Development of Decision Support Tools to Assess the Sustainability of Coastal Lakes
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Development of Decision Support Tools to Assess the Sustainability of Coastal Lakes 1Ticehurst, J.L., 2Rissik, D. 1Letcher, R.A., 1Newham, L.H.T., and 1Jakeman, A.J. 1Integrated Catchment Assessment and Management Centre, 2Department of Infrastructure, Planning and Natural Resources, E-Mail: [email protected] Keywords: Coastal lakes, Sustainability assessment, Bayesian decision network, Decision support. EXTENDED ABSTRACT The integration was completed using a Bayesian Coastal lakes in New South Wales provide decision network (BDN). This approach was important ecological, social and economic benefit advantageous over other methods because it is for much of the state’s population. However they suited to the rapid accumulation and integration of are naturally sensitive to catchment inputs, existing information sourced from observed data, particularly when the lakes are periodically closed model simulation and expert opinion, at various to the ocean. Demand on the lakes and their scales, from many disciplines. The BDN framework catchment’s finite resources through: encroaching structure also inherently represents uncertainty in urban development; poor agricultural the input data but can be readily up-dated when management; the need to protect native flora and new information becomes available. fauna; a growing market for seafood; and increasing tourism; is increasing conflict over Consultation with local stakeholders was an their use and sustainable management. These imperative component throughout the whole issues are intricately linked, so the management process, but it played a particularly important role of coastal lake systems requires knowledge of the in the development of the BDN framework and in processes and interactions between all key defining the scenarios. The close interaction with components of the system. This is a complex future users of the tool meant that the product was problem requiring the integration of, often more likely to be adopted. minimal, information, from various disciplines. Few tools exist to assist catchment and lake Table 1. Method undertaken for a detailed managers to analyse the whole lake system and sustainable assessment of eight coastal lakes in make more informed management decisions. New South Wales, Australia. The New South Wales government recognized the Stage Phase threat to the coastal regions and issued a 1 build understanding of constraints, issues and ‘Statement of Intent’ in 2003, to conduct a targets for lake and catchment health Comprehensive Coastal Assessment for the state. 2 develop an initial conceptual framework for Stage one included a sustainability assessment of BDN and potential future scenarios eight coastal lakes in the state (Cudgen, Myall, Coila, Narrawallee Inlet, Burrill, Wollumboola, 3 review BDN framework with stakeholders Merimbula and Back lakes). The research 4 revise initial framework presented in this paper was conducted to contribute to the Coastal Lake Assessments. 5 populate BDN links with data 6 incorporate the BDN model into a user friendly This paper describes the development of a software platform decision support tool to inform of the potential 7 review the interface and populated BDN with impacts of management decisions on all key stakeholders components of a coastal lake system. The method used to develop the decision support tool, in short, 8 revise interface and populated BDN to reflect stakeholder feedback involved collecting information about potential management decisions, and the key values of the 9 distribute the sustainability assessment tool to lake, and integrating this into a single, simple relevant stakeholders with appropriate training tool. A more detailed depiction of the process is in its use. presented in Table 1. 2414 Myall, Wollumboola, Narrawallee, Burrill, Coila, 1. INTRODUCTION Merimbula and Back). The CLAM tool for The coastal regions of NSW are appreciated for the Merimbula lake is presented and discussed as a social, economic and ecological value they bring to case study. their resident and visiting populations. In recent times there has been an active migration of the 2. BAYESIAN DECISION NETWORK human population to coastal areas, as well as an APPROACH increase in coastal tourism. This creates a greater Many approaches exist for integrative modelling. need for urban development and tourist facilities. A review by Jakeman et al. (2005) presents various At the same time there has been an increased approaches such as expert systems, coupled pressure for the conservation of natural ecosystems component models, metamodels, agent-based in the coastal zone. In addition, agricultural models and risk assessment approaches. The production is commonly intensifying in an attempt methods vary in properties such as their ability to to remain profitable in the current market. Coastal account for quantitative verses qualitative data, lakes are naturally sensitive to catchment inputs, and their inherent ability to be used in decision- but the different use of land, flora, fauna and water making or to reflect uncertainty. A Bayesian within coastal catchments creates pressure and network approach was chosen for this analysis for conflict over the management of these limited reasons discussed below. resources. Bayesian networks conceptualise a system through In the past coastal management has focused on one a series of variables joined by causal links (Pearl or two facets of the system, such as fish species or 1988). Bayesian Decision Networks (BDN) are habitat management (e.g. Alder et al. 2000). structured with decision variables (scenario However, in order to manage the complex systems choices), interim variables (state indicators) and of coastal lakes, knowledge of all key processes utility variables (outputs or goals). within the whole catchment is required. In fact, Underwood (2002:487) commented that “Never Catchment planning is unavoidably complex has there been more need for urgent, integrated (Ewing et al. 2000) but the BDN approach offers a and coherent decision-making about coastal comparatively simple method of integration environmental issues”. Progress is being made because each process does not have to be explicitly towards a more holistic approach to catchment represented (Borsuk et al. 2004). management (e.g. Bennett and Lawrence 2002, Courtney and White 2000, Alder et al. 2000), but Causal links within the framework represent the even these can be dominated by one catchment relationship between variables using probability process. For example Ewing et al. (2000:449) distributions. Thus the uncertainty in the describes a hydrological and water quality model relationship between each variable can be with “provision for some basic socioeconomic explicitly represented (Varis and Kuikka, 1997), analysis”. allowing the user to make a judgement on the reliability of the model predictions. It is a ‘huge ask’ for catchment managers to have adequate knowledge across all facets of the BDNs can efficiently incorporate social, economic catchment system to make integrative and and ecological values within the modelling informed decisions. Decision support tools are a framework because the approach lends itself to the possible means to integrate such complex systems easy incorporation of both qualitative and and array of knowledge, and present it in a quantitative data (Varis and Kuikka 1997). So simplistic way for them (Ewing et al. 2000). when observation data or model simulation is not However, the acceptance and therefore the success available, expert and local knowledge can be of such tools depends strongly upon community utilised. As new information becomes available, consultation (Courtney and White 2000, Alder et the BDN can be readily updated (Walters 1986, al. 2000). Borsuk et al. 2004). Thus the BDN approach provided an efficient This paper presents the method for the method for the integration of social, economic and development of a decision support tool to assist in ecological values within a complex system, Coastal Lake Assessment and Management utilizing available quantitative and qualitative data (CLAM). The approach could be considered and explicitly representing the uncertainty in the another example of Adaptive Environmental model predictions. Assessment and Management (AEAM), as defined by Ewing et al. (2000). CLAM integrates social, economic and ecological values for the catchment considered. Eight separate tools were developed for eight coastal lake catchments in NSW (Cudgen, 2415 3. MODEL AND SOFTWARE assess the potential impacts of the DESCRIPTION management scenarios tested. The model development process is outlined in Table 2. Summary of features available in the Table 1. An initial effort was made to develop a CLAM software. relevant BDN framework but community consultation played an important role throughout the model development process, by providing Software Features available feedback on the representation of the catchment Page system and the scenario options. Welcome Project background, contacts and licensing agreements The probability distributions for each BDN variable (Stage 5, Table 1) were derived through Info Photograph gallery of the catchment, brief the analysis of observed data, model simulation, a list of facts about the catchment series of general assumptions or expert opinion. Maps Series of catchment properties which can be Community input was obtained from reports and overlaid, such as landuse protected areas, from direct consultation, and provided expert local erosion potential