Modelling process overview

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 & information

for direct model input & parameterisation, for constraining parameter value options, for calibration/validation/reality checks (see conceptual model below)

hydrometric observation data

catchment property data

quality, time period, scale of measurement

Developing 'conceptual' models of catchment processes

interpret the available data & info about the catchment before settling on a model structure

helps with looking at the units and connectivity might be important to include; determining starting value ranges for uncertain input parameters

basic catchment process info: water balance or runoff ratio likely range, likely dominant flow paths under different conditions (seasons, extremes, etc) - flashy vs slow responses, etc, role of deeper GW

spatial diversity within catchment - rainfall, topography, geology, soil, land cover - which types are likely to be most different from one another (need separate representation vs lumping - not always use the land cover map classes as received from another source...)

what can be gleaned from data analyses, catchment properties + pre-existing local/regional studies

what is understood about the likely impacts of the scenarios to be modelled on the different processes

what is fairly well understood vs still very uncertain

Building & running the numerical model

Selecting a model structure

Selecting a modelling tool - separate page??

Formatting all the inputs and putting them in, deciding parameter values & ranges

Model validation & calibration

Comparing to both to observed data sets & conceptual model