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MobiTC, automatic calculation of the historical shoreline changes ...

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examples on three different coastal morphologies ... Europôle de l'Arbois, BP80, 13545 Aix-en-Provence Cedex 04, France – email : [email protected] ... (2009)) is the automation of the baseline for calculations and the implementation of ...
ICSE6 Paris - August 27-31, 2012

- Trmal, Pons and Sabatier

ICSE6-184

MobiTC, automatic calculation of the historical shoreline changes: examples on three different coastal morphologies Céline TRMAL1, Frédéric PONS1, François SABATIER2 1

Centre d’Étude Techniques de l’Équipement Méditerranée CS 70499, 13593 Aix-en-Provence Cedex 3, France - email : [email protected] ; [email protected] 2

Aix Marseille Université, Centre Européen de Recherche et d'Enseignement des Géosciences de l'Environnement Europôle de l'Arbois, BP80, 13545 Aix-en-Provence Cedex 04, France – email : [email protected]

CETE Méditerranée developed a software, MobiTC, to predict historical shoreline change, with a willing of rapidity and simplicity. The originality of the software in comparison with other similar software is the automation of a baseline for calculations, statistics are carried out transects by transects, which are perpendicular to the baseline. The baseline goes throught the historical shorelines and so follows the general shoreline shape. This method improves the calculations and allows to predict the shoreline evolution, in one step, along a long shoreline or along a complex coastal morphology such as sand spit or successive bays. MobiTC includes the state of the art of shoreline change rate calculation, by using also metadata such as the shoreline uncertainties. The results are then visualized in such a way that they help the user to interpret the results. In this article, the possibilities of MobiTC will be illustrated by its application on three different Mediterranean coastal morphologies: a pocket beach, a long sandy beach and a sand spit.

Key words Coastal erosion, shoreline, shoreline change rates, mapping, software

I

INTRODUCTION

Nowadays, in France it appears necessary to simplify and homogenize the analysis of shoreline changes. The public policies in particular through the national strategy on coastal management and coastal hazard prevention are the first targets. To fulfil this need, it appeared necessary to develop a tool, simple and fast to implement, integrating the state of the art and providing homogeneous indicators everywhere. The originality of MobiTC compare to other similar software like DSAS (an ArcGis extension, Himmelstoss (2009)) is the automation of the baseline for calculations and the implementation of numerous statistical methods to calculate the shoreline change rate but also to carry out rhythmic analysis. It uses the different positions of the shoreline over time but also the metadata of the historical shorelines. For example, information on the acquisition method of the shoreline, their errors are taken in account. It procures also a way of capitalizing the historical shorelines. Graphics and mapping of the different indicators calculated help the user at the interpretation of the results. MobiTC is free, self-sufficient and compatible with most of the GIS software thanks to the different export/import such as the mif/mid format. The three examples presented in this article show the different possibilities of MobiTC on different types of coast. II

THE AUTOMATISED GENERATION OF THE BASELINE

In the literature, most of the studies of the shoreline change rate are carried out by noting all the positions of historical shorelines along transects that are perpendicular to the baseline. Thus the shape of the baseline conditions transects and so influences the calculation of the erosion rate.

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This baseline is in general, for not saying always, done by hand and follows more or less the general shape of the coast. This step can become fastidious over long coast line of several kilometres, in particular in the case of complex shoreline morphology and so can be subjective and not reproducible. One of the originality of MobiTC is to generate a baseline automatically, this time it follows the coast shape. The principle of the generation is based on the skeleton. The skeleton is the easiest and simplest way for representing the mean lines of a shape (Pons, 2010). Here, the shape is the envelope containing all the historical shorelines. This envelope is obtained by a triangulation based on points along each shoreline with a threshold on the element length. The skeleton computed in MobiTC uses the Voronoi diagrams. Figure 1 illustrates the different steps to obtain the baseline.

