Acquire the data

Subtask Description:
Acquire, analyse and use the Input data.

Action points of the implementation:

Acquire the data documented above, in order of priority.
Analyse the data statistically, in order to understand variability.
Re-evaluate the relevance level of your inputs.
If data unavailable, decide on a suitable (temporary or permanent) substitute, which can include proxies, results from other models, or `expert's best guess'.
Convert the data to the units used in the model, etc, and, depending on software, insert in appropriate model-linked database (or Extend block)
Add appropriate documentation to the metadata table and where relevant copy into the model data-base.

Result: Refined Input Table and documented sets of data in a form usable to the simulation.

Area:
Thau Lagoon, France

Policy Issue:
Managing the microbiological contamination.

Human Activities:
Urban activities, agriculture, shellfish farming, recreational activities.

General Information:
The natural marine heritage of the area is linked to high productivity and biological diversity which involve water management issues, as the variety of economic activities in the lagoon, in terms of exploitation, the lagoon economic exploitation often creates antagonism and conflicts. Urban and land-use pressures are high and increasing while agriculture is in decline and the phenomenon of agri-urban areas is spreading, causing increasing microbiological contamination effects that have impact to the shellfish farming activity. The main stakeholder concerns are connected to the management of water resources in relation to the population growth and the viability of the traditional activities (shellfish farming and recreational activities).

Example of Implementation (Click on tumbnail for full version):

Comments:
It is very difficult to provide an example for most of the action points of this subtask. At the same time it is very important to highlight the importance of data acquisition for the successful formulation of the model. Acquiring all the necessary data on time, identifying what is missing and deciding how the gaps or deficiencies are going to be dealt with is a process in which sufficient time should be invested. The same applies to the statistical analysis of the data, the conversion of the data into suitable units and the creation of the database that will incorporate the necessary documentation for the inputs. Failure to complete this subtask can lead to important delays and mistakes during the actual model formulation. Here, as an “example of implementation”, part of a well structured database is provided, illustrating part of the hydrological data for the Thau lagoon area.

Contact: Johanna Balle-Beganton, Johanna.Beganton@ifremer.fr .