Stochastic Modelling Approach to identify Uncertainties of Karst Conduit Networks in Carbonate Aquifers - Data

Banusch, Sandra; Somogyvari, Mark; Sauter, Martin; Renard, Philippe; Engelhardt, Irina

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 Universität Berlin » Research Data