Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-16021
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Main Title: Stochastic Modelling Approach to identify Uncertainties of Karst Conduit Networks in Carbonate Aquifers - Data
Author(s): Banusch, Sandra
Somogyvari, Mark
Sauter, Martin
Renard, Philippe
Engelhardt, Irina
Type: Generic Research Data
URI: https://depositonce.tu-berlin.de/handle/11303/17242
http://dx.doi.org/10.14279/depositonce-16021
License: https://creativecommons.org/licenses/by-nc/4.0/
Abstract: This dataset contains (1) The realizations for the five hundred 3D conduit networks (.vtk output files) generated using the SKS algorithm (Borghi et al., 2012), which form the basis for the Karst Probability Map. (2) An overview and further explanations of the parameters assigned to the Fast-Marching-Algorithm in the SKS. (3) Climate data (Precipitation, Tmin & Tmax) from 1990 to 2018 over the recharge area of the Western Mountain Aquifer (Israel & Palestinian Territories). Information on each station can be found in the file "stations". It includes data for research paper: "Banusch, S., Somogyvari, M., Sauter, M., Renard, P., Engelhardt, I. (2022). Stochastic Modelling Approach to identify Uncertainties of Karst Conduit Networks in Carbonate Aquifers" published in Water Resources Research
Subject(s): karst
stochastic modelling
Issue Date: 20-Jul-2022
Date Available: 20-Jul-2022
Language Code: en
DDC Class: 551 Geologie, Hydrologie, Meteorologie
TU Affiliation(s): Fak. 6 Planen Bauen Umwelt » Inst. Angewandte Geowissenschaften » FG Hydrogeologie
Appears in Collections:Technische Universit├Ąt Berlin » Research Data

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