Earth and environmental sciences rely on detailed information about subsurface processes. Whereas geophysical techniques typically provide highly resolved spatial images, monitoring subsurface processes is often associated with enormous effort and, therefore, is usually limited to point information in time or space. Thus, the development of spatial and temporal continuous field monitoring methods is a major challenge for the understanding of subsurface processes. We have developed a novel method for ground-penetrating-radar (GPR) reflection monitoring of subsurface flow processes under unsaturated conditions and applied it to a hydrological infiltration experiment performed across a periglacial slope deposit in northwest Luxembourg. Our approach relies on a spatial and temporal quasicontinuous data recording and processing, followed by an attribute analysis based on analyzing differences between individual time steps. The results demonstrate the ability of time-lapse GPR monitoring to visualize the spatial and temporal dynamics of preferential flow processes with a spatial resolution in the order of a few decimeters and temporal resolution in the order of a few minutes. We observe excellent agreement with water table information originating from different boreholes. This demonstrates the potential of surface-based GPR reflection monitoring to observe the spatiotemporal dynamics of water movements in the subsurface. It provides valuable, and so far not accessible, information for example in the field of hydrology and pedology that allows studying the actual subsurface processes rather than deducing them from point information.

Abstract. Hillslope-stream connectivity controls runoff generation, both during events and baseflow conditions. However, assessing subsurface connectivity is a challenging task, as it occurs in the hidden subsurface domain where water flow cannot be easily observed. We therefore investigated if the results of a joint analysis of rainfall event responses of near-stream groundwater levels and stream water levels could serve as a viable proxy for hillslope-stream connectivity. The analysis focuses on the extent of response, correlations, lag times and synchronicity. A newly developed data analysis scheme of separating the aspects of (a) response timing and (b) extent of water level change provides new perspectives on the relationship between groundwater and stream responses. In a second step we investigated if this analysis can give an indication of hillslope-stream connectivity at the catchment scale. Stream- and groundwater levels were measured at five different hillslopes over 5 to 6 years. Using a new detection algorithm we extracted 706 rainfall response events for subsequent analysis. Carrying out this analysis in two different geological regions (schist and marls) allowed us to test the usefulness of the proxy under different hydrological settings while also providing insight into the geologically-driven differences in response behaviour. For rainfall events with low initial groundwater level, groundwater level responses often lag behind the stream with respect to the start of rise and the time of peak. This lag disappears at high antecedent groundwater levels. At low groundwater levels the relationship between groundwater and stream water level responses to rainfall are highly variable, while at high groundwater levels, above a certain threshold, this relationship tends to become more uniform. The same threshold was able to predict increased likelihood for high runoff coefficients, indicating a strong increase in connectivity once the groundwater level threshold was surpassed. The joint analysis of shallow near-stream groundwater and stream water levels provided information on the presence or absence and to a certain extent also on the degree of subsurface hillslope-stream connectivity. The underlying threshold processes were interpreted as transmissivity feedback in the marls and fill-and-spill in the schist. The value of these measurements is high, however, time series of several years and a large number of events are necessary to produce representative results. We also find that locally measured thresholds in groundwater levels can provide insight into catchment-scale connectivity and event response. If the location of the well is chosen wisely, a single time series of shallow groundwater can indicate if the catchment is in a state of high or low connectivity.

In the course of the Helmholtz MOSES initiative two monitoring systems are being developed which consist of the same key components and thus functionality but with very different scopes of application. One is a stationary data logger with a classic measurement routine (on/off duty cycle) and support for various hardware interfaces (2xSDI12, 1xRS485, 2xUART, amongst others). The other is a drifting data logger that stays idle until a flood event activates the logger and carries it downstream. On-board are turbidity, EC and temperature sensors, a GPS and an inertial measurement unit (IMU) monitoring turbulence. Advancements in electronics driven by automotive, mobile and IoT applications led to the development of very powerful, small and low power microcontrollers. This is why we decided to leave the realms of ATMega 8-bit systems (such as Arduino) and move towards ARM Cortex 32-bit systems. More precisely we used the Teensy 3.5 microcontroller development system as the core for the two systems. It is superior to Arduino in terms of performance while its developing team tries to maintain compatibility to Arduino in terms of programming vocabulary. This allows easier migration but comes also with restrictions regarding the capabilities of the hardware. The other key component is the FiPy which supports five different wireless network types (WiFi, Bluetooth, LoRa, Sigfox, LTE-M) in one module. In comparison to most other hardware it runs MicroPython which adds more complexity to the project. Even though it is a microcontroller and features also several hardware interfaces, power consumption is far from low power, which is why it is used here only for remote communication and data transmission. In addition, several design decisions were made regarding power path routing and jumper configuration to improve the systems’ overall versatility, debugging capabilities and low power functionality, which are often key to the feasibility of a remote monitoring system.