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Estimation of Extreme Water Levels Due to Cyclonic Storms: A Case Study for Kalpakkam Coast

A.D. Rao, Indu Jain and R. Venkatesan* Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi – 110 016, * IGCAR, Department of Atomic Energy, Kalpakkam-603 102, India

Received February 27, 2009, Revised May 13, 2009, Accepted May 15, 2009

Abstract Numerical ocean models are considered today as an essential tool to predict spurt in the sea level rise and associated inland extent of flooding that could be generated by a cyclonic storm crossing any coastal stretch. For this purpose, the advanced two-dimensional depth- integrated (ADCIRC-2DDI) circulation model based on finite-element formulation is applied for the simulation of surges and associated water levels off Kalpakkam coast. Using the long term inventory of cyclone database, synthesized tracks are deduced for affected coastal districts of , a state bordering the Bay of Bengal encompassing the Kalpakkam region. Return periods are also computed for the intensity and frequency of cyclones at each coastal district of Tamil Nadu. Using the ADCIRC-2DDI model, validation of surges and associated water levels generated by the November 2000 cyclone, which had landfall near coast was initially carried out. The simulation exercise exhibits a good agreement with available observations from post-storm survey reports. Considering the importance of Kalpakkam region, extreme water levels are computed based on a 50-year return period data, for the generation of storm surges, associated water levels and extent of inland inundation. Based on experimental evidence, it is advocated that this region could be inundated from produced water levels when pressure deficit exceeds a threshold value of 66hPa. Also it is noticed that the horizontal extent of inland inundation ranges between 1-1.5 km associated with the peak surge.

Keywords: ADCIRC model, storm surges, return period, inland inundation, water levels

1. INTRODUCTION Inland intrusion of water associated with storm surges is the main cause for extensive damage due to extreme events along the Indian coastline. Storm surges have inundated large stretches of coastal regions; sometimes penetrating up to 10-15 km inland, particularly, when the cyclone passes through a river deltaic region (SMRC, 1998). To minimize the damage, prediction of inland inundation is as important as the prediction of surge heights. Generally, in storm surge prediction models, the rigid lateral boundaries are taken as vertical sidewalls through which there is no flux of water. In a realistic sense, water level associated with the surge will continuously move onshore. Hence, the assumption of idealized vertical walls will lead to spurious error in simulations of the surge development. In addition, simplified horizontal inland extrapolation of the predicted surge height from the fixed sidewall which estimates the distance of inland penetration do not take into account the underlying dynamics of the intrusion processes. The importance of a numerical model comes to light when providing an early warning to a low-lying area thereby guiding evacuation and rescue operations. Earlier, Jelesnianski and Chen (1979) developed a numerical model that allows flow of water inland from the model coastline. This has been accomplished by prescribing the advancing waterfront to move discontinuously from one

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grid point to another according to a preset criterion. However, to obtain acceptable accuracy, this procedure requires extremely fine grid spacing, which may not be otherwise necessary. In India, the models based on finite-difference methods have been developed and used extensively to simulate/predict storm surges for more than two decades. Johns et al. (1982) employed a finite- difference method which involves a continuously moving lateral boundary. In this model, the coastline representation is based on a conformal mapping procedure which cannot be used in case of sharp curvatures in the boundary. A detailed review of the problem concerning storm surges in the Bay of Bengal is provided by Dube et al. (2000). Rao et al. (2008) describes a comprehensive comparison of surge simulations using finite-difference and finite-element models. The study concludes that resolving the atmospheric forcing of the cyclone is as important as providing the detailed coastline geometry for surge development. Although the coastal stretch covering Tamil Nadu is vulnerable to storm surges, no attempt seems to have addressed on modeling surges along the coast of Tamil Nadu except the study by Rao et al. (1994) which is also limited to computation of surges using finite-difference methods. Though very rarely cyclones form south of 10˚N, there are some instances of severe cyclonic storms striking these areas resulting in widespread destruction to life and property as shown in Table 1. The data provided in this table includes the surges based on records from India Meteorological Department (IMD) and SAARC Meteorological Research Centre (SMRC, 1998). In order to properly describe the physics of storm surges, a numerical model must resolve coastal features that can affect storm surge generation and propagation. This means the model domain must necessarily incorporate complex coastal geometries (bathymetry and topography), large gradients in bathymetry along the continental shelf that permit reasonable boundary conditions (i.e. tidal elevations). In this context, a finite-element based model is the best choice as it allows flexibility to represent a larger spatial domain while permitting higher grid resolutions near the landward boundary. Blain et al. (1994) showed in a grid convergence study that near-coastal resolution is the most critical factor in determining the accuracy of storm surge computations.

