8th International Coastal Symposium

Recent GIS based national assessments of climate change consequences in France.

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Recent GIS based national assessments of climate change consequences in France: methods, results and lessons learnt. Gonéri Le Cozannet†, Ahmed Ait-Kaci‡, Sébastien Colas∞, Xavier De Lacaze∞, Sophie Lecacheux†, Carola Mirgon†, Cédric Peinturier∞, Manuel Garcin† and Carlos Oliveros† †BRGM, 3, av. Guillemin, 45000 Orléans, France [email protected]

‡ BIPE, 11/13, rue René Jacques 92138 Issy-les-Moulineaux, France [email protected]

∞ MEDDE, French Ministry in charge of Environment, 92055 La Défense, Arche sud, France

www.cerf-jcr.org

ABSTRACT

www.JCRonline.org

Le Cozannet, G., Ait-Kaci, H., Colas, S., De Lacaze, X., Lecacheux, S., Mirgon, C., Peinturier, C., Garcin, M., and Oliveros, C., 2013. Recent GIS based national assessments of climate change consequences in France: methods, results and lessons learnt In: Conley, D.C., Masselink, G., Russell, P.E. and O’Hare, T.J. (eds.), Proceedings 12th International Coastal Symposium (Plymouth, England), Journal of Coastal Research, Special Issue No. 65, pp. 1421-1426, ISSN 0749-0208. This paper reviews two recent assessments undertaken in France for evaluating national scale consequences of global change for coastal hazards and risks, namely marine submersion and coastal erosion. In a first approach, the potential consequences of climate change were evaluated in a direct quantitative way, however with high uncertainties in the final evaluation. Recognizing that uncertainties could hardly be reduced, a second assessment based on a multi-criteria evaluation was then undertaken. Geomorphological and marine factors that account for physical vulnerability to coastal hazards were evaluated for 21 coastal entities in metropolitan France. The evaluation was structured using the analytical hierarchy process (AHP). The results highlighted the fact that in some specific regions such as Languedoc-Roussillon (Mediterranean coast) and Pertuis (Atlantic coast), the population is expected to increase more than the mean average, while the coastal zone are also likely to be more strongly affected by coastal hazards. While such national scale evaluations in highly diversified coastal environments are still arguable, they may help identifying unsustainability in current trends and help defining priorities for future adaptation strategies. ADDITIONAL INDEX WORDS: Climate change, global change, vulnerability, adaptation.

INTRODUCTION While it is almost certain that sea level rise will accelerate during the XXIst century, our ability to evaluate the consequences of this process in coastal areas is still limited (Nicholls & Cazenave, 2010). Even with little information, it is still considered as necessary to draw some outlines of future potential consequences of climate change for hazards and risks in coastal areas before developing adaptation strategies. Such sketches are also expected to provide useful information for evaluating development and risk prevention projects upon longer term perspectives. In France, the recent “Grenelle II” law requires adaptation strategies to be developed at regional level (administrative regions), based on evaluations of the territorial vulnerability. In this sense, vulnerability is understood as the expected long term implications of global change (Romieu et al., 2010), and not as its common sense in disaster risk management, where vulnerability of stakes is a component of risk. However, there is still much interest of national authorities for undertaking assessments of territorial vulnerability at national scale. Since the regulation favours the development of adaptation measures at the regional and local levels (e.g. Le Cozannet et al., 2013), we may wonder why national assessments are still required. In the case of the Netherlands, the modelling exercise of Horstmann et al. (2009) shows that a large scale adaptation strategy would be more efficient than adaptation measures focused ____________________ DOI: 10.2112/SI65-240.1 received 07 December 2012; accepted 06 March 2013. © Coastal Education & Research Foundation 2013

