**3.1 Hydrodynamic modelling**

Hydrodynamic modelling results allowed to evaluate the water level and magnitude of currents velocity in both arms during tidal ebbing and flooding situations, and to assess the influence of tidal and freshwater inflows regimes on its variability.

For dry weather conditions, the higher velocity values were obtained in the southern arm, near Gala Bridge, reaching 0.35 (neap tide, scenario H3) to 0.70 m.s-1 (spring tide, scenario H2) while in the northern arm these maximum values (which occur in the section N4) are lower, reaching 0.33 (neap tide) to 0.60 m.s-1 (spring tide), at 1km upstream the Figueira da Foz bridge. These results are depicted on Figure 16 mapping the effect of extreme tidal regimes on maximum currents velocity magnitude during the flooding period and considering dry-weather conditions.

In the southern arm, the flooding time, which decreases at the inner zones, is much shorter than the ebbing time, due to shallow waters and to large intertidal mudflats areas. This

constituent decay rates (Table 4) in order to assess and confirm the highest eutrophication vulnerability of the inner areas of the Mondego estuary south arm, due to the expected

**.s-1) TIDE LOAD DECAY RATE** 

**point** 

**diffuse** 

**1** 

**0** 

**0** 

**(day-1) Mondego Pranto** 

**medium** 

**medium** 

**RT 2 spring 0** 

**RT 5 10** 

**RT 11 1** 

**RT 13 1 RT 14 0,5** 

In this work only a few examples of the very large amount of MONDEST model results obtained for those different simulated scenarios can be presented. The main aim of the following item will be to highlight the evident influence of hydrodynamics (tidal regime and freshwater inflows) on estuarine residence time spatial variation, which can play a

Hydrodynamic modelling results allowed to evaluate the water level and magnitude of currents velocity in both arms during tidal ebbing and flooding situations, and to assess the

For dry weather conditions, the higher velocity values were obtained in the southern arm, near Gala Bridge, reaching 0.35 (neap tide, scenario H3) to 0.70 m.s-1 (spring tide, scenario H2) while in the northern arm these maximum values (which occur in the section N4) are lower, reaching 0.33 (neap tide) to 0.60 m.s-1 (spring tide), at 1km upstream the Figueira da Foz bridge. These results are depicted on Figure 16 mapping the effect of extreme tidal regimes on maximum currents velocity magnitude during the flooding period and

In the southern arm, the flooding time, which decreases at the inner zones, is much shorter than the ebbing time, due to shallow waters and to large intertidal mudflats areas. This

**RIVER FLOW (m<sup>3</sup>**

**RT 3 neap** 

**0** 

**0** 

Table 4. Simulated management scenarios for estuarine residence time calculation

**15** 

**RT 6 15** 

**15** 

**75** 

special role in estuarine eutrophication vulnerability assessment.

influence of tidal and freshwater inflows regimes on its variability.

**RT 7 1** 

**RT 8 75 RT 9 340** 

occurrence of higher RT values.

**SCENARIO**

**RT 1** 

**RT 4** 

**RT 10** 

**RT12** 

**3. Results and discussion 3.1 Hydrodynamic modelling** 

considering dry-weather conditions.

asymmetry is influenced by the tidal regime and has a fast increase into the inner areas of this arm reaching 2.5 hours: 5 hours for flooding and 7.5 hours for ebbing time. In the northern arm, between the sections N1 and N4, there is a little delay of fifteen minutes in the high tide occurrence and a bigger delay in ebb tide (about two hours).

Fig. 16. Effect of tidal regime on ebbing maximum values of currents velocity magnitude (scenarios H2 and H3)

Figure 17(a) shows an example of the tidal regime effect in the mean velocity magnitude (MVM) variation, at section N4 (where maximum values of this parameter occurred). It should be noted that for a neap tide, the VMM during the tidal flooding period is almost an half of the value reached for a typical sprig tide.

For upstream estuarine sections, water surface levels in high tide are similar, but, in ebb tide, water surface level increases in the inner section due to the effect of the estuarine bathimetry (elevation of bottom level) (Fig. 17b).

Fig. 17. (a) Effect of tidal regime on ebbing maximum values of currents velocity magnitude (section N4); (b) Surface water level variation along the estuarine system (N1, N7, N8)

#### **3.2 Model calibration and validation**

The velocities and water levels field data obtained from the sampling programme were used for model calibration and validation. Figure 18 shows an example of a specific procedure performed in section S1 (Gala bridge/Lota) for the parameter "surface water level (SWL)". Two different sensitivity analyses were carried out to define the accurate values to adopt for the main calibration parameters used in both (hydrodynamic and water transport) modules of *Mondest* model: one for the Manning bottom friction coefficient (n) and horizontal Eddy

A Hydroinformatic Tool for Sustainable Estuarine Management 21

prism for the both estuary arms (north and south) based on this procedure calculation for each control sections along the Mondego estuary, considering the flooding period of the

