Predicting water quality and ecological responses

Abstract Changes to climate are predicted to have effects on freshwater streams. Stream flows are likely to change, with implications for freshwater ecosystems and water quality. Other stressors such as population growth, community preferences and management policies can be expected to interact in various ways with climate change and stream flows, and outcomes for freshwater ecosystems and water quality are uncertain. Managers of freshwater ecosystems and water supplies could benefit from being able to predict the scales of likely changes. This project has developed and applied a linked modelling framework to assess climate change impacts on water quality regimes and ecological responses. The framework is designed to inform water planning and climate adaptation activities. It integrates quantitative tools, and predicts relationships between future climate, human activities, water quality and ecology, thereby filling a gap left by the considerable research effort so far invested in predicting stream flows. The modelling framework allows managers to explore potential changes in the water quality and ecology of freshwater systems in response to plausible scenarios for climate change and management adaptations. Although set up for the Upper Murrumbidgee River catchment in southern NSW and ACT, the framework was planned to be transferable to other regions where suitable data are available. The approach and learning from the project appear to have the potential to be broadly applicable. We selected six climate scenarios representing minor, moderate and major changes in flow characteristics for 1oC and 2oC temperature increases. These were combined with four plausible alternative management adaptations that might be used to modify water supply, urban water demand and stream flow regimes in the Upper Murrumbidgee catchment. The Bayesian Network (BN) model structure we used was developed using both a ‘top down’ and ‘bottom up’ approach. From analyses combined with expert advice, we identified the causal structure linking climate variables to stream flow, water quality attributes, land management and ecological responses (top down). The ‘bottom up’ approach focused on key ecological outcomes and key drivers, and helped produce efficient models. The result was six models for macroinvertebrates, and one for fish. In the macroinvertebrate BN models, nodes were discretised using statistical/empirical derived thresholds using new techniques. The framework made it possible to explore how ecological communities respond to changes in climate and management activities. Particularly, we focused on the effects of water quality and quantity on ecological responses. The models showed a strong regional response reflecting differences across 18 regions in the catchment. In two regions the management alternatives were predicted to have stronger effects than climate change. In three other regions the predicted response to climate change was stronger. Analyses of water quality suggested minor changes in the probability of water quality exceeding thresholds designed to protect aquatic ecosystems. The ‘bottom up’ approach limited the framework’s transferability by being specific to the Upper Murrumbidgee catchment data. Indeed, to meet stakeholder questions models need to be specifically tailored. Therefore the report proposes a general model-building framework for transferring the approach, rather than the models, to other regions.  Please cite this report as: Dyer, F, El Sawah, S, Lucena-Moya, P, Harrison, E, Croke, B, Tschierschke, A, Griffiths, R, Brawata, R, Kath, J, Reynoldson, T, Jakeman, T 2013 Predicting water quality and ecological responses, National Climate Change Adaptation Research Facility, Gold Coast, pp. 110 Changes to climate are predicted to have effects on freshwater streams. Stream flows are likely to change, with implications for freshwater ecosystems and water quality. Other stressors such as population growth, community preferences and management policies can be expected to interact in various ways with climate change and stream flows, and outcomes for freshwater ecosystems and water quality are uncertain. Managers of freshwater ecosystems and water supplies could benefit from being able to predict the scales of likely changes. This project has developed and applied a linked modelling framework to assess climate change impacts on water quality regimes and ecological responses. The framework is designed to inform water planning and climate adaptation activities. It integrates quantitative tools, and predicts relationships between future climate, human activities, water quality and ecology, thereby filling a gap left by the considerable research effort so far invested in predicting stream flows. The modelling framework allows managers to explore potential changes in the water quality and ecology of freshwater systems in response to plausible scenarios for climate change and management adaptations. Although set up for the Upper Murrumbidgee River catchment in southern NSW and ACT, the framework was planned to be transferable to other regions where suitable data are available. The approach and learning from the project appear to have the potential to be broadly applicable. We selected six climate scenarios representing minor, moderate and major changes in flow characteristics for 1oC and 2oC temperature increases. These were combined with four plausible alternative management adaptations that might be used to modify water supply, urban water demand and stream flow regimes in the Upper Murrumbidgee catchment. The Bayesian Network (BN) model structure we used was developed using both a ‘top down’ and ‘bottom up’ approach. From analyses combined with expert advice, we identified the causal structure linking climate variables to stream flow, water quality attributes, land management and ecological responses (top down). The ‘bottom up’ approach focused on key ecological outcomes and key drivers, and helped produce efficient models. The result was six models for macroinvertebrates, and one for fish. In the macroinvertebrate BN models, nodes were discretised using statistical/empirical derived thresholds using new techniques. The framework made it possible to explore how ecological communities respond to changes in climate and management activities. Particularly, we focused on the effects of water quality and quantity on ecological responses. The models showed a strong regional response reflecting differences across 18 regions in the catchment. In two regions the management alternatives were predicted to have stronger effects than climate change. In three other regions the predicted response to climate change was stronger. Analyses of water quality suggested minor changes in the probability of water quality exceeding thresholds designed to protect aquatic ecosystems. The ‘bottom up’ approach limited the framework’s transferability by being specific to the Upper Murrumbidgee catchment data. Indeed, to meet stakeholder questions models need to be specifically tailored. Therefore the report proposes a general model-building framework for transferring the approach, rather than the models, to other regions.&nbsp

