Oil Spill Vulnerability Atlas for the Cantabrian Coast (Bay of Biscay, Spain)

OIL SPILL VULNERABILITY ATLAS FOR THE CANTABRIAN COAST (BAY OF BISCAY, SPAIN)

S. Castañedo Ocean and Coastal Research Group, IH Cantabria, Universidad de Cantabria, Av. de los Castros sin 39005 Santander, Spain. Phone: 34-942-201852. Fax: 34-942-201860. E-mail: castanedos(ä)unican.es Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021

C. Pombo Ocean and Coastal Research Group, IH Cantabria, Universidad de Cantabria, Av. de los Castros sin 39005 Santander, Spain. Phone: 34-942-201852. Fax: 34-942-201860. E-mail: castanedosûpunican.es

F. Fernandez Submarine Outfalls and Environmental Hydraulics Group. IH Cantabria, Universidad de Cantabria. Av. de los Castros sin. 39005. Santander, Spain.

R. Medina Ocean and Coastal Research Group, IH Cantabria, Universidad de Cantabria, Av. de los Castros sin 39005 Santander, Spain. Phone: 34-942-201852. Fax: 34-942-201860. E-mail: castañedosápunican.es

A. Puente Submarine Outfalls and Environmental Hydraulics Group. IH Cantabria, Universidad de Cantabria. Av. de los Castros sin. 39005. Santander, Spain.

J. A. Juanes Submarine Outfalls and Environmental Hydraulics Group. IH Cantabria, Universidad de Cantabria. Av. de los Castros sin. 39005. Santander, Spain.

ABSTRACT INTRODUCTION In order to respond rapidly and successfully to an oil spill occur- The vulnerability of a coastal area can be defined as the coast's ring in a defined geographical area, a contingency plan which capacity to cope with, resist and recover from the impact caused includes information and processes for oil spill containment and by oil spills. Note that this concept includes political-institutional, clean-up is required. An important part of the plan s development, economic and socio-cultural factors. should involve evaluating oil spill risk based on the identification One of the earlier attempts to estimate coastal oil spill vul- of vulnerable coastal environments. In this work, a methodology nerability corresponds to Gundlach and Hayes (1978) where a to determine an index that represents the oil spill vulnerability of classification of coastal environments based on their physical and a specific coast is developed. In order to provide a useful decision- geological characteristics is presented. More recently, the glob- making tool, special emphasis is given to the integration in one ally used Environmental Sensitivity Index (ESI) maps developed single index, of physical, biological as well as socio-economical by NOAA (Petersen et al., 2002) include the physical features of aspects. To do this, three intermediate indexes which include dif- the shore, biological information and human use of the shoreline. ferent indicators are defined. The oil spill vulnerability index, V, Based on this work, a GIS-based ESI classification of the Canta- is calculated by means of a weighting scheme as a result of the bria shoreline (N of Spain) was undertaken in the framework of the participation of interest groups involved in the decision-making Emergency Prestige Spill Response System (ESRS) implemented process. The presented methodology is applied to the Cantabrian by the Regional Government and the University of Cantabria coast (Bay of Biscay, Spain) which was one of the areas most (Juanes et al. 2007). affected by the Prestige oil spill. The work is based on GIS tech- In Europe there are some recent examples. In France, CEDRE nology allowing an efficient information management and the (Centre of Documentation, Research and Experimentation on Ac- generation of updated oil spill vulnerability maps. cidental Water Pollution) is leading the development of an oil spill

