ALBERT

Description: The complex and computationally expensive nature of landscape evolution models poses significant challenges to the inference and optimization of unknown model parameters. Bayesian inference provides a methodology for estimation and uncertainty quantification of unknown model parameters. In our previous work, we developed parallel tempering Bayeslands as a framework for parameter estimation and uncertainty quantification for the Badlands landscape evolution model. Parallel tempering Bayeslands features high-performance computing that can feature dozens of processing cores running in parallel to enhance computational efficiency. Nevertheless, the procedure remains computationally challenging since thousands of samples need to be drawn and evaluated. In large-scale landscape evolution problems, a single model evaluation can take from several minutes to hours and in some instances, even days or weeks. Surrogate-assisted optimization has been used for several computationally expensive engineering problems which motivate its use in optimization and inference of complex geoscientific models. The use of surrogate models can speed up parallel tempering Bayeslands by developing computationally inexpensive models to mimic expensive ones. In this paper, we apply surrogate-assisted parallel tempering where the surrogate mimics a landscape evolution model by estimating the likelihood function from the model. We employ a neural-network-based surrogate model that learns from the history of samples generated. The entire framework is developed in a parallel computing infrastructure to take advantage of parallelism. The results show that the proposed methodology is effective in lowering the computational cost significantly while retaining the quality of model predictions.

Description: Assessing the size of a former ocean of which only remnants are found in mountain belts is challenging but crucial to understanding subduction and exhumation processes. Here we present new constraints on the opening and width of the Piemont–Liguria (PL) Ocean, known as the Alpine Tethys together with the Valais Basin. We use a regional tectonic reconstruction of the Western Mediterranean–Alpine area, implemented into a global plate motion model with lithospheric deformation, and 2D thermo-mechanical modeling of the rifting phase to test our kinematic reconstructions for geodynamic consistency. Our model fits well with independent datasets (i.e., ages of syn-rift sediments, rift-related fault activity, and mafic rocks) and shows that, between Europe and northern Adria, the PL Basin opened in four stages: (1) rifting of the proximal continental margin in the Early Jurassic (200–180 Ma), (2) hyper-extension of the distal margin in the Early to Middle Jurassic (180–165 Ma), (3) ocean–continent transition (OCT) formation with mantle exhumation and MORB-type magmatism in the Middle–Late Jurassic (165–154 Ma), and (4) breakup and mature oceanic spreading mostly in the Late Jurassic (154–145 Ma). Spreading was slow to ultra-slow (max. 22 mm yr−1, full rate) and decreased to ∼51 mm yr−1 after 145 Ma while completely ceasing at about 130 Ma due to the motion of Iberia relative to Europe during the opening of the North Atlantic. The final width of the PL mature (“true”) oceanic crust reached a maximum of 250 km along a NW–SE transect between Europe and northwestern Adria. Plate convergence along that same transect has reached 680 km since 84 Ma (420 km between 84–35 Ma, 260 km between 35–0 Ma), which greatly exceeds the width of the ocean. We suggest that at least 63 % of the subducted and accreted material was highly thinned continental lithosphere and most of the Alpine Tethys units exhumed today derived from OCT zones. Our work highlights the significant proportion of distal rifted continental margins involved in subduction and exhumation processes and provides quantitative estimates for future geodynamic modeling and a better understanding of the Alpine Orogeny.