Jaroslav Mysiak

Towards the development of a decision support system for water resource management

Developing decision support systems for environmental applications is an intricate, challenging task. The increasing complexity of environmental decision problems, the growing number of subjects involved and keen competition between conflicting interests make decisions and decision support difficult. Decision support systems have been developed since the 1970s to help tackle semi-structured and unstructured decision problems. Despite their popularity, the success of DSS development is uncertain and many computerised decision-support tools have failed when dealing with complex and unstructured problems. This article describes the development methodology and progress of mDSS, a decision support system for water resource management that has been developed under the European research project MULINO. The mDSS tool is designed to integrate environmental (especially hydrological) models with multiple-criteria evaluation procedures. A number of prototypes have been developed and the final version is expected at the end of the 3-year project. The system’s development is driven by the experience acquired in several case studies selected in five European countries. Although the main aim of the MULINO project and the DSS is to help with increasingly complex decisions of general water management, the concepts of sustainable river basin management introduced by the water framework directive are addressed as well. � 2004 Elsevier Ltd. All rights reserved.

MULINO-DSS: a computer tool for sustainable use of water resources at the catchment scale

MULINO, an ongoing project financed by the European Commission, has released the prototype of a Decision Support System software (mDSS) for the sustainable management of water resources at the catchment scale. The software integrates socio-economic and environmental modelling, with geo-spatial information and multicriteria analysis. The policy background refers to the EU Water Framework Directive. The challenging multi-disciplinary context was approached by developing an innovative and dynamic implementation of the DPSIR framework, originally proposed by the European Environmental Agency. In mDSS integrated assessment modelling provides the values of quantitative indicators to be used for transparent and participated decisions, through the application of value functions, weights and decision roles chosen by the end user. Simple routines for the sensitivity analysis and comparison of alternative weight vectors also provides effective decision support by exploring and finding compromises between conflicting interests/perspectives in a multi-stakeholder context.

Assessing direct and indirect economic impacts of a flood event through the integration of spatial and computable general equilibrium modelling

In this paper we developed and tested an integrated methodology for assessing direct and indirect economic impacts of flooding. The methodology combines a spatial analysis of the damage to the physical stock with a general economic equilibrium approach using a regionally-calibrated (to Italy) version of a Computable General Equilibrium (CGE) global model. We applied the model to the 2000 Po river flood in Northern Italy. To account for the uncertainty in the induced effects on regional economies, we explored three disruption and two recovery scenarios. The results highlight that: i) the flood event produces indirect losses in the national economic system, which are a significant share of the direct losses, and ii) the methodology is able to capture both positive and negative economic effects of the disaster in different areas of the same country. The assessment of indirect impacts, in particular, is essential for a full understanding of the economic outcomes of natural disasters. Rarely the accounting of flood losses includes indirect economic impacts.The proposed method integrates spatial and computable general equilibrium modelling for the estimation of indirect impacts.We analyse a flood event in Northern Italy, reporting indirect economic impacts as around 20 percent of direct impacts.Economic benefits arise in non-flooded sub-regions of Italy.

Bridging the gaps between design and use: developing tools to support environmental management and policy

Abstract Integrated assessment models, decision support systems (DSS) and Geographic Information Systems (GIS) are examples of a growing number of computer-based tools designed to provide decision and information support to people engaged in formulating and implementing environmental policy and management. It is recognised that environmental policy and management users are often not as receptive to using such tools as desired but that little research has been done to uncover and understand the reasons. There is a diverse range of environmental decision and information support tools (DISTs) with uses including organisational and participatory decision support, and scientific research. The different uses and users of DISTs each present particular needs and challenges to the tool developers. The lack of appreciation of the needs of end-users by developers has contributed to the lack of success of many DISTs. Therefore it is important to engage users and other stakeholders in the tool development process to help bridge the gap between design and use. Good practice recommendations for developers to involve users include being clear about the purpose of the tool, working collaboratively with other developers and stakeholders, and building social and scientific credibility.

Reflections on the Current Debate on How to Link Flood Insurance and Disaster Risk Reduction in the European Union

Flood insurance differs widely in scope and form across Europe. Against the backdrop of rising flood losses, a debate about the role of EU policy in shaping the future of this compensation mechanism is led by policy-makers and industry. While the question of supply and demand is at the core of the debate, we argue that another key dimension is often overlooked: how to use insurance as a lever for risk reduction and prevention efforts. We investigate whether and how current EU policies influence flood insurance and how this interplays with the national policy level. First, we consider affordability, availability, and risk reduction linkages in an EU context, and then gather insights from two contrasting cases of flood insurance: the UK, where flood insurance provision is widely available, but subject to ongoing reform; and the Netherlands, where several efforts to introduce broader flood insurance coverage have failed. This is followed by an analysis of how EU policy could help address the challenges at member state level, based on a stakeholder workshop discussion. We conclude that there is wide agreement that a complete harmonization of flood insurance offering across the EU is unlikely to be effective. However, there is clear scope for EU policymakers to play a greater role in linking risk transfer and prevention, beyond existing channels, to ensure an integrated approach to flood risk management across the EU.

