This dataset presents the raw data of an experimental series of analogue models performed to investigate the influence of inherited brittle fabrics on narrow continental rifting. This model series was performed to test the influence of brittle pre-existing fabrics on the rifting deformation by cutting the brittle layer at different orientations with respect to the extension direction. An overview of the experimental series is shown in Table 1. In this dataset we provide four different types of data, that can serve as supporting material and for further analysis: 1) The top-view photos, taken at different steps and showing the deformation process of each model; they can be used to interpret the geometrical characteristics of rift-related faults; 2) Digital Elevation Models (DEMs) used to reconstruct the 3D deformation of the performed analogue models, allowing for quantitative analysis of the fault pattern. 3) Short movies built from top-view photos which help to visualize the evolution of model deformation; 4) line-drawing of fault and fracture patters to be used for fault statistical quantification. Further details on the modelling strategy and setup can be found in Corti (2012), Maestrelli et al. (2020), Molnar et al. (2020), Philippon et al. (2015), Zwaan et al. (2021) and in the publication associated with this dataset. Materials used for these analogue models were described in Montanari et al. (2017) Del Ventisette et al. (2019) and Zwaan et al. (2020).
This dataset presents the raw data from one experimental series (named CCEX, i.e., Caldera Collapse under regional Extension) of analogue models performed to investigate the process of caldera collapse followed by regional extension. Our experimental series tested the case of perfectly circular collapsed calderas afterward stretched under regional extensional conditions, that resulted in elongated calderas. The models are primarily intended to quantify the role of regional extension on the elongation of collapsed calderas observed in extensional settings, such as the East African Rift System. An overview of the performed analogue models is provided in Table 1. Analogue models have been analysed quantitatively by means of photogrammetric reconstruction of Digital Elevation Model (DEM) used for 3D quantification of the deformation, and top-view photo analysis for qualitative descriptions. The analogue materials used in the setup of these models are described in Montanari et al. (2017), Del Ventisette et al. (2019), Bonini et al., 2021 and Maestrelli et al. (2021a,b).
The main component of this data publication is a dataset of predicted daily nutrient concentrations for NO3-N and TP for 150 monitoring stations along 60 German rivers (main rivers). The aim of this dataset is to fill the data gap of daily nutrient concentrations for a better understanding of nutrient transport from the rivers to the seas. So far, nutrient concentrations are sampled on a fortnightly basis, which can be insufficient for nutrient retention models working on a daily basis. With this method and available datasets, river basin managers have the opportunity to look at nutrient concentrations or load patterns on a finer resolution to adapt their management to improve water quality. The dataset was obtained by a random forest model (RF) based on measured NO3-N and TP concentrations between the years 2000 and 2019. The data was requested or where available downloaded from official websites of the Federal States or River Basins. Different variables for NO3-N and TP were finally considered in the models to produce the RF, like discharge, land use, day of the year.
In Finger et al. (2022), we created consistent three-dimensional models in terms of temperature, density and composition of the upper mantle of the cratonic part of the African continent by combining seismic [Celli et al., 2020] and gravity [Förste et al., 2014] data with mineral physics constraints in an iterative integrated inversion approach [Kaban et al., 2014; Tesauro et al., 2014]. Further, we calculated a new model of depth to the Moho to correct the gravity field for crustal effects and calculate the residual topography, and provide an update for the average crystalline crust density from Litho1.0 [Pasyanos et al., 2014]. To calculate depth to the Moho, data from the GSC [Global Seismic Catalog, Mooney, 2015 with updates up to 2019] were combined with those published by Globig et al. [2016]. Here, we share data used from the GSC, final models of the upper mantle and crust that are discussed in the article, as well as the test cases set up in the uncertainty assessment. The upper mantle models are given in six layers centered at 50, 100, 150, 200, 250 and 300 km. In addition, density variations determined for the crust are given in an additional layer at 15 km depth. All fields range from -40.5°N to 40.5°N and -20.5°E to 55.5°E with a 1° by 1° lateral resolution. The data is provided in binary format as three netCDF4 files, containing the final results discussed in the paper ("Results_AF"), and the two uncertainty assessment cases for an upwards/downwards shifted Moho ("Results_AF_Moho_up" / "Results_AF_Moho_down"), respectively. In addition, data extracted from "Results_AF" to create the six profiles shown in the main article, and measurements of depth to Moho from the GSC are provided as ASCII formatted .dat files.
In Finger et al. (2021), we created consistent three dimensional models in terms of temperature, density and composition of the upper mantle of the cratonic South American Platform ("Upper MAntle Model") by combining seismic (Celli et al., 2020, Schaeffer & Lebedev, 2013) and gravity (Förste et al., 2014) data with mineral physics constraints in an iterative integrated inversion approach (Kaban et al., 2014; Tesauro et al., 2014). We further compiled a new crustal model ("Crustal Model"), including sediment and average crustal density and depth to the Moho to correct the gravity field for crustal effects and calculate the residual topography. To obtain these models we used data from the GSC (Global Seismic Catalog, Mooney, 2015 with updates up to 2019). To calculate depth to the Moho, the GSC data were combined with those published by Rivadeneyra-Vera et al. (2019). Here, we share the initial and final models of the upper mantle, sediment density and crust that are discussed in the article as well as the test cases set up in the uncertainty assessment. The upper mantle models are given in six layers centered at 50, 100, 150, 200, 250 and 300 km. All models range from -60.5°N to 15.5°N and -90.5°E to -29.5°E, except for the sediment density model (-59.5°N to 24.5°N and -99.5°E to -25.5°E) with a 1° by 1° lateral resolution. A detailed description of the respective files is given in each subfolder. All data are in ASCII format.
We present a 3-D lithospheric-scale data-constrained structural model covering the area of North Patagonian Massif Plateau (NPM) and its surroundings. These data are supplementary material to “Lithospheric 3D gravity modelling using upper-mantle density constraints: Towards a characterization of the crustal configuration in the North Patagonian Massif area, Argentina” (Gómez Dacal et al. 2017). The North Patagonian Massif (NPM), in central Argentina, includes a plateau of an average altitude of 1200 m.a.s.l. mostly surrounded by basins that stand between 500 to 700 m below it. Geological observations and previous works indicate that the present-day elevation of the plateau was reached in the Paleogene by a sudden uplift that did not involve noticeable deformation. To gain insight into the causes of the uplift and the geodynamic development of the area, it is necessary to characterize the present-day configuration of the lithosphere.
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