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Water resources systems are usually characterized by multiple interdependent components that together result in complex technical, economic, social and environmental process.

Planners and experts working to improve the performance of these complex systems must identify and evaluate alternatives to inform decision makers.

Models that can integrate diverse knowledge across a range of processes (for instance, hydrological, economical, social and environmental) are essential to evaluate, understand and to make trade-offs. The importance of integrating models or tools to augment the effectiveness of planning, and management decision-making process has been acknowledged in literature (see for example, Cai et al., 2003; Loucks and van Beek, 2005;

Pahl-Wostl, 2007; Liu et al., 2008; Grundmann et al., 2012; Carmona et al., 2013; Zagonari and Rossi, 2013).

Given the demand for the development and use of integrated approaches to assist with water resources planning and management decision-making processes, this section presents some fundamental issues constituted behind integrated model development and common modeling approaches.

2.1.1 The Integrated Water Resources Management Concept

The concept of integrated water resources management has been developing since the past few decades as a response to the growing pressure on our water resources system caused by growing demographic and socio-economic changes. The Global water partnership (GWP) has defined IWRM as:

“a process which promotes the co-ordinated development and management of water, land and related resources, in order to maximize the resultant economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems” (GWP, 2000).

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This insight led to the idea that the water resources system and its variety of users should be studied in an integrated manner.

The primary challenge to proceed with the concept of the IWRM is lack of consensus what is meant by integration in the context of water resources management. This necessitates identifying different processes that need to be integrated – so that management options for a problem in one part of a water system do not lead to the emergence of another problem somewhere else in the system. The evolving concept of integration of processes in the context of water resources management has the following main dimensions according to Jakeman and Letcher (2003):

 Integration of issues – this is an initial step in integration, which is intended to combine or integrate different issues (e.g., hydrological, economic, social and environmental issues). It is aimed at looking various parts of the system as a whole to avoid potential negative effects of management options.

 Integration with stakeholders – embedded in the IWRM concept, there is an essence that integrated modeling specifically intended to support decision-making demand an interdisciplinary and participatory process to allow a better understanding of complex phenomena (Rotmans and Van Asselt, 1996; Carmona et al., 2013). Close involvement of stakeholders is key for better decision implementation, as participation provides the means to foster communication, integration of knowledge, encourage social learning and improve understanding of the system by including local knowledge (Voinov and Bousquet, 2010).

 Integration of scales of consideration – water resources systems involve feedbacks across multiple scales. Components of the system may often be considered at a variety of spatial and temporal scales. In integrated modeling for supporting management decisions, the selection of scales may depend on factors such as: data availability and computational limitations, intended end users or stakeholders, model components representing different processes and their linkage.

These types of integrations are not mutually exclusive. There are diverse mechanisms to accommodate the specific requirements of integration – starting with identification of issues to be treated with coupling models representing the processes, up to approaches that incorporate knowledge from different sources into models and communication of results.

Stakeholder participation is an important feature of all these integration processes. See also the decision-making process cycle with its main steps and the area of influence of participatory planning, simulation-optimization modeling and decision analysis in section 1.3.1 above, Fig. 4.

2.1.2 Issues to be Considered for Model Choice

While choosing a modeling approach to be used in water resources management, it is central to reflect on some fundamental issues such as: purpose of the model, availability of data and intended end users of the model as well as requirements on the format and scale of the model outputs.

In the context of IWRM, models are primarily developed and employed to serve one or more of purposes like: management and decision-making under uncertainty, prediction, forecasting and social learning. There is usually overlap among these models and their purposes are not mutually exclusive. Management and decision-making under uncertainty is intended to offer a framework for making decisions in a systematic and rational way.

Different models may serve this purpose; these models may be simulation-based and/or optimization-based models. Simulation models are developed to answer ‘what if’ type of questions, while optimization models are developed to provide the ‘best’ option under a given objective, subject to constraints. Simulation and optimization can be coupled to provide better insight into complex decision-making processes (see for example, Schütze and Schmitz, 2010; Grundmann et al., 2012; Carmona et al., 2013). Decision support models are generally employed to assist in evaluating alternatives to avoid future problems and consider likely learning opportunities from the decisions.

Data availability is another important factor that influences model choice. In wider context, data may be classified as qualitative or qualitative. Quantitative data refers to the measureable characteristics or fluxes in a system, while qualitative data refers to information obtained from expert opinion and/or stakeholder beliefs gathered in the form of interviews and surveys. Depending on the selected type of modeling approach, qualitative and qualitative data may be used for conceptualizing the underlying framework, or parameterization as well as calibration of the models.

The water resources decision-making is a complex process that involves the management of risk that may arise from various sources of uncertainties (Vucetic and Simonovic, 2011).

Uncertainty in models may be resulting from variability (probabilistic) and interpretation as

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well as lack of knowledge (fuzzy) and consequent ambiguity related to issues of complexity.

Therefore, how at best the uncertainties are treated in the process of model choice, development and output analysis is imperative to the effectiveness of management and decision-making processes. In an effort to incorporate uncertainties into modeling frameworks, it is important to pick a model that can explicitly deal with associated uncertainties. It is also important to pay attention to what type of uncertainties – probabilistic and/or fuzzy – a particular modeling framework can accommodate. Another important factor in the selection of models is the intended purpose of the model. For instance, in management and decision-support models, the end users may be more interested in evaluating the magnitude of impacts of alternative management options (or scenarios) rather than accurate prediction values (Reichert and Borsuk, 2005).

2.2 Common Approaches to Modeling Complex Water Resources