SSF STREAM CONNECT
Project staff:
Prof. Dr. Markus Weiler
Dr. Ilja van Meerveld
Dr. Theresa Blume
Description:
The SSF Connect project investigates longitudinal patterns of subsurface stormflow (SSF) at the stream reach scale, aiming to identify and quantify preferential flow pathways that govern rapid water and solute transfer from hillslopes to streams. Building on Phase 1 of the DFG Research Unit 5288, which established systematic SSF monitoring across four catchments (Ore Mountains, Sauerland, Black Forest, Alps), this project advances experimental and modeling approaches to move beyond point-scale observations toward continuous, spatially resolved insights. A key innovation is the deployment of permanent fiber-optic distributed temperature sensing (DTS) systems along footslopes and stream banks, enabling high-resolution, long-term monitoring of temperature anomalies linked to SSF. These anomalies serve as proxies for lateral and vertical preferential flow, particularly in riparian zones and near man-made structures such as tile drains and road-side ditches. Complementary methods include automated salt dilution gauging, soil temperature profiling, thermal infrared imaging, and geophysical surveys (EMI, GPR) to map subsurface structures and validate flow dynamics. The project further integrates these data with the hydrological model RoGeR, enhancing its capacity to simulate preferential flow across scales. By analyzing temporal and spatial patterns of inflows during baseflow and storm events, SSF Connect addresses critical questions about the stability of flow hotspots, the representativeness of hydrograph separation, and the role of anthropogenic infrastructure in accelerating SSF. The results will provide a new paradigm for monitoring SSF at the catchment scale, offering scalable, low-cost proxies for assessing subsurface connectivity, improving flood forecasting, and informing sustainable land and water management.
Research Questions
1. Do temperature measurements in the footslopes, the riparian zone, the stream banks and the stream itself contain sufficient information to identify the occurrence of SSF, and distinct flow paths and hot spots? Can we differentiate groundwater inflows from the inflow of SSF?
2. Do hotspots from inflows to the stream remain the same during baseflow and event conditions or do new hotspots emerge during SSF events? How representative is classical hydrograph separation based on end member mixing given the losses to and mixing in the hyporheic zone?
3. What is the impact of anthropogenic structures, specifically tile drains and ditches at road cuts, in providing a shortcut of SSF to the stream? Can these structures be used to determine SSF dynamics and chemistry? As they are likely to only capture part of the SSF, can we quantify the bias if these structures are used as proxies to understand when and where SSF occurs?
4. How can we correctly represent preferential flow processes in the model RoGeR across different scales, based on the observations at the trench/hillslope scale (links to Subsurface Controls, Transform) and the insights gained from answering the three research questions above.
1. Methods/ Approach
The SSF Connect project develops an innovative, integrated approach to monitor subsurface stormflow (SSF) at the stream reach scale. At its core is the permanent installation of Distributed Temperature Sensing (DTS) systems in the subsurface (1.2 m depth) and along the streambed, enabling continuous monitoring of temperature anomalies linked to advective water movement through preferential flow paths. These data are complemented by automated salt dilution gauging, providing quantitative estimates of streamflow gains and losses along the reach. Additional methods include high-resolution soil temperature profiling (10 cm intervals) and geophysical surveys (EMI and GPR) to map subsurface structures and locate anthropogenic features such as tile drains and roadside ditches. Data from trenches, DTS, salt dilution, and geophysics are integrated with the hydrological model RoGeR, which is enhanced to simulate preferential flow across scales. A key focus is the implementation of a gravity-driven film flow approach, offering a parsimonious and efficient parameterization of lateral preferential flow. The project aims to identify SSF hotspots, assess their stability during baseflow and storm events, and quantify the influence of artificial infrastructure on flow dynamics. By combining continuous, spatially resolved observations with advanced modeling, SSF Connect provides a scalable, cost-effective framework for understanding the spatiotemporal patterns of SSF, representing a major advancement in catchment hydrology and offering new tools for water resource management and climate adaptation.