Fast and invisible: Conquering Subsurface Stormflow
through an Interdisciplinary Multi-Site Approach
(DFG RU 5288)

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:

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:

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:

In many natural landscapes, subsurface stormflow (SSF) is a runoff-producing mechanism which can substantially contribute to the storm hydrograph of a stream. Despite its importance, there is a lack of systematic studies exploring SSF across sites with different land uses and hydrogeological characteristics. Thus, we face limitations to properly conceptualize and parametrize hydrological models. In order to gain a better understanding of the processes governing SSF, multiple SSF-capturing trenches were excavated. The selected trench sites span over different land uses, geology, soils and climates in Germany and Austria. Depending on local boundaries, the trenches were designed with a width of 11–15 m allowing to collect water flowing laterally at depths of up to 1–3 m. Using separate drainage pipes, the trench’s face is divided into an upper and lower flow-capture zone. Combining the measurements of vertically separated SSF outflow with upstream monitored groundwater levels and soil moisture dynamics, allows to estimate flow propagations along the hillslope. Besides the continuous monitoring, these installations were used to measure SSF events triggered by artificial rainfall. In this study we investigated the SSF response at 11 different trench sites under controlled conditions using a large-scale (200 m²) experimental sprinkling system in combination with deuterated water, which served as an artificial tracer. The irrigation was applied at a rate of ca. 16 mm h-1 for about 3 hours. The analysis focuses on trenchflow dynamics (e.g., timing and magnitude of the peak flow, recession curve analysis) and their relationship with changes in soil moisture and groundwater level. The experiments highlighted the vastly different responses between sites; while some trenches remained dry, others were characterized by extremely high subsurface runoff coefficients and short response times.

Abstract:

Principles of optimality provide an interesting alternative to modeling hydrological processes in detail on small scales and have received growing interest in the last years. Inspired by the more than 20 years old concept of minimum energy dissipation in river networks, we present a corresponding theory for subsurface flow in order to obtain a better understanding of preferential flow patterns in the subsurface. The concept describes flow patterns which are optimal in the sense of minimizing the total energy dissipation at a given recharge under the constraint of a given total porosity. Results are illustrated using two examples: two-dimensional flow towards a spring with a radial symmetric distribution of the porosity and dendritic flow patterns. The latter are found to be similar to river networks in their structure and, as a main result, the model predicts a power-law distribution of the spring discharges. In combination with two data sets from the Austrian Alps, this result is used for validating the model. Both data sets reveal power-law-distributed spring discharges with similar scaling exponents. These are, however, slightly larger than the exponent predicted by the model. As a further result, the distributions of the residence times strongly differ between homogeneous porous media and optimized flow patterns, while the mean residence times are similar in both cases.

Abstract:

The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al.(2017).

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