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 thumbnail for full version
Click on thumbnail for full version
Comments:
This is a well organised example of an input data table, relating to the natural system of Barcelona coast. It incorporates the type of input, the part of the system that it refers to (atmospheric, marine, etc.), whether it is internal or external to the system, natural or human, the type of data it will represent to the model (parameter, boundary condition, forcing function, initial value), the units, the time period for which time-series are available, the frequency for which the data are available, possible conversions of the data, the data source, the level of relevance to the model, the availability of the data and its purpose in the model (input, simulation, calibration, validation, proxy). Two more fields have been 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 on 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 .