# Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area

^{1}

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

_{2}fluxes [45]. Concerning the sub-system coastal area, studies were directed to analyse the effects of the Tagus estuarine plume [45,46,47].

## 2. Materials and Methods

#### 2.1. Study Area

^{9}m

^{3}and a surface area of approximately 320 km

^{2}[7,56]. This estuary is composed of a central body 30 km long and 10 km wide, connected to the Atlantic Ocean through a channel 12 km long and 2 km wide [57] forming a NE-SW oriented talweg [58]. Its width varies from 400 m at its head to 15 km in the central bay, with a depth range of 0 to 20 m (average depth of 5.1 m) [59], and presents extensive intertidal zones that occupy 40% of the estuary [60]. The coastal zone adjacent to the open ocean of the study area comprises 70 km of continental shelf that extends along the 39° N parallel, limited by the Cape Raso in the north and the Cape Espichel in the south, with the shelfbreak at 140 m depth [61]. It is a narrow platform that extends, on average, until 180 m depth and with a width ranging from 3 km (near the Cape Espichel) to 30 km [61]. This area is dominated by two important geomorphological features, the Cascais and Lisbon submarine canyons (the Cascais canyon is located NW of the Lisbon canyon and separated from the latter by the 1000 m high ridge of the Afonso Albuquerque Plateau [62]).

^{3}s

^{−1}, with monthly averages ranging from 6 to 2090 m

^{3}s

^{−1}(2006–2018; National Water Resources Information System, SNIRH), and although being usually a well-mixed estuary, stratification may occur at high flow rates [64]. Flow is related to the amplitude of the tide which is also responsible for the mixture processes within the estuary. Indeed, the primary driver of the circulation in the Tagus estuary are tides, but other factors also influence it, such as river flow, atmospheric pressure, and the wind [65]. In addition, the estuary is strongly ebb-dominated due to the large extension of tidal flats [59].

^{−1}, 8.5% of occurrence, to 14 m s

^{−1}, 7.5% of occurrence), whilst in summer winds from the north or from northwest prevail (ranging from 1 m s

^{−1}, 5% of occurrence, to 15 m s

^{−1}, 20% of occurrence) [47,67].

#### 2.2. Model

^{2}s

^{−1}was used.

^{3}s

^{−1}for Sorraia river and between 1 and 9 m

^{3}s

^{−1}for Trancão river. Monthly climatological values of freshwater temperature and salinity for the three rivers and for water discharges from 14 wastewater treatment plants (WWTPs) were also imposed. Model configurations for the TagusROFI are summarized in Table 1.

#### 2.3. Available Observations Data

#### 2.3.1. Water Level

#### 2.3.2. Seawater Temperature and Salinity

#### 2.3.3. Current Velocity

#### 2.3.4. Seawater Temperature Based on Satellite Images

#### 2.4. Statistics

## 3. Results and Discussion

#### 3.1. Water Level–Time Series Data

#### 3.2. Seawater Temperature and Salinity–Time Series Data

^{3}s

^{−1}, ranging from 44 to 8711 m

^{3}s

^{−1}(Figure 5). From the analyses of Figure 5, it can be seen that the observed and simulated results present a similar pattern for both variables. Daily fluctuations observed in SST and salinity were related to different river flows during flood and ebb periods. The high Pearson correlations coefficients obtained for SST (r = 0.91) and salinity (r = 0.86) reveal the good agreement between observations and simulated results (Figure 5; Table 3).

^{6}m

^{3}, the river flow is only relevant to the non-linear mixing processes during high river flow events. At the end of the comparison period, an extreme event occurred where the mean daily river flow over three consecutive days attained 7500 m

^{3}s

^{−1}which represents 25% of the volume of the tidal prism. This has led to the abrupt decrease of salinity (Figure 5).

#### 3.3. Currents–ADCP Analysis

^{−1}(ranging from 0.1 to 9.2 m s

^{−1}; data recorded in MS, Figure 1), and the mean flow rate of the river was 104 m

^{3}s

^{−1}(varying between 27 and 451 m

^{3}s

^{−1}; data recorded in HS, Figure 1). Figure 6 compares raw data from ADCP with model results. There is a good qualitative agreement between the present model and ADCP measurements since predictions follow the same pattern of the observation data for current intensity and direction, as well as for both components of velocity (u and v). Periodical oscillations on the direction of the current due to tide are also perceptible in Figure 6.

#### 3.4. Seawater Temperature–Validation with Satellite

^{3}s

^{−1}km

^{−1}) compared with the following years, which presented very similar annual average values (≈300 m

^{3}s

^{−1}km

^{−1}) (Figure 9). The surface seawater temperature drop in the upwelling region can be detected by remote sensing since the upwelled water is characterized by lower temperature comparing to the surrounding seawater. Although satellite products and MOHID results allow identifying the part of the coastal area where the upwelling process occurred, this phenomenon is more evident in ODYSEEA and MOHID, where a dark blue strip parallel to the N-S shoreline is clearly visible, which corresponds to upwelled water (Figure 8). Furthermore, the visual analysis of this figure also allows concluding that upwelling was less intense in 2014 than in the subsequent years analysed.

