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Historical Earthquakes in Valencia

The “1396 Tabernes” earthquake occurred in the Valldigna valley and it has been considered one of the largest Iberian Peninsula recorded earthquakes. The information used for such claims has always been from secondary sources in the area because the originals were believed to be lost. In this work, the recently edited copy of the book about the Royal Monastery Nuestra Señora de la Valldigna history, the “Chronological history” of Father Estevan Gil, has permitted to correct the date of December 16th instead of December 18thfor the main earthquake. The earthquake damage is reinterpreted from the original source. In addition, the importance of the November 7th 1330 earthquake which represents the first destruction of the monastery, is pointed out. The original book provides information on the last destruction of the church in the 1644 earthquake, its damage and reconstruction. Together with another book, also recently published by Tomás Gómez, on the castilian visit of 1666, it allows us to discover what the monastery was like and understand the damage and reconstruction. Finally, two other earthquakes are mentioned in the years 1724 and 1748 that are also reflected in Father Gil’s book.

Entrance of the Royal Monastery Nuestra Señora de la Valldigna

Cite as: Tent-Manclús, J. E. (2022): Los terremotos del sur de la provincia de Valencia según las fuentes del Real Monasterio de Nuestra Señora de la Valldigna (E de España, Provincia de Valencia). Cuaternario y Geomorfología, 36 (1-2): 77-103. https://doi.org/10.17735/cyg.v36i1-2.91108

K-nearest neighbors algorithm used for classifying geological variables.

The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN algorithm ideal for classifying datasets of geological variables and parameters prior to 3D visualization. This paper introduces a machine learning KNN algorithm and Python libraries for visualizing the 3D stratigraphic architecture of sedimentary porous media in the Quaternary onshore Llobregat River Delta (LRD) in northeastern Spain. A first HTML model showed a consecutive 5 m-equispaced set of horizontal sections of the granulometry classes created with the KNN algorithm from 0 to 120 m below sea level in the onshore LRD. A second HTML model showed the 3D mapping of the main Quaternary gravel and coarse sand sedimentary bodies (lithosomes) and the basement (Pliocene and older rocks) top surface created with Python libraries. These results reproduce well the complex sedimentary structure of the LRD reported in recent scientific publications and proves the suitability of the KNN algorithm and Python libraries for visualizing the 3D stratigraphic structure of sedimentary porous media, which is a crucial stage in making decisions in different environmental and economic geology disciplines.

The 3D stratigraphic architecture (coarse lithosomes and the basement top surface (BTS)) of the onshore LRD. (A) Gravel and coarse sand lithosomes and BTS. (B) Gravel lithosomes and BTS. (C) Coarse sand lithosomes and BTS. (D) Basement top surface. The color assigned to each granulometry class is cyan for gravel, yellow for coarse sand, and reddish-brownish for the basement. An interactive 3D HTML version of this model is included in Supplementary Materials

Interactive figures here

Cite as: Bullejos, M., Cabezas, D., Martín-Martín, M., Alcalá, F.J., 2022. A K-Nearest Neighbors Alborithm in Python for Visualizing the 3D Stratigraphic Architecture of the Llobregat River Delta in NE Spain.  J. Mar. Sci. Eng. https://doi.org/10.3390/jmse10070986 

A Python Application for Visualizing the 3D Stratigraphic Architecture

A Python application for visualizing the 3D stratigraphic architecture of porous sedimentary media has been developed. The application uses the parameter granulometry deduced from borehole lithological records to create interactive 3D HTML models of essential stratigraphic elements.

The 3D distribution of the granulometry classes along the Z axis in each of the 433 compiled boreholes in the LRD. The plotting adopted a 1:1:50 (x = 2, y = 2 and z = 0.5) aspect ratio for better display. The color assigned to each granulometry class is cyan for gravel, yellow for coarse sand, gray for silt–clay, and red for the basement.

