the impact of extreme wet or extreme dry conditions on SSF occurrence and SSF volumes.

Abstract:

Subsurface stormflow (SSF) can be a major streamflow generation process in small catchments. It is known that SSF generated on the hillslopes of the catchment may change both in its chemical and quantitative composition on the way to the stream. This occurs primarily due to processes in the riparian zone. The riparian zone plays the role of a "reactor" where mixing, storage, and biogeochemical transformation of the hillslope SSF composition occurs. However, we still lack a comprehensive understanding of this “gatekeeper function” of the riparian zone, controlling the timing and spatial patterns of connectivity and the chemistry of the water being transferred from the hillslopes into the stream. In our study we aim to investigate the SSF signal transformation in the riparian zone. We installed three “dual-use trenches” per catchment in four different catchments located in Germany and Austria. With this novel dual-use trench approach we are able to measure hillslope SSF as well as inject tracer into the riparian zone. We measure response dynamics, timing, flow volumes and chemistry at the upslope side of the trench. We will identify tracers or tracer combinations that characterize SSF and can be used to identify hillslope SSF in riparian zone groundwater and stream flow. The inter-comparison of the four different catchments allows us to evaluate the influence of landscape and climate characteristics. We then use tracer injections at the downslope side of the dual-use trench in combination with an array of shallow groundwater observation wells downslope of the trench to investigate the physical and chemical transformation of hillslope SSF in the riparian zone. This array of wells extends both upstream and downstream of the trench, enabling us to trace the transformation of the uninterrupted physical and chemical signal of SSF on the adjacent hillslopes on its passage to the stream and to evaluate the influence of parafluvial flow. Here, we present first data on tracer concentrations in hillslope SSF and riparian zone groundwater from our test catchments. Ultimately, we aim to develop a conceptual matrix, by which it will be possible to estimate the degree of SSF transformation in the riparian zone, depending on watershed characteristics (topography, soil depth and soil hydraulic properties) and hydrological conditions (antecedent wetness of the watershed and seasonal dynamics).

Abstract:

The use of artificial rainfall simulation (ARS) is a common method to study the interaction of soil and water (Strauss et al. 2000). Traditionally, precipitation simulation has been used as a tool to assess and determine the importance of surface runoff, usually with reference to soil erosion. Large-scale experiments are generally rare, although they are an efficient way to obtain directional soil hydraulic properties that functionally average local heterogeneities. Flow processes in the subsurface are usually measured indirectly. Such non-destructive methods for measuring subsurface flow processes often rely on soil moisture measurements or other indirect geophysical measurements (ERT, EMI, GPR,...) often accompanied by isotope or tracer analyses. Direct measurement of subsurface rainfall runoff involves considerable effort and cost, and in some cases, it is even impossible e.g., when it is not possible to dig a drainage ditch. At BFW - Department of Natural Hazards, about 150 representative plots in the Eastern Alps have been irrigated over the last 30 years using portable sprinkler systems for large plots (50 to 400 m²). In total, more than 350 rain simulation trials have been conducted. Specifically, this BFW rainfall simulation database contains data from 11 plots and 21 experiments where subsurface storm runoff was directly quantified. The results derived from these eleven test plots basically confirm the often-observed bimodal nature of subsurface flow, consisting of preferential/macropore flow and flow through the soil matrix (e.g., Weiler et al. 2005, Dasgupta et al. 2006, …). Preferential flow paths are mostly attributable to heterogeneities in the soil. Preferential macropore flow can be differentiated by means of such various types of heterogeneities. Four specific categories may be distinguished: phytogenic macropores (e.g. cavities left by decomposing roots); zoogenic macropores e.g. mole burrows, mouse holes); geogenic heterogeneities (e.g. periglacial cover beds, bedrock fissures and cracks) and anthropogenic heterogeneities (e.g. drainage systems, tillage pans). Each of these four categories is covered by at least one experiment in the BFW data record. The observed subsurface hydrographs provide insight into the process-dependent differences in precipitation-infiltration-subsurface runoff response. In a research group currently applied for at the DFG (SSF Research Unit), new and novel irrigation experiments for the measurement of subsurface stormflow will be carried out in four test areas and the existing ones from the BFW database will be reanalyzed and modeled.