The mean tidal flow estimation in each estuarine section can be performed using the correspondents' tidal prism values and the real duration of the ebbing and flood events. The mean tidal flow values obtained for several hydrodynamic scenarios in the sections N0 and

flooding ebbing flooding ebbing flooding ebbing

) Duration (h) Mean tidal flow (m<sup>3</sup>

.s-1)

H 1 9.178 9.894 6.25 6.25 408 440 H 2 12.02 13.063 6.25 6.25 534 581 H 3 5.818 5.692 6.25 6.25 259 253 H 7 14.792 15.386 6,25 6,25 657 684 H 10 11.387 12.089 6.00 6.50 527 517 H 1 2.334 2.341 5.50 7.00 118 93 H 2 3.265 3.276 5.50 7.00 165 130 H 3 1.269 1.266 6.00 6.50 59 54 H 7 3.449 345 5.50 7.00 174 137 H 10 3.325 3.337 5.50 7.00 168 132

The analysis of the salinity distribution in the estuary had, as a primary goal, the identification of the areas that, throughout the tidal cycle, present salinity values within the range of 17 to 22‰, defined by Martins et al. (2001) as the most favourable for algal growth

The Pranto river inflow in estuary southern arm has shown a strong influence on salinity distribution decreasing drastically its values to a range far from the one defined as the most favourable for this estuarine eutrophication process. Figure 20 shows the opening Alvo sluices effect on southern arm salinity gradients caused by Pranto river flow discharge of 30 m3.s-1, during the ending of ebbing and the beginning of tidal flooding periods (scenarios

Fig. 20. Effect of Pranto river flow discharge on estuarine salinity distribution (high tide)

**SLUICES OPEN SLUICES CLOSED** 

scenario H1.

S1 are summarized in Table 5.

Section Scenario Tidal prism (hm<sup>3</sup>

Table 5. Synthesis of mean tidal flow calculation (sections N0 and S1)

**3.4 Hydrodynamic influence on estuarine salinity distribution** 

**S1** 

in this specific aquatic ecosystem.

SL 3 and SL1) (Duarte & Vieira, 2009a).

**N0** 

viscosity coefficient (Eh); and the other for the horizontal dispersion coefficient (Dh). For each calibration parameter, three different values were tested comparing field data with the corresponding model results.

Fig. 18. Hydrodynamic module calibration (spring tide) and validation (neap tide) (station S1)

For the simulated management scenarios and based on calculated correlation coefficients, the best agreements were obtained considering the following parameters values: the ordered pair (n=0.02 m-1/3.s; Eh= 20 m2.s-1), for the hydrodynamic module; and Dh= 30 m2.s-1, for the water transport module.

A more detailed description of these sensitivity analyses (scenarios, results and discussion) can be found in Duarte (2005).

#### **3.3 Tidal prism and flow estimation**

In this work a new approach was developed for tidal flow estimation, based on the previous tidal prism calculation using mathematical modelling. The adopted approach allows to consider the temporal variation of the cross section area during the tidal cycle and, mainly, the real asymmetry of tidal flooding and ebbing periods verified in the inner estuarine areas. Tidal prisms were calculated as the difference between the water volume in a specific high tide and the correspondent previous ebb tide, which can be automatically given by the query tools of the post-processor module (SMS). Figure 19 shows the spatial variation of tidal

Fig. 19. Tidal prism spatial variation in both estuary arms (flooding of scenario H1)

viscosity coefficient (Eh); and the other for the horizontal dispersion coefficient (Dh). For each calibration parameter, three different values were tested comparing field data with the

Fig. 18. Hydrodynamic module calibration (spring tide) and validation (neap tide)

For the simulated management scenarios and based on calculated correlation coefficients, the best agreements were obtained considering the following parameters values: the ordered pair (n=0.02 m-1/3.s; Eh= 20 m2.s-1), for the hydrodynamic module; and Dh= 30 m2.s-1,

A more detailed description of these sensitivity analyses (scenarios, results and discussion)

In this work a new approach was developed for tidal flow estimation, based on the previous tidal prism calculation using mathematical modelling. The adopted approach allows to consider the temporal variation of the cross section area during the tidal cycle and, mainly, the real asymmetry of tidal flooding and ebbing periods verified in the inner estuarine areas. Tidal prisms were calculated as the difference between the water volume in a specific high tide and the correspondent previous ebb tide, which can be automatically given by the query tools of the post-processor module (SMS). Figure 19 shows the spatial variation of tidal

Fig. 19. Tidal prism spatial variation in both estuary arms (flooding of scenario H1)

corresponding model results.

for the water transport module.

can be found in Duarte (2005).

**3.3 Tidal prism and flow estimation** 

(station S1)

prism for the both estuary arms (north and south) based on this procedure calculation for each control sections along the Mondego estuary, considering the flooding period of the scenario H1.

The mean tidal flow estimation in each estuarine section can be performed using the correspondents' tidal prism values and the real duration of the ebbing and flood events. The mean tidal flow values obtained for several hydrodynamic scenarios in the sections N0 and S1 are summarized in Table 5.


Table 5. Synthesis of mean tidal flow calculation (sections N0 and S1)
