%0 Generic %1 gonzaleznicolas2021regimeandmemory %A Gonzalez-Nicolas Alvarez, Ana %D 2021 %K darus mult ubs_10002 ubs_10021 ubs_20002 ubs_20019 ubs_30028 ubs_30165 ubs_40041 unibibliografie %R 10.18419/darus-2034 %T Regime-and-memory model (RMM) Code %X 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 chemodynamic-type catchment behaviors, and it resembles the regression slope in plots of log(C)-log(Q). More information about the code can be found in the related publication Gonzalez-Nicolas et al. (2021) https://doi.org/10.3390/w13131723 This dataset includes Matlab codes and data used for the sampling strategies. Main file is "Main_MCMC_designs.m". Sampling strategies used within this manuscript are already designed. These are the files with extension "*.mat". File "data_Schwientek_et_al_2013.xls" includes all data between 7/01/2011 and 4/01/2012 (6604 observations). The following needs to be changed in the main file and adapted to each individual scenario: %% READ OBSERVATIONS %% INPUT PARAMETERS %% PREPARE MCMC

@misc{gonzaleznicolas2021regimeandmemory, abstract = {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 chemodynamic-type catchment behaviors, and it resembles the regression slope in plots of log(C)-log(Q). More information about the code can be found in the related publication Gonzalez-Nicolas et al. (2021) https://doi.org/10.3390/w13131723 This dataset includes Matlab codes and data used for the sampling strategies. Main file is "Main_MCMC_designs.m". Sampling strategies used within this manuscript are already designed. These are the files with extension "*.mat". File "data_Schwientek_et_al_2013.xls" includes all data between 7/01/2011 and 4/01/2012 (6604 observations). The following needs to be changed in the main file and adapted to each individual scenario: %% READ OBSERVATIONS %% INPUT PARAMETERS %% PREPARE MCMC}, added-at = {2022-03-08T18:44:43.000+0100}, affiliation = {Gonzalez-Nicolas Alvarez, Ana/Universität Stuttgart}, author = {Gonzalez-Nicolas Alvarez, Ana}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2c2298eef23e1f73001585e5ae5403b70/unibiblio}, doi = {10.18419/darus-2034}, howpublished = {Software}, interhash = {8f7c688c8191e732937fd90b1f95bc98}, intrahash = {c2298eef23e1f73001585e5ae5403b70}, keywords = {darus mult ubs_10002 ubs_10021 ubs_20002 ubs_20019 ubs_30028 ubs_30165 ubs_40041 unibibliografie}, note = {Related to: 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, 1723. doi: 10.3390/w13131723}, orcid-numbers = {Gonzalez-Nicolas Alvarez, Ana/0000-0003-2869-8255}, timestamp = {2023-12-20T11:00:17.000+0100}, title = {Regime-and-memory model (RMM) Code}, year = 2021 }