137 138 2008 INTERNATIONAL OIL SPILL CONFERENCE

Sensitivity Atlas for the Finisterre region (Michel Girin, personal Tide is semidiurnal with a mean and spring tide range of 3 m and 5 communication). This atlas is structured in three main levels based m respectively. Mean grain size of the beaches is 0.3 mm. on physical, biological and economical features related to the The Cantabrian coast is divided into a series of pocket beaches coast. In Denmark, the National Environmental Research Institute and small isolated inlets between rocky headlands. Considering has elaborated the Environmental Oil Spill Sensitivity Atlas cover- structural and functional points of view, three types of environ- ing West Greenland which provides an overview of such aspects as mental units have been distinguished: estuaries, rocky shores and the occurrence of wildlife, human resource use and archaeological sandy beaches. The analysis carried out covered 14 estuaries and sites that are particularly sensitive to oil spills (http://www.dmu. 200 km of rocky shores and sandy beaches, including five differ- dk/International/ Arctic/Oil/Sensitivity+Atlas/). ent Sites of Interest for Conservation at the European level within Most of the aforementioned studies provide the information the Natura 2000 network that cover about 25% of the shoreline. in the form of an atlas, individually including physical, biological and economics aspects of the shoreline related to oil spill impact. METHODS Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 Usually, the physical analysis assesses the potential impact of oil spill based on the oil persistence in the coast. Previous works Based on detailed analyses carried out en previous studies (FLTQ investigated the relative importance of several factors to the litto- 2006), shoreline segments of 200 m length, L, have been selected ral self-cleaning capacity (Michel et al., 1978; Tsouk et al., 1985). as the main analysis units. This length allows differentiating physi- In these studies the effects on the oil persistence of the sedimen- cal, biological and economic units. A geographic information sys- tological composition of the beaches and the wave energy related tem (GIS), based on l:5000-scale aerial photography and a digital characteristics and processes were examined. They found that the elevation model of 2x2 m of resolution, provided the detailed beach profile and factors determining the coast exposure to wave information and the physical support for their spatial delimitation. action were of primary importance. In Figure 2 (b) an example of the analysis unit used in this study The biological aspects aim to measure the ecological impacts. is presented. As Figure 2 (a) shows, the study shoreline does not Although each spill event can be considered a unique blend of follow the estuaries' perimeters but it crosses the inlets'. Shoreline place, oil properties, nature and human influences, current knowl- segments corresponding to the inlet type have been treated with edge of oil fate and effects allows us to understand and anticipate the estuaries criteria. likely impacts and predict recovery (Hayes et al., 1992; Sloan, To obtain the oil spill vulnerability index for a specific coastal 1999). Furthermore, the numerous oil disasters that occurred in area three intermediate indexes representing the physical (Ip), the 90 's have provided a continuous testing ground to improve biological (IB) and socio-economical (Is) coastal characteristics assessment procedures and to validate hypotheses on environ- have been defined and calculated for each shoreline segment. The mental damage (e.g. Guven et al., 1998; Peterson, 2000; Gelin, oil spill vulnerability index, V, is calculated by means of the fol- et al., 2003; French, 2004; Zenetos et al., 2004). Nevertheless, lowing expression the ecological impact of a certain oil spill must integrate such valuable information as the intrinsic sensitivity of different coastal V = IpVo (1) areas, species and communities inhabiting the aquatic ecosystem where Vo is expressed as with the local singularities, such as the health status, the degree of exposure to the oil spill (intensity, duration, frequency) or the Vo=f(IeJs) (2) resilience. where/stands for a function as The assessment of the socio-economic cost derived from ac- b] b2 f(x,y) = a\x +aiy (3) cidental oil spills is a challenge for the economic science. Usually, private cost and collective damages are considered in the cost where ai, bi, a2 and ¿?2 are the parameters to be determined valuation. However, the disasters will also cause non-commercial by means of the participation of interest groups involved in the damages that can not be easily priced, as for example, those re- decision-making process. In the following, the methodology to lated to the recreational use of the natural areas (Garcia Negro et obtain the three indexes, Ip, IB and Is, and the final vulnerability al., 2007). A number the studies based on traditional economic index, V, are defined. analysis as well as on new methodologies such as the Habitat Equivalency Analysis (HEA), have explored this subject (Preston Physical index, Ip et al. (1990), Brown (1992), Cohen (1995), Dunford et al. (2004) and Roach and Wade (2006), among others). The physical index assesses the potential impact of oil spill based on the oil persistence in the coast. According to this, this index In this paper, a methodology to determine an index that repre- classifies the coastal segments based on its self-cleaning capacity. sents the oil spill vulnerability of a specific coast is developed. In It is here defined as order to provide a useful decision-making tool, special emphasis is given to the integration in one single index of: physical, biological IP = E + SP (4) as well as socio-economical aspects. The presented methodology where E is the coast exposure to waves and SP is the mean is applied to the Cantabrian coast (Bay of Biscay, Spain) which shoreline slope. E is calculated as was one of the most affected areas by the Prestige oil spill (Cas- tañedo et al. 2006; Juanes et al. 2007). The work is based on GIS E = O + S (5) technology allowing an efficient information management and the O S generation of updated oil spill vulnerability maps. where and are the orientation and the sinuosity of the considered shoreline segment respectively. Regarding the substrate permeability, previous analysis (not STUDY AREA shown here) demonstrated that the effect of this factor can be considered included in the slope parameter. Analyzed steep shoreline The area of interest is the Cantabrian coast, Northern coast of sections presented an impermeable behaviour for the oil, while Spain (Bay of Biscay) (see Figure 1). flatter sections usually act as permeable surfaces. Exposed wave- Regarding the wave climate, waves on the Bay of Biscay ap- cut platforms in bedrock are the exception of this rule. These flat proach mostly from the northwest with a mean significant wave environments have impermeable substrate and oil will not adhere height, Hs, of 1 m and a typical winter storm wave of Hs ~ 5 m. to the rock platform. In this study, this exceptionality is assumed REGIONAL RESPONSE 139

