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Landscape Evolution Models (LEMs) are prime tools to simulate the evolution of source-to-sink systems through ranges of spatial and temporal scales. Plethora of different empirical laws have been successfully applied to describe the different parts of these systems: fluvial erosion, sediment transport and deposition, hillslope diffusion, or hydrology. Numerical frameworks exist to facilitate the combination of different subsets of laws, mostly by superposing grids of fluxes calculated independently. However the exercise becomes increasingly challenging when the different laws are inter-connected: for example when a lake breaks the upstream-downstream continuum of the amount of sediment and water it receives and transmits; or when erosional efficiency depends of the composition of a sediment flux affected by multiple processes. In this contribution, we present a method mixing the advantages of cellular-automata and graph theory to address such cases. We demonstrate how the former guarantees finite knowledge of all fluxes independently from the process-law implemented in the model while the latter offer a wide range of tools to process numerical landscapes, including landscapes with closed basins. We provide three scenario largely benefiting from our method: i) one where lake systems are primary controls on Landscape evolution, ii) one where sediment provenance is closely monitored through the stratigraphy and iii) one where heterogeneous provenance influences fluvial incision dynamically. We finally outline the way forward to make this method more generic and flexible.

Creative processes of artists often start with hand-drawn sketches illustrating an object. Pre-visualizing these keyframes is especially challenging when applied to volumetric materials such as smoke. The authored 3D density volumes must capture realistic flow details and turbulent structures, which is highly non-trivial and remains a manual and time-consuming process. We therefore present a method to compute a 3D smoke density field directly from 2D artist sketches, bridging the gap between early-stage prototyping of smoke keyframes and pre-visualization. From the sketch inputs, we compute an initial volume estimate and optimize the density iteratively with an updater CNN. Our differentiable sketcher is embedded into the end-to-end training, which results in robust reconstructions. Our training data set and sketch augmentation strategy are designed such that it enables general applicability. We evaluate the method on synthetic inputs and sketches from artists depicting both realistic smoke volumes and highly non-physical smoke shapes. The high computational performance and robustness of our method at test time allows interactive authoring sessions of volumetric density fields for rapid prototyping of ideas by novice users. ISSN:1467-8659 ISSN:0167-7055

Although an important component of natural scenes, the representation of skyscapes is often relatively simplistic. This can be largely attributed to the complexity of the thermodynamics underpinning cloud evolution and wind dynamics, which make interactive simulation challenging. We address this problem by introducing a novel layered model that encompasses both terrain and atmosphere, and supports efficient meteorological simulations. The vertical and horizontal layer resolutions can be tuned independently, while maintaining crucial inter-layer thermodynamics, such as convective circulation and land-air transfers of heat and moisture. In addition, we introduce a cloud-form taxonomy for clustering, classifying and upsampling simulation cells to enable visually plausible, finely-sampled volumetric rendering. As our results demonstrate, this pipeline allows interactive simulation followed by up-sampled rendering of extensive skyscapes with dynamic clouds driven by consistent wind patterns. We validate our method by reproducing characteristic phenomena such as diurnal shore breezes, convective cells that contribute to cumulus cloud formation, and orographic effects from moist air driven upslope.

We give an overview of the Instructed Glacier Model (IGM) -- a new framework to model the evolution of glaciers at any scale by coupling ice dynamics, surface mass balance, and mass conservation. The key novelty of IGM is that it models the ice flow by a Convolutional Neural Network (CNN), which is trained from physical high-order ice flow mechanical models. Doing so has major advantages in both forward and inverse modelling.In forward modelling, the most computationally demanding model component (the ice flow) is substituted by a very cheap CNN emulator. Once trained with representative data, IGM permits to model individual mountain glaciers several orders of magnitude faster than high-order ones on CPU with fidelity levels above 90 % in terms of ice flow solutions leading to nearly identical transient thickness evolution. Switching to Graphics Processing Unit (GPU) permits additional significant speed-ups, especially when modelling large-scale glacier networks and/or high spatial resolutions.In inverse modelling, the substitution by a CNN emulator does not only speed up but facilitates dramatically the data assimilation step, i.e. the search for optimal ice thickness and ice flow parameter spatial distributions that match spatial observations at best (such as ice flow, surface topography or ice thickness profiles) while being consistent with the high-order ice flow mechanics. The reason is that inverting a CNN can take great benefit from the tools used for its training such as automatic differentiation, stochastic gradient methods, and GPU. IGM is an open-source Python code (https://github.com/jouvetg/igm), which deals with two-dimensional gridded input and output data. Together with a companion library of trained ice flow emulators, IGM permits user-friendly, computationally highly-efficient, easy-to-customize, and mechanically state-of-the-art glacier forward and inverse modelling at any scale. We illustrate its potential by replicating a simulation of the great Aletsch Glacier, Switzerland, from 1880 to 2100, based on a Stokes model. The complete workflow (data assimilation and 220 years long forward modelling) at 100 m of resolution takes about 1-2 min on the GPU of a laptop and can be replicated and adapted easily using an online Colab notebook.

