GIS for Coastal Zone Management - Chapter 10 doc

CHAPTER TENDecision-Making in the Coastal Zone Using Hydrodynamic Modelling with a GIS Interface Jacques Populus, Lionel Loubersac, Jean-François Le Roux, Frank Dumas, Valerie Cummins,

CHAPTER TEN

Decision-Making in the Coastal Zone Using

Hydrodynamic Modelling with a GIS Interface

Jacques Populus, Lionel Loubersac, Jean-François Le Roux, Frank

Dumas, Valerie Cummins, and Gerry Sutton

10.1 INTRODUCTION AND CONTEXT

There are many kinds of coastal water quality issues They arise from various sources of inputs to the coastal zone that are either chronic or accidental Pollution

of seawater mostly results from a) point source and diffuse pollution originated from agricultural, industrial and urban activities, or b) pollution from maritime activities, e.g waste oil as well as all types of toxic substances being dumped into the sea, including radioactive ones (Kershaw, 1997)

Toxic phytoplankton blooms are a new plague Although they are not the direct result of human behaviour, they are probably linked to human activities, and particularly contaminated ballast water These harmful disruptions have severe effects on shellfish stocks, entailing long production shutdowns Problems also currently exist with open sewers discharging into places designated for shellfish

production or into recreational waters (Boelens et al., 1999).

After flooding, there is run-off pollution from agriculture and urban areas and nitrate concentrations and bacterial counts increase remarkably The increase

in nitrate concentrations can lead to dramatic eutrophication, whereas pathogenic bacteria can make aquaculture products hazardous to human health (Lees, 2000) Other activities or phenomena such as dredging, deep water sludge disposal or landfill seepage are concerns for water quality and marine living resources (Sullivan, 2001)

While hydrodynamic modelling results and the handling of geo-referenced information are becoming more readily available to coastal management stakeholders within GIS (Geographic Information Systems), there is still a lack of direct interfacing of model results with baseline mapping data (BASIC, 2001) This paper discusses solutions to bridge this gap and illustrates them with two case

studies where effective model outputs are being used for improved environmental management and decision-making

10.2 HYDRODYNAMIC MODELLING BASICS

Mathematical models (Garreau, 1997) can solve geophysical fluid mechanics equations using a number of simplifying assumptions In essence, knowledge of the bathymetry, wind tide and currents are used to predict water levels and concentrations of conservative elements over space and time

The ability of these models to accurately and reliably reproduce the important features of complex systems has improved considerably along with rapid growth in understanding of the underlying physical phenomena, and the ability to quantify them in terms of valid mathematical formulations The widespread and affordable availability of high-powered computing facilities has also contributed to this development, given the heavy processing loads involved in running all but the simplest models

Confidence in the predictive capacity of models is governed by the quality of fit between modelled output data and real field measurements Standard practice in building a typical coastal model entails a number of discrete steps, the first of which involves reconstructing the morphology of the area of interest in the form

of a digital terrain model The next step involves adding water to the system, and then setting it in motion through replication of vertical tidal fluctuations and horizontal wind friction Together these forcing factors create gradients, which in turn drive horizontal current flows A range of assumptions is usually made in order to simplify the system, and allow it to run effectively It is recognised that models do not strive to exactly reproduce in detail all the features of a natural system; however the aim is to arrive at a situation where the model is capable of reliably reproducing the principal features through an iterative process of validation and calibration

10.3 GIS FOR COASTAL ZONE MANAGEMENT

A Geographic Information System (GIS) is a computer-based information system used to digitally represent and analyse geographic features It is used to input, store, manipulate, analyse and output spatially referenced data (Burrough and McDonnell, 1998) A GIS can be distinguished from database management systems or from visualisation packages through its specialised capability for spatial analysis The use of GIS for coastal zone management has expanded rapidly during the past decade and references are numerous (Durand, 1994; Populus, 2000; Wright and Bartlett, 2000) For optimum efficiency, geo-referenced data should be properly stored in geo-databases built on spatial data model design (Prélaz Droux, 1995) Some of the greatest challenges currently faced by those handling coastal zone data are a) the land-sea interface, with different mapping references in both horizontal and vertical modes, b) water dynamics and the related temporal issues, and c) 3D display requirements

10.4 TOOLS AND DATA

10.4.1 Technical details of regional and local models

MARS-2D is a bi-dimensional model using a finite difference method called ADI (Salomon, 1995) A broad regional model, extending between 40˚N and 65˚ N and from 20˚ W to 15˚ E with a 5 km grid, is used as a framework in which to embed further models of smaller extent for areas of interest along French Atlantic and English Channel coasts Commonly, the embedding system has up to 5 levels allowing phenomena to be examined at resolutions from 1km down to 50m This type of model is suitable for applications in areas whose waters are typically well mixed (e.g., coastal or mega-tidal areas) The model is designed to solve for tidal and wind driven currents and the transport of dissolved materials

