The significance of the work goes beyond regional curiosity. Alluviated valleys are among the most heavily used and most vulnerable landscapes on Earth. Their flat, fertile floodplains host towns, roads, and farmland, and their sand and gravel bodies often serve as important groundwater aquifers. Yet while the neighboring Upper Rhine Graben—one of Europe’s most important sedimentary basins and transboundary water resources—has been drilled, mapped, and modeled for decades, the tributary valleys draining the Black Forest into the Rhine remained largely unquantified. Older regional studies existed, but most were spatially limited, relying on a handful of drillings, and many never reached bedrock at the deepest points of the valleys. A coherent, catchment-wide picture of the subsurface was simply missing.

To close that gap, the team assembled an extraordinary legacy dataset: 7,070 data points compiled by the Baden-Württemberg State Office for Geology, Resources and Mining, including boreholes, prospecting pits, and sampling locations, with the oldest documents dating back to the 1930s. The records were collected for everything from road construction and well drilling to contaminated-site monitoring and wind park investigations. After careful quality screening, only about a third of the points proved usable, and just 978 boreholes—roughly 14 percent of the original dataset—actually reached bedrock within the mapped valley floors. That attrition rate illustrates a common challenge in geomorphology: the subsurface is known only where someone has happened to drill, and drilling clusters where people build.

The researchers attacked the quantification problem with two complementary methods. The first approach compiled 41 composite valley cross sections, each stitched together from one to twelve boreholes that penetrated to bedrock. By projecting the borehole positions onto hypothetical transects across each valley and interpolating between measured sediment depths, the team approximated the buried bedrock topography and computed cross-sectional areas of the sediment fill. Multiplying these average depths by the mapped valley floor area of each catchment yielded benchmark volume estimates. The second approach treated sediment depth as a predictable function of landscape characteristics. Using four predictor variables—distance to the valley floor boundary, flow accumulation spread across the valley floor, flow accumulation quantiles, and elevation quantiles—the authors fitted both linear regression and random forest models, an ensemble machine learning technique, to the borehole data and applied the best models to every grid cell of the valley bottoms.

Valley floors themselves had to be mapped first. The team used the multi-resolution valley bottom flatness algorithm, which identifies low, flat areas at multiple spatial scales, tuning its parameters catchment by catchment against the geological map. The result was 175 square kilometers of valley floor, just 8.3 percent of the 2,094-square-kilometer study area, which spans nine catchments ranging from 13 to 1,034 square kilometers, from the Rench in the north to the Neumagen in the south. The large Kinzig catchment contains nearly half of all valley floor area, followed by the Dreisam and the Elz. The Dreisam stands out in another way: with its broad, tectonically shaped Zarten basin, it devotes 12.5 percent of its catchment area to valley fill, the highest proportion in the study.

The cross sections revealed a striking heterogeneity in the buried landscape. Valley floors range from 16 meters to 3 kilometers wide, and average sediment depths from 2 to 36.3 meters. Narrow headwater valleys tend to show classic V-shaped fills, sometimes surprisingly deep relative to their width. But the main valleys tell a different story: nearly half of the well-constrained profiles show a remarkably flat bedrock erosion surface capped by a shallow sediment cover, typically less than 15 meters thick—even in valleys nearly a kilometer wide. Only toward the Upper Rhine Graben do some valley sections widen into box- or trough-shaped forms containing sediments up to 100 meters thick. Several profiles also display abrupt vertical jumps in bedrock depth, some coinciding with mapped or suspected fault lines, hints of either tectonic displacement or strongly asymmetric incision.

The two methods produced broadly consistent but not identical totals. The cross-section benchmarks yielded a median study-area volume of 1.2 cubic kilometers, with the Kinzig holding about 45 percent, the Dreisam 24 percent, and the Elz 17 percent. Regression modeling pushed the median total higher, to 2.8 cubic kilometers, with the Kinzig at roughly 42 percent and the Dreisam rising to 31 percent. The random forest models generally outperformed the linear ones, explaining up to 80 percent of the variance in sediment depth, and their spatial predictions better reproduced the shallow, trough-like geometry of the main valleys, whereas linear models tended to exaggerate V-shaped forms. The authors caution that linear interpolation between boreholes likely underestimates fill volumes where the deepest parts of a valley fall between drill sites, and that data quality, clustering, and the semi-automated valley floor mapping all introduce uncertainty.

