Spatiotemporal variability of water transit time distributions along an alpine stream network

This repository hosts the data and the codes to reproduce the analysis and the results presented in the manuscript:"Spatiotemporal variability of water transit time distributions along an alpine stream network"by Giulia Grandi et al. File "analyze_results.m": run the code to reproduce results of the manuscript and some useful Figures. Folder "input" contains the input structures to run the analyze_results.m script:- "Results.m" contains the results obtained from the MCMC sampling performed via the DREAM_ZS sampler.- "Variables.m" embeds the input variables as detailed in the script "analyze_results.m". Folder "auxiliary_func" contains the auxiliary functions to perform the posterior calculation and produce some plots:- "ComputeGaussianLogL.m" : performs the calculation of the gaussian log-Likelihood.- "ComputeLogPrior.m" : performs the calculation of the log-Prior for each parameter of the model based on the setting embedded in V.SP.- "subaxis.m" and "parseArgs.m" : functions to obtain nice subplot proposed by Aslak Grinsted (2026). "Subaxis - Subplot (https://ch.mathworks.com/matlabcentral/fileexchange/3696-subaxis-subplot), MATLAB Central File Exchange. Retrieved March 9, 2026."- "PlotPrior.m" : fuction to plot nicely the prior distribution (also in case of pooling). To use the model for a different case study, prepare the "V" data structure as detailed in the description of the analyze_results.m file and use the function "modelSASfunction", which return the log of the posterior density, with any sampler of choice. To use the DREAM_ZS sampler (as in the present study), please refer to "https://github.com/Zaijab/DREAM" for download. Language: MatLab (tested on Version R2024b)