Historical shorelines

Triangularisation based on points on the historical shorelines

Outline kept as the envelope of the historical shorelines

Voronoï diagrams from points on the envelope

Skeleton kept as the baseline, which follows the historical shorelines

Figure 1 Steps for creation of the skeleton

Transects are then generated perpendicular to that baseline and all the calculations are based on the intersections between historical shorelines and transects. III

USE OF THE METADATA IN MOBITC

MobiTC uses in its calculations the metadata of the historical shorelines. The user can save them in a special spread sheet compatible with MobiTC. The name of the GIS layer of the shoreline, also contains the main metadata (date, type of shoreline, error...) III.1

Dealing with the shoreline errors in MobiTC

Errors linked to the shoreline can be classified in two main categories:  errors inherent to the position of the shoreline, they come from : the means used for the land survey or digitalization by photo-interpretation, to the meteorological conditions... For instance, Crowell et al. (1991) estimated the different errors that are adding when digitalizing the shoreline from aerial photographs or from T-sheets.  errors linked to the date of the shoreline, they are often due directly to a lack of rigour when storing the metadata on the shoreline. Those errors are taking into account in MobiTC by first the visualisation of an error bar both on the position and on the date in the graphs representing the shoreline rate, transect by transect and also in the calculation of different parameters of the shoreline change. An example is the calculation of linear trend by the weighted least square (WLS in Genz et al. 2007). Each historical shoreline is weighted by the inverse of the square error.

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Other visualisations of the metadata

The visualization of the calculation transect by transect take the form of graphs that represents the position of the historical shorelines over the years. On the graphs, by the shape of the symbol representing the position of the coastline the user can know the nature of the coastline (land survey or digitalization), its colour matching the type of limit used to define the coastline (25 types of limits were found: foot cliff ...). The owners of the coastlines are also explicitly mentioned. Figure 3 shows two examples. IV IV.1

HELPS FOR THE ANALYSES OF THE RESULTS Different statistical methods for the evolution rate

In order to guide the user through a robust analysis of the mobility of the coastline, a number of statistical methods identified in the literature are implemented. Concerning the evolutions transect by transect, Genz and al. (2007) realised a complete and critical list of them. At present MobiTC integrates the calculation of the linear tend with confidence intervals, the linear trend with weighted uncertainties of the shoreline, a factor of complexity of the model allowing to detect nonlinear trends and the changes of tendency (Fenster and Dolan, 1994). It is also possible to study the distributions of every parameter (e.g. linear trend) along the baseline. The calculation of the spectrum also allows to determine the cyclic forms of the coast as well as their wavelength (Walton, 1999). The forward objective is to integrate a maximum of calculation method into MobiTC while guiding the user in the judgment of their relevance. IV.2

Simultaneous GIS visualisations

A particular care was given to the depictions and outputs of MobiTC. The objective is to avoid at most the boring operations of shaping of the results by familiar or not users with GIS. It is first of all possible to display the various parameters at the same time with by default an highlighting of the problems. For example on figure 4 and figure 5, when a coefficient of regression close to 0 appears in black, the trend is not valid. Also when the number of shoreline is low, it appears in dark orange. It is also possible to treat simultaneously several sectors. The calculation of the baseline is made from all the shoreline available on the various sectors. So there are as many baselines as sectors. This allows in the end to have the same scales of colour for all the sectors. The user can so estimate, compare a sector with regard to another one and rank them. V

THREE EXAMPLES ON DIFFERENT COASTAL MORPHOLOGIES

During its development MobiTC was tested on several coastal configurations in order to adapt it to all the coastal geometries. The objective is still to limit at most the manipulations of files or software. Below three examples of configuration of sandy coast are presented. It should be noted that the tool was also tested successfully on coast with cliffs in La Manche. The results (rate of evolution,… ) of these 3 examples are not to be looked as such, these sectors were studied for the validation of MobiTC, the results can be inaccurate because certain shorelines did not contain enough metadata (inaccurate date, way of acquisition and precision unknown). V.1

Test 1: a pocket beach

On this pocket beach (figures 2 and 3), about ten shorelines were digitized from vertical aerial. This example illustrates the fact that the baseline generated in an automatic way follows the mean shape of the coastline. In Figure 3, the result of the ordinary least square is shown. Those graphs produced for each transect, keep records of the type of shorelines (for instance, the swash limit here), their owners. In the first transect the evolution rate is well evaluated by a linear trend whereas on the second transect the positions are more fitted by a quadratic model. The inflexion date in the case is 1993. The user should then identify physical changes within the beach around the date before used it.