Source to sink systems involve processes happening at very large timescales and the current state of the earth only represents a brief snapshot of it through space and time. These processes encompass any of those involved in the removal, transport and deposition of material from sources to sinks. The relatively stable incising valleys of the upland source landscapes allow for very efficient mathematical expressions to model their evolution over geological timescales. The transport part of the system is more challenging to study and resists radical simplification. Softer and lower-relief compared to their upstream counterparts, they are much more dynamics and undergo convoluted cycles of erosion/deposition/remobilisation only leaving sparse clues. The presence (or absence) of materials from identified provenance in the transport zone is commonly used to interpret landscapes connectivity through time. However, recent studies suggest that the dynamic nature of the transport section can make apparent provenance data ambiguous and misleading.In this contribution, we leverage the ability of a newly developed cellular automata landscape evolution modelling framework, CHONK, to investigate the transport zone. CHONK is a landscape evolution modelling framework combining advantages of cellular-automata methods with common eulerian ones. Equations are implemented in a cell referential and cells are processed in a lake-aware multiple flow topological order. Because everything happens within a cell before communicating with downstream landscape, this framework allows fine tracking of sediment provenance through space and time, unconditionally to which law is implemented, or how complex the landscape structure.We set up a basic mountain range with its foreland, exhume a discrete pluton of different rock type and track the pathways of the sediments through time, including in a stratigraphy allowing remobilisation. We show how, even in this simplistic setting, complex and stochastic patterns of sediment pathways arise. We explore at which degree these patterns are predictable and at extents they are stochastic – in other word we track the variability of the proportion of sediment coming from the pluton at given locations through time. Finally, adding more complexity to the settings with variable tectonic and climatic cycles, intermediate sink (lakes) and heterogeneous lithologies, we offer a perspective on the framework’s potential to study the role of sediment flux in shaping the landscape and its record in novel ways.

Fluid control often uses optimization of control forces that are added to a simulation at each time step, such that the final animation matches a single or multiple target density keyframes provided by an artist. The optimization problem is strongly under-constrained with a high-dimensional parameter space, and finding optimal solutions is challenging, especially for higher resolution simulations. In this paper, we propose two novel ideas that jointly tackle the lack of constraints and high dimensionality of the parameter space. We first consider the fact that optimized forces are allowed to have divergent modes during the optimization process. These divergent modes are not entirely projected out by the pressure solver step, manifesting as unphysical smoke sources that are explored by the optimizer to match a desired target. Thus, we reduce the space of the possible forces to the family of strictly divergence-free velocity fields, by optimizing directly for a vector potential. We synergistically combine this with a smoothness regularization based on a spectral decomposition of control force fields. Our method enforces lower frequencies of the force fields to be optimized first by filtering force frequencies in the Fourier domain. The mask-growing strategy is inspired by Kolmogorov's theory about scales of turbulence. We demonstrate improved results for 2D and 3D fluid control especially in higher-resolution settings, while eliminating the need for manual parameter tuning. We showcase various applications of our method, where the user effectively creates or edits smoke simulations. ISSN:1467-8659 ISSN:0167-7055

The name “FastScape” has been used to describe a landscape evolution model as well as a set of efficient algorithms to simulate various processes of erosion, transport and deposition (e.g., fluvial, hillslope and marine). We also use this name for a set of software components (https://github.com/fastscape-lem) aimed at making those models and algorithms readily accessible to a wide range of users, from experts in landscape evolution modelling to scientists, researchers and teachers in the broader Earth science community. Those software components are organised as a stack where each level has a distinct scope. At the bottom of this stack, “fastscapelib-fortran” is the original, full-featured implementation of the FastScape model, which provides a Fortran API as well as Python bindings. Its successor “fastscapelib” is a library written in modem C++ that directly exposes the FastScape algorithms (e.g., flow-routing, depression-resolving, channel erosion, hillslope diffusion) through basic APIs in C++, Python and potentially other languages such as R or Julia in the future. Built on top of those core libraries, “fastscape” is a high-level yet flexible tool that helps anyone who wants to quickly build, extend or simply run FastScape model variants in a user-friendly, interactive environment. Through its xarray-centric interface, it is deeply integrated with the rest of the Python scientific ecosystem, therefore offering great capabilities at user’s fingertips for pre/post-processing, visualisation and simulation management. One of our primary concern is following good practices (API design, testing, documentation, distribution...) while developing each of these tools. We show through a gallery of examples how the FastScape software stack has been used in research and outreach projects. We plan to provide better integration with other tools for topographic analysis/modelling (e.g., Landlab, LSDTopotools) in the future and we also greatly encourage contributions from the broader community.

