Decision support systems and tools

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This article gives a short introduction to decision support systems and some decision support tools available to decision makers and policy makers. It is partially based on Nostrum DSS Guidelines.


Decision Support Systems

Decision Support Systems (DSS) are interactive computer-based systems designed to assist decision makers in exploring problems, evaluating alternative options and understanding their consequences. A DSS can integrate data, models, analytical methods and other sources of information through an interface accessible to its intended users.

Decision support systems also serve in participatory processes by facilitating dialogue and exchange of information to provide insights to non-experts and support them in exploring policy options. Decision support systems further assist in documenting the decision-making process that leads to the choice of a particular option, contributing to its increasing transparency and fairness.

Environmental decision support systems typically combine databases, simulation or assessment models and a user interface. Models can represent the physical, ecological, economic and social consequences of alternative policies, strategies or interventions under different scenarios. Besides quantitative data and model results, a DSS may incorporate expert knowledge and stakeholder values, preferences and experience. DSS can also serve as tools for communication, training and experimentation[1].

Applications in coastal management

Examples for the use of decision support systems are:

DSS for risk assessment

DSS can support coastal risk assessment by combining spatial information on hazards, exposure and vulnerability and by comparing the consequences of alternative management measures under different scenarios. Various indices have been developed for this purpose that combine selected indicators into spatially explicit measures that can be visualized in geographic information systems (GIS). Their interpretation depends strongly on the choice, scaling and weighting of the underlying indicators. Barzehkar et al. (2021[3]) list the following indices (see also Vulnerability and risk.):

  • Coastal Vulnerability Index (CVI) indicates the extent to which a system is susceptible to, and unable to cope with, adverse effects. It provides quantitative analysis for ranking vulnerabilities of coastal sections and helps identify the vulnerable areas that require protection measures.
  • Coastal exposure index (CEI) evaluates the likelihood of socioeconomically valuable features such as infrastructure and urban areas to be negatively affected by a hazard, such as flooding.
  • Coastal Risk Index Maps (CRI) are derived from the CVI and CEI to identify coastal sectors affected by natural hazards. The maps can help develop plans for coastal protection against climate-induced hazards.
  • Coastal Area Index (CAI) is used in spatial planning strategies to identify priority areas for coastal protection in regions experiencing economic development.
  • Coastal Resilience Index (CoRI) is used to estimate the ability of the coastal area to respond to hazards in a way that reduces their impact. Important factors influencing resilience are distance from the shoreline, elevation changes and human activities.

Decision support systems focused on risk assessment require spatial data at a resolution appropriate to the management problem. A small grid cell scale may be required to accurately identify the spatial distribution of vulnerability at the local level and to identify suitable buffer zones for coastal protection and infrastructure development.

Types and components of Decision Support Systems

Different types of DSS can be distinguished. Power (2008[4]) lists the following types:

  • Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation. They can include physical, ecological and economic simulation and optimization models, to be used in interactive mode in the decision-making process. They help in the analysis of possible trade-offs, in the development of 'What if …?' scenarios and in conflict situations for the identification of the most suitable solutions.
  • Communication support DSS allow diverse groups of people to participate in decision-making processes and to work on a shared task. Tools include groupware, bulletin boards, audio and videoconferencing and other (web-based) systems to support collaborative decision making. They help multidisciplinary teams involved in the analysis of a coastal problem to establish a 'common language' and think in a structured way. Criteria, objectives and constraints about the problem become more explicit through the shared decision-making process.
  • Data-driven DSS or data-oriented decision support systems enable access to and manipulation of spatial geo-referenced data (actual and historical) and time series data. The graphic features support communication between stakeholders with different backgrounds. Visual aids are important for audiences that are composed not only by experts but also by the general public.
  • Document-driven DSS manage, retrieve and analyze unstructured or semi-structured information in electronic documents. They can integrate different types of knowledge and information from different disciplines and perspectives; search and retrieval facilities are therefore important components.
  • Knowledge-driven DSS provides specialized problem solving expertise stored as facts, rules, procedures, or otherwise.

A simple and flexible user interface is an important component of a Decision Support System. It allows users to provide information, select scenarios or alternatives, and inspect model or analysis results. An effective user interface facilitates communication and increases acceptance of the system by its intended users, including coastal managers, policy makers, decision makers and other stakeholders.

Decision support tools and methods

Two important decision support tools are MCDA and GIS.

Multi-Criteria Decision Analysis (MCDA)

Multi-Criteria Decision Analysis (MCDA) comprises methods for comparing alternative policy or management options according to multiple criteria. Criteria can be assessed using model results and other quantitative information, but can also incorporate the knowledge, experience, expectations, interests and concerns of experts and stakeholders. MCDA can therefore support decisions involving objectives and impacts that cannot all be quantified or expressed in common units. This aspect is particularly important for coastal management planning, which may require the simultaneous consideration of economic, social, cultural and ethical values. See the article Multicriteria techniques for further details.

Geographic Information Systems (GIS)

Geographic Information Systems (GIS) are important decision support tools for storing, combining, analysing and visualizing spatial information. GIS can integrate physical, ecological and socioeconomic data and display the spatial consequences of alternative management measures. It can be combined with MCDA by assigning scores and weights to spatial criteria to identify areas with different management priorities. GIS is also widely used to map coastal hazards, vulnerability and resilience and can support stakeholder communication by presenting complex spatial information in an accessible form.


Qualitative tools can also support deliberation rather than numerical evaluation. An example is the Quasta tool described in Stakeholder analysis, which helps structure stakeholder involvement in a decision-making process.


Related articles

Multicriteria techniques
Integrated Coastal Zone Management (ICZM)
Policy instruments for integrated coastal zone management
Input-output matrix


References

  1. ↑ Welp M. (2001). The use of decision support tools in participatory river basin management. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 26 7-8, 535-539.
  2. ↑ Turschwell, M.P., Hayes, M.A., Lacharite, M., Abundo, M., Adams, J., Blanchard, J., Brain, E., Buelow, C.A., Bulman, C., Condie, S.A., Connolly, R.M., Dutton, I., Fulton, E.A., Gallagher, S., Maynard, D., Pethybridge, H., Plaganyi, E., Porobic, J., Taelman, S.E., Trebilco, R., Woods, G. and Brown, C.J. 2022. A review of support tools to assess multi-sector interactions in the emerging offshore Blue Economy. Environmental Science and Policy 133: 203–214
  3. ↑ Barzehkar, M., Parnell, K.E., Soomere, T., Dragovich, D. and Engstrom, J. 2021. Decision support tools, systems and indices for sustainable coastal planning and management: A review. Ocean and Coastal Management 212, 105813
  4. ↑ Power, D.J. 2008. Decision Support Systems: A Historical Overview. In: Handbook on Decision Support Systems 1. International Handbooks on Information Systems. Springer, Berlin, Heidelberg.


The main authors of this article are Margaretha Breil and Job Dronkers
Please note that others may also have edited the contents of this article.
Citation: Margaretha Breil; Job Dronkers; (2026): Decision support systems and tools. Available from http://www.coastalwiki.org/wiki/Decision_support_systems_and_tools [accessed on 4-10-2026]
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