Model-driven optimization of coastal sea observatories through data assimilation in a finite element hydrodynamic model (SHYFEM v. 7_5_65)
<p>Monitoring networks aims at capturing the spatial and temporal variability of one or several environmental variables in a specific environment. The optimal placement of sensors in an ocean or coastal observatory should maximize the amount of collected information and minimize the developmen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-02-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/14/645/2021/gmd-14-645-2021.pdf |
| Summary: | <p>Monitoring networks aims at capturing the spatial and temporal variability of
one or several environmental variables in a specific environment. The optimal
placement of sensors in an ocean or coastal observatory should maximize the
amount of collected information and minimize the development and operational
costs for the whole monitoring network. In this study, the problem of the design
and optimization of ocean monitoring networks is tackled throughout the
implementation of data assimilation techniques in the Shallow water HYdrodynamic
Finite Element Model (SHYFEM). Two data assimilation methods – nudging and
ensemble square root filter – have been applied and tested in the Lagoon of
Venice (Italy), where an extensive water level monitoring network exists. A
total of 29 tide gauge stations were available, and the assimilation of the
observations results in an improvement of the performance of the SHYFEM model, which went from an initial root mean square error (RMSE) on the water level of
5.8 <span class="inline-formula">cm</span> to a final value of about 2.1 and 3.2 <span class="inline-formula">cm</span> for each of the two data assimilation
methods. In the monitoring network optimization procedure, by
excluding just one tide gauge at a time and always the station that contributes
less to the improvement of the RMSE, a minimum number of tide gauges can be
found that still allow for a successful description of the water level
variability. Both data assimilation methods allow identifying the number of
stations and their distribution that correctly represent the state variable in
the investigated system. However, the more advanced ensemble square root filter
has the benefit of keeping a physically and mass-conservative solution of the
governing equations, which results in a better reproduction of the hydrodynamics
over the whole system. In the case of the Lagoon of Venice, we found that, with
the help of a process-based and observation-driven numerical model, two-thirds
of the monitoring network can be dismissed. In this way, if some of the stations
must be decommissioned due to a lack of funding, an a priori choice can be made,
and the importance of a single monitoring site can be evaluated. The developed
procedure may also be applied to the continuous monitoring of other ocean
variables, like sea temperature and salinity.</p> |
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| ISSN: | 1991-959X 1991-9603 |