and it is addressed later on in the cleaning parameter, in which the R2% = 0,9/7s (7) type of substrate is taken into account. On the other hand, for intermediate (1/10 < SP < 1/2) and steep The orientation factor, O, classifies the coast in function of its (SP > 1/2) slopes, the following equation (Van der Meer, 1993) degree of exposure to the waves. Those sections opened to domi- was used nant waves will present a higher degree of exposure to the wave action and, consequently, a faster self-cleaning process. Therefore, Ri% = 2:3 Hs (8) to rank the coastal areas regarding the orientation, 0, the dominant In the above expressions Ri% is the run-up that only two waves have to be determinated. In this study the wave reanalysis percent of the wave run-up values observed will reach or exceed data, SIMAR-44, have been used. These data were generated by and Hs is the considered significant wave height. Here, the 95th Puertos del Estado using the WAM model (Hasselman et al., 1998) percentile HS95% : 4 m has been taken as representative. To obtain and consist of 44-year hindcast (1958-2001) of wind, wave and this value, wave data from a nearby deep-water buoy (the Bilbao sea-level for North Atlantic waters and coastal seas. Analysis of buoy) was used. Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 the given data shows that the most energetic and frequent waves According to these values, and applying Eqs. (7) and (8), the come from the northwest sector whereas the northeast waves are vertical limits of the zone where the shoreline slope should be shorter and less frequent (usually in the summer season). Waves calculated were determined. Figure 4 presents the results with an from NW, N and NE approach with a period between 12-20 s, 7-15 illustrative scheme and Table 2 presents the proposed shoreline s and 4-8 s, respectively. slope scale and the description of the Cantabrian shoreline envi- The orientation lines have been defined as those straight lines ronments included in each slope type. that join the start and the end points of each shoreline segment. To obtain the physical scaling, Eq. (4) was applied. The wave Based on the azimuth of each line and on the wave data analysis exposure, E, was considered to be predominant over the shoreline carried out before, an orientation scale is developed for Canta- slope, SP, in terms of the self-cleaning capacity of a shoreline sec- bria's coastline. The scale goes from 1 to 3. Shoreline sections tor. Table 3 gives the proposed scale for the Ip. oriented to the dominant waves (Azimuth 22.5Q-225Q) are given a In order to account the different characteristics that estuaries score of 1, those oriented to waves from NE - E sector (Azimuth present regarding wave exposure as well as slope, these environ- 22.59-90Q) 2, and the rest (Azimuth 90Q-225Q) 3 on the scale. Note ments have been analyzed separately from the rest of habitats. The that, the higher the score, the more protected the analyzed area self-cleaning capacity of these areas is very low and, consequently, and, consequently, the slower the self-cleaning process. they were given the maximum value for the exposure and slope The sinuosity parameter, S, acts as a correction factor of the indicators to reach a Ip =10. orientation indicator. Zones with more sinuosity present irregulari- ties where oil could persist despite high wave energy. The sinuos- Biological index, IB ity, 5, of each shoreline segment has been calculated using the following relation The IB wants to assess the ecological impacts. For this purpose, the same three general indicators have been proposed to integrate S = l/L (6) specific IB indexes for the corresponding established types of where L is the shoreline segment length (= 200 m) and / is coastal environments (estuaries, coastal rocky zones and beaches): the orientation line length for this segment. Note that for