Hedwig van Delden

Selecting among five common modelling approaches for integrated environmental assessment and management

The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings. We review five common integrated modelling approaches.Model choice considers purpose, data type, scale and uncertainty treatment.We present a guiding framework for selecting the most appropriate approach.

Integration of multi-scale dynamic spatial models of socio-economic and physical processes for river basin management

Planners, policy-makers and their technicians have the difficult task to intervene in complex human-natural systems. It is not enough for them to focus on individual processes; rather it is necessary to address the system as a complex integral whole. In the given circumstances, integrated models as part of Policy Support Systems (PSS) can provide support. The MedAction PSS incorporates socio-economic and physical processes in a strongly coupled manner. It is implemented with the GEONAMICA application framework and is intended to support planning and policy making in the fields of land degradation, desertification, water management and sustainable farming. The objective of this paper is to provide some insight in the individual models, the model integration achieved, as well as the actual use of the MedAction PSS. For the latter an application example is developed. The paper also argues that technical and scientific aspects of Policy Support Systems are not the sole elements deciding on their use in practice and concludes with some lessons learned during the development and use of the MedAction PSS and similar systems. 2005 Elsevier Ltd. All rights reserved.

How Can We Make Progress with Decision Support Systems in Landscape and River Basin Management? Lessons Learned from a Comparative Analysis of Four Different Decision Support Systems

This article analyses the benefits and shortcomings of the recently developed decision support systems (DSS) FLUMAGIS, Elbe-DSS, CatchMODS, and MedAction. The analysis elaborates on the following aspects: (i) application area/decision problem, (ii) stakeholder interaction/users involved, (iii) structure of DSS/model structure, (iv) usage of the DSS, and finally (v) most important shortcomings. On the basis of this analysis, we formulate four criteria that we consider essential for the successful use of DSS in landscape and river basin management. The criteria relate to (i) system quality, (ii) user support and user training, (iii) perceived usefulness and (iv) user satisfaction. We can show that the availability of tools and technologies for DSS in landscape and river basin management is good to excellent. However, our investigations indicate that several problems have to be tackled. First of all, data availability and homogenisation, uncertainty analysis and uncertainty propagation and problems with model integration require further attention. Furthermore, the appropriate and methodological stakeholder interaction and the definition of ‘what end-users really need and want’ have been documented as general shortcomings of all four examples of DSS. Thus, we propose an iterative development process that enables social learning of the different groups involved in the development process, because it is easier to design a DSS for a group of stakeholders who actively participate in an iterative process. We also identify two important lines of further development in DSS: the use of interactive visualization tools and the methodology of optimization to inform scenario elaboration and evaluate trade-offs among environmental measures and management alternatives.

Combining Two Approaches of Integrated Scenario Development to Combat Desertification in the Guadalentín Watershed, Spain

Desertification in Spain is a largely society-driven process, which can be managed effectively only through an understanding of environmental, sociocultural, and economic driving forces. This calls for a more active role of decision makers and other stakeholders. We present two promising approaches—participatory stakeholder workshops and a spatial policy support system (PoSS)—to develop future scenarios of land-use change for a watershed in Spain. We furthermore discuss the efforts involved and the added values of combining both methods. Based on two local workshops, three scenarios were constructed, which were subsequently formalised, parameterised, and quantified. We conclude that there are large advantages of linking narrative storylines and a spatial PoSS. Storylines ensure an active participation of a large range of stakeholders, additionally offering the possibility to develop highly integrated scenarios. The PoSS provides a spatially detailed and quantitative output, that can also be used to check the internal consistency of the qualitative scenarios. Linking stories and models can thus open the way for more successful management strategies to combat land degradation.

A review of current calibration and validation practices in land-change modeling

Land-change models are increasingly used to explore land-change dynamics, as well as for policy analyses and scenario studies. In this paper we review calibration and validation approaches adopted for recently published applications of land-change models. We found that statistical analyses and automated procedures are the two most common calibration approaches, while expert knowledge, manual calibration, and transfer of parameters from other applications are less frequently used. Validation of model results is predominantly based on locational accuracy assessment, while a small fraction of the applications assessed the accuracy of the generated land-use or land-cover patterns. Of the reviewed model applications, thirty-one percent did not report any validation. We argue that to mature as a scientific tool, and to gain credibility for scenario studies and policy assessments, the validation of land-change models requires consideration of challenges posed by uncertainty, complexity, and non-stationarity of land-change processes, and equifinality and multifinality of land-change models.