International audience; We present a new algorithm for solving the common problem of flow trapped in closed depressions within digital elevation models, as encountered in many applications relying on flow routing. Unlike other approaches (e.g., the so-called "Priority-Flood" depression filling algorithm), this solution is based on the explicit computation of the flow paths both within and across the depressions through the construction of a graph connecting together all adjacent drainage basins. Although this represents 5 many operations, a linear time-complexity can be reached for the whole computation, making it very efficient. Compared to the most optimized solutions proposed so far, we show that this algorithm of flow path enforcement yields the best performance when used in landscape evolution models. Besides its efficiency, our proposed method has also the advantage of letting the user choose among different strategies of flow path enforcement within the depressions (i.e., filling vs. carving). Furthermore, the computed graph of basins is a generic structure that has the potential to be reused for solving other problems as well , such as the simulation of erosion. This sequential algorithm may be helpful for those who need to, e.g., process digital elevation models of moderate size on single computers or run batches of simulations as part of an inference study.

The purpose of the European Stroke Organisation-Karolinska Stroke Update Conference is to provide updates on recent stroke therapy research and to give an opportunity for the participants to discuss how these results may be implemented into clinical routine. The meeting started 22 years ago as Karolinska Stroke Update, but since 2014 it is a joint conference with European Stroke Organisation. Importantly, it provides a platform for discussion on the European Stroke Organisation guidelines process and on recommendations to the European Stroke Organisation guidelines committee on specific topics. By this, it adds a direct influence from stroke professionals otherwise not involved in committees and work groups on the guideline procedure. The discussions at the conference may also inspire new guidelines when motivated. The topics raised at the meeting are selected by the scientific programme committee mainly based on recent important scientific publications. This year's European Stroke Organisation-Karolinska Stroke Update Meeting was held in Stockholm on 11-13 November 2018. There were 11 scientific sessions discussed in the meeting including two short sessions. Each session except the short sessions produced a consensus statement (Full version with background, issues, conclusions and references are published as web-material and at and ) and recommendations which were prepared by a writing committee consisting of session chair(s), scientific secretary and speakers. These statements were presented to the 250 participants of the meeting. In the open meeting, general participants commented on the consensus statement and recommendations and the final document were adjusted based on the discussion from the general participants Recommendations (grade of evidence) were graded according to the 1998 Karolinska Stroke Update meeting with regard to the strength of evidence. Grade A Evidence: Strong support from randomised controlled trials and statistical reviews (at least one randomised controlled trial plus one statistical review). Grade B Evidence: Support from randomised controlled trials and statistical reviews (one randomised controlled trial or one statistical review). Grade C Evidence: No reasonable support from randomised controlled trials, recommendations based on small randomised and/or non-randomised controlled trials evidence.

International audience; Terrains are a crucial component of three-dimensional scenes and are present in many Computer Graphics applications. Terrain modeling methods focus on capturing landforms in all their intricate detail, including eroded valleys arising from the interplay of varied phenomena, dendritic mountain ranges, and complex river networks. Set against this visual complexity is the need for user control over terrain features, without which designers are unable to adequately express their artistic intent. This article provides an overview of current terrain modeling and authoring techniques, organized according to three categories: procedural modeling, physically-based simulation of erosion and land formation processes, and example-based methods driven by scanned terrain data. We compare and contrast these techniques according to several criteria, specifically: the variety of achievable landforms; realism from both a perceptual and geomorphological perspective; issues of scale in terms of terrain extent and sampling precision; the different interaction metaphors and attendant forms of user-control, and computation and memory performance. We conclude with an in-depth discussion of possible research directions and outstanding technical and scientific challenges.

