Understanding near-surface biogeochemical dynamics is vital in the context of rapid environmental change. Spectral induced polarization (SIP), a non-invasive geophysical method, holds potential for monitoring microbial activity and abundance. A key driver of subsurface biogeochemical processes. We investigated the SIP responses of Shewanella oneidensis MR-1 in reactors packed with alginate beads as an inert porous medium. By analysing the imaginary conductivity ( response of the SIP signal, we found that SIP signals closely tracked microbial growth phases, as confirmed by measured colony forming units, CFUs, (R² = 0.80) and ATP (R² = 0.90) measurements. SIP responses peaked during exponential growth and declined in the stationary phase. Notably, the bead-packed systems provided stable signals due to reduced cell settling (often a drawback of pure suspension experiments). Our results demonstrate that SIP can effectively detect and monitor biologically driven changes in the electrical properties of porous media. By working with inert beads, we have isolated cells' responses from interactions between cells and mineral or organic colloids. This study supports the advancement of SIP as a high-resolution method for quantifying dynamic microbial activity in porous media. Ongoing research aims to upscale our findings to study the effect of microbial metabolic state on their electrical properties. Planned retentostat experiments are expected to improve our quantitative understanding of microbially generated SIP signals and contribute to their eventual deployment as an off-the-shelf monitoring tool for non-geophysicists.

The real-time monitoring of mineral dissolution processes would constitute a much-needed advancement in remediation strategies at contaminated aquifers. Recent advances in applied geophysical techniques have highlighted the potential of methods such as spectral induced polarization (SIP) for monitoring subsurface (bio)geochemical processes non-invasively. SIP's unique ability to trace geochemical changes stems from its capability to detect changes in the charge storage properties at the mineral-fluid interface in porous media. The unique link between geo-electrical and geochemical processes makes SIP a valuable tool for monitoring changes in redox-active minerals such as oxides and reduced minerals such as iron sulfides. Here, we present results from a flow-through column experiment, where we triggered the dissolution of naturally occurring reduced iron (sulfide) phases by infiltrating 0.01 M HCl into aquifer sand collected from the Fuhrberger Feld Aquifer (Hannover, Germany). We integrated our geochemical investigation with geophysical measurements collected over both space and time. We further developed a reactive transport model to simulate coupled chemical and physical processes. Our model, calibrated using observed breakthrough curves, accounted for both the dissolution of iron sulfides and the protonation of residual mineral surfaces under acidic conditions. The incorporation of mineral dissolution as well as protonation of the residual mineral surface at lower pH in our reactive transport model reveled a strong linear correlation between the dissolution front arrival time and the timing of a measured anomaly in the SIP signal. These results underscore the potential of SIP as a powerful tool for subsurface process monitoring and predictive environmental modeling.

River valley floors are low-relief, confined landscapes that temporarily store sediment moving from mountains to lowlands. This transient storage affects sediment budgets, global element cycles, and the preservation of environmental signals. However, the factors controlling valley-floor width remain poorly understood, preventing landscape evolution models from reproducing and forecasting those diverse landforms. In this study, we analyze valley-floor width and four potential controlling factors—river discharge, tectonic uplift, lithology, and lateral sediment supply from hillslopes—across ~126,000 locations in 84 catchments along the western Andes (5°–40°S). Using a random forest regression model, we identify river discharge as the dominant control on valley width, followed by lateral sediment supply, tectonic uplift, and erodibility. When organizing the data by catchment and elevation, correlation analyses reveal that discharge has greater influence at lower elevations, while uplift plays a stronger role at higher altitudes. A comparison with a theoretical model—predicting steady-state valley width based on discharge, uplift, and sediment supply—shows over 95% agreement, reinforcing the significance of these parameters. Discrepancies between model predictions and observed data mostly occur in transient stream segments, where dynamic processes are not captured by the model. Overall, our findings improve understanding of valley floor formation and sediment storage and aid in interpreting past climate and tectonic activity through valley morphology.

The Atacama Desert in northern Chile is one of the most arid regions on Earth, with an extremely hyperarid core receiving less than 2 mm of rainfall per year. In this virtually waterless world, mechanisms and rates of geomorphic processes are so far poorly understood. New detailed field data and monitoring of local conditions are hence much needed, and would ultimately provide valuable insights into geomorphic processes under extreme hyperaridity. The DFG-funded project “Key mechanisms and chronology of geomorphological processes in hyperarid landscapes” (ref. no. AG 432/1-1, MA 5768/6-1) aims to fill this knowledge gap by studying processes, drivers and time scales of hillslope sediment production and transport in hyperarid landscapes. Specifically, it aims at investigating the so-called zebra stripes, arguably the most enigmatic and widespread hillslope landform in the central Atacama Desert. Zebra stripes cover slopes between the coastal range and the pre-Andean cordilleras and are defined as contour-parallel, thin lateral bands of loose angular gravels resting on hillslopes between 4° and 30°. Backed by geomorphological and geochronological investigations from recent years, the new project will focus on repeated field geomorphological investigations at zebra stripe key sites by (i) conducting on-site monitoring of local environmental conditions and processes; and (ii) obtaining both relative and absolute chronological information on zebra stripe formation time scales utilising rock surface luminescence and terrestrial cosmogenic nuclide dating techniques. This contribution introduces the project and presents first data of monitoring and dating results.

Current soil erosion models are constrained by parameter uncertainty, limited empirical data, and an inability to capture the complex spatiotemporal dynamics of surface processes. This study introduces a novel image-based approach using 3D photogrammetric time series to detect and quantify both erosive and non-erosive soil processes.

Using Structure from Motion (SfM) and high-frequency time-lapse photogrammetry, we generate dense 3D surface models of bounded experimental plots during controlled rainfall simulations. These multi-site datasets capture surface evolution in detail, enabling analysis of processes such as soil compaction, aggregate breakdown, sheet erosion, and rill formation.

To address early-stage surface subsidence (e.g., due to compaction) that masks initial sediment yield measurement, we develop a correction method. Based on soil and plot properties, non-linear regression is used to derive s-shaped correction functions that estimate and adjust for these masking effects.

A hierarchical, time series-based change detection strategy supports automated process classification by analyzing full surface model sequences, moving beyond bitemporal comparisons. This enables the temporal segmentation of overlapping erosional phases, enhancing interpretation of subtle and high-magnitude changes.

The datasets also support the calibration of a runoff-driven soil erosion model using microtopographic inputs. Multiple spatiotemporal averaging techniques are assessed to identify robust calibration metrics. Results show no single metric captures all aspects of erosional behavior, highlighting the need for multi-metric evaluation.

By integrating time-lapse imaging, 4D analysis, and advanced model evaluation, a comprehensive pathway from pixel-level measurements to supporting process-level understanding is introduced to improve soil erosion modeling under dynamic environmental conditions.