Fostering assumption-based stress-test thinking in managing groundwater systems: learning to avoid failures due to basic dynamics

Sustainable groundwater resource management can only be achieved if planning processes address the basic dynamics of the groundwater system. Conceptual and distributed groundwater models do not necessarily translate into an understanding of how a plan might operate in reality. Prompted by Australian experiences, ‘iterative closed-question modelling’ has been used to develop a process of iterative dialogue about management options, objectives and knowledge. Simple hypothetical models of basic system dynamics that satisfy agreed assumptions are used to stress-test the ability of a proposed management plan to achieve desired future conditions. Participants learn from models in which a plan succeeds and fails, updating their assumptions, expectations or plan. Their new understanding is tested against further hypothetical models. The models act as intellectual devices that confront users with new scenarios to discuss. This theoretical approach is illustrated using simple one and two-cell groundwater models that convey basic notions of capture and spatial impacts of pumping. Simple extensions can address uncertain climate, managed-aquifer recharge and alternate water sources. Having learnt to address the dynamics captured by these models, participants may be better placed to address local conditions and develop more effective arrangements to achieve management outcomes

Using Participatory Rapid Appraisal and DPSIR approaches for participatory modelling: A case study for groundwater management in South Australia

Groundwater management faces a growing number of complexities and uncertainties including: the impacts of climate change, increasing demand, and socio-economic and ecological outcomes of management policies. To help deal with these issues, social learning is an interactive process which brings together scientists, policy makers, and stakeholder groups in order to share their views and develop a common framework for managing the system. This project aims to use a participatory modelling approach to support social learning about the future of groundwater management in South Australia. This paper reports on the data collection and analysis methods used in the scoping phase of the study. The central focus is on the process undertaken rather than the content of the results

Design and implementation of a web-based groundwater data management system

Understanding and managing groundwater resources requires the integration of large amounts of high quality data from different sources. With the recent advances in GIS, data storage, web-based applications, and visualisation technologies, groundwater dat

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In complex socio-ecological systems, such as managing natural resources, human frames and mental models play a central role in deriving the system's behaviour. Differences in stakeholder views and perceptions may impede the design and implementation of c

Simulation Analysis of a Military Casualty Evacuation System

This paper aims to analyse several parameters of the casualty evacuation system and their effects through the simulation platform. A discrete event simulation (DES) model is used for the analysis. Five scenarios contemplating different fleets' prerequisites for survival, ambulance allocation and casualty treatment allocation parameters are used to test the performance of the military evacuation system. The result shows that change in parameters such as ambulance return time, redeployment time, transport duration etc., effects the time of evacuation as well as the time of resuscitation and damage control surgery. The percentage of casualties that required damage control surgery that received it within the required time is on average, 63.78 % and the waiting time for bed is 0 minutes. In order to facilitate the evacuation of combat casualties, this simulation model supports decision-making. This analysis can also be used to support the resource allocation of the military casualty evacuation system