A new efficient method to solve the stream power law Key Points: We present an efficient (O(N) and implicit) method to solve a river erosion model taking into account sediment deposition. We show how the foreland stratigraphy is controlled by the efficiency of river erosion and the efficiency of sediment transport by rivers. We observe autogenic aggradation and incision cycles in the foreland once the system reaches a dynamic steady state. The stream power law model has been widely used to represent erosion by rivers, but does not take into account the role played by sediment in modulating erosion and deposition rates. Davy and Lague (2009) provide an approach to address this issue, but it is computationally demanding because the local balance between erosion and deposition depends on sediment flux resulting from net upstream erosion. Here, we propose an efficient (i.e., O(N) and implicit) method to solve their equation. This means that, unlike other methods used to study the complete dynamics of fluvial systems (including the transition from detachment-limited to transport-limited behavior, for example), our method is unconditionally stable even when large time steps are used. We demonstrate its applicability by performing a range of simulations based on a simple setup composed of an uplifting region adjacent to a stable foreland basin. As uplift and erosion progress, the mean elevations of the uplifting relief and the foreland increase, together with the average slope in the foreland. Sediments aggrade in the foreland and prograde to reach the base level where sediments are allowed to leave the system. We show how the topography of the uplifting relief and the stratigraphy of the foreland basin are controlled by the efficiency of river erosion and the efficiency of sediment transport by rivers. We observe the formation of a steady-state geometry in the uplifting region, and a dynamic steady state (i.e., autocyclic aggradation and incision) in the foreland, with aggradation and incision thicknesses up to tens of meters.

International audience; Most mountain ranges are formed by the compression and folding of colliding tectonic plates. Subduction of one plate causes large-scale asymmetry while their layered composition (or stratigraphy) explains the multi-scale folded strata observed on real terrains. We introduce a novel interactive modeling technique to generate visually plausible, large scale terrains that capture these phenomena. Our method draws on both geological knowledge for consistency and on sculpting systems for user interaction. The user is provided hands-on control on the shape and motion of tectonic plates, represented using a new geologically-inspired model for the Earth crust. The model captures their volume preserving and complex folding behaviors under collision, causing mountains to grow. It generates a volumetric uplift map representing the growth rate of subsurface layers. Erosion and uplift movement are jointly simulated to generate the terrain. The stratigraphy allows us to render folded strata on eroded cliffs. We validated the usability of our sculpting interface through a user study, and compare the visual consistency of the earth crust model with geological simulation results and real terrains.

International audience; We introduce a novel method for interactive generation of visually consistent, snow-covered landscapes and provide control of their dynamic evolution over time. Our main contribution is the real-time phenomenological simulation of avalanches and other user-guided events, such as tracks left by Nordic skiing, which can be applied to interactively sculpt the landscape. The terrain is modeled as a height field with additional layers for stable, compacted, unstable, and powdery snow, which behave in combination as a semi-viscous fluid. We incorporate the impact of several phenomena, including sunlight, temperature, prevailing wind direction, and skiing activities. The snow evolution includes snow-melt and snowdrift, which affect stability of the snow mass and the probability of avalanches. A user can shape landscapes and their evolution either with a variety of interactive brushes, or by prescribing events along a winter season time-line. Our optimized GPU-implementation allows interactive updates of snow type and depth across a large (10 × 10 km) terrain, including real-time avalanches, making this suitable for visual assets in computer games. We evaluate our method through perceptual comparison against exiting methods and real snow-depth data.

This paper was presented at the Eurographics 2017 conference; International audience; One challenge in portraying large-scale natural scenes in virtual environments is specifying the attributes of plants, such as species, size and placement, in a way that respects the features of natural ecosystems, while remaining computationally tractable and allowing user design. To address this, we combine ecosystem simulation with a distribution analysis of the resulting plant attributes to create biome-specific databases, indexed by terrain conditions, such as temperature, rainfall, sunlight and slope. For a specific terrain, interpolated entries are drawn from this database and used to interactively synthesize a full ecosystem, while retaining the fidelity of the original simulations. A painting interface supplies users with semantic brushes for locally adjusting ecosystem age, plant density and variability, as well as optionally picking from a palette of precomputed distributions. Since these brushes are keyed to the underlying terrain properties a balance between user control and real-world consistency is maintained. Our system can be be used to interactively design ecosystems up to 5 × 5 km 2 in extent, or to automatically generate even larger ecosystems in a fraction of the time of a full simulation, while demonstrating known properties from plant ecology such as succession, self-thinning, and underbrush, across a variety of biomes.

International audience; At large scale, landscapes result from the combination of two major processes: tectonics which generate the main relief through crust uplift, and weather which accounts for erosion. This paper presents the first method in computer graphics that combines uplift and hydraulic erosion to generate visually plausible terrains. Given a user-painted uplift map, we generate a stream graph over the entire domain embedding elevation information and stream flow. Our approach relies on the stream power equation introduced in geology for hydraulic erosion. By combining crust uplift and stream power erosion we generate large realistic terrains at a low computational cost. Finally, we convert this graph into a digital elevation model by blending landform feature kernels whose parameters are derived from the information in the graph. Our method gives high-level control over the large scale dendritic structures of the resulting river networks, watersheds, and mountains ridges.