on single coastal sections. While this statement is undoubtedly true when a country needs to manage the risk of drastic marine submersions over a substantial part of its territory, it might be arguable in France. Indeed, a large part of the metropolitan French coastline is characterised by a multiplicity of hotspots disseminated along the coast on a wide variety of geomorphological landscapes, whose response to sea level rise will much vary (Paskoff, 2004). Thus, the response to coastal changes cannot be unique and national scale vulnerability assessments are more aimed at ensuring that (1) human and financial means for adaptation are allocated proportionally to the actual threats and (2) appropriate adaptation strategies or measures will be transported across administrative regions and promoted by the regulation framework (e.g. through the “national strategy for shoreline management” being currently developed). Consequently, under the impulsion of the ministry in charge of Environment, several assessments of the potential consequences of global change for coastal erosion and flooding hazards and risks have been undertaken at the national level in France since 2006. Fundamentally, these evaluations were all based on processing and analyses of public data within Geographical Information Systems (GIS). They consist in adaptations of two kinds of approaches:  quantitative direct evaluations – typically, such evaluations adapt a risk evaluation framework, in which simple maps depicting the potential extents of erosion and submersion were drawn and crossed with the asset at risks (Figure 1). The most typical example of such approach is probably the DIVA software (Hinkel and Klein, 2009), which provides evaluations

Journal of Coastal Research, Special Issue No. 65, 2013

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of potential damage costs due to climate change in coastal areas.  qualitative multicriteria evaluations – these approaches use available information on coastal geomorphology and marine forcing factors as concurring indications of the vulnerability. In the field of coastal vulnerability, this approach has been promoted through the well-known “Coastal Vulnerability Index” (CVI) proposed by Gornitz et al. (1991). An extension of this index was proposed by Boruff et al. (2005) to take into account the social component of vulnerability. While the results of such vulnerability assessments cannot be used for cost-advantage evaluations, they are relevant in participatory approaches aiming at evaluating the relevance of adaptation strategies and measures (Figure 2). This paper briefly reviews how a direct quantitative method was applied for France. It then presents the method and results of a qualitative multicriteria evaluation that followed shortly this first study. In discussion, this paper addresses the following questions: how useful are GIS assessments for helping decision making in adaptation of coastal zones? Can adaptation strategies be effectively inferred from these evaluations?

DIRECT QUANTITATIVE EVALUATION A first direct quantitative evaluation was undertaken in 2009 as part of the French Climate Plan, with the aim of rationalizing adaptation measures through cost advantage analyses (Le Cozannet et al., 2010).This first study adapted a risk evaluation framework, in which simple maps depicting the potential extents of erosion and submersion were drawn and crossed with the asset at risks. Then, the associated costs were evaluated using simple vulnerability functions and some public figures of coastal disaster macroeconomic costs. This approach was applied to the Languedoc-Roussillon Region in Southern Mediterranean France and the results were qualitatively up-scaled to metropolitan France by a board of experts in risk evaluation. Unsurprisingly, the results highlighted local critical situations in which hazard and its potential aggravation meets already existing urban, touristic and industrial assets, particularly in low lying areas, on sand spits and near to estuaries. They also suggested that in a long term perspective, the costs of erosion damage or of protection against erosion should increase significantly. However, the huge uncertainties associated to the results actually prevented from undertaking any convincing cost-benefit analysis. These uncertainties were related to the hazard and hazard change zonation (Yates et al., 2011). The main concern was actually the evaluation of potential damages costs which was considered unreliable due to the paucity of data on costs of coastal risks in France. Beyond the data issues, it was also suspected that many unknown would ever prevent from any accurate evaluation of costs and advantages, at least in the form hoped by users. Some concerns in this field were related to the choice of actualization rates and the unpredictability of the costs of damages, e.g. due to the fact that the costs of natural disasters are not limited to direct capital losses, as shown by Zylberberg (2010).

Figure 1. Framework of a quantitative direct approach of the vulnerability of the ‘natural’ coastal system itself, using the marine and geomorphological factors that cause physical vulnerability to erosion and inundation in the context of sea level rise; (2) an evaluation of potential future human changes in the coastal zone. Because the weighting in qualitative multicriteria approaches is known to be often subjective, we used a decision making approach, the Analytical Hierarchy Process (AHP, Saaty, 2008) in order to help defining the weights. The method aims at ranking a certain number of coastal entities upon their physical vulnerability. It proceeds similarly to in Le Cozannet et al. (2013), however with application to different geographical entities and scales. The main steps in this approach are presented below.

