diff --git a/docs/cookbooks/MultivariateFlagging.rst b/docs/cookbooks/MultivariateFlagging.rst
index c7297ade17f4497c58b3ae5766beb2433c8ad702..ac09cdd1aebbf3371b4291fb689262c9a35092f2 100644
--- a/docs/cookbooks/MultivariateFlagging.rst
+++ b/docs/cookbooks/MultivariateFlagging.rst
@@ -1,4 +1,4 @@
-.. SPDX-FileCopyrightText: 2021 Helmholtz-Zentrum für Umweltforschung GmbH - UFZ
+.. SPDX-FileCopyrightTextText: 2021 Helmholtz-Zentrumrum für Umweltforschung GmbH - UFZ
 ..
 .. SPDX-License-Identifier: GPL-3.0-or-later
 
@@ -347,7 +347,7 @@ correlated with relatively high *kNNscores*, we could try to calculate a thresho
 `STRAY <https://arxiv.org/pdf/1908.04000.pdf>`_ algorithm, which is available as the method:
 :py:meth:`~saqc.SaQC.flagByStray`. This method will mark some samples of the `kNNscore` variable as anomaly.
 Subsequently we project this marks (or *flags*) on to the *sac* variable with a call to
-:py:meth:`~saqc.SaQC.transferFlags`. For the sake of demonstration, we also project the flags
+:py:meth:`~saqc.SaQC.concatFlags`. For the sake of demonstration, we also project the flags
 on the normalized *sac* and plot the flagged values in the *sac254_norm* - *level_norm* feature space.
 
 
@@ -355,8 +355,8 @@ on the normalized *sac* and plot the flagged values in the *sac254_norm* - *leve
 .. doctest:: exampleMV
 
    >>> qc = qc.flagByStray(field='kNNscores', freq='30D', alpha=.3)
-   >>> qc = qc.transferFlags(field='kNNscores', target='sac254_corrected', label='STRAY')
-   >>> qc = qc.transferFlags(field='kNNscores', target='sac254_norm', label='STRAY')
+   >>> qc = qc.concatFlags(field='kNNscores', target='sac254_corrected', label='STRAY')
+   >>> qc = qc.concatFlags(field='kNNscores', target='sac254_norm', label='STRAY')
    >>> qc.plot('sac254_corrected', xscope='2016-11') # doctest:+SKIP
    >>> qc.plot('sac254_norm', phaseplot='level_norm', xscope='2016-11') # doctest:+SKIP
 
@@ -365,8 +365,8 @@ on the normalized *sac* and plot the flagged values in the *sac254_norm* - *leve
    :include-source: False
 
    qc = qc.flagByStray(field='kNNscores', freq='30D', alpha=.3)
-   qc = qc.transferFlags(field='kNNscores', target='sac254_corrected', label='STRAY')
-   qc = qc.transferFlags(field='kNNscores', target='sac254_norm', label='STRAY')
+   qc = qc.concatFlags(field='kNNscores', target='sac254_corrected', label='STRAY')
+   qc = qc.concatFlags(field='kNNscores', target='sac254_norm', label='STRAY')
 
 .. plot::
    :context: close-figs
diff --git a/docs/resources/data/hydro_config.csv b/docs/resources/data/hydro_config.csv
index c97df2be1da86607ce0a1e0ddff58ab945d63180..d9858e02317f94f6956978cd35c38ab4c0145176 100644
--- a/docs/resources/data/hydro_config.csv
+++ b/docs/resources/data/hydro_config.csv
@@ -16,6 +16,6 @@ water_z                 ; transform(field=['water_temp_raw'], func=zScore(x), fr
 sac_z                   ; transform(field=['sac254_raw'], func=zScore(x), freq='20D')
 kNN_scores              ; assignKNNScore(field=['level_z', 'water_z', 'sac_z'], freq='20D')
 kNN_scores              ; flagByStray(freq='20D')
-level_raw               ; transferFlags(field=['kNN_scores'], label='STRAY')
-sac254_corr             ; transferFlags(field=['kNN_scores'], label='STRAY')
-water_temp_raw          ; transferFlags(field=['kNN_scores'], label='STRAY')
\ No newline at end of file
+level_raw               ; concatFlags(field=['kNN_scores'], label='STRAY')
+sac254_corr             ; concatFlags(field=['kNN_scores'], label='STRAY')
+water_temp_raw          ; concatFlags(field=['kNN_scores'], label='STRAY')