scholarly journals The influence of layer and voxel geological modelling strategy on groundwater modelling results

2021 ◽  
Author(s):  
Trine Enemark ◽  
Lærke Andersen ◽  
Anne-Sophie Høyer ◽  
Karsten Jensen ◽  
Jacob Kidmose ◽  
...  
Keyword(s):  
Significance Test ◽  
Groundwater Model ◽  
Layer Model ◽  
Dense Area ◽  
Test Taking ◽  
Geological Modelling ◽  
Model Predictions ◽  
Voxel Model ◽  
Parameter Values ◽  
Modelling Approach

Reliable groundwater model predictions are dependent on representative models of the geological environment, which can be modelled using several different techniques. In order to inform the choice of the geological modelling technique, the differences between a layer modelling approach and a voxel modelling approach were analyzed. The layer model consist of stratigraphically ordered surfaces, while the voxel model consist of a structured mesh of volumetric pixels. Groundwater models based on the two models were developed to investigate their impact on groundwater model predictions. The study was conducted in the relatively data-dense area Egebjerg, Denmark, where both a layer model and a voxel model has been developed based on the same data and geological conceptualization. The characteristics of the two methodologies for developing the geological models were shown to have a direct impact on the resulting models. The differences between the layer and the voxel models were however shown to be diverse and not related to larger conceptual elements with few exceptions. The analysis showed that the geological modelling approaches had an influence on preferred parameter values and thereby groundwater model predictions of hydraulic head, groundwater budget terms and particle tracking results. A significance test taking into account the predictive distributions showed that for many predictions the differences between the models were significant. The results suggest that the geological modelling strategy has an influence on groundwater model predictions even if based on the same geological conceptualization.

Land Use Regression of Ambient Endotoxin Concentrations in a Livestock Dense Area: Robustness of Model Predictions at Residential Addresses of Health Study Participants

2018 ◽  
Vol 2017 (1) ◽  
pp. 408
Author(s):  
Myrna M.T. de Rooij ◽  
D.J.J. Heederik ◽  
.J.H.M. van Nunen ◽  
L.A.M. Smit ◽  
F. Borlée ◽  
...  
Keyword(s):  
Land Use ◽  
Health Study ◽  
Land Use Regression ◽  
Dense Area ◽  
Model Predictions ◽  
Study Participants

scholarly journals Simulating tubulin-associated unit transport in an axon: using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data

2017 ◽  
Vol 473 (2201) ◽  
pp. 20170045 ◽  
Author(s):  
I. A. Kuznetsov ◽  
A. V. Kuznetsov
Keyword(s):  
Experimental Data ◽  
Confidence Intervals ◽  
Surrogate Data ◽  
Model Parameters ◽  
Model Predictions ◽  
Estimate Parameter ◽  
Minimum Number ◽  
Percentile Bootstrap ◽  
Parameter Values ◽  
Best Fit

In this paper, we first develop a model of axonal transport of tubulin-associated unit (tau) protein. We determine the minimum number of parameters necessary to reproduce published experimental results, reducing the number of parameters from 18 in the full model to eight in the simplified model. We then address the following questions: Is it possible to estimate parameter values for this model using the very limited amount of published experimental data? Furthermore, is it possible to estimate confidence intervals for the determined parameters? The idea that is explored in this paper is based on using bootstrapping. Model parameters were estimated by minimizing the objective function that simulates the discrepancy between the model predictions and experimental data. Residuals were then identified by calculating the differences between the experimental data and model predictions. New, surrogate ‘experimental’ data were generated by randomly resampling residuals. By finding sets of best-fit parameters for a large number of surrogate data the histograms for the model parameters were produced. These histograms were then used to estimate confidence intervals for the model parameters, by using the percentile bootstrap. Once the model was calibrated, we applied it to analysing some features of tau transport that are not accessible to current experimental techniques.

scholarly journals Groundwater Quality Evolution Model in the Ring of Cenotes, Yucatan, Mexico

2021 ◽  
Author(s):  
Rosela Pérez-Ceballos ◽  
Cesar Canul-Macario ◽  
Roger Pacheco-Castro ◽  
Julia Pacheco-Ávila ◽  
Jorge Euán-Ávila ◽  
...  
Keyword(s):  
Carbonate Rocks ◽  
Preferential Flow ◽  
Karst Aquifers ◽  
Flow Paths ◽  
Hydrogeochemical Evolution ◽  
Preferential Flow Paths ◽  
Model Predictions ◽  
Chicxulub Crater ◽  
Saturation Indexes ◽  
Modelling Approach

