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Skip to main content. Log In Sign Up. Rovisco Pais Lisboa Portugal www. No part f this book may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or by any dewcargar storage and retrieval system, without permission in writing from the Publisher.

Color version book www. Dias Alternative method to initialize Regional Ocean Models using geostropgic velocities: Piedra-Cueva Faecal pollution modelling as a management tool in coastal areas: Cho MOHID as a tool to evaluate the impact of water discharge from dams on the advection of estuarine fish larval stages P. Neves Modelling mussel growth in Tagus estuary: Descargxr Assessment of primary productivity and nutrients for a coastal lagoon in Southern Brazil L.

Fernandes An integration methodology to estimate water fluxes and constituents budgets in coastal areas: Neves The editors would like to thank the authors who contributed to this book for their enthusi- asm and willingness to share their own work and experience descafgar MOHID users.

The MOHID model is the result of a collaborative effort and cumulative development of more than 20 years of work, and, while it is impossible to acknowledge here all those involved, we dedicate the book to this vast team of technology experts and scientists.

The MOHID modelling system is an open source code with hundreds of active users worldwide, and we would like to express our gratitude to this wide descargat of users for their contribution to the continuous advance and descaegar of the model. Finally, our thanks go to the IST Press team for the professional advice and assistance throughout the editing process.

They must satisfy the Gauss theorem when applied eescargar a physical space delimited by open surfaces and must guarantee descargr when dealing with transformation processes that in environmental systems are mostly due to biological activity, involving energy fluxes in the form of mass transfer between consumers and producers. MOHID is an environment modelling system dealing with transport and with biogeoche- mical transformation processes in complex geometries.

It was developed to be used by researchers and by professionals and to be applicable to a large range of scales and physical conditions. Researchers require tools able to test hypotheses and compare op- tions. Professionals require efficiency for quick results production.

A wide range of scales requires the consideration of the corresponding transport processes and of interactions between descargsr. This chapter describes the MOHID architecture and engineering developed to satisfy the requirements derived from the range of user profiles, physical scales and biogeochemi- cal processes to be considered. The architecture designed permitted the integration of several models in the modelling system and the engineering descadgar simplified the de- velopment of the information tools necessary to manage field data and model results in complex systems.

Together with the HDF format personal computers permitted the use of small pieces of software not available in former mainframes that have strongly improved modellers productivity. Scientific developments carried up to the nineties in the framework of a set of Ph. D the- ses concerned with hydrodynamics [] and with eulerian ecological modelling [5] and M. These developments included 2D and 3D de- velopments, mesoscale and Boussinesq wave modelling and eulerian and lagrangian models.

These developments generated different models of difficult maintenance in a quick scientific and technological evolving context. The need to combine them generating a modular system where differences were handled in specific parts of the code was high. The new MOHID model should be able to deal with 2D and 3D simulations, to deal with Eu- lerian, Cartesian or Lagrangian vertical coordinates, to deal Eulerian or Lagrangian transport references and to use the same biogeochemical formulations independently of the number of spatial dimensions or space reference and should allow alternative formulations for every process in order to be flexible in terms of scientific developments.

Neves The finite-volume method already used by Martins [4] was adopted to make the spatial description independent of the vertical coordinate and of the number of vertical dimensions and all the transformations processes occurring inside the volume were programed using a 0D formulation in order to make them independent of the spatial reference, being the code sharable by the eulerian and the lagrangian formulations.

A fractional time step was used in order to split the resolution of processes using the most adequate temporal discretization or calculation sequence in each of decargar. This approach was necessary to decouple the resolution of the transport and transformation processes, but also to decouple the resolution of biogeochemical processes creating the independence need to aggregate developments carried out by different people. The resolution of evolution equations in their integral form simplified the design of the desired architecture.


This form requires the explicit consideration of fluxes across the sur- faces surrounding the integration volumes easing conservation during transport which is often violated in mathematical models when flux divergence is computed.

After accomplishment of the requirements described above a modular system to simu- late free surface flows was achieved in the early years of decade. MohidStudio2 was developed to simplify the imple- mentation of ncch model, assessment and processing of input data and the management of simulations, ncluding results visualizing and archiving. AquaSafe3 was designed to automate procedures including the production of web services to integrate results of different models and field data in order to adequate the products to corporate user needs.

Using the Gauss theorem, Equation 1 is transformed into the differential conservation equation: It was designed to automate procedures including the production of web services to integrate results of different models and data.

Neves Equation 2 states that the rate of change of a property in a point balances the divergence of the advection plus diffusion fluxes at that point plus the production minus the consumption rate per unit of volume. Manipulating Equation 2 one can write the conservation equation in a lagrangian reference where the time derivative states that the rate of change in an elementary volume of fluid balances diffusion across its boundaries plus sources minus sinks: In this case the surface could be deformed, but the total volume inside the surface would remain constant.

The calculation of these fluxes requires the knowledge of the velocity and diffusivity along the Control-Volume CV surface, which value depends on the scales resolved by the model. On the top of the water column is separated from the atmosphere by the air-water interface and the benthic layer separates the water column from the sediment at the bottom.

MOHID includes modules for the processes in the water column, in the sediments and in the interfaces and uses atmos- pheric information provided by meteorological models or data from meteorological stations to describe the atmosphere.

Air-water fluxes are the only variables owned by the air-water interface. They can be specified by the meteorological model or computed using air temperature, moisture, wind speed, cloud cover and solar radiation and coefficients provided by the user. Precipitation has to be specified by the user. On the contrary the benthic interface layer lying between the water column and the sediment computes fluxes but is also owner of state variables having negligible mobility filter feeders, microphytobenthos, decomposers, etc.

