Stochastic Simulation and Safety Research for Hydrosystems (LS3)

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81 to 90 of 110 Results

low_q_sampling_designs.tab Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM) Tabular Data - 1.8 KB - 5 Variables, 75 Observations - UNF:6:UggYis04XhJBnQYF8+RFqA== This file includes the low Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.
time_frequency_sampling_designs.tab Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM) Tabular Data - 1.7 KB - 5 Variables, 75 Observations - UNF:6:R3xLV6UfgUTLeW1ijWj5sQ== This file includes the time frequency sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.
high_q_sampling_designs.tab Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM) Tabular Data - 1.8 KB - 5 Variables, 75 Observations - UNF:6:XkKTlOfntjxfQhiH0L7XFA== This file includes the high Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.
low_and_high_q_sampling_designs.tab Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM) Tabular Data - 1.8 KB - 5 Variables, 75 Observations - UNF:6:5Q7YX9enLUIl09INbcWNMA== This file includes the low and high Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.
flow_discharge_frequency_sampling_designs.tab Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM) Tabular Data - 2.6 KB - 6 Variables, 75 Observations - UNF:6:hD62pRgyjaW0dI4vof74IA== This file includes the river discharge frequency sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.
Regime-and-memory model (RMM) Code Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/DARUS-2034, DaRUS, V1 We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime. This parameter can morph the model among chemostatic-type and chemodyn...
RMM_code.tar Jun 24, 2021 - Regime-and-memory model (RMM) Code TAR Archive - 618.5 KB - MD5: f774bb6bef0ff777247ad0b45474674f This includes the Matlab files and input files to run the Regime-and-Memory model (RMM) described in Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M.; Nowak, W.. Characterization of Export Regimes in Concentration–Discharge Plots via an Advanced Time-Series Model and Event-Based Sampling Strategies. Water 2021, 13 (accepted)
License.txt Jun 24, 2021 - Regime-and-memory model (RMM) Code Plain Text - 1.5 KB - MD5: 8ee31a20b6dfb6cf41b5ac673b720631
Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data Jun 18, 2021 - Modeling Strategies for Gas migration in Subsurface Banerjee, Ishani, 2021, "Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data", https://doi.org/10.18419/DARUS-1776, DaRUS, V1 This dataset contains modeling data used to obtain the results and figures in the manuscript: "Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data." In particular, the model realization data and post-processing codes for the manuscript can be found here.
Moments.m Jun 18, 2021 - Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data Plain Text - 962 B - MD5: a4c60d20771a1040ed1f89b4f38bed34 Code code: Spatial moments (zeroth, first and second) computation of images in 2D space

low_q_sampling_designs.tab

Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM)

Tabular Data - 1.8 KB - 5 Variables, 75 Observations -

This file includes the low Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.

time_frequency_sampling_designs.tab

Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM)

Tabular Data - 1.7 KB - 5 Variables, 75 Observations -

This file includes the time frequency sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.

high_q_sampling_designs.tab

Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM)

Tabular Data - 1.8 KB - 5 Variables, 75 Observations -

This file includes the high Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.

low_and_high_q_sampling_designs.tab

Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM)

Tabular Data - 1.8 KB - 5 Variables, 75 Observations -

This file includes the low and high Q sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.

flow_discharge_frequency_sampling_designs.tab

Jun 24, 2021 - Sampling Strategies of the Regime-and-memory model (RMM)

Tabular Data - 2.6 KB - 6 Variables, 75 Observations -

This file includes the river discharge frequency sampling strategies used in the manuscript Gonzalez-Nicolas et al. (2021), "Characterization of export regimes in concentration–discharge plots via an advanced time-series model and event-Based sampling strategies", Water.

Regime-and-memory model (RMM) Code

Jun 24, 2021 - CAMPOS Project P8: Conceptual Model Uncertainty

Gonzalez-Nicolas Alvarez, Ana, 2021, "Regime-and-memory model (RMM) Code", https://doi.org/10.18419/DARUS-2034, DaRUS, V1

We introduce a simple stochastic time-series model (regime-and-memory model, RMM) for concentrations in the river that accounts for fluctuating release and transport with memory, using an autocorrelation over time.One explicit parameter of our model represents the export regime. This parameter can morph the model among chemostatic-type and chemodyn...

RMM_code.tar

Jun 24, 2021 - Regime-and-memory model (RMM) Code

TAR Archive - 618.5 KB -

This includes the Matlab files and input files to run the Regime-and-Memory model (RMM) described in Gonzalez-Nicolas, A.; Schwientek, M.; Sinsbeck, M.; Nowak, W.. Characterization of Export Regimes in Concentration–Discharge Plots via an Advanced Time-Series Model and Event-Based Sampling Strategies. Water 2021, 13 (accepted)

License.txt

Jun 24, 2021 - Regime-and-memory model (RMM) Code

Plain Text - 1.5 KB -

Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data

Jun 18, 2021 - Modeling Strategies for Gas migration in Subsurface

Banerjee, Ishani, 2021, "Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data", https://doi.org/10.18419/DARUS-1776, DaRUS, V1

This dataset contains modeling data used to obtain the results and figures in the manuscript: "Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data." In particular, the model realization data and post-processing codes for the manuscript can be found here.

Moments.m

Jun 18, 2021 - Replication Data for: Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data

Plain Text - 962 B -

Code

code: Spatial moments (zeroth, first and second) computation of images in 2D space

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