Karst aquifers show dissolution/precipitation processes of the minerals present in the carbonate rocks. The Ring of Cenotes (RC) extends along the edge of the Chicxulub crater, in the limestone platform of the Yucatan Peninsula (YP), where groundwater shows preferential flow paths toward the coast near Celestun and Dzilam Bravo towns. This study aimed to describe the regional hydrogeochemical evolution of groundwater of the RC, and its association with the dissolution/precipitation of the minerals present along its path to the ocean. To achieve this aim, we: a) characterized groundwater's hydrogeochemistry; b) determined the calcite, dolomite, and gypsum saturation indexes (reaction phases with the groundwater) in the study area; c) proposed a hydrogeochemical model developed through PHREEQC using an inverse modelling approach. The model predictions confirmed that there are two evolution pathways of the groundwater consistent with the preferential flow paths suggested in a previous regionalization of the RC. On the western path, where groundwater flows towards Celestun, an important marine intrusion influences the hydrogeochemical processes and represents a risk for the prevalence of freshwater. On the eastern path, where groundwater flows toward Dzilam Bravo, the hydrogeochemistry in the sinkholes correlates well with rainfall, suggesting a higher vulnerability during droughts than during rainy periods.

scholarly journals Lithospheric model along transect HT-1 across Western Carpathians and Pannonian Basin based on 2D integrated modelling

2020 ◽  
Vol 50 (4) ◽  
Author(s):  
Jana DÉREROVÁ ◽  
Miroslav BIELIK ◽  
Igor KOHÚT ◽  
Dominika GODOVÁ ◽  
Ján VOZÁR ◽  
...  
Keyword(s):  
Pannonian Basin ◽  
Western Carpathians ◽  
Integrated Modelling ◽  
Trial And Error ◽  
Simultaneous Interpretation ◽  
Model Predictions ◽  
Trial And Error Method ◽  
Error Method ◽  
Good Agreement ◽  
Modelling Approach

2D integrated modelling approach was applied to determine the lithospheric structure along transect HT-1 located in the Carpathian-Pannonian Basin–European platform region. Our approach combines simultaneous interpretation of surface heat flow, topography, gravity and geoid data. All available geophysical and geological data were used to create an initial model that has been afterwards modified by trial and error method until reasonable fit was obtained between input data and model predictions. The main focus of our study was the position and shape of the lithosphere-asthenosphere boundary (LAB). In the Pannonian Basin the modelled LAB is at depths of about 80–90 km and rapidly dips towards the Western Carpathians where its depth reaches values 145 to 150 km. Beneath the European platform the LAB depth is about 135–140 km. We can observe a slight lithospheric root under the Western Carpathians. This lithospheric thickening is interpreted as a small remnant of a subducted slab. This result is in a good agreement with the previous lithospheric models in the Carpathian-Pannonian Basin.

scholarly journals An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3

2020 ◽  
Author(s):  
Steven J. Phipps ◽  
Jason L. Roberts ◽  
Matt A. King
Keyword(s):  
Parameter Space ◽  
Ice Sheet ◽  
Physical Processes ◽  
Dimensional Parameter ◽  
Model Predictions ◽  
Observation Uncertainty ◽  
Parameter Values ◽  
The Antarctic ◽  
Optimal Set ◽  
Generate Model

Abstract. Physical processes within geoscientific models are sometimes described by simplified schemes known as parameterisations. The values of the parameters within these schemes can be poorly constrained by theory or observation. Uncertainty in the parameter values translates into uncertainty in the outputs of the models. Proper quantification of the uncertainty in model predictions therefore requires a systematic approach for sampling parameter space. In this study, we develop a simple and efficient approach to identify regions of multi-dimensional parameter space that are consistent with observations. Using the Parallel Ice Sheet Model to simulate the present-day state of the Antarctic Ice Sheet, we find that co-dependencies between parameters preclude the identification of a single optimal set of parameter values. Approaches such as large ensemble modelling are therefore required in order to generate model predictions that incorporate proper quantification of the uncertainty arising from the parameterisation of physical processes.

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