Measuring the neighbourhood effect to calibrate land use models

Abstract Many spatially explicit land use models include the neighbourhood effect as a driver of land use changes. The neighbourhood effect includes the inertia of land uses over time, the conversion from one land use to another, and the attraction or repulsion of surrounding land uses. The neighbourhood effect is expressed in the neighbourhood rules, but calibration of the neighbourhood rules is not straightforward. This paper aims to characterise the neighbourhood effect of observed land use changes and use this information to improve the calibration of land use models. We measured the over- and underrepresentation of land uses in the neighbourhood of observed land use changes using a modified version of the enrichment factor. Enrichment factors of observed land use changes in Germany between 1990 and 2000 indicate that the neighbourhood effect exists. This suggests that it is appropriate to use neighbourhood rules to simulate urban land use changes. Observed enrichment factors were used to calibrate a land use model for Germany from 1990 to 2000 and the obtained neighbourhood rules were validated independently from 2000 to 2006. The results show that both the allocation accuracy and the pattern accuracy of the land use model improved for the calibration period, as well as for the independent validation period. This indicates that enrichment factors can be used to improve the calibration of the neighbourhood rules in land use models.

An Activity-Based Cellular Automaton Model to Simulate Land-Use Dynamics

In recent decades several methods have been proposed to simulate land-use changes in a spatially explicit way. In these models land is generally represented on a lattice with cell states indicating the predominant land use. Since a cell can have only one state, mixed land uses and different densities of one land use can only be introduced superficially, as separate cell states. In this paper we describe a cellular automata model that simulates dynamics in both land uses and activities, where activities represent quantitative information, such as the number of inhabitants at a location. Therefore each cell has associated with it (1) a value representing one of a finite set of land-use classes, and (2) a vector of numerical values representing the quantity of each modelled activity that is present at that location. This allows simulation of incremental changes as well as mixed land uses. The proposed model is tested with a synthetic application that uses two activities: population and jobs. It simulates the emergence of human settlements over time from local interactions between activities and land uses. Assessment of results indicates that the model generates realistic urbanization patterns.

Linking Narrative Storylines and Quantitative Models to Combat Deserti ication in the Guadalentín Watershed (Spain)

Desertification in Spain is largely a society-driven problem, which can be effectively managed only through a thorough understanding of the principal ecological, sociocultural, and economic driving forces (UNCCD 1994). This calls for a more active role of decision-makers and other stakeholders. We present a promising approach, involving stakeholders in the scenario-development process and linking these narrative storylines with an integrated quantitative model. Within the framework of a larger EC-financed project, dealing with desertification in the Mediterranean region, multi-scale scenarios were developed for Europe, the Northern Mediterranean, and four local areas. In the same project, a policy-support system (PSS) was developed. The main objective of this exercise was to establish a link between the qualitative scenarios and the PSS for the watershed of the Guadalentin river in Spain. From the results of two scenario workshops, three scenarios were selected, all linked to the same Mediterranean scenario. Our selection aimed to maximize both the variety in the narrative storylines and the expected output of the PSS. The scenarios were subsequently formalized, ensuring that the same information was present for all three scenarios; semi-quantified (translated) by linking them to the main entry points of the PSS; and quantified by parameterizing the model. The results indicate the potential of the constructed quantitative scenarios. This chapter illustrates the practical potential and pitfalls of linking qualitative storylines and quantitative models. Future research should, however, also focus on the more fundamental theoretical obstacles that are easily overlooked.

New Ways of Supporting Decision Making: Linking Qualitative Storylines with Quantitative Modelling

To explore how people will live and work in Europe, what the landscape will look like and what the environmental consequences will be in some 35 years from now, the PRELUDE project (EEA 2007) of the European Environment Agency developed five different land-use scenarios for Europe. The project was carried out according to a Story And Simulation (SAS) approach in which, iteratively, storylines developed in participatory sessions are underpinned by land-use models. Storylines in this context are defined as narratives about future developments in Europe. They provide qualitative information on a broad range of issues in an integrated context.

Multi-objective optimisation framework for calibration of Cellular Automata land-use models

Abstract Modelling of land-use change plays an important role in many areas of environmental planning. However, land-use change models remain challenging to calibrate, as they contain many sensitive parameters, making the calibration process time-consuming. We present a multi-objective optimisation framework for automatic calibration of Cellular Automata land-use models with multiple dynamic land-use classes. The framework considers objectives related to locational agreement and landscape pattern structure, as well as the inherent stochasticity of land-use models. The framework was tested on the Randstad region in the Netherlands, identifying 77 model parameter sets that generated a Pareto front of optimal trade-off solutions between the objectives. A selection of these parameter sets was assessed further based on heuristic knowledge, evaluating the simulated output maps and parameter values to determine a final calibrated model. This research demonstrates that heuristic knowledge complements the evaluation of land-use models calibrated using formal optimisation methods.