straight the conservation state (/c), which take into account the current shoreline sections the value of S will approximate to 1. On the structural and functional status of the water body in which each other hand, the more sinuous a segment is, the lower the value of segment is included; the singularity value (Is), which considers the S will be. conservation value of the segment according to its legal protection Applying Eq. (5), the sum of the orientation and sinuosity status; and, the resilience factor (Ir), or the power of the commu- scores gives a total score which has been grouped as shown in nity to recover following the perturbation caused by an oil spill Table 1. Exposed shoreline sections receive high wave energy and and the speed with which it is able to do so. have a low sinuosity. Therefore, the oil that reaches these zones Evaluation of those indicators is carried out using specific cri- will be easily removed by waves. On the contrary, sheltered areas teria for segments assigned to each coastal type. So, Ic estimates are mainly protected from the most energetic waves and they also of segments corresponding to estuarine water masses are based on have a high sinuosity that will produce a higher oil residence "ecological status" assessments, according to the Water Frame- time. work Directive 2000/60/CE, meanwhile the structural complexity The shoreline slope, SP, is a determinant factor regarding the of coastal dunes and the presence/absence of discharges to the oil persistence in the coast. Areas with a gentle slope will more shoreline are the selected features in the case of dunes and rocky easily retain the oil that those which are steeper. Based on the shores, respectively. experience acquired during the Prestige oil spill cleaning-up, the On the other hand, a more homogeneous criteria has been se- mean slope associate to the swash process in high tide was adopted lected for singularity estimates (Is) of all the coastal types, which as an adequate indicator. In order to determine the vertical limits is based on legal declarations of conservation values at local (i.e. of this zone (flooding level) the effects of the: astronomical tide, protected landscapes, regional parks), national (i.e. natural parks) storm surge and wave run-up, were considered. or international levels (i.e. Ramsar sites, European Sites of Inter- Since the storm surge and the wave run-up are random vari- est for Conservation). Special concern is dedicated to small island ables, the flooding level is also a random variable. Sea level data spaces in the case of the coastal rocky type. from the Santander tidal gauge were used. This data set consists of Finally, the third indicator, the resilience factor (Ir) uses three hourly sea-level measured during the last five years and includes different approaches for each coastal type. In the case of estuarine three additive components: mean sea level, tidal and surge level. habitats, this factor is estimated by quantifying the percentage of Figure 3 shows the calculated sea level (tide + storm surge) accu- vegetated surfaces within the intertidal areas, weighing the scores mulative distribution function, relative to the lowest astronomical according to the total intertidal size of each estuary. Oppositely, tide (LAT) at Santander. Based on this analysis, the calculated 90th the Ir of coastal dunes is assessed in terms of percentage of length percentile sea level was around 4,0 meters above the LAT. of the sandy area that is currently vegetated. Finally, a physical Regarding the wave run-up, two formulations, depending on criterion, the intertidal slope together with the presence of boul- the shoreline slope, were used. For smooth slopes (SP < 1/10) the ders and cobbles, is considered for resilience estimations in rocky Holman (1986) relation was applied shores. 140 2008 INTERNATIONAL OIL SPILL CONFERENCE