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:

The transport of water-soluble organic matter (WSOM) during stormflow events is an important link between hillslope hydrology and biogeochemical cycling, as it determines the movement of organic carbon from soils to streams. Hydrological dynamics in hillslopes, particularly subsurface stormflow (SSF), exhibit substantial spatial and temporal variability, making quantification and generalization challenging. SSF can account for up to 90% of rainfall input to stream discharge during storm events, highlighting its importance in catchment hydrology. Despite its significance, current research frequently overlooks WSOM dynamics during SSF, which are not only key components of carbon cycling but may also serve as tracers for identifying potential critical source areas. This emphasizes the importance of studying hillslope hydrological dynamics and determining the factors that contribute to SSF spatial and temporal variability. Furthermore, the specific flow paths within hillslopes remain poorly understood, which complicates the identification of spatial sources and transport mechanisms for organic carbon. To fill these knowledge gaps, we conducted a field study in the Black Forest, Germany, using a trench system to collect lateral subsurface flows at two depths (0-100 cm and 100-200 cm) over several rain events. We analysed WSOM concentration and quality using absorbance and fluorescence properties to assess the variability in critical source areas. We also conducted isotopic analyses of oxygen (δ¹⁸O) and hydrogen (δ²H) of the same water samples to infer flow pathways with a conservative tracer. This approach provides valuable insights into the temporal dynamics and spatial heterogeneity of SSF. Our findings will contribute to our understanding of flow paths, transit times, and the characteristics of WSOM export, offering a deeper understanding of subsurface flow processes in catchments. Finally, the findings of this study can help to improve biogeochemical models and improve scaling of hillslope processes models, particularly in understanding their contribution to organic carbon transport via SSF.

Abstract:

Hydrological dynamics of hillslopes, particularly subsurface stormflow (SSF), are highly complex and variable in space and time. Frequently, available studies are often limited to single slopes or few storm events. As a result, the transfer of these findings to other slopes or catchments is associated with great uncertainties. Thus, for upscaling and model validation, a quantification of the hydrological dynamics of hillslopes and the factors influencing the spatial and temporal patterns of subsurface stormflow is urgently needed. Closely related to the hydrological dynamics of hillslopes is the export of organic carbon from the soils to the adjacent stream. However, the spatial sources of carbon are still largely unclear because the exact flow paths of SSF within the slope are not well known. In order to address this knowledge gap, we took a hydro-biogeochemical approach, that measures the water-soluble organic matter (WSOM; concentration, absorbance and fluorescence) along 480 locations on 100 hillslopes, in four contrasting catchments – varying from low to high mountain ranges (Sauerland, Ore Mountains, Black Forest, Alps). This enables us to derive empirical relations among different landforms (i.e., convergent, divergent and planar slope shapes, flow path lengths and valley shapes), bedrock and soil properties, and to quantify the spatial variability and stability of subsurface hydrological process patterns (e.g., flow directions, transit times, hydrochemical and biochemical composition). Distributed sampling of WSOM along the soil profile (6 WSOM samples per profile; both during wet and dry conditions) will help to assess the vertical and lateral subsurface flowpaths of water in the unsaturated and saturated zone, and the spatial discretization of source areas for SSF. We will use an array of state-of-the-art laboratory equipment and methods (TOC-Analyzer, Fluorescence Spectrometry) to analyze WSOM. First results will show depth profiles of WSOM in the four contrasting catchments from the low to high mountain ranges (Sauerland, Ore Mountains, Black Forest, Alps). By these depth profiles source areas of SSF can be detected.

Abstract:

Where does water go when it rains? Where are floods generated and how? What controls stream water quality during events? These questions are important to many fields from engineering and flood protection to water and ecosystem management and prediction of impacts of global change. The most elusive processes in the process-ensemble underlying these questions is subsurface stormflow (SSF), the fast event response triggered by lateral subsurface flow. SSF is prevalent and a more important process than generally accounted for because a basic understanding based on systematic studies across scales and sites is still lacking. However, only with systematic studies will it be possible to really advance our understanding by discovering general principles of SSF functioning and to provide protocols and best practices for its assessment, both experimentally and with respect to modelling. In many natural landscapes, SSF, i.e. any subsurface flow that occurs in response to a precipitation event, plays a major role in runoff generation: either by contributing directly to streamflow or by producing saturated areas or return flow, which then is the underlying cause of saturation excess overland flow. Therefore, much of what we see as event response in the hydrograph might be the direct or indirect result of SSF. It is likely that the discharge signal of SSF, including the indirectly triggered response in the stream, is larger than we generally assume. While its importance is probably largest in the headwaters, headwaters make up 70% of the stream network and greatly influence the supply and transport of water and solutes downstream. However, SSF is elusive and poorly accounted for as measurements are difficult for several reasons: the inaccessibility of the subsurface, the large spatial variability and heterogeneity, the variable sources and the fact that it is a threshold-driven process that only occurs during certain events. Thus, systematic studies of SSF are lacking, mainly due to difficulties of quantification. We suggest such a systematic study of SSF in different environments, across scales, and using a well-designed and replicated selection of approaches including novel approaches. This will be followed by a systematic evaluation of methods and possible proxies as well as model intercomparison, evaluation and improvement. Thereby, we will focus on 4 challenges: 1) Development of novel experimental methods,2) Spatial patterns of SSF, 3) Thresholds and cascading effects of SSF, 4) Impacts of SSF. Whereas standard single research projects investigate part of this puzzle at a specific location, this Research Unit provides the unique opportunity of fitting a large number of puzzle pieces together. This Research Unit will have a strong emphasis on experimental work in four contrasting catchments from the low to high mountain ranges (Sauerland, Ore Mountains, Black Forest, Alps) that then directly feeds into a collaborative modelling effort, which in turn influences experimental design in an iterative process.

