Difference between revisions of "Modelling process overview"

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This page is intended to give an overview of different aspects of the modelling process, particularly in the context of how they interact with model structure decisions and modelling software tool selection. Here [[Basic terminology|'model structure']] refers to things like how the catchment is broken up into modelled units, such as subcatchments or smaller units representing areas of a particular land cover type, and how different units are connected in the model. Structure choices are linked to the choice of [[Basic terminology|'modelling software tool']], such as WRSM-Pitman, ACRU, or SWAT, because different modelling tools allow for different kinds of structures and process representation. There can be multiple modelling tools that will be able to meet certain structure needs and wants in some cases, while in other cases no tool may meet them all. There are other considerations, such as ease of use, that will contribute to modelling tool selection. There is never enough time and data to build "the perfect" model and compromises will always need to be made. Identifying 'needs' and 'nice-to-haves' in as much as possible early on will assist in appropriate, 'fit-for-purpose' tool selection.  
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This page is intended to give an overview of different aspects of the modelling process, particularly in the context of how they interact with model structure decisions and modelling software tool selection. Here [[Basic terminology|'model structure']] refers to things like how the catchment is broken up into modelled units, such as subcatchments or smaller units representing areas of a particular land cover type, and how different units are connected in the model. Structure choices are linked to the choice of [[Basic terminology|'modelling software tool']], such as WRSM-Pitman, ACRU, or SWAT, because different modelling tools allow for different kinds of structures and process representation. There can be multiple modelling tools that will be able to meet certain structure needs and wants in some cases, while in other cases no tool may meet them all. There are other considerations, such as ease of use, that will contribute to modelling tool selection. There is never enough time and data to build "the perfect" model and compromises will always need to be made. Identifying 'needs' and 'nice-to-haves' for the modelling project in as much as possible early on will assist in appropriate, 'fit-for-purpose' tool selection and model building.  
  
 
The process of catchment modelling is generally not linear. The sections given below don't imply steps that are necessarily completed sequentially; there will often be iterations and circling back for revising.   
 
The process of catchment modelling is generally not linear. The sections given below don't imply steps that are necessarily completed sequentially; there will often be iterations and circling back for revising.   
  
 
== Defining the modelling project goal(s) ==
 
== Defining the modelling project goal(s) ==
The purpose of the modelling project will impact what
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Defining the goals of a modelling project in as much detail as possible, and prioritising across them, allows one to move backwards from needed and desired model outputs to model structure needs. 
  
Conceptual model
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For example: a very broad goal of a modelling project could be to look at impacts of invasive alien trees on water supply from a catchment. More specific goals in such a project could be to look at the impacts of invasive alien trees on the 98% assurance yield of a particular water supply reservoir, or on the water level of an aquifer in a particular part of the catchment, or on streamflow in particular places within the catchment (withdrawal points, critical habitat points, etc) during dry periods of certain recurrence frequencies. Looking at these more specific goals would help in determining whether model output on a monthly scale would be sufficient or shorter time-scales are needed, whether groundwater storage volumes or levels are a needed output from the model, what spatial scales one might want to get model streamflow outputs for, etc. In this example, more specific goals for modelling would also include defining what alternative land cover states would be used as reference to determine the "impact" of the invasive alien trees.  This would also impact the model structure and the needed tool capabilities in terms of how different land cover types and properties can be represented.     
  
Input data
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There can be feedback in this process: for reasons of data, time, or other constraints, detailed output goals may need to be re-adjusted. 
  
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== Taking stock of available data ==
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== Developing 'conceptual' models of catchment processes ==
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== Building & running the numerical model ==
 
Selecting a model structure
 
Selecting a model structure
  
 
Selecting a modelling tool
 
Selecting a modelling tool
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== Model validation & calibration ==
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Comparing to conceptual model, to data

Revision as of 14:00, 26 April 2021

This page is intended to give an overview of different aspects of the modelling process, particularly in the context of how they interact with model structure decisions and modelling software tool selection. Here 'model structure' refers to things like how the catchment is broken up into modelled units, such as subcatchments or smaller units representing areas of a particular land cover type, and how different units are connected in the model. Structure choices are linked to the choice of 'modelling software tool', such as WRSM-Pitman, ACRU, or SWAT, because different modelling tools allow for different kinds of structures and process representation. There can be multiple modelling tools that will be able to meet certain structure needs and wants in some cases, while in other cases no tool may meet them all. There are other considerations, such as ease of use, that will contribute to modelling tool selection. There is never enough time and data to build "the perfect" model and compromises will always need to be made. Identifying 'needs' and 'nice-to-haves' for the modelling project in as much as possible early on will assist in appropriate, 'fit-for-purpose' tool selection and model building.

The process of catchment modelling is generally not linear. The sections given below don't imply steps that are necessarily completed sequentially; there will often be iterations and circling back for revising.

Defining the modelling project goal(s)

Defining the goals of a modelling project in as much detail as possible, and prioritising across them, allows one to move backwards from needed and desired model outputs to model structure needs.

For example: a very broad goal of a modelling project could be to look at impacts of invasive alien trees on water supply from a catchment. More specific goals in such a project could be to look at the impacts of invasive alien trees on the 98% assurance yield of a particular water supply reservoir, or on the water level of an aquifer in a particular part of the catchment, or on streamflow in particular places within the catchment (withdrawal points, critical habitat points, etc) during dry periods of certain recurrence frequencies. Looking at these more specific goals would help in determining whether model output on a monthly scale would be sufficient or shorter time-scales are needed, whether groundwater storage volumes or levels are a needed output from the model, what spatial scales one might want to get model streamflow outputs for, etc. In this example, more specific goals for modelling would also include defining what alternative land cover states would be used as reference to determine the "impact" of the invasive alien trees. This would also impact the model structure and the needed tool capabilities in terms of how different land cover types and properties can be represented.

There can be feedback in this process: for reasons of data, time, or other constraints, detailed output goals may need to be re-adjusted.

Taking stock of available data

Developing 'conceptual' models of catchment processes

Building & running the numerical model

Selecting a model structure

Selecting a modelling tool

Model validation & calibration

Comparing to conceptual model, to data