Integrated assessment of the biological index (IB) is carried out bait. In this sector, the economic loss of the aquaculture activity by summing up the three intermediate scores. has also been included. Unfortunately, only information from one of the three aquaculture farms located in the region was available Socio-economic index, IS for this study. To estimate shellfish, data regarding the total shellfish capture in each extraction area in Cantabria during 2002-2004 Is The estimates the economic damage caused by a marine oil spill was gathered and processed by the University of Cantabria and in terms of income losses resulting from interrupting activities the mean fresh market price for each species during 2005 was related to the coast uses. The cleaning cost is also included in this applied, shellfish was equally assigned to each shoreline segment index. Cantabria's economic activities which have been consid- within a specific extracting area (previously delimitated in the ered are: fisheries and shellfish sectors, tourism, harbour activity GIS application). and recreation. Recreation activity estimates the economic loss in The economic losses in the tourism sector were evaluated activities that can be marketed in terms of generated employments by means of the average expenditures per traveller spending at such as sailing, diving and surfing. Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 least one night in the study area. This quantity includes all the The economic damage (in ) assigned to each shoreline seg- traveller's expenses: lodging, meals, shopping, recreation, trans- ment, /, ,, was carried out as port, car renting and others (source: Deloitte and Exceltur (2005)).

= Table 4 shows the type of lodging establishments considered. Al- / c + fishery + shellfish + tourism + harbour + recreation (9) though shoreline segment was selected as the main analysis unit, where c is the cleaning-up cost indicator and fishery, shellfish, etc in order to obtain tourism in a proper way, bigger units representing stand for the economic loss associated to each considered activ- the Cantabrian coastal tourism areas were established. The criteria ity. to delimitate these tourism units were: (1) the unit has to represent The value of ,· will depend on the oil type and the season. Oil the tourism influence of the accommodation nucleus, (2) it has type determines the recovery time and the degree of impact of to facilitate the data collection, and (3) the tourism units have to an oil spill on an activity. Here the recovery time, Rt, has been exhibit a similar ratio, R= shoreline length (m)l surface (km2), to defined as the time (months) that an activity needs to return to a allow the comparison between them. Figure 5 (a) shows the five normal situation and the impact degree, Id, takes into account the established tourism units for Cantabria's coast and Figure 5 (b) percent of the activity income that is affected by the oil spill. presents the value of R for all of them. In this study, the value of Rt and Id for a Prestige fuel type The resulting tourism was divided among the shoreline segments (heavy fuel - fuel oil No. 6) have been determined. These within a specific tourism area. The 75% of tourism was assigned to values were obtained interviewing the Prestige oil spill response beaches and estuaries and the rocky shores received the rest of managers in Cantabria. The value of these factors for others oil the losses. spill types should be determined. The assessment of the economic cost derived from an acciden- Owing to the seasonality of most of the considered activities, tal oil spill in the harbour activity was carried out based on data the period in which the oil spill occurs is also a determinant factor provided by the Port of Santander which is the only commercial in the socio-economic cost assessment. To take this into account, port in the region of Cantabria. The daily economic losses for a seasonality coefficient, Ks, was included in the calculation of the the APS (Port Authority of Santander) considering an oil spill economic loss for each activity, j blocking the harbour were estimated at 50.000 . Due to the APS j = [( 8j I month)Ks](IdxRt) (10) income represents the 15% of the rest of port activities, the daily economic damage will be more than 330.000 (David Marcano, where j stands for the monthly generated income for each personal communication). Table 4 presents the expression used to activity j: fishery (j=l), shellfish (j=2), tourism (j=3), harbour calculate harbour. activity (j=4) and recreation 0=5)· Table 7 shows the value of Ks To evaluate the economic loss in the recreational use of the used in each activity. coast, recreation, sailing, diving, surfing and marinas activities were g analyzed, sailing, diving, surfing were calculated with data from 30 To estimate fishery, the species considered have been the clubs and schools (Cantabrian Sailing Federation, Cantabrian sardine, horse mackerel and hake (inshore fishing) and the blue Surfing Federation and personal communications). The monthly mackerel, blue fin tuna and anchovy (off-shore fishing). Inshore average cost per mooring, mooring, was estimated at 416,6 . fisheries are heavily affected by an oil spill. Usually, after a disas- (Gamma SL). The estimated recreation was evenly divided among ter similar to the Prestige oil spill, the littoral is closed for fishing the shoreline segments affected by the activity considered. Surfing and shellfish extraction during several months (Loureiro et al., activity was associated to a beach; sailing to a marine or mooring 2006). However, off-shore fishing will be damaged only if the area and diving to a coastal strip. fishing boats were at port at the moment of the oil spill arrival. Finally, in order to assess the cleaning-up cost, c, the following In this case, the equipment could be oiled which could derive in expression is proposed important economic losses. In order to take into account this issue, the treatment for each species has been done depending on its fish- c=C(BL) (11) ing area (see Table 4). where C is the cleaning-up cost per m2\ B is the affected cross To calculate the monthly generated income of the fishing ac- distance (width) and L is the shoreline segment length or the es- fishery, tivity, the total landings of inshore and off-shore species tuary perimeter. To obtain C, data were provided by the Spanish in each Cantabria fishing port during 2001-2002 was used. These public company TRAGSA which was in charge of the Cantabrian data were obtained form the Statistic Institute of the Cantabrian coast cleaning-up during the Prestige oil spill (2002-2003). The Government (www.icane.es). Moreover, the mean fresh market affected cross distance, B, was carried out depending on the shore- price for each species during 2005 was used. line slope (see Table 5). The monthly generated income for inshore species was equally Once the indicators representing the economic loss for each assigned to each Cantabria shoreline segment. However, for off- activity were estimated, the addition of these values will give the shore species, it was assigned to the corresponding port and was economic damage associated to each shoreline segment, / (Eq. equally distributed to the shoreline segments included in the influ- 9). Next, to obtain Is, / was categorised into ten categories using ence area of the port. Jenks' natural breaks classification to determine interval breaks Regarding the shellfish sector, the species considered have (source: ESRI knowledgebase). been the clam, goose barnacle, two species of razor clams and REGIONAL RESPONSE 141