MARS-3D (Lazure, 1998) is a fully finite difference model, in both vertical and horizontal orientations, which uses a time splitting method based on MARS-2D for the barotropic mode Good coupling between MARS-2D and 3D modes has largely been achieved through the use of iterative methods MARS-3D is used at resolutions ranging from 5 km over regional areas of epicontinental seas, down to

100 metres over detailed areas, narrow bays and estuaries It is currently run operationally at the regional scale (with a 5 km mesh) on all French seaboards Table 10.1 gives an overview of MARS model features

Table 10.1 Comparison of MARS-2D and MARS-3D main features

Area English Channel, Bay of Biscay English Channel, Bay of Biscay Grid and time step From 50m up to 10km ~ 5km, 5 – 20 minutes Period of time From days to decade Year to decade

Applications Tide currents, dissolved matter, salinity under homogenous

conditions

Tide, currents, temperature, salinity, transport of dissolved matter

Type 2D Finite difference 3D Finite difference

10.4.2 The modelling system

A modelling chain has been developed at Ifremer over a period of many years The system has a series of pre-processors and tools for the graphic display of results produced by the MARS computation kernel

This mathematical model uses some simplified hypotheses to solve the equations that govern how marine currents and sea levels evolve In order to function, the process requires an input water level along the edge of the area of interest These boundaries are usually unknown locally, since they are dependent

on tidal and weather conditions, which are themselves usually derived from modelling over a much larger area Thus, the modelling process advances through the generation of a series of sequentially nested models An initial general model covering a large area of the continental shelf and the Channel is followed by a succession of intermediate models of increasingly smaller scope, but higher resolution Boundary conditions for the wide-area model are resolved using world tide models, into which modelled meteorological forcing factors have been assimilated The modelling chain can be summed up as follows:

x A generated link calculates the position, extent and resolution of each sub-model, from the large-area model to the detailed high resolution model based

on computational and hydrodynamic design criteria Computational efficiency

is optimised by maintaining a maximum resolution ratio (mesh size ratio) of between four and five between any two consecutively nested models Hydrodynamic criteria are observed as far as possible in the design through avoidance of islands or zones with violent currents, although at present the system only works when model boundaries are strictly aligned to parallels and meridians This link of the chain has a user-friendly graphic interface and generates a descriptive file of the entire nesting process

x The second link in this computation chain is a software program which calculates an interpolated bathymetry for each nested model The link also has

a graphic interface developed in UNIRAS, which restores a depth for each calculation link in a file The bathymetry used for the large-area model has been validated, and is essentially taken as fixed However, it is updated on an occasional basis, as new information becomes available The MARS-2D computation kernel is used in both case studies below, where prevailing tidal currents have a relatively homogenous vertical structure, providing a good approximation of the mean current fields pertaining in the study areas

x Lastly, a range of graphic tools are used to display the resulting modelled outputs which are written in NETCDF format (Rew and Davis, 1990) NETCDF is a widely used self-documenting format, which also provided a suitable platform upon which the ArcView portal was subsequently developed

10.4.3 Reference mapping data

Currently, coastal practitioners must refer to common baseline or reference data, i.e., primary data to which secondary (or more application-related) data will be subsequently linked (Allain, 2000) The coastline, bathymetric data, and major administrative boundaries are examples of such baseline data that could be readily

provided to a wider public under optimal conditions of accuracy, updating, and scalability to suit various needs

However, it is noted that the bathymetry of inter-tidal areas, and other near-shore zones, is often less easily available or poorly defined Such paucity of data is usually associated with the high cost of acquisition and restricted accessibility Bathymetric data for the two study sites under consideration was available from the French hydrographic service at a scale of 1:50, 000

ArcView™ was the main GIS platform used for the studies, within which the Spatial Analyst™ extension facilitated a number of operations on raster images such as recoding, resampling, changing extent, computing statistics and the use of algebraic image combination functions Existing ArcView functionality also facilitated interactions between raster and vector data layers drawing on the attributes of file features attaching to vector data sets However a major hurdle remains in the efficient handling of large numbers of raster data layers that typically accrue as the output from multiple model runs

10.4.4 An Integrated GIS/model interface

The primary rationale behind the creation of a GIS/model interface was to allow a) consultation and display of results contained in the output files produced by the MARS hydrodynamic model; and b) extraction of these results to import them to ArcView The concept was initially tested through the development of ModelView

