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

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