Data and codes related to the article: Horner et al. Streamflow uncertainty due to the limited sensitivity of controls at hydrometric stations

The data files and R code files are related to the article Horner et al. "Streamflow uncertainty due to the limited sensitivity of controls at hydrometric stations" published in Hydrological Processes. <strong>Data: </strong> 1/ Q_Craponne.txt Original streamflow time series of Craponne hydrometric station which was used to generate the synthetic stage time series using the theoretical equations of the 5 fictive hydrometric stations. Column separator: semi-colon (;)<br> Column 1 ==&gt; Time (%Y-%m-%d %H:%M)<br> Column 2 ==&gt; Streamflow (in m3/s) 2/ h_Mercier.txt Original stage time series for Mercier hydrometric station Column separator: semi-colon (;)<br> Column 1 ==&gt; Time (%Y-%m-%d %H:%M)<br> Column 2 ==&gt; Stage(in mm)<br> Missing value code: NA 3/ Gaugings_Mercier.txt Gaugings (date, stage, streamflow and associated uncertainty) of the Mercier hydrometric station before and after hydraulic control change which occured in November 2013. Column separator: semi-colon (;)<br> Column 1 ==&gt; Date (%Y-%m-%d)<br> Column 2 ==&gt; Stage_m (in m)<br> Column 3 ==&gt; Streamflow_m3_per_s (in m3/s)<br> Column 3 ==&gt; Uncertainty (unitless) <strong>R codes:</strong> 0/ other ressources:<br> All the ressources related to the bayesian estimation of the rating curve can be found on github: https://github.com/BaM-tools<br> Time aggregation of time series was done using the tAgg R package available on github: https://github.com/IvanHeriver/tAgg 1/ functions.R<br> This files contains several functions. Comments within the file explains each of the function: hydraulicEquations(): returns a list of the theoretical equations for the rating curves of the five fictive cases hydraulicEquationsInverter(): inverts of a theoretical rating curve (given a function Q=f(h), it returns a function h=f(Q)) computeAM30(): computes the AM30 generate_nonsyst_errors(): generates a matrix of non systematic errors generate_syst_errors(): generates a matrix of systematic errors get_resampling_indices_from_periodicity(): returns the indices of the resampling time steps used to generate systematic errors given a time vector and a periodicity Some of the code require the following packages: dplyr and RcppRoll 2/ examples.R<br> This file contains some code illustrating the usage of the functions in the "functions.R" file.