## 4. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

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**Figure 1.**Map of the TagusROFI area showing the sites where environmental parameters were taken. HS–Hydrologic Station; LTG–Lisbon Tide Gauge; CTG–Cascais Tide Gauge; CTD–Conductivity, Temperature, and Depth probe; ADCP–Acoustic Doppler Current Profiler; MS–Meteorological Station.

**Figure 2.**TagusROFI domain bathymetry. Colours represent the depth in meters (m) and land in grey. The colour scale is logarithmic.

**Figure 3.**

**Left**: Comparison of the observed (green dots) and simulated (blue dots) water levels at CTG (

**top**) and LTG (

**bottom**) stations. Difference between Observed and Modelled data.

**Right**: Performance of the MOHID forecast for the TagusROFI. Model comparison vs tide gauge for CTG (

**top**) and LTG (

**bottom**) stations.

**Figure 4.**Tidal wave lag between CTG (coastal area) and LTG (in the Tagus estuary) stations. Green dots and crosses represent observed data whereas blue lines represent the modelling results.

**Figure 5.**

**Left**: Comparison of the observed (green dots) and simulated (blue dots) surface seawater temperature (

**top**) and salinity (

**bottom**).

**Right**: Performance of the MOHID Water results for the TagusROFI. Model vs CTD for surface seawater temperature (

**top**) and salinity (

**bottom**).

**Figure 6.**Profiles comparison of the velocity module, velocity components u and v and directions between MOHID Water results (

**top**) and ADCP data (

**down**) in function of depth and time; and wind time-series. Data obtained off Cascais between 2 and 17 July 2009. For both observations and modelling results, the output was of 15 min.

**Figure 7.**Profiles comparison between MOHID Water results (

**top**) and ADCP data (

**bottom**) for the velocity components u and v in function of depth. Data obtained off Cascais between 2 and 17 July 2009. Grey lines represent velocity at each instant of time measured or predicted, and blue and green lines represent the average trend.

**Figure 8.**Interannual comparison of surface seawater temperature between MOHID and Satellite L4 gridded products (OSTIA-5km, ODYSSEA-2 km; and MUR 1 km) for the period 2014–2016.

**Figure 10.**Spatial distribution of the differences between MOHID and the three satellite products (OSTIA, ODYSSEA, and MUR) for the Pearson correlation coefficient (r), BIAS and RMSE, between 2014–2016.

Settings | Level 1 –WestIberia | Level2–PCOMS | Level 3-TagusROFI |
---|---|---|---|

Model characterization | 2D-Barotropic | 3D–Baroclinic | 3D-Baroclinic |

Grid corners | 33.50° N–49.90° N 1.00° W–13.50° W | 34.38° N–45.00° N 12.60° W–5.50° W | 38.16° N–39.21° N 10.02° W–8.90° W |

Cells dimension | 208 × 156 | 177 × 125 | 121 × 146 |

Bathymetry | EMODnet^{a}Hydrography portal | EMODnet^{a}Hydrography portal | Delaunay triangulation with IH Data and GEBCO |

Horizontal Grid | Regular: (≈5.7 km) | Regular: (≈5.7 km) | Irregular: 200 m to 2 km |

Vertical Grid | 1 layer | 7 Sigma Layer (0 m–8.68 m) 43 Cartesian layers | 7 Sigma Layer (0 m–8.68 m) 43 Cartesian layers |

Δt | 60 seconds | 60 seconds | 6 seconds |

Tides | FES2004^{b} & FES2012^{c} | From Level1 | From Level2 |

OBC Water | From MercatorOcéan PSY2V4 (Releases 1–4)^{d} | From Level2 | |

Assimilation | Flow relaxation scheme of 10 cells with a time decay of 1 week at the open boundary and 0 inside the domain | Flow relaxation scheme of 10 cells with a time decay of 1 week at the open boundary and 0 inside the domain | |

OBC Atmosphere | MM5^{e}(9 km) | MM5^{e}(9 km) | WRF^{f}(3 km) |

Discharges | No | No | Tagus (hourly), Sorraia, Trancão and WWTP (monthly) |

Turbulence | GOTM^{g} | GOTM^{g} | |

Bottom | Rugosity of 0.0025 m^{2} s^{−1} | Rugosity of 0. 0025 m^{2} s^{−1} | Rugosity of 0. 0025 m^{2} s^{−1} |

**Table 2.**Water level. Data summary and results of statistics used to assess the level of agreement between measured data and modelling results. n—number of observations; r—correlation coefficient; BIAS—Average bias; RMSE—Root mean square error.