RESULTS validation. Environmental Toxicology and Chemistry, 23(10), 2441-2456. In order to combine the Ip, IB, and Is indexes to obtain a single Garcia Negro, M.C., Villasante, C.S. and Carballo Pénela, A. value, V, the function/in Eq. (2) has to be estimated. Substituting (2007) Compensating system for damages caused by oil spill the calculated indexes in Eq. (3) yields pollution: Background for the Prestige assessment damage in f(x, y) = a\lBb] +ailsh2 Galicia, Spain. Ocean & Coastal Management, 50, 57-66. Gelin, A., Gravez, V. and Edgar, G.J. (2003) Assessment of Jessica provided oil spill impacts on intertidal invertebrate communities. Marine f=0 if /ß = /s = 0and Pollution Bulletin, 46, 1377-1384. Gundlach, E.R. and Hayes, M.O., (1978) Vulnerability of coastal /= 1 if IB = Is= 1 environments to oil spill impacts. Marine Technology Society where/, IB and Is are normalized values (0-1). After applying Journal. 12, 18-27. Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 the restrictions established in Eq. (12), the final model stands as Guven, K.G., Okus, E., Unlu, S., Dogan, E. And Yuksek, A. (1998) b] b2 Oil pollution of marine organisms after Nassia tanker accident Vo = rIB +(l-r)Is (12) in the Black Sea, Bosphorus and the Sea of Marmara. Turkish To carry out the parameters r, bi and bi of Eq. (12) for the Journal of Marine Sciences, 4(1), 3-10. Cantabrian coast, a survey involving different stakeholders has Hasselman, S. & K., Janssen, P. A. E. M., Komen, G. J., Bertotti, been carried out. The sectors considered were: fisheries and L., Lionello, P., Guillaume, A., Cardone, V. C, Greenwood, J. aquaculture, resource management, species and habitat protection, A., Reistad, M.; Zambresky, L., Ewing, J. A. (1998) The WAM tourism, recreation and research institutions. The form to be filled model -Athird generation ocean wave prediction model. Jour- out consisted of twelfth shoreline segments representing different nal of Physical Oceanography, 18, 1775-1810. type of environments from the biological and socio-economic Hayes, M.O., Hoff, R., Michel, J., Scholz, D. and Shigenaka, point of view. The survey query aimed to rank these coastal envi- G. (1992) An Introduction to Coastal Habitats and Biologi- ronments depending on their oil spill vulnerability. The answers cal Resources for Oil Spill Response. Report No. HAZMAT had to be based on the interviewee's opinion, experience and/or 92-4. Seattle, Washington: National Oceanic and Atmospheric knowledge. Administration. After analyzing the survey answers, the best fit model results Holman, R. (1986) Extreme value statistics for wave run-up on a were r = 0.7, b\ - 1 and bi - 4.4. Finally, the expression to assign natural beach. Coastal Engineering, 9, 527-544. a vulnerability index for a coastal segment has been obtained Juanes, J.A., Puente, A., Revilla, J.A., Alvarez, C, Medina, R., 4 4 Castañedo, S., Morante, L., Gonzalez, S. and Garcia-Castrillo, V = lp (0.7/B + 0.3/5 · ) (13) G. (2007) The Prestige oil spill in Cantabria (Bay of Biscay). As mentioned, all the generated information was integrated on Part II: Environmental assessment and monitoring of coastal a GIS. Particularly, the tree indexes, Ip, IB, and Is, as well as the ecosystems. Journal of Costal Research, Vol. 23(4), 978-992. final index, V, calculated for every shoreline segment, were repre- Loureiro, M.L., Ribas, A., Lopez, E. and Ojea, E. (2006) Esti- sented in form of vulnerability maps (see Figure 6). mated cost and admissible claims linked to the Prestige oil spill. Ecological Economics. 