Selection of coastal entities The first step is to select the geographical entities to which the evaluation will apply. Since one objective of the national scale assessment is to identify where more human and financial means would be needed, these entities could be administrative regions or at least entities where public action is possible. In this prospective study, it was hypothesized that a future public authority would act at the scale of a limited number of coastal entities, defined as relatively homogeneous from a coastal geomorphological point of view. The idea behind is the same as what already exists for water management with watershed agencies acting at the scale of hydrosystems. Here, 21 entities were selected and cut upon coastal and hinterland geomorphological criteria (Figure 3). In summary, this provides rather homogeneous entities in Mediterranean France, from Belgium to the Seine estuary and from the Gironde estuary to Spain. It is more arguable between the Seine estuary and the Gironde estuary. Whatever the relevance of this delineation, it is then hypothesized that public authorities want to know how threats are distributed among these entities.

MULTICRITERIA EVALUATION: METHOD Principles Recognizing that it would not be possible to perform a direct quantitative assessment with a sufficient accuracy to inform decision making, we undertook to use a qualitative multicriteria approach to identify unsustainable trends in the coastal zone in a more qualitative manner. This analysis included (1) an assessment

Figure 2. Scheme showing how vulnerability mapping exercises can be used in a participatory approach for evaluating the relevance of adaptation measures (after Hallegatte, 2009). The evaluation of adaptation measure may follow a multicriteria analysis of costs and advantages of adaptation measures that are reviewed. CGDD/SOeS (2012) shows recommendations for practical implementations of such approaches for support to public authority’s decision making in flood disaster prevention.



Table 2. Extract of the pairwise comparison matrix produced for comparing the 21 entities with respect to the criterion “storm surge” (method in Saaty, 2008). The real size of the matrix is 21x21. West Basque Flemish ... Relative corsica coast plain importance 1 2 5 ... 0.014 West corsica 1/2 1 4 ... 0.022 Basque coast 1/5 1/4 1 ... 0.089 Flemish plain ... ... ... ... ... ...

Defining vulnerability criteria The second step is to define the criteria (and associated data) that will help to evaluate the physical vulnerability of these entities. Here, consistently with previous studies (e.g. Gornitz et al., 1994), we selected nine criteria that can be gathered in three categories: marine, state and context factors (Table 1). These criteria include:  Marine factors that help identifying the coastal entities the most exposed to hydrodynamic processes. While the accuracy of these datasets would be a matter of discussion for other applications, they are considered sufficient in this qualitative evaluation. Moreover, the Eurosion dataset (www.eurosion.org) has the advantage of being homogeneous at the scale of the study.  State factors, that corresponds to the geomorphology in the coastal zones in the selected entities. We consider here the coastal geomorphology (Beaches, cliffs, coastal swamp, artificialized coast, etc.), the topography (zones located bellow an elicited maximum expected sea level during an extreme event) and the lithology, which provides information on the susceptibility of erosion in the selected entities.  Context factors allow differentiating zones that benefit from sediment inputs from those that face chronic erosion.

GIS processing and “Radius of influence of coastal hazards” The third step is to extract from the GIS database the information associated with each of this criterion and to evaluate how they will worsen or reduce physical vulnerability (Table 1). This step includes most of the GIS processing. In particular, it is necessary here to define a zone within which the coastal hazards will be contained during the 21st century. The approach is similar to the definition of the “radius of influence of coastal erosion” in the Eurosion project. This is done here by defining a zone which encompasses: an envelope of the maximum extent of areas affected by coastal erosion by 2070; this is done by defining:  a 500m buffer zone around beaches (200m around erodible cliffs coastlines)  an envelope of the maximum extent of marine submersion: this is done by extracting area lying bellow the centennial sea level, plus one meter, to take into account future sea level rise (IGN and SHOM data processed by the French State technical services (Cete-Cetmef) and BRGM). The resulting zone is named “radius of influence of coastal hazards” (Ricoh) bellow. It enables an identification of the maximum number of stakes at risks at decadal to centennial timescales.