On the basis of the high density of boreholes and the subsequent geological knowledge gained during the last six decades, the Quaternary onshore Llobregat River Delta in northeastern Spain was selected to show the application. The public granulometry dataset produced by the Water Authority of Catalonia from 433 boreholes in this strategic coastal groundwater body was clustered into the clay–silt, coarse sand, and gravel classes. Three interactive 3D HTML models were created. The first shows the location of the boreholes granulometry. The second includes the main gravel and coarse sand sedimentary bodies (lithosomes) associated with the identified three stratigraphic intervals, called lower (>50 m b.s.l.) in the distal Llobregat Delta sector, middle (20–50 m b.s.l.) in the central Llobregat, and upper (<20mb.s.l.) spread over the entire Llobregat. The third deals with the basement (Pliocene and older rocks) top surface, which shows an overall steeped shape deepening toward the marine platform and local horsts, probably due to faulting. The modeled stratigraphic elements match well with the sedimentary structures reported in recent scientific publications.

This proves the good performance of this incipient Python application for visualizing the 3D stratigraphic architecture, which is a crucial stage for groundwater management and governance.

Cite as: Bullejos, M., Cabezas, D., Martín-Martín, M., Alcalá, F.J., 2022. A Python Application for Visualizing the 3D Stratigraphic Architecture of the Onshore Llobregat River Delta in NE Spain. Water . https://doi.org/10.3390/w14121882

Field work in the Eocene Prebetic II

The rain in Spain…

Well the second field work campaign in the Eocene Prebetic was conditional by the bad weather, rain, wind, snow and cold.

The picture shows the members of the team imply in this field try to the Eocene rocks within the provinces of Alicante and Murcia.

From left to right: Jose Enrique Tent-Manclus, Josep Tosquella, Crina Miclaus and Manuel Martin Martin in Santiago de la Espada.

This is the second  field season of the project of the  Spanish research agency (Agencia Estatal de Investigación) of the Spanish Science and innovation minister (Ministerio de Ciencia e Innovación)  entitle as “EVOLUCION TECTONO-DEPOSICIONAL DE CUENCAS SEDIMENTARIAS CENOZOICAS: CARACTERIZACION 2D-3D Y MEJORA DE PATRONES ESTANDAR” (PID2020-114381GB-I00). See previous post.

Field work in the Eocene Prebetic

The good weather in Alicante during the winter season has permitted to do the first field season of our project of the  Spanish research agency (Agencia Estatal de Investigación) of the Spanish Science and innovation minister (Ministerio de Ciencia e Innovación)  entitle as “EVOLUCION TECTONO-DEPOSICIONAL DE CUENCAS SEDIMENTARIAS CENOZOICAS: CARACTERIZACION 2D-3D Y MEJORA DE PATRONES ESTANDAR” (PID2020-114381GB-I00). See previous post.

The picture shows the members of the team imply in this field try to the Eocene rocks within the provinces of Alicante and Murcia.

Crina Miclaus (Alexandru Ioan Cuza University)

Josep Tosquella (Huelva University)

Manuel Martin-Martin (Alicante University)

Jose Enrique Tent-Manclus (Alicante University)

The members of the team on the Campello Harbour. From left to right, Manuel Martin-Martin, Crina Miclaus, Jose Enrique Tent-Manclús and Josep Tosquella.

Next picture shows a nummulite-rich limestone in a quarry near Onil, one of the visited sections in our field work.

Nummulites sections in an Eocene limestone near Onil (Alicante).

 

Software for Geological modelling (part I)

Geological modelling is the ability to create computerized representations of subsurface geology. Many times, every once in a while, I have searched internet to find nice-looking geological models, just to find ideas or whatever the workers were doing. I like the ones with many colours (using all-the-rainbow) with a 3d immersive-perspective, nice vertical and horizontal axis lines and a 3d north-arrow. The idea of being true or just being a well-documented cartoon of something real was not important at the first point. For most geologists a nice looking 3d geological model is supposed to be truer than a simple map.

Then the next search is about the new accepted manuscripts of recently published papers in some scholarly journals, academic journals, to see what was new about illustrating works. My filling and also of my staff companions are that nice-looking figures illustrating a geological manuscript permit a better, faster, less time-consuming publish research results. All of us remember some not top-quality (debatable quality) works published because they have awesome figures.

Well, now we known the interest of geological modelling but most of the time what we need just a geoscience art-work.

A geological model can be obtained after doing three phases, that can produce each one a geological 3d illustration, and can be considered a computerized subsurface geological representation.