The most provocative finding concerns two catchments whose sediment volumes are disproportionately large relative to their valley floor area: the Dreisam and the Schutter. Both carry a distinctive structural imprint. The Dreisam lies within the Freiburg–Bonndorf–Bodensee fault zone, a large crustal-scale deformation zone inherited from the late Paleozoic Variscan orogeny, and its Zarten basin holds more than 50 meters of fluvial sediment. The Schutter, meanwhile, is crossed by the Cenozoic main border fault that separates the uplifted Black Forest block from the subsiding Upper Rhine Graben. The authors suggest these crustal discontinuities may be linked to enhanced fluvial incision, focusing erosion along fractured rock and deepening the valleys—and their sediment repositories—far beyond what catchment size alone would predict.

That tectonic signature extends across the region. The Black Forest and the Vosges have been uplifted as rift shoulders of the Upper Rhine Graben since the early Miocene, and many Black Forest valleys, including the Elz and Glotter trunk valleys, follow NE- to NNE-oriented faults traceable to the Variscan orogeny. In the Elz valley, where a normal fault is well documented and current seismic activity has been recorded, the cross sections show an asymmetric bedrock surface sloping toward the northwest, along with a localized depression that may represent an abandoned channel on the footwall side of the fault—potentially even unpaired bedrock terraces formed by tectonic deflection of the river. Comparable evidence is absent along the Kinzig, where no major valley fault exists, reinforcing the interpretation that these subsurface anomalies are structural rather than purely fluvial in origin.

Compared with alpine settings, the Black Forest’s sediment storage is modest. Valley fills here cover a smaller share of catchment area than in the Himalayas, where glacially overdeepened valleys hold vast sediment volumes, and the volume–area scaling derived from Himalayan data would overestimate most Black Forest storage. Instead, the region’s wide, shallow valleys—broadened by lateral erosion and sediment accumulation rather than renewed bedrock incision—resemble the European Alps in their areal footprint but hold comparatively thin fills. For water managers, the new maps offer practical value: the sediment bodies are porous aquifers, and spatially resolved depth estimates feed directly into groundwater models, such as ongoing stress tests of the Dreisam valley. For geologists, the buried valley geometry doubles as a low-cost probe of active tectonics in a region where seismic hazard assessment depends on knowing where faults move. What looks like a sleepy forest valley, it turns out, is a ledger of millions of years of rifting, uplift, and river work—now, at last, counted.

Subject of Research: Quantification of alluvial valley fill sediments and the tectonic control on valley morphology in the southwestern Black Forest, Germany

Article Title: Sediment storage quantification in the Black Forest highlights tectonic influence on typically wide and shallow valleys

Article References: Sediment storage quantification in the Black Forest highlights tectonic influence on typically wide and shallow valleys. (n.d.). https://doi.org/10.5194/egqsj-74-301-2025

Image Credits: AI Generated

DOI: 10.5194/egqsj-74-301-2025

Keywords: Black Forest, valley fill, sediment storage, tectonics, Upper Rhine Graben, borehole data, random forest regression, geomorphology, Quaternary, groundwater, fault zones, fluvial incision

The research, led by Manoharan Sambath and Sembulichampalayam Sennimalai Chandrasekaran of Vellore Institute of Technology together with Sandeep Maithani of the Indian Institute of Remote Sensing, forms part of a broader effort to assess urban seismic risk in India, a country where rapid construction often outpaces detailed geotechnical knowledge. Funded by the Indian Space Research Organisation through its RESPOND program, the study combined borehole records, geophysical surveys and computational modeling to produce some of the most granular ground-motion estimates yet available for the city.

At the heart of the work lies a technique called Site-Specific Seismic Ground Response Analysis, or SSGRA. The method takes an earthquake signal defined at bedrock depth and propagates it upward through the local soil column, accounting for how each layer stiffens, softens and dissipates energy as it is deformed. Because soil is not a simple elastic medium, the team ran two parallel formulations: an equivalent linear approach, which uses averaged stiffness and damping values, and a more computationally demanding nonlinear analysis that tracks the true stress-strain behavior of the sediments under strong cyclic loading.