59, 48-63. Meer, J.W. van der (1993) Conceptual design of rubble mound ACKNOWLEDGEMENTS breakwaters. Delft Hydraulics Publication number 483. The authors would like to thank the Marcelino Botin Foundation Michel, J., Hayes, M.O. and Brown, P.J. (1978) Application of for funding this project. Sonia Castañedo is indebted to the Span- an oil spill vulnerability index to the shoreline of Lower Cook ish Ministry of Education and Science for the funding provided in Inlet, Alaska. Envir. Geol., 2, 107-117. the "Ramon y Cajal" Program. Petersen, J., Michel, J., Zengel, S., White, M., Lord, C. and Park, C. (2002) Environmental Sensitivity Index Guidelines. Version 3.0. NOAA Technical Memorandum NOS OR&R 11. Seatle: REFERENCES Office of Response and Restoration, National Oceanic and Brown Jr. G. (1992) Replacement cost of birds and mammals. Atmospheric Administration. Available at: http://www.evostc.state.ak.us/Publications/eco- Peterson, C.H. (2000) The Exxon Valdez oil spill in Alaska: acute, nomic.cfm. Last accessed: February 2007. indirect and chronic effects on the ecosystem. Advances in Castañedo, S., Medina R., Losada, I.J., Vidal, C, Méndez, F.J., Marine Biology, 39, 3-84. Osorio, A., Juanes, J.A., and Puente, A., (2006). The Prestige Preston, Thorgrimson, Shildler, Gates and Ellis (1990) An assess- oil spill in Cantabria (Bay of Biscay). Part I: Operational ment of the impact of the Exxon Valdez oil spill on the Alaska forecasting system for quick response, risk assessment and tourism industry. McDowell Group. Available at: http://www. protection of natural resources, Journal of Coastal Research, evostc.state.ak.us/Publications/economic.cfm. Last accessed: Vol. 22(6), 1474-1489. February 2007. Cohen, MJ. (1995) Technological disasters and natural resource Roach, B and Wade, W.W. (2006) Policy evaluation of natural re- damage assessment: an evaluation of the Exxon Valdez oil sources injuries using habitat equivalency analysis. Ecological spill. Land Economics. 71 (1), 65-82. Economics. 58, 421-433. Deloitte y Exceltur (2005): Impactos sobre el entorno, la economía Sloan, N.A. (1999) Oil Impacts on Cold-Water Marine Resources: y el empleo de los distintos modelos de desarrollo turístico A Review Relevant to Parks Canada's Evolving Marine Man- del litoral Mediterráneo español, Baleares y Canarias. Anexo date. Parks Canada. National Parks, Occasional Paper no. 11. metodológico. Madrid. Queen Charlotte, BC, 67 p. Dunford, R.W, Ginn, T.C and Desvousges, W.H. (2004) The use of Tsouk. E., Amir, S. and Goldsmith, V. (1985). Natural self- habitat equivalency analysis in natural resource damage assess- cleaning of oil-polluted beaches by waves. Marine Pollution ments. Ecological Economics. 48, 49-70. Bulletin, 16(1), 11-19. FLTQ (Fundación Leonardo Torres Quevedo) (2006) Programa Zenetos, A., Hatzianestis, J., Lantzouni, M., Simboura, M., Skliva- de predicción, protección y evaluación del vertido del buque gou, E. and Arvanitakis, G. (2004) The Eurobulker oil spill: Prestige en las costas de Cantabria. mid-term changes of some ecosystem indicators. Marine Pol- French, D. (2004) Oil spill impact modeling: development and lution Bulletin, 48, 122-131. 142 2008 INTERNATIONAL OIL SPILL CONFERENCE

