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        Study Sites


These are the EcoManage study sites (follow the link for a detailed description of each site):

Santos Estuary - Brazil
Bahía Blanca Estuary - Argentina
Aysén Fjord - Chile
 

A brief description of the sites is presented bellow, along with a general description of the baseline DPSIR methodology used in their study and the adopted modeling tools.



 Brief description

EcoManage project aims to push the capacity of assisting managers to join knowledge horizontally from ecological and socio-economic disciplines. The three key aspects of EcoManage are (1) the consideration that a coastal zone depends on local pressures, but also on pressures originated in the drainage basin, transported mostly by rivers and by groundwater, (2) that socio-economic activities are the driving forces of those pressures and that their impacts on the ecosystem have feedback on socio-economics and (3) the impacts depend on physical characteristics of the ecosystem that together with the loads determine its ecological state.

Three coastal zones showing conflicting interests between urban, industrial and agricultural pressures and environmental maintenance have been selected for developing the system. The selected areas are: Aysén Fjord in Chile, Bahía Blanca estuary in Argentina and Santos estuary in Brazil.


Location of Ecomanage Study sites

Relationships between the origins and consequences of environmental problems will be described using a Driving forces, Pressures, States, Impacts and Responses (DPSIR) framework and indexes will be used to assess links between DPSIR elements. Drainage Basin has an important role in the application of the DPSIR framework.

DPSIR methodology
 

The DPSIR (Driver-Pressure-State-Impact-Responses) methodology is an effective tool for establishing cause-effects relationships in the use and exploitation of natural resources and its status. It has the ability to link large-scale human drivers of change with management responses (e.g., sewage treatment, management policies, etc.) to their impacts on the systems. 


The DPSIR methodology pathway of addressing the human-ecosystem interaction.

This approach has the advantage of integrating socio-economic aspects with ecological impacts, addressing not just the consequences of human activities on the system, but also its feedback.

Modelling tools



MOHID model (http://www.mohid.com)

All estuarine modeling and part of the watershed modeling is being done with the MOHID model. This model has been successfully implemented in the past to several study sites and used as a modeling tool in a number of similar research projects

Starting in 1985 with a 2D hydrodynamic semi-implict model with finite differences, the MOHID system has been developed throughout the years by a team of researchers and students to become a 3D hydrodynamic model with a finite volume discretization.

In time, the simulated physical processes have increased dramatically, and as a direct result of this progress, the scope of MOHID applications has become wider, both in detail and in scale (from estuaries to ocean basins). Among several possible examples of MOHID use as a numerical tool in the study of marine systems there is the study of internal tides and of different aspects of the dynamics of estuaries, from a general circulation 3D modelling to more specific physical processes like mixing.

Coastal and oceanic-scale simulations have also been studied. Just to name a few, the slope current along the Western European Margin, the circulation off the Iberian coast and in a broader scale, the circulation in the European ocean margin. The wide spectrum of applications reveals MOHID versatility and utility, and the gain in experience has contributed to test and improve it.

MOHID code, developed in FORTRAN 95 programming language, is adapted around the concept of object-oriented programming. To achieve versatility, MOHID has been written in a modular way, allowing an easy inclusion of new biogeochemical models. The first attempt to incorporate a water quality module in the MOHID system took place in 1995 with the coupling of the hydrodynamic model with an Eulerian transport model to simulate nitrogen and phosphorus cycles and primary production in Tagus estuary, Portugal. The emergence of new challenges in model simulations allied with demanding problems to study has led to the awareness that the water quality module had to become 0D, enabling its use independently of the adopted transport model dimension and referential (1D, 2D or 3D). This philosophy in the model structure means that any adopted or developed model can address all the biological or chemical processes without any dependence on the hydrodynamic processes. For its versatility, the actual version of MOHID retains this philosophy.

In the last years the MOHID system have incorporated in its code three basic water quality models, each one with its own level of detail and best suited to specific aquatic systems.

          (1) model WaterQuality, initially developed using the US Environmental Protection Agency model. Despite successful improvements made in this code, the baseline philosophy has been rather untouched when it comes to nutrient cycles and biological/chemical processes. This model is best suited to applications in estuaries and coastal systems.

          (2) CE-QUAL-W2 River Basin Model developed by the US Army Corps of Engineers. It is characterized by a detailed parameterization for both biological and chemical processes and it has been developed to simulate freshwater systems like rivers, branches, lakes, dams and reservoirs.

          (3) LIFE model, a detailed biogeochemistry pelagic model based on the ERSEM model. The model has a decoupled carbon-nutrients dynamics with an explicit parameterization of carbon, nitrogen, phosphorus and silica cycles. It considers a functional group approach with several groups of producers, consumers and decomposers. All living and organic matter compartments of the model have variable stoichiometry, and the model also accounts for the synthesis of chlorophyll allowing a temporal and spatial variation of C:Chla ratios in producers populations.
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