The input side of the calculation was equally rigorous. The researchers drew on a probabilistic seismic hazard analysis of the Coimbatore region, which they had previously developed using a logic-tree framework, to define five distinct hazard zones based on bedrock peak ground acceleration. For each zone, they constructed a Uniform Hazard Response Spectrum and then spectrally matched eleven suitable recorded ground motions to it, ensuring that the input signals carried the right energy content across the frequency range that matters for buildings. These matched motions were then applied for two hazard levels, corresponding to return periods of 475 and 2475 years, roughly the shaking expected once in 475 and once in 2475 years respectively.

Characterizing the soils themselves required fieldwork across the city. The team used 40 geospatially distributed bore logs, which record the layering and index properties of the subsurface, together with active Multichannel Analysis of Surface Waves tests. MASW surveys measure how seismic surface waves disperse through the ground, allowing engineers to compute the average shear-wave velocity in the top 30 meters, a parameter known as Vs30 that has become the international standard for classifying site conditions. Soils with low Vs30 values, typically soft clays and loose sands, amplify ground motion far more than dense gravels or rock.

The results paint a strikingly uneven picture of Coimbatore’s seismic vulnerability. The neighborhoods of Rathinapuri, Avinashi, Gandhipuram and NGGO Colony showed a broad variation in surface peak ground acceleration, meaning that even within these areas, the intensity of shaking could differ substantially from one site to the next depending on local soil conditions. Such block-by-block variability has direct consequences for building codes, which often assume a single design value across an entire city.

Perhaps the most consequential finding concerns spectral acceleration, the quantity that most directly governs structural design. The central part of the city exhibits the highest surface spectral accelerations at spectral periods of 0.5 and 1.0 seconds, ranges that coincide with the natural vibration periods of many mid-rise reinforced concrete buildings. In an earthquake, structures resonate with ground motion at their own natural periods, so elevated spectral acceleration in this band implies that a significant share of Coimbatore’s building stock could experience forces well above what a uniform hazard map would suggest.

The study also found a clear geographic pattern in amplification, the ratio of surface motion to bedrock motion. The western region of the city experienced higher amplification factors for the 475-year return period event, indicating that its subsurface conditions selectively boost moderate-intensity shaking. Interestingly, the relationship between amplification and shaking intensity is not constant: as input motions grow stronger, soils soften and damp more, which is precisely why the team ran both linear-equivalent and nonlinear analyses across the two return periods rather than relying on a single scenario.

The comparison with codified design spectra carries a cautionary message for practitioners. The site-specific Acceleration Design Response Spectrum proposed in the study was found to be overestimated, particularly for the second group of bedrock PGA-based hazard zones, when set against the nonlinear surface response spectra computed by the analysis. In other words, for those hazard zones, the design spectrum is conservative, demanding more seismic resistance than the physics of the soil column requires. While conservatism is not inherently dangerous, it imposes unnecessary construction costs; the flip side is that in zones where the spectrum is not conservative, the margin of safety may be thinner than assumed.

For Coimbatore, a city whose economy is anchored by textile manufacturing, engineering industries and a dense fabric of both formal and informal construction, the maps produced by this study offer a practical template for risk-sensitive planning. The work also demonstrates a methodology that other Indian cities can replicate: combine probabilistic hazard analysis with dense geotechnical sampling, geophysical profiling and dual-formulation site response modeling to move from city-wide averages to neighborhood-level truth. As India’s seismic monitoring network expands and urban populations grow, studies of this kind convert abstract hazard curves into concrete guidance about where the ground will shake hardest, and where engineers should look most carefully before the next earthquake tests their assumptions.

Subject of Research: Site-specific seismic ground response analysis and geospatial mapping of surface ground motion parameters for Coimbatore city, India

Article Title: Geospatial variation of surface ground motion parameters using the 1-D Site-Specific Seismic Ground Response Analysis (SSGRA) for Coimbatore city, Tamil Nadu, India

Article References: Geospatial variation of surface ground motion parameters using the 1-D Site-Specific Seismic Ground Response Analysis (SSGRA) for Coimbatore city, Tamil Nadu, India. (n.d.). https://doi.org/10.1007/s10518-026-02705-4

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02705-4

Keywords: seismic hazard, ground response analysis, Coimbatore, shear-wave velocity, MASW, peak ground acceleration, spectral acceleration, site amplification, soil dynamics, earthquake engineering, India, borehole data