FIGURES Sea level accumulative distribution function Santander tidal gauge I I I I Registro: 82821 horas

Í 0.6 — — — / / / /

/ Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 / \ /

Mir |TM i I I ! I Mil MM II I I MM I II I MM MM MM

FIGURE 3. SEA LEVEL (TIDE + STORM SURGE) CUMULATIVE DISTRIBUTION FUNCTION RELATIVE TO THE M7FOR SANTANDER

9°W 6°W 3°W 0° FIGURE 1. LOCATION MAP High tide + run-up (P > 1/2) High tide + run-up (1/10< P < 1/2) High tide + run-up (P < 1/10) High tide nar

MSL NMMA

FIGURE 4. VERTICAL LIMITS (RELATIVE TO THE MEAN SEA LEVEL, MSL) OF THE ZONE WHERE THE SHORELINE SLOPE IS EVALUATED

(a)

(b) R=shoreline length (m)l surface (km2) FIGURE 2. (A) SHORELINE (RED); (B) ANALYSIS UNIT (YELLOW)

FIGURE 5. A) COASTAL TOURISM UNITS IN CANTABRIA. B) R=SHORELINE LENGTH (M)/ SURFACE (KM2) FOR EACH UNIT REGIONAL RESPONSE 143

Shoreline Shoreline slope, SP Coastal environments slope scale Rocky cliffs with steep > 1/2 (Steep) 1 slope Rocky cliffs with intermediate slope Cliffs with cobble- or \/\0

Exposure Shoreline slope Total Score Ip TABLES 1 (Exposed) 1 (Steep) 2 1 Orientation Sinuosity score Total score Exposure 1 (Exposed) 2 (Intermediate) 3 2 score 2 (Semi-exposed) 1 (Steep) 3 3 1 1 1 (Exposed) 3 (Smooth) 4 4 1 2 <3 1 (Exposed) 2 (Semi-exposed) 2 (Intermediate) 4 5 2 1 3 (Sheltered) 1 (Steep) 4 6 1 3 2 (Semi-exposed) 3 (Smooth) 5 7 2 2 = 4 2 (Semi-exposed) 3 (Sheltered) 2 (Intermediate) 5 8 3 1 3 (Sheltered) 3 (Smooth) 6 9 2 3 4 (Estuary) 4 (Estuary) 8 10 3 2 >5 3 (Sheltered) 3 3 TABLE 3. PHYSICAL INDEX, IP

TABLE 1. EXPOSURE SCALE 144 2008 INTERNATIONAL OIL SPILL CONFERENCE

Activity Economic loss Comments Fishery K ,i «*-,= + (€ (IdxRt) • To carry out s the data was gathered É(V-^> É -.'-^> from the Statistic Institute of the J Cantabrian Government (www.icane.es) N, M: number of inshore and off-shore species respectively during 2001-2002. is¡: monthly generated income for the inshore specie i os¡: monthly generated income for the off-shore specie i Ks.r. seasonality coefficient for specie i

g Shellfish • To carry out aq, the monthly generated y (€ * Κ ) + (€ * -À: ) (IdxRt) income was equally assigned to each L ■ J shoreline section associated to the Downloaded from http://meridian.allenpress.com/iosc/article-pdf/2008/1/137/1746033/2169-3358-2008-1-137.pdf by guest on 01 October 2021 N: number of shellfish species considered in the study aquaculture farm. Source: Tinamenor s¡: monthly generated income for extracting the shellfish specie i aquaculture farm g (http://www.tinamenor.es). aq. monthly generated income for the aquaculture activity • As the Rt for these activities, in the case Ks.r. seasonality coefficient for specie i of a heavy oil spill, is over one year, Ks,aq: seasonality coefficient for the aquaculture values equal to 1 were used for Ks.i and

Ks.aq-

g Tourism • Data to estimate night j and ^5./ were €-^-É [(«i..,*,)*., l('**o obtained from the Statistic Institute N: types of lodging establishments considered in the study (l=hotel, 2=apartment, of the Cantabrian Government 3=second house, 4= camping) (www.icane.es) during 2005. Seasonality g information was not available for the nightf. monthly generated income per person/night in an establishment type i second house lodging type. For this type, Rr. monthly rooms in a lodging establishment type i. a value equal to 1 was used.

Harbour harbour = ε (IdxRt) • Data from the Port Authority of activity ε: are the monthly losses (in euros) resulting from interrupting the port activity Santander (APS). Year 2005. (David (25 days of damage) Marcano, personal communication)

Recreation € = Γ(€* + €* +€*, ) + (ΛΓ€ )]KxIdxRt • The seasonality coefficient, Ks, was rmcnamoti 1 v **»βιψ <*»"* "*i"m maanng ' 1 i g g g obtained from an analysis performed by surfing, diving, sailing: monthly generated income for the surfing, diving and sail- the University of Cantabria. ing activities respectively. N: number of moorings mooring: monthly average cost per mooring

TABLE 4. EXPRESSIONS TO ESTIMATE THE INCOME LOSSES RESULTING FROM INTERRUPTING ACTIVITIES RELATED TO THE COAST USES

Shoreline slope B(m) Steep 4 Intermediate 6 Smooth 10 Estuaries 10

TABLE 5. VALUE OF B