(Loubersac et al., 2000), a prototype interface the functionality of which was

successfully demonstrated in the case of hydrobiological contamination in the Bay

of Marennes-Oléron, France

As a further development, in order to broaden the scope of application a platform-independent stand-alone interface, MODELCON, was designed for use in conjunction with a range of GIS packages In order to ensure optimum compatibility with standard software packages and other GIS (e.g Excel, MapInfo™ etc.), MODELCONV extracts NETCDF files to a standard ASCII format The MODELCONV interface was developed in JAVA, with Microsoft’s Visual Studio 6 environment and the JAVA library to access NETCDF files (NETCDF JAVA version 2), ensuring maximum portability in anticipation of future use on Unix systems or via the Web

10.4.5 A Geographic conversion module

An additional processing module was developed in order to address specific geoprocessing requirements beyond those available in the standard version of ArcView This module operates as an ArcView extension and was implemented in Avenue It enables the user to perform a range of geodesic processing operations

on point, multipoint, polyline and polygon data, as well as 2-D and 3-D related measurements (pointM, multipointM, polylineM, polygonM, pointZ, MultipointZ, PolylineZ, PolygonZ)

This module also allows data to be projected or unprojected, i.e as

geographic co-ordinates (latitude, longitude), or projected Cartesian co-ordinates

including 3-D (X, Y, Z) Other operations that are supported include:

x switching between geodesic systems: WGS 84, NTF and Europe 50;

x switching ellipsoids: Clarke 1880, IAG GRS 80 and Hayford 1909;

x switching projections: Lambert (various), Transverse Mercator (UTM)

10.5 CASE STUDY ONE: SHELLFISH PRODUCTION IN THE GOLFE DU

MORBIHAN, SOUTHERN BRITTANY

10.5.1 Water quality issues in the Golfe du Morbihan

The Golfe du Morbihan is located in southern Brittany, France Enclosing an area

of 125 km2, with many islands and extensive intertidal flats, the basin connects to

the open ocean via a 1km wide channel Its perimeter is highly indented, and is

traversed by numerous streams and rivers The main anthropogenic pressures

related to two main cities, Auray (11,000 inhabitants) and Vannes (50,000

inhabitants), are augmented by very significant seasonal tourist populations

Important natural shellfisheries (Venus spp.) are commercially exploited, and the

gulf also supports a valuable oyster farming industry Both rely on suitable water

quality being maintained within narrow sanitary limits In general, water and

shellfish quality criteria are set by the EU Shellfish Hygiene Directive (Lees,

1995) However, at national level slight differences are found in the interpretation

of shellfish hygiene E coli guidelines, specifically in stating what proportion of

samples must fall under the concentration thresholds and in the treatments required

prior to human consumption (BASIC, 2001) In France, these values are defined

by the modified decree n° 94-340 of 28 April 1994, as shown in Table 10.2 below

Shellfish farmers must take different measures for depuration with respect to these

categories

Table 10 2 French shellfish hygiene categories

Level of contamination in faecal coliforms*

Categories

A t 90% d 10% 0%

* per 100g shellfish

10.5.2 Microbiological modelling

Faecal coliforms (FC), of which Escherichia coli is a major component, are good

indicators of bacteriological contamination levels in seawater and shellfish EU health standards for recreational waters and shellfish harvesting zones are based on organism counts These bacteria mainly come from rivers and streams which receive waste water from various sources including surface runoff and soil outwash, sewage treatment plant discharges (especially in heavy rainfall situations, when function is impaired by lower residence time) and unauthorised discharges Other direct sources are storm water drain systems discharging directly into the sea and diffuse contamination in the vicinity of moored boats

Coliform bacteria do not tolerate exposure to solar UV radiation, and thus have a limited life span in seawater Their survival time will vary depending on their metabolic state and environmental conditions Bacterial survival times are positively influenced by the following:

x lower winter temperatures which can slow down bacterial metabolism and extend survival based on slower rates of consumption of energy reserves;

x increased turbidity values, linked to levels of suspended solids Turbidity has

a dual effect, as a potential food source and as protection against solar UV (ultraviolet) radiation Turbidity is usually higher in winter, due to greater discharge and sediment resuspension

In general modelling applications, bacterial survival is represented by the term T90 (being time at which 90% of the bacteria will have disappeared), which assumes an exponential rate of decline in numbers Values for T90 are normally established on an empirical basis, and those used in the current study were based

on experience at local sites (Guillaud, 1997)

