Figure 4 . Relative sea level change computed using all
reservoirs in the Zarfl et al. (2015) database, assumed to be
completed by 2040, with seepage included as described in the text.
(a ) Global GRD fingerprint signal. Colors as in Fig. 3.
(b ) Detail of frame (a ) in South America, showing sea
level rise of a few mm along the west coast of Ecuador and Peru and
around the mouth of the Amazon River in Brazil. Cool colors show sea
level fall; warm colors show sea level rise. (c ) Detail of
frame (a ) in Southeast Asia, indicating sea level rise of a few
mm along the low-lying coasts of Bangladesh and Myanmar, and 1–2 mm
along the Vietnamese coast along the Gulf of Tonkin.
4 Discussion
4.1 Tide Gauge Observations
Our time series provides a globally resolved estimate of the yearly
change in sea level from 1900 – 2011 due to the construction of
reservoirs. Tide gauges record local changes in sea level, which may
show the effect of reservoir construction. Because of the variability in
sea level recorded in tide gauge data, only the largest, most rapid
changes will be visible. These are likely to be not the result of
sustained building of reservoirs over time, but rather a tide gauge’s
proximity to a single large reservoir. To determine whether any of these
changes are resolvable in the tide gauge record, we first calculate the
maximum yearly rate of change predicted at each tide gauge site in the
Permanent Service for Mean Sea Level (PSMSL) revised local reference
(RLR) database (http://www.psmsl.org/data/obtaining/; Holgate et
al ., 2013), shown in Fig. 5a. The largest predicted changes in sea
level due to water impoundment are in northern Europe, Ghana, Malaysia,
and the Saint Lawrence Seaway in Canada, all of which have tide gauges
in close proximity (< 200 km) to the construction of a single
large reservoir.
We begin by correcting the tide gauge data using two barotropic ocean
circulation models (Piecuch et al ., 2019). These models predict
sea surface height from surface wind stress and air pressure records
from two forcing datasets, ERA-20C (Poli et al ., 2013) and
NOAA-20CRv2 (Compo et al ., 2011), and extend throughout the
20th century. At each tide gauge location, we subtract
the annual average sea surface height derived in these models at each
candidate tide gauge location from the raw tide gauge data to remove the
atmospheric contribution from the sea level records. We then compare the
atmospheric-corrected sea level time series to our predicted changes due
to historical impoundment, focusing on locations where we predict that
the largest water impoundment-induced signals occurred.
The largest predicted rates of change due to impoundment occur at two
tide gauges in the St. Lawrence River in Canada, Baie-Comeau and
Point-au-Père/Rimouski. The filling of the Manicouagan reservoir from
1968 – 1974 is predicted to have caused a sea level rise at these sites
of almost 40 mm over six years (more than 6 mm yr-1,
which is more than 7 times the GMSL rise over this period, 0.8 mm
yr-1; Dangendorf et al ., 2019) The expected,
observed, and corrected tide gauge records are shown in Fig. 5b–c.
There is too much variability in the observations to confidently detect
the signal associated with the construction of the Manicouagan reservoir
in the tide gauge data. In any case, the St. Lawrence River is a
controlled waterway, so the impoundment signal in the record may be
muted or entirely absent. Other sites were either not in operation at
the right time (e.g ., Stenungsund, Sweden; Tema, Ghana; and
Cendering, Malaysia). Candidate tide gauge predictions and observations
are shown in Fig. S3. A more complete characterization of sea level
behavior, whether through using a variety of ocean reanalysis models
(Chepurin et al ., 2014) or more sophisticated modeling techniques
(Piecuch et al ., 2017), may resolve an impoundment signal in tide
gauge data sets.