Inputs

Subtask Description:
Identify inputs and useful variables, assess relevance, and assemble metadata.

Action points of the implementation:

Identify conservative imports and information inputs, such as river discharge or meteorological data, which will not be calculated within the model but provided as tables of data or simple functions (such as a sine wave for solar irradiance).
Identify any removals, losses, or exports, which will be dealt with in the same way; for examples: animal mortality due to a hunting quota (table of monthly kills); fixed rents or taxes.
Identify inputs that are the subjects of scenarios, such as monthly number of tourists, for which there might be several sets of data.
Identify where these inputs connect to the cause-&-effect chains in the Virtual System and decide whether they are conservative quantities, directly adding to or subtracting from model state variables, or information that acts indirectly through controls on rates.
Identify variables that can will probably be used for testing or calibrating the sub-model or functional unit; these might be state variables (e.g., salinity, chlorophyll concentration, cash value of capital equipment), fluxes (e.g. primary production, income from sale of mussels), or `indicators' as agreed with stakeholders.
Assess their relevance (i.e. the priority that should be assigned to them in acquisition of data).
Decide whether your tests will involve simulation of specific events (e.g. for the year 2009) or of characteristic patterns (e.g. for generalized seasonal cycle); this may be decided by relevance and data availability for forcing and testing.
Assemble information about these inputs including descriptions, units, main effects within the (virtual) system, relevance/priority, data source (details of person, institution, published work, web-page, etc.).

Result: a table of the input metadata and functions necessary for the simulation analysis.

Area:
Barcelona Coast, Spain

Policy Issue:
Investigation of the effects of changes in water quality on the aesthetic & recreational aspects of the beaches

Human Activities:
Large scale urban & industrial activity, tourism.

General Information:
The quality of the water in the various beaches is affected significantly during heavy storms. Wastewater treatment plants are unable to deal with the sudden increase of inflow and the capacity of storm collectors is often insufficient to temporarily store this water for later treatment. This results in large quantities of untreated wastewater being released into the coast, causing bacteria concentration to exceed safety levels thus obliging the beach authorities to temporarily prohibit bathing or just causing aesthetic degradation that prohibits beach users from bathing. Reduced use of the coastal water influences the beach users decision whether to stay at the beach or to leave, thus affecting the revenue received by the local businesses and being an important stakeholder concern.

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

Comments:
This is a well organised example of an input data table, regarding the social system of Barcelona coast. It incorporates the broad name of the inputs, the part of the system that refers to (here: camera model, beach users preference, etc.), identification of whether it is internal or external to the system, natural or human, the type of data it will represent in the model (parameter, boundary condition, forcing function, initial, value), the units, the time period for which time-series are available, the time step in which the data are available, possible conversion, the source that provided them, the level of reference to the model, the feasibility of acquiring them, and the purpose in the model (input, simulation, calibration, validation, proxy). Additionally here, two more fields are added: “Name in Extend” and “Extend blocks number”. Although the choice of the modelling software is a matter between the scientific team and the modellers, similar fields, that provide details for the use of the inputs in the model, are useful because a) they provide transparency to the model and b) they promote reusability as it is easier for the first time user to go through the model and identify which inputs are used for what purpose.

Contact: Ben Tomlinson, tomlinson@icm.csic.es .