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Hypothetical example to illustrate uncertainty analysis workflow concepts. In an unconfined, alluvial aquifer a new irrigation development (D), using both surface and groundwater is proposed. The river is regulated, considered to be losing-disconnected and supports a Ramsar wetland (R). In the aquifer is an existing stock and domestic bore (B) and a spring (S), both up-gradient from a geological fault that may or may not act as a barrier to flow.
Source publication
IAH and NCGRT organised a workshop on uncertainty analysis in groundwater modelling, preceding the 2017 Australasian Groundwater Conference in Sydney. Hugh Middlemis (HydroGeoLogic) led a discussion among a team of experts representing a wide range of groups, including model users, model developers, government agencies, consultants, researchers and...
Contexts in source publication
Context 1
... four sources of scientific uncertainty result in predictive uncertainty -the bias and other error associated with model simulations (see Figure 2, after . Bias refers to systematic error, which displaces the model outputs away from the accepted 'true' value, and error refers to the difference (spread) between the average value of model simulations and the accepted true value. ...
Context 2
... define the objectives of uncertainty analysis for an issue, we need to consider the risk assessment and management framework in its entirety, including the balance between determining uncertainty; reducing uncertainty through monitoring and scientific investigations; and managing or treating risk, at times in response to new information ( Figure 2). Each situation is different, and the balance of these components will vary. ...
Context 3
... me illustrate this with a very simple example ( Figure 2). In an unconfined, alluvial aquifer a new irrigation development is proposed (D), using both surface water and groundwater. ...
Context 4
... in the example in Figure 2 that the choice is made to not represent the fault in the groundwater model; for example, because a lot of extra data is required, such as the geometry of the fault, the displacement and the hydraulic properties of the fault. Assume that such data is not available in this example, so the first question is scored 'high', Likewise, adding a fault to a groundwater model requires additional time and resources especially since the added complexity will require model runs during model calibration and uncertainty analysis. ...
Citations
... The prediction of future impacts on groundwater systems from the climate is hampered by uncertainty related to future rainfall projections (and carbon emissions and warming scenarios) and its impact on groundwater recharge and groundwater demand, as well as the uncertainty associated with hydrogeological properties. Groundwater management therefore needs to occur within a risk framework to ensure the management objectives are still met despite this uncertainty [25,26]. Since uncertainty and risk are key issues for the paper, this paper is divided into five sections, structured around risk: ...
... Risk management is therefore a critical component of planning processes [56,57]. In the case of groundwater, there is an additional deficiency in knowledge: sufficient understanding of the hydrogeological properties and groundwater inputs and outputs to predict the Water 2021, 13, 3588 7 of 36 response of groundwater systems to stresses [25]. The future climate is therefore just one more uncertainty, albeit a major one. ...
... Groundwater management actions taken today may lead to impacts in decades to come and hence beyond the current planning cycle. Scenario modelling is generally used to compare the impact of an action compared to the status quo [25]. Water management plans will influence the spatial and temporal distribution of groundwater extraction, as will commodity prices and climate. ...
The trend to a hotter and drier climate, with more extended droughts, has been observed in recent decades in southern Australia and is projected to continue under climate change. This paper reviews studies on the projected impacts of climate change on groundwater and associated environmental assets in southern Australia, and describes groundwater planning frameworks and management responses. High-risk areas are spatially patchy due to highly saline groundwater or low-transmissivity aquifers. The proportional reduction in rainfall is amplified in the groundwater recharge and some groundwater discharge fluxes. This leads to issues of deteriorating groundwater-dependent ecosystems, streamflow depletion, reduced submarine discharge, groundwater inundation and intrusion in coastal regions and reduced groundwater supply for extraction. Recent water reforms in Australia support the mitigation of these impacts, but groundwater adaptation is still at its infancy. Risk management is being incorporated in regional water and groundwater management plans to support a shift to a more sustainable level of use and more climate-resilient water resources in affected areas. The emerging strategies of groundwater trade and managed aquifer recharge are described, as is the need for a national water-focused climate change planning process.
... As groundwater models are simple representations of a complex reality, their predictions are inherently uncertain. Characterisation of the predictive uncertainty provides the decisionmaker the insights needed to understand the risks when it comes to groundwater management (Middlemis et al., 2019). A good characterisation of the predictive uncertainty of a groundwater model has the potential to increase the likelihood to successfully identify suitable locations for developing a new groundwater resource (Sidiropoulos and Tolikas, 2004), or aid in the design of mine dewatering and provide more robust estimates of environmental impact of mine operations (Currell et al., 2017). ...
... The objective of a groundwater model has an influence on how uncertainties should be dealt with (Middlemis et al., 2019). In the following sections we will differentiate between prediction focused and exploration focussed groundwater modelling. ...
Groundwater models are widely applied in groundwater management to guide decision making. The success of groundwater management is directly dependent on a good understanding of the groundwater system. A conceptual model is a summary of our current knowledge about a groundwater system describing the dominating processes and the overall physical structure of the geology. One of the major sources of uncertainties in groundwater model predictions is the conceptual uncertainty that arises when more than one conceptual model can explain the available data. The goal of this thesis is to identify current approaches, unify scattered insights and develop a systematic methodology of hydrogeological conceptual model development and testing, which leads to an improved characterisation of conceptual uncertainty.
Conceptual model development involves formulation of hypotheses about the groundwater system functioning. These are the initial decisions in the modelling that drive the groundwater model predictions and form the basis of the uncertainty analysis. In this thesis we advocate for a systematic model development approach based on mutually exclusive hypotheses. We developed bold hypotheses about the model structure, challenging what was considered possible for the system, in order to give more transparent explanation of which model structures were considered possible.
Conceptual model testing consists of holding the developed models against data to evaluate their validity. Model testing is essential in order to gain confidence in the developed models and remove those models from the ensemble that are inconsistent with the data. We show that model testing does not have to be a time-consuming task but can happen in relatively simple forward models. We advocate for reserving as much data as possible for the model testing exercise rather than using all data for model development in order to be able to explain why no other conceptual models are plausible.
The methodology developed in this thesis is applied to the Wildman River area, Northern Territory, Australia. By acknowledging the existence of conceptual uncertainty, we increase the confidence in the water balance for the area. A second aspect of the investigation is the connectivity of sinkhole-like depressions in the area to groundwater and whether they may act as conduits of groundwater recharge.
The insights gained from this thesis enables more accessible methodology for conceptual model development and testing. By acknowledging and accounting for conceptual uncertainty, more confidence can be gained in groundwater model predictions leading to improved groundwater management.