Network Analysis, Creative System Modelling and Decision Support: The NetSyMoD Approach

This paper presents the NetSyMoD approach - where NetSyMod stands for Network Analysis - Creative System Modelling - Decision Support. It represents the outcome of several years of research at FEEM in the field of natural resources management, environmental evaluation and decision-making, within the Natural Resources Management Research Programme. NetSyMoD is a flexible and comprehensive methodological framework, which uses a suite of support tools, aimed at facilitating the involvement of stakeholders or experts in decision-making processes. The main phases envisaged for the process are: (i) the identification of relevant actors, (ii) the analysis of social networks, (iii) the creative system modelling and modelling of the reality being considered (i.e. the local socio-economic and environmental system), and (iv) the analysis of alternative options available for the management of the specific case (e.g. alternative projects, plans, strategies). The strategies for participation are necessarily context-dependent, and thus not all the NetSyMod phases may be needed in every application. Furthermore, the practical solutions for their implementation may significantly differ from one case to another, depending not only on the context, but also on the available resources (human and financial). The various applications of NetSyMoD have nonetheless in common the same approach for problem analysis and communication within a group of actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through the mDSS software.

Preface: Thematic issue on the assessment and evaluation of environmental models and software

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Chapter Two Good Modelling Practice

– see front matter 2010 Elsevier Ltd. A doi:10.1016/j.envsoft.2010.08.008 A key ambition in developing and using environmental models and software is to exert a positive impact on policy and management processes, outputs and outcomes. The scientific development community typically want to contribute to achieving a diverse range of objectives including but not limited to better managing scarce resources; maintaining or enhancing adaptive capacity; supporting processes that enhance the inclusivity of environmental decision making, and; avoiding, resolving and mediating conflict. To successfully achieve these ambitions environmental models and software need to be scientifically and technically sound, reliable, usable and cost effective. Butmore than this, there is a need to understand the impacts that they have, and the relative costs, benefits and dis-benefits to those who use them. Such knowledge will provide strategic advice to both research funders and eventual users considering the development, procurement and use of modelling technology as a means of influence or achieving outcomes. Such knowledge will also contribute to our understanding of the relationships betweenmodes of scientific information and knowledge provision, policy and management action, and environmental outcome. The primary aim of this Thematic Issue is to act as a catalyst to stimulate debate about how we should assess and evaluate environmental models and software, through bringing together work on how to scientifically and technically assess models and software with emerging research concernedwith answering questions about the use and impact of these technologies. By technical assessment we mean here the objective, quantitative assessment of model and software technology attributes. What concepts can be used to frame assessment and evaluation? What methods are suitable? What do we know about the use and impact of environmental models and software in policy and management both empirically and theoretically? How are environmental models and software embedded in societal processes? The Issue is composed of a collection of eight papers which fall into these categories:

Improving Flood Damage Assessment Models in Italy

Abstract Models have become indispensable in environmental assessment, planning and management. However as models have increasingly been developed and disseminated, the risk of their misuse or misunderstanding of their capabilities has increased. Whether a model is used for simulation, prediction, decision making or communication of scientific analyses, it is important that its development and application conform to protocols or standards that help to maximise the scientific soundness, utility and defensibility of models and their outputs. The complexity and uncertainty inherent in environmental assessment make the pursuit of good modelling practice especially important, in spite of limited time and resources. This paper is an attempt to identify the key components of best modelling practice and our collective progress in its achievement, taking into account previous relevant reviews undertaken by several authors and agencies. The details are always likely to be the subject of lively debate, but the general components of ‘good modelling practice’ are probably not controversial. They are clear purpose, adequate reporting, and serious evaluation. Although these are common strands in the various definitions of good modelling practice the emphasis varies between different types of model application. For this reason it is important that good practice should not become overly prescriptive. We report a preliminary analysis which suggests that progress towards improving modelling practice is slow. This is despite very widespread agreement on what constitutes good practice. Why is this so? In the research community at least, the drivers for model development and evaluation are funding and publication. If modelling practice needs to be improved, and we think it does, sponsors and journals need to take a lead in creating an environment where developing a model requires that the work be undertaken under some system of good modelling practice. The suggestion has been made of a ‘good practice check list’ in the journal, Environmental Modelling and Software. While such a system would need to be flexibly applied, the principle is sound, and such steps should move us forward.

Participatory Modelling and Decision Support for Natural Resources Management in Climate Change Research

Flood damage assessments are often based on stage-damage curve (SDC) models that estimate economic damage as a function of flood characteristics (typically flood depths) and land use. SDCs are developed through a site-specific analysis, but are rarely adjusted to economic circumstances in areas to which they are applied. In Italy, assessments confide in SDC models developed elsewhere, even if empirical damage reports are collected after every major flood event. In this paper, we have tested, adapted and extended an up-to-date SDC model using flood records from Northern Italy. The model calibration is underpinned by empirical data from compensation records. Our analysis takes into account both damage to physical assets and losses due to foregone production, the latter being measured amidst the spatially distributed gross added value.