  • The first level is the geological 3D sketch in this level show a simplistic way of showing a complex geology. The software to do so is the kind of a “mudball” modelling software as for instance (sketchup) https://www.sketchup.com/, Blender (https://www.blender.org), or Tinkercad (https://www.tinkercad.com). But taking in an account that we normally like to start with a geological map or an aerial photomosaic (like google Earth). The software must have 2D mapping and mosaic tiles import filters capabilities. As my experience of working with 2D for mapping the best choice is Autocad 3d Map (Autodesk). I can map then, then create surface an made simplistic geological model, what a sketch is.
Abanilla Sierra 3d model made using autocad from Tent-Manclús (2013) PH D. Thesis. This is an example of a geological model of level 1 in perspective but drawn in 2D.
  • The second level is the realistic 3d model representation. In this step we like to integrate the relief, using a Digital Elevation Model (DEM), with the aerial photomosaic, and the information below the land surface. For geological model we like a 3d net used as scale to appreciate the rock volumes. Also, we like a software with capabilities of change the vertical factor and to create immersive perspectives. All this can be done also with Autodesk programs, but it takes a lot of time to produce the model because they are designed for computer-lovers than like to spend days in front of the screen. The final result can be the better one, but geologist usually like to check the results in the field, not spending all the time with the computer. This last reason is that I prefer a simpler graphical interface so do a nice-looking illustration from a point of view of an Earth scientist, not a blockbuster movie. Therefore, my choose is the golden software surfer program.
Pinoso Diapir 3D model made for the book “Rutas Azules por el Patrimonio Hidrogeológico de Alicante” Diputación de Alicante.2015
  • The third level is using the realistic model to go back and forth in time to see the deformation history and trying to understand the forces and the deformation phases to produce the 3d geometry. This is the goal of the structural geology. To achieve this level most of the time it has to be a simplified the previous model to work with because some information is useless in this level as for instance the aerial photomosaics. For this phase are designed the principal geomodelling software as for instance Petrel, Gocad or MOVE. All mentioned software is oriented to the petroleum industry so it means that are not cheap. In my case the easier to get access has been the MOVE and that’s my choice.
Shallow water simulation on see this blog the previous post and also the work  ‎Miguel Lastra, Manuel J. Castro Díaz, Carlos Ureña, Marc de la Asunción (2017):  Efficient multilayer shallow-water simulation system based on GPUs. Mathematics and Computers in Simulation, Volume 148, 2018,  48-65. DOI: https://doi.org/10.1016/j.matcom.2017.11.008

Finally, the example that I most like is the British Geological Survey model of the Assynt culmination Geologica 3D model that you can download here in a 3D pdf file.

http://nora.nerc.ac.uk/id/eprint/504722/1/Assynt_Culmination.pdf

 

New project to study sedimentary basins.

The Spanish research agency (Agencia Estatal de Investigación) of the Spanish Science and innovation minister (Ministerio de Ciencia e Innovación)  has conceded a new project to study the Cenozoic sedimentary basins entitle as “EVOLUCION TECTONO-DEPOSICIONAL DE CUENCAS SEDIMENTARIAS CENOZOICAS: CARACTERIZACION 2D-3D Y MEJORA DE PATRONES ESTANDAR” (PID2020-114381GB-I00).

This research project  will develop techniques for the analysis of various types of Cenozoic sedimentary basins in a general compressive or convergent framework (associated with strike-slip faults, transported -piggy-back or wedge-top-, and complex foreland systems). The stratigraphic architecture, biostratigraphic control of the different sedimentary bodies, stratigraphic discontinuities will be studied, as well as  sediments  sources (both terrigeneous and biogenic) through mineralogical, petrographic and geochemical studies.

TEAM

Principal investigator: Manuel Martín-Martín (Alicante University)

Jesús M. Soria (Alicante University)

Manuel Bullejos Lorenzo (Granada University)

Antonio Sánchez Navas (Granada University)

Agustín Martín-Algarra (Granada University)

José Enrique Tent-Manclús (Alicante University)

Josep Tosquella (Huelva University)

Carlos Ureña Almagro (Granada University)

Fernando Pérez-Valera (Alicante University)

Francisco Javier Alcalá-García (Instituto Geológico y Minero de España, IGME)

Estelle Mortimer (University of Leeds)

Douglas Patton (University of Leeds)

Francesco Perri (Calabria University)

Salvatore Critelli (Calabria University)

Crina Miclaus (Alexandru Ioan Cuza University)

Francisco Serrano (Malaga University)