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Regression coefficient 90% upper confidence interval (m/yr)

Linear evolution rate (m/yr) 90% lower confidence interval (m/yr)

Figure 2 Processing of a pocket beach

Figure 3. Example of output graphs on two transects (number 4 and 58 of figure 2)

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Test 2: a long sandy beach

In this example all the French Camargue, built up by the delta of the Rhône (baseline of 88 km) was treated all in one go. Sixteen historical shorelines were used. They were not worked again so as to clean estuaries, what would improve the baseline. Moreover for the realization of the baseline, 1823, 1841 and 1895 were not selected because those shorelines contained numerous islands at the level of the delta of the Rhône but used in the trend calculations. Figure 4 represents the baseline and the results, by displaying concerns, transects are spaced out by a kilometre. The selected displays are the number of date in gradation of orange, the coefficient of regression of the linear fitting in black's gradation and the linear rate of evolution in gradation of red to green. Figure 4 Processing of a long sandy beach

Number of historical shorelines

Regression coefficient

Linear evolution rate (m/yr)

V.3

Test3: a sand spit

The last tested sector of this article is the Gracieuse sandy spit (figure 5). Fifteen shoreline were used here, they date from 1940 till 2003. This test required a special development to process the sandy spit. For the elaboration of the baseline, the envelope leans on the shorelines which in most of the cases (and it is what the authors recommend during the acquisition of shorelines in the case of spit) go round over the spit. So the envelope corresponds to the total evolution of the spit and the baseline represents well the "average" shape of the spit. In the case of spit, the baseline is gone through at first in a direction to calculate the evolution on sea side, then in the extremity some transects are generated for the evolution of the end and then the baseline is gone through the other way around for the evolution on land side.

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Number of historical shorelines

Regression coefficient 90% upper confidence interval (m/yr)

Linear evolution rate (m/yr) 90% lower confidence interval (m/yr)

Figure 5 Processing of a sand spit

VI

CONCLUSION AND PROSPECTS

MobiTC offers the possibility of studying the mobility of the historic shorelines on territories with complex shape thanks to its automatic generation of the baseline, with a concern of simplicity for the user. Numerous statistical method of evolution rate calculation are implemented allowing the user to lead a critical and robust analysis of the mobility. MobiTC also gets a means to capitalize shorelines with their metadata in a rigorous way. It is intended to use MobiTC within the framework of the updating of the sedimentology catalogues to determine rate of erosion and accretion at a national scale from national shorelines produced in this frame and shorelines which will be at disposal, but also more widely within the framework of the national strategy of shoreline management to determine eventually sectors to risk erosion and for the elaboration of risk prevention plan. VII ACKNOWLEGMENTS The development of MobiTC was carried out within the framework of the updating of sedimentology catalogues headed by CETMEF for the Ministry of Ecology and in particular the Head office of Planning, Housing and Nature and the Head office of Risk Prevention. VIII REFERENCES CROWELL M., LEATHERMAN S.P., BUCKLEY M.K. (1991). Historical shoreline change: error analysis and mapping accuracy. Journal of Coastal Research, Vol. 7, n° 3, pp 839-852. FENSTER M., DOLAN R. (1994). Large-scale reversals in shoreline trends along the U.S. mid-Atlantic coast. Geology 22, n° 6 (June), pp 543-546.doi:10.1130/0091-7613(1994)0222.3.CO;2 GENZ A.S., FLETCHER C.H., DUNN R.A., FRAZER L.N., ROONEY J.J. (2007). The predictive accuracy of shoreline change rate methods and alongshore beach variation on Maui, Hawaii. Journal of Coastal Research, Vol. 23, n° 1, pp 87-105.doi:10.2112/05-0521.1

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HIMMELSTOSS E. (2009). DSAS 4.0 Installation Instructions and User Guide. Digital Shoreline Analysis System (DSAS) version 4.0 - An ArcGIS extension for calculating shoreline change, U.S. Geological Survey open-File Report 2008-1278, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L. PONS F. (2010). Hydraulic study of the marseille vieux-port river basin. ISTE LTD and John Wiley & Sons, Inc Environmental hydraulics, Practical Applications in Engineering edited by Jean-Michel Tanguy, pp 167-181. WALTON Jr. T.L. (1999). Shoreline rhythmic pattern analysis. Journal of Coastal Research. Vol. 15, n° 2, pp 379-387.

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