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Pairwise comparison of coastal entities In a fourth step, each entity is compared to the others with respect to each criterion. The AHP (Saaty, 2008) is used here to build pairwise comparison matrices that enable to compute the relative importance of each entity in explaining physical vulnerability with respect to a criterion. One strength of the method is that it enables to incorporate quantitative data together with qualitative opinion. This is done using a scale that helps defining, based on expert’s opinion, the relative importance of the difference between two entities with respect to a criterion. Let’s take for example the criterion “storm surge”: this data exists in the database of the marine hydrodynamic institute (SHOM) database along the Atlantic coast. However, experts are qualitatively able to state that the surges are less high in Mediterranean Sea than in Atlantic. This parameter is thus judged less important in west Corsica than for the Basque coast or strong the Flemish plain (difference of importance of 2 and 5 respectively in Saaty’s scale). This enables to construct a pairwise comparison matrix that is used to compute the relative importance of the criterion “storm surge” for all 21 coastal entities contributing to coastal vulnerability (Table 2). The relative importance is calculated according to Saaty (2008) by “raising the matrix to large power and summing each row and dividing each by the total sum of all the rows”. This process is repeated for each criterion. For this study, ten 21x21 matrices are elaborated.

Final evaluation Finally, the last step is to combine all these criteria for a final evaluation. This is done by a weighted summation of the values obtained for each criterion. The weights in this sum are obtained using the same approach. For example, it was considered that the state factors were the most important ones in evaluating physical vulnerability (difference of importance of 5 with marine factors in Saaty’s scale and 3 with context factors). The subjective explanation for this is that much of the future evolution of the coastal area can be deducted from observations of the present landforms, which are describe in the state factors in this study. We note for example that Cooper and Jay (2002) based their predictions of large-scale coastal trends mainly on the categorization of coastal landforms. These considerations, although recognized rough, help assigning weights to each criterion for the final evaluation (Figure 4). Once the final

Figure 3. Coastal entities used in this study.


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Table 1. Criteria chosen for evaluating physical vulnerability of coastal entities and associated data source. Criteria Reasons for higher coastal Associated GIS modellingfor each coastal entity vulnerability Marine factors (29 virtual point locations off the French metropolitan coast); data source: Eurosion, SHOM, expert elicitation Tidal range, mean wave Lower values of tidal range, higher heigths, centenial surge, mean Each entity receives the value of the closest virtual waves, surge and observed sea levels heigth of 10% highest waves, point in the Eurosion database. rates. observed sea level rise State factors; data source: IGN, BRGM, Eurosion Topography lithology, Low lying areas, soft lithologies and Calculation of (1) surfaces of zones located bellow an geomorphology erodible coastal geomorphologies. elicited maximum expected sea level during an extreme event, (2) surfaces of soft lithologies within the “Ricoh” and (3) length of the erodible coastal geomorphologies Context factors; data source: Eurosion, Corine Land Cover Historical erosion, Areas currently affected by erosion face Calculation of the length of coastline affected by anthropisation chronic sediment deficit; Higher erosion. Within each coastal entity and associated urbanisation reduces possibilities for watershed, calculation agriculture and urbanised sediment mobility. surfaces. summation is done, the 21 coastal entities can be ranked upon their physical vulnerability.

2003 by the group of official statistics Languedoc-Roussillon "in all [demographic] scenarios, coastal areas [of LanguedocRoussillon] should stay ahead of population growth until 2030".

