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.

Data:

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 (;)
Column 1 ==> Time (%Y-%m-%d %H:%M)
Column 2 ==> Streamflow (in m3/s)

2/ h_Mercier.txt

Original stage time series for Mercier hydrometric station

Column separator: semi-colon (;)
Column 1 ==> Time (%Y-%m-%d %H:%M)
Column 2 ==> Stage(in mm)
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 (;)
Column 1 ==> Date (%Y-%m-%d)
Column 2 ==> Stage_m (in m)
Column 3 ==> Streamflow_m3_per_s (in m3/s)
Column 3 ==> Uncertainty (unitless)

R codes:

0/ other ressources:
All the ressources related to the bayesian estimation of the rating curve can be found on github: https://github.com/BaM-tools
Time aggregation of time series was done using the tAgg R package available on github: https://github.com/IvanHeriver/tAgg

1/ functions.R
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
This file contains some code illustrating the usage of the functions in the "functions.R" file.