Using data-driven algorithms for semi-automated geomorphological mapping.

In this paper, we compare the performance of two data-driven algorithms to deal with an automatic classification problem in geomorphology: Direct Sampling (DS) and Random Forest (RF). The main goal is to provide a semi-automated procedure for the geomorphological mapping of alpine environments, using a manually mapped zone as training dataset and predictor variables to infer the classification of a target zone. The applicability of DS to geomorphological classification was never investigated before. Instead, RF based classification has already been applied in few studies, but only with a limited number of geomorphological classes. The outcomes of both approaches are validated by comparing the eight detected classes with a geomorphological map elaborated on the field and considered as ground truth. Both DS and RF give satisfactory results and provide similar performances in term of accuracy and Cohen's Kappa values. The map obtained with RF presents a noisier spatial distribution of classes than when using DS, because DS takes into account the spatial dependence of the different classes. Results suggest that DS and RF are both suitable techniques for the semi-automated geomorphological mapping in alpine environments at regional scale, opening the way for further improvements.

Combining global climate models using graph cuts.

Global Climate Models are the main tools for climate projections. Since many models exist, it is common to use Multi-Model Ensembles to reduce biases and assess uncertainties in climate projections. Several approaches have been proposed to combine individual models and extract a robust signal from an ensemble. Among them, the Multi-Model Mean (MMM) is the most commonly used. Based on the assumption that the models are centered around the truth, it consists in averaging the ensemble, with the possibility of using equal weights for all models or to adjust weights to favor some models. In this paper, we propose a new alternative to reconstruct multi-decadal means of climate variables from a Multi-Model Ensemble, where the local performance of the models is taken into account. This is in contrast with MMM where a model has the same weight for all locations. Our approach is based on a computer vision method called graph cuts and consists in selecting for each grid point the most appropriate model, while at the same time considering the overall spatial consistency of the resulting field. The performance of the graph cuts approach is assessed based on two experiments: one where the ERA5 reanalyses are considered as the reference, and another involving a perfect model experiment where each model is in turn considered as the reference. We show that the graph cuts approach generally results in lower biases than other model combination approaches such as MMM, while at the same time preserving a similar level of spatial continuity. Supplementary Information: The online version contains supplementary material available at 10.1007/s00382-022-06213-4.

From white to green: Snow cover loss and increased vegetation productivity in the European Alps.

Mountains are hotspots of biodiversity and ecosystem services, but they are warming about twice as fast as the global average. Climate change may reduce alpine snow cover and increase vegetation productivity, as in the Arctic. Here, we demonstrate that 77% of the European Alps above the tree line experienced greening (productivity gain) and <1% browning (productivity loss) over the past four decades. Snow cover declined significantly during this time, but in <10% of the area. These trends were only weakly correlated: Greening predominated in warmer areas, driven by climatic changes during summer, while snow cover recession peaked at colder temperatures, driven by precipitation changes. Greening could increase carbon sequestration, but this is unlikely to outweigh negative implications, including reduced albedo and water availability, thawing permafrost, and habitat loss.

Quantifying year-round nocturnal bird migration with a fluid dynamics model.

To understand the influence of biomass flows on ecosystems, we need to characterize and quantify migrations at various spatial and temporal scales. Representing the movements of migrating birds as a fluid, we applied a flow model to bird density and velocity maps retrieved from the European weather radar network, covering almost a year. We quantified how many birds take-off, fly, and land across Western Europe to (1) track bird migration waves between nights, (2) cumulate the number of birds on the ground and (3) quantify the seasonal flow into and out of the study area through several regional transects. Our results identified several migration waves that crossed the study area in 4 days only and included up to 188 million (M) birds that took-off in a single night. In spring, we estimated that 494 M birds entered the study area, 251 M left it, and 243 M birds remained within the study area. In autumn, 314 M birds entered the study area while 858 M left it. In addition to identifying fundamental quantities, our study highlights the potential of combining interdisciplinary data and methods to elucidate the dynamics of avian migration from nightly to yearly time scales and from regional to continental spatial scales.

Publisher Correction: A 3D geological model of a structurally complex Alpine region as a basis for interdisciplinary research.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A 3D geological model of a structurally complex Alpine region as a basis for interdisciplinary research.

Certain applications, such as understanding the influence of bedrock geology on hydrology in complex mountainous settings, demand 3D geological models that are detailed, high-resolution, accurate, and spatially-extensive. However, developing models with these characteristics remains challenging. Here, we present a dataset corresponding to a renowned tectonic entity in the Swiss Alps - the Nappe de Morcles - that does achieve these criteria. Locations of lithological interfaces and formation orientations were first extracted from existing sources. Then, using state-of-the-art algorithms, the interfaces were interpolated. Finally, an iterative process of evaluation and re-interpolation was undertaken. The geology was satisfactorily reproduced; modelled interfaces correspond well with the input data, and the estimated volumes seem plausible. Overall, 18 formations, including their associated secondary folds and selected faults, are represented at 10 m resolution. Numerous environmental investigations in the study area could benefit from the dataset; indeed, it is already informing integrated hydrological (snow/surface-water/groundwater) simulations. Our work demonstrates the potential that now exists to develop complex, high-quality geological models in support of contemporary Alpine research, augmenting traditional geological information in the process.