Abstract:

Subsurface hillslope-stream connectivity is a major control on runoff-generation and catchment storage dynamics. However, detecting this connectivity is challenging, as processes in the subsurface are not easily observable. Furthermore, we are faced with a high spatial variability as well as pronounced temporal dynamics. In this context, we are investigating three catchments in German mid-mountain ranges: Black Forest, Ore Mountains and Sauerland. The experimental design consists of three trenched hillslopes per catchment as well as numerous observation wells and stream gauges along the stream. Water samples are taken at all locations during snapshot campaigns and are analyzed for major cations and anions to complement event-based sampling at the trenches and in the stream. This comparative design aims at moving beyond single-site insights to gaining a broader view of the process and its spatio-temporal patterns. First observations of these patterns based on physical and chemical signals of subsurface connectivity are presented.

Abstract:

Subsurface stormflow (SSF) is a key runoff generation mechanism in small catchments, yet its dynamics and thresholds remain poorly understood due to the challenges of observing and measuring subsurface processes. To address this, we conducted a study in a headwater catchment in the Black Forest, Germany, where we investigated the depth of SSF flow paths, if SSF is dominated by event water and if all SSF events have similar tracer behavior. Three trenches were installed on slopes with different landuse and topography. They were excavated down to bedrock ( 15 m wide, 2.5 m deep), collecting SSF separately from upper and lower soil layers. Continuous measurements of SSF volume and temperature were combined with water sampling for natural tracers: stable water isotopes, dissolved organic carbon, electric conductivity, and major ions. During the study period, 6 large SSF events were recorded in each trench. Using heat as a tracer we found stable SSF flowpath depths across events. Multitracer analysis suggested that SSF consisted mostly of pre-event water, with antecedent wetness governing event water contributions. Our results also show that C–Q relationships for solutes varied considerably between events and trenches, with some (e.g., Si) remaining chemostatic while others (e.g. DOC, SO24− and NO−3 ) behaved chemodynamically. This indicates that the chemical composition of SSF depends on both the antecedent hydrometeorological conditions and local factors such as landuse, reinforcing the complexity of these processes. Our results highlight the dynamic nature of subsurface stormflow and the challenges involved in its characterization.

Abstract:

Subsurface flow in preferential pathways in soils may transport water more rapidly than the soil matrix, which may be quickly activated during precipitation events and enhancing infiltration or interflow. Vertical pathways are particularly important for runoff generation. However, identifying these pathways is challenging because traditional methods such as piezometers, soil moisture sensors, or hillslope trenches do not adequately capture the spatial scale and frequency of prefer ential flow features, while other experimental techniques like dye tracing are labor-intensive and invasive. In this study, we introduce a novel method to identify the locations of preferential flow by analysing vertical soil profiles of stable water isotope. Across four catchments, we drilled 100 soil cores (1–3 m deep) per catchment and analyzed the stable isotope composition of the soil water in 10–20 cm depth intervals to construct depth profiles. We employed clustering techniques to group soil-water isotope profiles and selecting those that match to a seasonal sampling date to establish a reference profile for each catchment using LOESS regression, representing profiles influenced solely by matrix infiltration. Deviations from these reference profiles were then used as indicators of being influenced by vertical or lateral preferential flow. Our results revealed evidence of preferential flow in all studied catchments. Especially in the alpine catchment with highly heterogeneous soils many profiles showed distinct preferential flow features, including multiple, vertically independent pathways occurring at variable depths, even among adjacent profiles. These findings demonstrate the feasibility of using soil water isotope profiles to assess preferential flow pathways highlighting the substantial spatial and vertical variability of preferential flowpaths at hillslope and catchment scale.

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.