Tide Gauge | Average (min–max) MOHID | Average (min-max) Tide Gauge | n | Pearson (r) | BIAS | RMSE |
---|---|---|---|---|---|---|

CTG | 2.02 (0.39–3.73) | 2.02 (0.31–3.69) | 4445 | 0.995 | 0.003 | 0.17 |

LTG | 2.01 (0.32–3.70) | 2.00 (0-17–3.77) | 4341 | 0.994 | 0.005 | 0.45 |

**Table 3.**Surface seawater temperature and salinity. Data summary and results of statistics used to assess the level of agreement between measured data and modelling results. n—number of observations; r—correlation coefficient; BIAS—Average bias; RMSE—Root mean square error.

Parameter | Average (min-max) MOHID | Average (min-max) CTD | n | Pearson (r) | BIAS | RMSE |
---|---|---|---|---|---|---|

Temperature | 14.2 (11.4–17.4) | 14.3 (11.9–17.3) | 21436 | 0.91 | 0.1 | 0.4 |

Salinity | 28.0 (2.1–35.6) | 27.4 (1.3–35.3) | 21436 | 0.86 | –0.9 | 2.9 |

**Table 4.**Current velocity and direction. Data summary and results of statistics used to assess the level of agreement between measured data and modelling results. n—number of observations; r—correlation coefficient; BIAS—Average bias; RMSE—Root mean square error.

Average (min-max) MOHID | Average (min-max) ADCP | n | Pearson (r) | BIAS | RMSE | |
---|---|---|---|---|---|---|

Depth (2.5 m–15 m) | ||||||

Vel. Modulus (m s^{−1}) | 0.16 (0.0087–0.41) | 0.17 (0.0054–0.43) | 1440 | 0.68 | 0.014 | 0.10 |

Direction (rad) | 151 (0.2–360) | 134 (2.4–359) | 0.63 | –9.8 | 45 | |

Velocity u (m s^{−1}) | 0.097 (−0.069–0.30) | 0.099 (−0.14–0.34) | 0.63 | 0.0019 | 0.092 | |

Velocity v (m s^{−1}) | −0.089 (−0.38–0.11) | −0.11 (−0.43–0.11) | 0.73 | −0.025 | 0.11 | |

Depth (15 m–30 m) | ||||||

Vel. Modulus (m s^{−1}) | 0.10 (0.0039–0.30) | 0.12 (0.0025–0.34) | 1440 | 0.62 | 0.018 | 0.065 |

Direction (rad) | 151 (0.2–360) | 164 (2–358) | 0.66 | –14 | 50 | |

Velocity u (m s^{−1}) | 0.084 (−0.046–0.30) | 0.092 (−0.086–0.29) | 0.63 | 0.0082 | 0.066 | |

Velocity v (m s^{−1}) | −0.052 (−0.15–0.098) | −0.035 (−0.26–0.13) | 0.71 | –0.029 | 0.071 |

**Table 5.**Surface seawater temperature from satellite data. Data summary and results of statistics used to assess the level of agreement between remote sensing data and modelling results. n–number of observations; r–correlation coefficient; BIAS–Average bias; RMSE–Root mean square error.

Year | Satellite | Average MOHID | Average L4 products | n (per day) | Pearson (r) | BIAS | RMSE |
---|---|---|---|---|---|---|---|

2014 | OSTIA | 17.11 | 17.18 | 355 | 0.937 | −0.064 | 0.846 |

ODYSSEA | 17.11 | 17.17 | 2095 | 0.948 | −0.059 | 0.773 | |

MUR | 17.12 | 17.20 | 8356 | 0.934 | −0.078 | 0.894 | |

2015 | OSTIA | 16.50 | 16.91 | 255 | 0.919 | −0.407 | 0.946 |

ODYSSEA | 16.51 | 16.83 | 2095 | 0.924 | −0.320 | 0.889 | |

MUR | 16.56 | 16.87 | 8356 | 0.912 | −0.359 | 0.992 | |

2016 | OSTIA | 16.74 | 16.19 | 355 | 0.930 | −0.176 | 0.866 |

ODYSSEA | 16.71 | 16.83 | 2095 | 0.864 | −0.127 | 0.978 | |

MUR | 16.73 | 16.83 | 8356 | 0.916 | −0.102 | 0.914 |

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

de Pablo, H.; Sobrinho, J.; Garcia, M.; Campuzano, F.; Juliano, M.; Neves, R. Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area. *Water* **2019**, *11*, 1713.
https://doi.org/10.3390/w11081713

**AMA Style**

de Pablo H, Sobrinho J, Garcia M, Campuzano F, Juliano M, Neves R. Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area. *Water*. 2019; 11(8):1713.
https://doi.org/10.3390/w11081713

**Chicago/Turabian Style**

de Pablo, Hilda, João Sobrinho, Mariangel Garcia, Francisco Campuzano, Manuela Juliano, and Ramiro Neves. 2019. "Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area" *Water* 11, no. 8: 1713.
https://doi.org/10.3390/w11081713