Susan M. Cuddy

A framework for modelling multiple resource management issues - An open modelling approach

Abstract Our experience with development and distribution of environmental decision support systems (EDSSs) for delivering research outcomes to catchment managers has identified major impediments to their adoption. These include protracted development time, focus on single impacts, difficulty in combining results with other EDSSs, and no attention to socio-economic factors. Based on the premise that decision support tools can play a major role in the integration and adoption of research outcomes, we are developing a software tool for rapid building of EDSSs which can handle multiple issues across different scales. The prototype is called the Open Modelling Engine (OME). This paper describes the background to the development of the OME, its basic architecture, an OME-built EDSS for catchment nutrient management, and concludes with a discussion on research direction and opportunity.

Tarsier and ICMS: two approaches to framework development

Modelling frameworks provide models with support components that handle tasks such as visualisation, data management and model integration. Within these broad requirements different approaches to framework development are possible. Tarsier is a modelling framework that supports the development of models in a high-level language, such as C++. This approach allows Tarsier model developers to craft object oriented solutions to large modelling problems. ICMS is a software system that supports the development of models in a custom modelling language that allows modellers with little programming experience to develop, integrate and visualise catchment models. Both frameworks provide sophisticated tools for model linking, data management, and data analysis and visualisation. By focusing on different user groups, Tarsier and ICMS have evolved into quite different environments, yet both satisfy the definition of a modelling framework. This paper concentrates on the components within each framework and the strengths and weaknesses of the different approaches.

Including stakeholder input in formulating and solving real-world optimisation problems

Multi-objective evolutionary algorithms (MOEAs) are becoming increasingly popular for solving formal environmental and water resources optimisation problems. In the past, the focus of these studies has generally been on methodological issues related to the optimisation algorithm. However, in recent years, there has been increased recognition of the need to apply these approaches to real-world problems to facilitate the realisation of their full potential. In order to assist with this, a framework for including stakeholder input in real-world optimisation problems is introduced in this paper, including a conceptual framework and a procedure for implementing it. The framework is applied to an urban water supply security study for Adelaide, South Australia. This study highlights the role of stakeholder input at the various stages of the optimisation process, as well as the resulting changes in the formulation, analysis and results. A discussion of the lessons learnt from the case study is also provided. Framework for including stakeholder input in evolutionary algorithm optimisation.Stakeholder input included at all stages of optimisation process.Framework applied to urban water supply security study in Adelaide, South Australia.

Integrated catchment modelling and decision support

This issue of Environmental Modelling and Software contains a selection of papers on the role of integrated modelling in supporting decision processes addressing regional catchment management issues. The papers have been selected from two sessions of the International Environmental Modelling Software Society (iEMSS) conference, held in Lugano, Switzerland, in June 2002 and all have a water allocation and management focus. Much of the emphasis of catchment management today, and thus the focus of catchment modelling, is on the prediction of the impact of proposed changes in water management, land management, or land use on the catchment character. In the past, much of this modelling has been to support decision makers within planning or resource management agencies. Increasingly, this decision-making is being taken into the public forum and integrated catchment models are being used to facilitate debates and consultation between the various stakeholders in regional planning exercises. Traditionally prediction of impacts has been confined to biophysical characteristics such as stream flow and water quality. While this has served the engineering community well, today’s more open and participatory approach to catchment management must also consider impacts on the human landscape. In fact, within the European region, the use of models and evaluation of environmental and social impacts is specifically included in the prospectus of the Water Framework Directive (2000/60/EC) of the European Union. Indeed, it is legislated that, by 2009, each European basin must have a plan that clearly specifies the interventions required to meet set water quality conditions, and the integrated approach to be followed. In this issue, we have assembled practical examples of integrated catchment modelling applications. These illustrate the wide-ranging nature of integrated catchment modelling and the contribution that it can make to the complex debate over resource development and resource conservation. The papers describe modelling work to support decision making at a range of scales, in both regulated and unregulated catchments, and for a range of users. The genesis of the modelling systems is interesting. Most have been commissioned by water management or regulatory bodies (eg water department or environmental protection agencies) to model likely impacts of alternate

Assessment of Ecological Responses to Environmental Flow Regimes using a Decision Support System Framework

The Environmental Flows Decision Support System (EFDSS) has been developed to allow the communities and governments in the Murray-Darling Basin of Australia to assess the environmental responses of the lowland floodplain rivers to proposed flow management scenarios. The system integrates a range of qualitative and quantitative ecological models which consider blooms of toxic blue-green algae as well as habitat conditions for fish, floodplain vegetation, and waterbird breeding. It has been designed to accommodate a wide range of users. In this paper the overall design concepts and components of the EFDSS are described.

The use of historical environmental monitoring data to test predictions on cross-scale ecological responses to alterations in river flows

Abstract Determination of ecological responses to river flows is fundamental to understanding how flow-dependent ecosystems have been altered by regulation, water diversions and climate change, and how to effect river restoration. Knowledge of ecohydrological relationships can support water management and policy, but this is not always the case. Management rules have tended to be developed ahead of scientific knowledge. The lag between practice and knowledge could be addressed by using historical monitoring data on ecological responses to changes in flows to determine significant empirical ecohydrological relationships, as an adjunct to investigating responses prospectively. This possibility was explored in the Murray–Darling Basin, Australia. We assessed 359 data sets collected during monitoring programs across the basin. Of these, only 32 (9%) were considered useful, based on a match between the scale at which sampling was done and ecological responses are likely to occur, and used to test flow–ecology predictions for phytoplankton, macroinvertebrates, fishes, waterbirds, floodplain trees, basin-scale vegetation and estuarine biota. We found relationships between flow and ecological responses were likely to be more strongly supported for large, long-lived, widespread biota (waterbirds, basin-scale vegetation, native fishes), than for more narrowly distributed (e.g. estuarine fishes) or smaller, short-lived organisms (e.g. phytoplankton, macroinvertebrates). This pattern is attributed to a mismatch between the design of monitoring programs and the response time frames of individual biota and processes, and to the use of local river discharge as a primary predictor variable when, for many biotic groups, other predictors need to be considered.

A provenance maturity model

The history of a piece of information is known as “provenance”. From extensive interactions with hydro-and geo-scientists in Australian science agencies we found both widespread demand for provenance and widespread confusion about how to manage it and how to develop requirements for managing it.

Which Buttons And Bars? An Exercise In Community Participation In Decision Support Software Development

In developing an environmental DSS it is important to have a good understanding of who will use it and how. The best way to do this is by interacting with a user group during the development process to ensure an appropriate design and to foster interest and ownership of the product. A prototype of the Environmental Flows Decision Support System (EFDSS) has been developed in this manner. Using the Border Rivers Catchment of NSW/QLD as a case study, a community reference group was established and regularly consulted throughout development of the system. Members provided important input and feedback on interface design resulting in numerous modifications and enhancements to the final prototype. Many lessons were learned and one of the spin-offs was the addition of an entire explanation module — EFDSSInfo — which had otherwise only been considered peripheral to the system.