Properties in the water column exchange material among them using the water as a trans- port agent. The planktonic properties move at the water speed, but particulate material can 4 Random velocity associated to the Brownian movement generating molecular diffusion or to turbulent movement mix the initial fluid with surrounding fluid the surface has to have additional movement to surround the initial molecules, i.

Neves have their own velocity too. It is the case of sediments that have its own settling velocity or oil that moves vertically in the water column to reach its stability depth usually the surface or fish larvae and dinoflagellates that can have alternated upward and downward movements in the water column. Macroalgae and suspended filter feeders are also water column properties — although they do not move with the water — because they can exchange material with seve- ral layers in the water column macroalgae length can be long compared with water column height and thus with model vertical layer thickness.

The module Water-Properties manages the simulation in the water column. The module water properties also manages the calculation of state variables derived from others, as is the case of water density or light intensity. The water The water columncolumn is sepa-is rated from the atmosphere by the Air-Water interface and from the consolidated sediment by the Benthic interface.

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Neves Processes in the sediment have the same origin and structure as the processes occurring in the water column, but are much slower due to lower mobility of the dissolved material. Like in the water column properties can be dissolved and unlike in the water column most material is particulate. Because of the low water content and mobility exchanges between deposited sediment and water column are slow and sediment is mostly anoxic.

In regions with high settling rate accretion of sediments is usually the main mechanism to maintain organic matter content in the sediment. The Sediment-Properties module manages the transport of properties inside the sediments computing advection using the water movement associated to the consolidation process in absence of groundwater exfiltration and diffusion using bioturbation diffusivity and invokes modules in charge of computing reactions and exchange between dissolved and particulate phases.

Mate- rial transferred into the sediment acquires its critical stress for erosion and generates a flux of properties as a function of the concentration in the benthic layer.


Fluxes of dissolved ma- terial are computed using the concentration difference between water and sediment and an exchange coefficient function of the flow next to the bottom in the first layer. Salt marshes and tidal flats are a limit case of the representation shown in Figure 1.

In these areas the sickness of the water column is zero at low water periods, allowing these zones to exchange directly with the atmosphere. In fact, on land a water column is an exception, although it can occur during flood events or in ponds and in the sediment i. As a consequence, in normal condi- tions, on land surface runoff occurs only in rivers and generalised surface runoff occurring only during storm events. Figure 2 represents schematically the elements composing a catchment. The soil is the sediment equivalent in the aquatic environment.

The river network or ponds is the water column equivalent in aquatic environment and soil surface is similar to salt marches, the major difference being the inundation frequency and the fact that the sediment below land surface is usually unsaturated. Neves The correspondence between compartments in land and aquatic environments permits the use of the same data structure to describe them and consequently both models can share the software architecture.

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Mathematical models ncy to describe nature using discrete values computed in a grid. The consideration of the grid as a finite number of adjacent volumes to which the conservation Equation 1 is applied simplifies the respect of the mass conservation principle and permits the use of irregular grids as that shown in Figure 3.

MOHID has adopted the integral form of the equations, fluxes being computed over the faces of the finite volumes cells. Inside the volumes source and sink terms are computed based on the local values. Diffusive fluxes are computed at each cell face using concentration values on each side of the face and advection is computed using the water discharge across the cell face and a concentration estimated using a spatial interpolation in order to generate upstream, central differences, QUICK or TVD methods.

Diffusivity and water fluxes are computed by the hydrodynamic module over the face using a staggered grid approach where velocities are computed on the faces of the cells described on Figure 3. In the hydrodynamic module as in the hydrological module descarhar conservative approach is also considered for advection deescargar diffusion, meaning that velocities are also com- puted using finite volumes obtained by interpolation of the control volumes used for scalars. Vertical description of a catchment.

The surface gets rain and at surface we can have a river network in normal conditions and generalised surface runoff during rain events. It is also at surface that vegetation grows and in the soil one can have a non-saturated zone vadose zone on the top of a saturated zone.

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All these compartments can exchange water in two senses. Example of spatial descretization combining domains with different types of coordinates left and an example of a finite-volume right.

The curvilinear grid is adequate to compute flows in descargsr anisotropic systems e. It saves memory and increases the transversal resolution, but it requires simplifications for momentum fluxes calculation, to be computationally efficient.

On vertical direction the internal product involved on the calculation of fluxes is simple because the area of cell surfaces projected on a horizontal plane is constant and uniform for every vertical column.

Vertical water fluxes are computed considering the rate of change of the cell volume and incompressibility. The most suitable coordinate is the one that minimises ad- vective fluxes between adjacent cells. In fact advective fluxes in presence of Courant numbers very much different from unit are a major source of numerical diffusion. Vertical velocities desacrgar usually much smaller than deacargar velocities and consequently the corresponding Courant number can be much smaller than one.

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The consideration of a lagrangian grid where cell boundaries have some vertical movement minimises the vertical diffusion. Rigid rectangular coordinates are the simplest because, apart from the surface layer, they do not move in time. They are adequate to simulate horizontal flows where topography plays a minor role.

This is the case of the deep oceans. On the contrary the sigma coordinate varies between zero at the bottom and 1 at the surface and consequently the layer thickness varies according to water column depth which depends on the bathymetry and on the movement of the free surface. Sigma coordinates are the most adequate to simulate the flow in coastal shallow areas.

Both coordinates can be combined with the lagrangian coordinate option to minimize numerical diffusion associated to high frequency waves.