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Wetland hydrological models

Wetland models enable users to quantify and predict the performance of wetland systems. This is important to understand how best to use both natural and constructed treatment wetlands to improve water quality, and to support wetland rehabilitation[2].

Pictorial conceptual model montage. Images by Lana Baskerville

Quick fact

Models are approximations
or simplified representations of a system of interest that link its state to its drivers (inputs) and responses (outputs)[1]

Wetland hydrological models

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Why is modelling important for wetlands?

Wetland hydrological models provide relationships among the numerous wetland forcing factors (factors exerting external influence on the wetland e.g. climatic inputs, inflow into the wetland etc.). They also incorporate relationships with wetland variables (processes occurring within the wetland e.g., relationships between climatic variables, water quality and quantity, chemical and biological processing within the wetland, etc.). Wetland models are used for many purposes, including informing policy, planning and decision making about wetland implementation and optimising functionality and performance[2].

Dynamic hydrological models differ from pictorial conceptual models and other types of models.

Scale

Scale is a very important consideration in terms of temporal, spatial and geographic variations in the inputs and outputs of a model. Current wetland hydrological models tend to focus on modelling individual wetlands. Scaling up the models to incorporate a catchment and to include multiple wetlands is challenging in terms of model design and function.

Potential modelling issues

The capability and accuracy of a wetland model to represent hydrological and biogeochemical processes depends on the scientific representation of the relationships between variables, and the data available as forcing data input, or to calibrate and validate the model.

A model may not perform well if the relationships are not well understood or defined (or the logic of the model does not adequately represent the processes being investigated), or the available data (e.g., data obtained from a field or experimental study) is poor or limited.

When this is the case, it is important to understand the uncertainty in the model output, and what steps need to be taken to reduce model uncertainty. One method to quantify uncertainty involves adjusting model parameters using upper and lower bounds of values from the literature or theory, to provide a band of model output that is highly likely to encompass the future observations[2].

QWMN Wetland Hydrology Models Review

Wetland Management Tools and Guides

Information sources for aquatic ecosystem rehabilitation planning

Water quality, water quantity and aquatic ecosystem monitoring

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References

  1. ^ Queensland Water Modelling Network (2018), Good Modelling Practice Principles. [online], Brisbane, Queensland. Available at: https://science.des.qld.gov.au/__data/assets/pdf_file/0011/81110/qwmn-good-modelling-practice-principles.pdf.
  2. ^ a b c Weber, T, de Groot, A, Hamilton, D, Yu, S & Bayley, M (2021), QWMN Wetlands Hydrology Models Review, Alluvium Consulting Australia, Griffith University, and Australian Wetlands Consulting.

Last updated: 31 May 2023

This page should be cited as:

Department of Environment, Science and Innovation, Queensland (2023) Wetland hydrological models, WetlandInfo website, accessed 1 February 2024. Available at: https://wetlandinfo.des.qld.gov.au/wetlands/facts-maps/modelling/wetlands-modelling/

Queensland Government
WetlandInfo   —   Department of Environment, Science and Innovation