Assessment of human changes Modifications of hazards are only one aspect of the consequences of global change in the coastal zones, the other being the human changes (e.g. Nicholls et al., 2008). Here, a first simple assessment of future human changes in French coastal zones by 2050/2070 was performed. A demographic model was run at the national scale, under the assumption that the present demographic trends would continue during this time period. The model takes account of birth rates, mortality, migrations and computes economic growth and interregional migrations to infer a scenario for population in each administrative region. This model does not claim predicting a unique plausible demographic scenario. On the contrary, it was aimed at identifying unsustainable trends in present development across a number of economic sectors. These regional demographic scenarios are used to define storylines of demography in the “Ricoh” zone:  a “preventive scenario” in which population in the Ricoh is not increasing; this scenario could be the consequence of a national strategy in favor of prevention of coastal risks;  a “moderate population increase scenario”, in which demographics in the Ricoh follows the trends in the regions associated to each coastal entity;  an “attractive scenario” in which population growth in the Ricoh is twice as large as the trend in the associated regions. An important limitation is the resolution of existing population densities. In order to estimate the population living in the “Ricoh” for each coastal entity, we used data from the national institute for statistics, which provides estimates of population densities at the resolution of a 200m grid in France (INSEE, 2009). Under the present trends, it seems that the third scenario would be the most plausible, at least in the near future. For example, according to the work of prospective population conducted in

Figure 4. Weightings used in this multicriteria approach.

RESULTS Physical component of vulnerability Results of the application of this qualitative multicriteria approach to the 21 coastal entities are presented in Figure 5. These results can be presented in the form of a ranking of these 21 coastal entities, from the most vulnerable to the least vulnerable. The evaluation focuses on the physical component of vulnerability of coastal systems to marine submersion and coastal erosion, in the context of climate change. By construction, this ranking favors larger coastal entities. As a summary, the results highlight the higher vulnerability of the entities “Pertuis”, “Languedoc and Rhône Delta” and “Aquitaine”. This is not surprising since these areas are characterized by large low lying areas and/or erodible coasts. The next entities are south and north Bretagne, then followed by the French part of the Flemish plain. In Bretagne, the high vulnerability is explained by the size of the coastal entities themselves, the number of small to medium scale vulnerable coastal systems disseminated along the coast and the total length of beaches presently affected by erosion. In the Flemish plain, the size of low lying area and areas bellow mean sea level accounts for the ranking. However, in this region, the questions of the long term evolution of shoreline, of the changes in flooding hazard and of adaptation cannot be disconnected from the maintenance of protective infrastructures against flooding. The least vulnerable entities include smaller regions, characterized by cliffs, thus with few low lying areas (e.g. Basque, North Cotentin, Opale, Albâtre and Vermeille coasts). We note also that although the entities corresponding to major estuaries are the smallest entities (Seine, Gironde, Loire), they lie in the middle of the ranking. The results are not sensitive to slight changes in the weighting of criteria. The reason for this is the following: we defined the 21 coastal entities according to their geological and geomorphological features. On the other hand, the same features are an important component in the evaluation of vulnerability. The coastal entities are thus delineated in a way that the state factors are most discriminating.



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Figure 5. Results of qualitative multicriteria evaluation for state factors (A) and coastal vulnerability (B). (C): Suggested regional scale adaptation strategies according to coastal entities profiles.

Population evolution

Limitations

Figure 6 provides an evaluation of the population evolution within the “radius of influence of coastal hazards” of each coastal entity, according to the three scenarios detailed above. The largest population is in the Flemish plain and Pertuis entities (due to the vast low lying areas) and in the French Riviera (due to important coastal cities). In scenarios 2 and 3, the population growth is most important along the Atlantic coast from Bretagne to the Spain boarder and along the Mediterranean coastline. The French Riviera appears as the least vulnerable entity with regards to the coastal erosion and marine submersion hazards. This is mainly due to the fact that low lying coastal areas remain quite small. On the other hand, other entities have few possibilities to further urbanize their Ricoh zones, either because it is already very anthropised (e.g. in the entities: Basque coast, Languedoc-Roussillon) or because the Ricoh zone is covered by forests (Aquitaine) and coastal marshes (Bretagne). Finally, in the Pertuis zone, 73% of the Ricoh zone is made of agricultural land according to the Corine Land Cover data. Since urbanized areas are primarily taken from agricultural land in recent urban development, this suggests that the Pertuis zone has the potential either to further increase its coastal vulnerability by allowing further sparse urbanization, or possibly to adapt by limiting it in the radius of influence of coastal hazards. Field surveys in this area moderate this judgment and show that in many places, the urbanization follows the limits of low lying wetlands used for agricultural purposes. Still, these considerations were used to build a decision tree in order to suggest adaptation strategies adapted to the profile of each coastal entity (Figure 5.C).