Social tipping points in global groundwater management.

Groundwater is critical to global food security, environmental flows, and millions of rural livelihoods in the face of climate change 1 . Although a third of Earth's largest groundwater basins are being depleted by irrigated agriculture 2 , little is known about the conditions that lead resource users to comply with conservation policies. Here we developed an agent-based model 3,4 of irrigated agriculture rooted in principles of cooperation 5,6 and collective action 7 and grounded on the World Values Survey Wave 6 (n = 90,350). Simulations of three major aquifer systems facing unsustainable demands reveal tipping points where social norms towards groundwater conservation shift abruptly with small changes in cultural values and monitoring and enforcement provisions. These tipping points are amplified by group size and best invoked by engaging a minority of rule followers. Overall, we present a powerful tool for evaluating the contingency of regulatory compliance upon cultural, socioeconomic, institutional and physical conditions, and its susceptibility to change beyond thresholds. Managing these thresholds may help to avoid unsustainable groundwater development, reduce enforcement costs, better account for cultural diversity in transboundary aquifer management and increase community resilience to changes in regional climate. Although we focus on groundwater, our methods and findings apply broadly to other resource management issues.

Influence of Alluvial Morphology on Upscaled Hydraulic Conductivity.

The hydraulic conductivity of aquifers is a key parameter controlling the interactions between resource exploitation activities, such as unconventional gas production and natural groundwater systems. Furthermore, this parameter is often poorly constrained by typical data used for regional groundwater modeling and calibration studies performed as part of impact assessments. In this study, a systematic investigation is performed to understand the correspondence between the lithological descriptions of channel-type formation and the bulk effective hydraulic conductivities at a larger scale (Kxeff , Kyeff , and Kzeff in the direction of channel cross section, along the channel and in the vertical directions, respectively). This will inform decisions on what additional data gathering and modeling of the geological system can be performed to allow the critical bulk properties to be more accurately predicted. The systems studied are conceptualized as stacked meandering channels formed in an alluvial plain, and are represented as two facies. Such systems are often studied using very detailed numerical models. The main factors that may influence Kxeff , Kyeff , and Kzeff are the proportion of the facies representing connected channels, the aspect ratio of the channels, and the difference in hydraulic conductivity between facies. Our results show that in most cases, Kzeff is only weakly dependent on the orientations of channelized structures, with the main effects coming from channel aspect ratio and facies proportion.

High resolution multi-facies realizations of sedimentary reservoir and aquifer analogs.

Geological structures are by nature inaccessible to direct observation. This can cause difficulties in applications where a spatially explicit representation of such structures is required, in particular when modelling fluid migration in geological formations. An increasing trend in recent years has been to use analogs to palliate this lack of knowledge, i.e., exploiting the spatial information from sites where the geology is accessible (outcrops, quarry sites) and transferring the observed properties to a study site deemed geologically similar. While this approach is appealing, it is difficult to put in place because of the lack of access to well-documented analog data. In this paper we present comprehensive analog data sets which characterize sedimentary structures from important groundwater hosting formations in Germany and Brazil. Multiple 2-D outcrop faces are described in terms of hydraulic, thermal and chemical properties and interpolated in 3-D using stochastic techniques. These unique data sets can be used by the wider community to implement analog approaches for characterizing reservoir and aquifer formations.

A composite annual-resolution stalagmite record of North Atlantic climate over the last three millennia.

Annually laminated stalagmites can be used to construct a precise chronology, and variations in laminae thickness provide an annual growth-rate record that can be used as a proxy for past climate and environmental change. Here, we present and analyse the first composite speleothem annual growth-rate record based on five stalagmites from the same cave system in northwest Scotland, where precipitation is sensitive to North Atlantic climate variability and the winter North Atlantic Oscillation (NAO). Our 3000-year record confirms persistently low growth-rates, reflective of positive NAO states, during the Medieval Climate Anomaly (MCA). Another persistently low growth period occurring at 290-550 CE coincides with the European Migration Period, and a subsequent period of sustained fast growth-rate (negative NAO) from 600-900 AD provides the climate context for the Viking Age in northern and western Europe.

Truncated plurigaussian simulations to characterize aquifer heterogeneity.

Integrating geological concepts, such as relative positions and proportions of the different lithofacies, is of highest importance in order to render realistic geological patterns. The truncated plurigaussian simulation method provides a way of using both local and conceptual geological information to infer the distributions of the facies and then those of hydraulic parameters. The method (Le Loc'h and Galli 1994) is based on the idea of truncating at least two underlying multi-Gaussian simulations in order to create maps of categorical variable. In this article, we show how this technique can be used to assess contaminant migration in highly heterogeneous media. We illustrate its application on the biggest contaminated site of Switzerland. It consists of a contaminant plume located in the lower fresh water Molasse on the western Swiss Plateau. The highly heterogeneous character of this formation calls for efficient stochastic methods in order to characterize transport processes.