Title
Landscape development modeling based on statistical framework
Abstract
Future biosphere modeling has an essential role in assessing the safety of a proposed nuclear fuel repository. In Finland the basic inputs needed for future biosphere modeling are the digital elevation model and the land uplift model because the surface of the ground is still rising due to the download stress caused by the last ice age. The future site-scale land uplift is extrapolated by fitting mathematical expressions to known data from past shoreline positions. In this paper, the parameters of this fitting have been refined based on information about lake and mire basin isolation and archaeological findings. Also, an alternative eustatic model is used in parameter refinement. Both datasets involve uncertainties so Monte Carlo simulation is used to acquire several realizations of the model parameters. The two statistical models, the digital elevation model and the refined land uplift model, were used as inputs to a GIS-based toolbox where the characteristics of lake projections for the future Olkiluoto nuclear fuel repository site were estimated. The focus of the study was on surface water bodies since they are the major transport channels for radionuclides in containment failure scenarios. The results of the study show that the different land uplift modeling schemes relying on alternative eustatic models, Moho map versions and function fitting techniques yield largely similar landscape development tracks. However, the results also point out some more improbable realizations, which deviate significantly from the main development tracks. Introduction of the statistical DEM model and its uncertainties.Statistical land uplift model parameter estimation using 14C radiocarbon data.Future surface water body estimation using GIS-based analysis.Area and volume probabilities for the future lakes based on statistical modeling.
Year
DOI
Venue
2014
10.1016/j.cageo.2013.09.013
Computers & Geosciences
Keywords
Field
DocType
different land uplift modeling,digital elevation model,future olkiluoto nuclear fuel,alternative eustatic model,future biosphere modeling,future site-scale land uplift,model parameter,statistical framework,refined land uplift model,landscape development,land uplift model,statistical model
Biosphere,Physical geography,Geomorphology,Data mining,Monte Carlo method,Surface water,Communication channel,Digital elevation model,Shore,Statistical model,Geology,Structural basin
Journal
Volume
Issue
ISSN
62
C
0098-3004
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Jari Pohjola100.68
Jari Turunen2526.63
Tarmo Lipping37014.54
Ari T. K. Ikonen400.34