Using public GIS data for evaluating the potential consequences of sea level rise, we reach the limits of these data in terms of accuracy (e.g. positioning of the coastline), resolution, precision (e.g. DEM), and sometimes inadequacy of the database for our application (e.g. description of agricultural area that are actually located in wetlands). The lack of data also prevents from addressing potential interactions with local scale. For example, data on dunes heights, width and potential fragility points would

Figure 6. Evaluation of population evolution scenarios in the coastal zones for each EREN (INSEE data processed by BIPE and BRGM).


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be needed. Finally, one most important limitation remains the rough delineation of the “radius of influence of coastal hazards”.

DISCUSSION How useful are such GIS assessments for helping decision making in adaptation of coastal zones? The direct quantitative assessment was intended to investigate how cost-efficient adaptation was. However, as recognized by the members of the working group in charge of this assessment, the final economic figures were unreliable. A secondary objective was to support adaptation measures. However, the adaptation measures proposed were actually developed independently from the assessment of potential consequences of climate change. This suggests that such direct quantitative approaches can hardly reach their goal in national scale applications in countries such as France, where many different kind of coastal erosion and marine submersion risk hotspots are disseminated along the coast. They should be kept for applications where hazard and risks can be accurately evaluated (see e.g. Hallegatte et al. 2011)). While the qualitative multicriteria approach is an attractive alternative to direct quantitative approaches, its application at the national scale raises many difficulties, including the selection and weighting of various criteria accounting for vulnerability, the use of data at the limit of their resolution, accuracy and precision. Meetings with a group of users suggested that a part of them considered that AHP was adding confidence in the results at national scale. Another criticism to the qualitative multicriteria approach was that a qualitative assessment based on expert opinion would possibly have produced similar conclusions. This might result from confusion of what GIS analyses are. From our opinion, GIS assessments can just aggregate and represent already existing knowledge through maps or figures. They cannot substitute to unknowns. Finally, we felt that these exchanges with users suggested that increased communication between scientists, GIS analysts and national decision making was still needed in this field, although much effort has been made from those parts in recent years (e.g. Planton et al., 2012). As a positive outcome, it was recognized that some adaptation options may be inferred from the qualitative multicriteria evaluation, suggesting that beyond the results and details in application, this type of GIS approach might be useful in helping decision makers to identify relevant adaptation options at scales relevant for public actions.

CONCLUSION This study concludes that it may be possible to inform decision making by analyzing together the present trends in human pressures on the coastal zones together with the profile of physical vulnerability to coastal erosion and marine erosion in the context of sea level rise. Through an example at national scale in France, we identified potential adaptation options for coastal entities, which were hypothesized to be relevant for public action in the future. The approach presented here enables to perform a preliminary identification of areas that are the most eager to further increase their maladaptation. This is the case along the Atlantic coast, between Bretagne and the Gironde estuary according to our results. In France, the recently approved law in favor of adaptation force scientists and coastal managers to work together on developing adaptation strategies for coastal areas. This study is a contribution to this effort at national scale. However, much interaction between science, GIS analysts and decision makers are still needed before the concepts presented in this paper are effectively stabilized and converted into appropriate actions.

ACKNOWLEDGEMENT This work was supported by the Ministry of Environment through the Directorates for Water & Biodiversity (Explore 2070 project) and for Risk Prevention. This article reflects the sole views of its authors. It does not necessarily replicate those of the French Ministry of Environment. We thank two anonymous reviewers for their positive comments.

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8th International Coastal Symposium

8th International Coastal Symposium

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