10.5.3 Simulation descriptions

In order to characterise coliform distributions under a range of environmental conditions, a series of MARS 2-D model simulations were undertaken in which the following parameters were varied:

x Tidal conditions Simulations were made over a period of three weeks under realistic tidal conditions, i.e of sufficient duration to capture both spring and neap cycles

x Seasonal influence This was investigated by varying discharge volumes, i.e coliform flux

x Weather conditions Three sets of commonly prevailing conditions were selected, in accordance with wind statistics derived from data supplied by the French meteorological office These were 1) zero wind (baseline condition), 2) westerly 8m.s-1 and 3) north easterly 8ms-1

x T90s A summer value of 10h, with 24h for winter was chosen in accordance with local measurements

x The impact of major malfunctioning of water treatment plants in heavy rainfall periods This was modelled by doubling the amounts of bacteria discharged over a 24-hour period, which is typical of what can occur during a summer storm The objective was to investigate the impact of episodic events on coliform distribution, particularly with respect to existing zonation patterns

The above scenarios were investigated through a combined series of seven simulations (two seasons under three different conditions, plus one exceptional situation type) In order to assess the validity of the simulations, the resulting coliform concentration distributions were then categorised according to EU shellfish farming criteria (Table 10.2) Model-derived zonation patterns were found to be in broad agreement with existing zonation plans based on both tissue sampling and water quality monitoring network samples

10.5.4 Simulation results

Having established the overall validity of modelled results, priority was given to locating the zones likely to be subject to the highest contamination These were found to be in upper reaches of the main rivers and in the bay of Vannes (Figure 10.1) Observations performed during model runs indicated that once steady state conditions are attained, the spring/neap tidal coefficient has little influence on subsequent coliform concentrations The impact of a constant, moderate wind (8 m/s) on contamination plumes was imperceptible, both in summer and winter In the summary of results, only the baseline “no wind” situation is referred to

T90 was found to exert the greatest influence on coliform concentration, and when set to 24hours gave rise to the highest levels of contamination This is reflected in the final model run for which a 24h T90 linked to winter discharge rates was chosen

10.5.5 Comparison between the actual classification and a simulation

Figure 10.2shows the results of zonation categories based on samples collected by the water quality monitoring network (Ifremer, 2003) Zonations are based around

30 such samples per site that are routinely collected over the course of each year at low water during each spring tidal cycle (theoretically least favourable situation) Dots indicate the locations of effluent discharge sources Figure 10.2 clearly shows the main water body of the gulf officially ranked as category A, whilst the estuaries and their outlets (north and northeast) are in the B or D categories It is notable that no estuarine areas have been zoned in the C category and have instead been allocated to category D as a precautionary measure in respect of the EU Shellfish Directive This precautionary designation takes into account the obvious

risk of contamination near urban and port areas, as well as the impact of reduced salinity on mariculture products in upper estuarine reaches

Figure 10.1 Screen capture from GIS showing the Golf du Morbihan Coloured areas denote EU

shellfish classifications based on simulated coliform concentration distributions

Comparing the results highlights the good consistency between simulation results and those obtained from monitoring network observations Whilst the general configuration of zonation categories (Figure 10.1) based on simulations is broadly consistent with the official classification scheme (Figure 10.2), the former logically appears to give rise to a less conservative regime under which the estuarine areas in the north and northeastern gulf are designated as category C, rather than the precautionary official D designation

This may be explained by the relative shortness of the period simulated (3 weeks), whereas the official designations are based on an annual monitoring cycle Other reasons may be that the coliform flows used for the simulation did not include the annual maxima (in the case of water collection and treatment plant malfunctions) Furthermore the actual T90 may exceed the 24h value used in simulations, especially in naturally turbid upper estuarine areas, or as a consequence of winter storm induced sediment resuspension

By comparing the Figures where the discharge points are identified by a dot symbol, we also note that the model, which minimised coliform concentration levels as seen above, reveals two B category zones in the outer Bay area These can be seen in Figure 10.1, located to the north and to the west of the Ile au Moines (the island is indicated by an M on the map) Their coincidence with

effluent discharge points (dots) suggests the logical cause of reduced water quality

in these areas This result highlights the valuable insights that can be obtained through the use of realistic simulations based on numerical models in identification

of localised water quality issues, which may then be addressed through the allocation of additional monitoring resources In this case, priority was given to the northern most area (associated with effluent discharge Arradon) owing to its proximity to significant shellfish farming areas, resulting in the establishment of an additional hygiene monitoring station

Figure 10.2 Screen capture from GIS showing the Golf du Morbihan Coloured areas denote EU

shellfish classifications based on measured coliform counts.

10.6 CASE STUDY TWO: THE WRECK OF THE IEVOLI SUN

10.6.1 Context of the case study

The Italian chemical tanker, Ievoli Sun, sailing from Rotterdam to Genoa sank

around 9 am local time on 31th October 2000 in the central English Channel, approximately 9 nautical miles north of Les Casquets (Channel Islands) and 20 nautical miles west-north-west of the French Cap de la Hague off the north coast

of Normandy (Figures 10.3and 10.4)