Table 1. List of severe cyclonic storms for Tamil Nadu

No Date Location Damage 1 13-23 May 1943 (SCS) South of Madras Extensive damage, low lying areas inundated 2 30 Nov 1952 (SCS) South of Nagapattinam 1.3m surge penetrated 8km inland, 400 deaths 3 28 Nov-2 Dec 1955, (SCS) Tanjavore district Surges up to 5m penetrated 16 km inland, 500 deaths 4 21 Oct 1963 (SCS) Cuddalore About 7m surge 5 3-8 Nov 1964 (SCS) Madras coast Low lying areas of Madras city flooded 6 20-23 Dec 1964 (SCS) Tondi (Rameswaram Island) 3-6m surge. 1,000 deaths 7 1-3 Nov 1966 (SCS) North of Madras Tidal bore flooded a large area of Madras city, 30 deaths, 3 ships grounded 8 2-8 Dec 1967 (CS) Nagapattinam Moderate surges. 7 deaths 9 12-23 Dec 1967 (SCS) Near Nagapattinam 7 deaths, tidal waves caused severe damage in coastal districts of Ramanathapuram and Tanjavur 10 24 Nov 1978 (SCS ) Between Kilakkarai and Rochemary Island 3-5m surge on the coasts of Tamilnadu and Sri Lanka. 1000 deaths in Sri Lanka. 10 deaths in India 11 11-17 Nov 1992 (SCS) Sri Lanka and Tuticorin 1-2m surge at Tuticorin, 170 killed, 160 missing 12 1-4 Dec 1993 (SCS) Near Karaikal 1-1.5m surge, 111 killed 13 29-31 Oct 1994 (SCS) Madras 1-2m surge, 304 killed, 60,000 hectares crop damaged 14 28 Nov-7 Dec 1996 (SCS) North Tamil Nadu About 1m surge 15 26 Nov-6 Dec 2000 (VSCS) South of Cuddalore 1.2-1.5m surge at Cuddalore 16 6-10 Dec 2005 (SCS) Thanjavur 0.5-1m surge at Thanjavur

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In the present work, we use a framework of Advanced Circulation (ADCIRC) model that integrates domain-specific tools, standard grid and portal tools to provide an integrated environment for forecasting and information dissemination. This framework allows storm surge computations to be run in a distributed grid environment. The coastal area of Kalpakkam considered for this present study is based on two reasons. Firstly, it is being affected by tropical cyclones as well as cyclones crossing the neighboring coastal district () threatening the safety of vital installations located along the coast and secondly, the availability of precise near-shore bathymetry data and land based topography which can result in accurate predictions. Keeping this in view, the ADCIRC model is applied for computation of extreme surges and associated water level encompassing Kalpakkam region utilizing more accurate on-shore and off-shore topography. It is to be noted that the vertical run-off height was conservatively used as benchmark for the design level criteria of facilities at Kalpakkam based on earlier studies using statistical analysis for extreme values. Present attempt would enable a realistic estimation of the same using an advanced numerical code with realistic representation of the boundary conditions.

2. DATA ANALYSIS AND METHODOLOGY The cyclone tracks along with information about its intensity and surge reports were collected for the period 1891-2007 for all coastal districts of Tamil Nadu from various sources viz; IMD’s atlases, SMRC (1998), Unisys Hurricane Database (2006), Kalsi et al. (2007) and several research publications. All the data were reconciled to make a uniform master database for cyclones and surge events for selected areas. From the generated database, frequencies and locations of landfall are determined at each stretch of the coast. The intensity of a cyclonic disturbance is measured by the strength of the associated winds. The international classification is given in Table 2. The number of cyclonic storms along the Tamil Nadu coast based on the intensity of cyclones is depicted in Figure 1. The number of cyclones grouped based on landfall location at different coastal districts of Tamil Nadu during this period is depicted in Figure 2. It is clear that Chennai is the most vulnerable coastal district of Tamil Nadu in terms of number of cyclones crossing the coast. It is also noticed that Tirunelveli and Karaikal districts are the least affected. Though, no tropical cyclone ever made a landfall in the coastal district of Kanyakumari, it was affected by tropical cyclones crossing the neighboring coastal districts.

Figure 1. Number of cyclones by category for Tamil Nadu

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Table 2. Classification of cyclones according to associated winds

Sl. No. Storm category Abb. Wind speed (knots) Wind speed (kmph) 1. Low Pressure Area LPA <17 <31 2. Depression D 17-27 31-49 3. Deep Depression DD 28-33 50-61 4. Cyclonic Storm CS 34-47 62-88 5. Severe Cyclonic Storm SCS 48-63 89-118 6. Very Sever Cyclonic Storm VSCS 64-119 119-221 7. Super Cyclone SC >120 >222

Figure 2. District-wise distribution of cyclones in coastal Tamil Nadu (1891-2007)

From this data base thus generated, it is noted that all the coastal districts of the Tamil Nadu are subjected to land falling cyclones, though its frequency is less. Therefore, using the cyclone database for the period 1971 to 2007, 11 severe storm surge events in Tamil Nadu were identified. The actual tracks of these 11 events are shown in Figure 3. Based on this inventory, 11 cyclone tracks noted above were represented by seven synthesized cyclone tracks shown in Figure 4 are prepared to provide a more comprehensive geographical coverage of the coastal areas of Tamil Nadu. These synthesized tracks are composite derived from observed tracks as well the theoretical ones based on most favorable direction of the cyclone for a particular region. Using pressure deficit (∆P) for each cyclone event, a suitable statistical analysis (Gumbel, 1954) was applied to calculate the maximum value of ∆P for return periods of 2, 5, 10, 25 and 50 years for Tamil Nadu coast as shown in Figure 5. Even though mathematically it is possible to project ∆P values up to 100 years or more, such projections beyond a 50-year period are not reasonable without having long term cyclone data. Computation of a particular return period requires normally at least double the length of data set to that of its period. The climate change and other anthropogenic effects add to these uncertainties. The feasibility study is carried out using parameters of the cyclone based on 50-year return period as an input to the model using the synthesized tracks. This may provide valuable information on extreme water levels that could occur along the coast.

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25

20 INDIA

Bay of Bengal 15

Arabian 10 Sea

5 65 70 75 80 85 90 Longitude Figure 3. Actual cyclone tracks of Tamil Nadu during 1971 – 2007

Figure 4. Synthesized cyclone tracks (solid line) for Tamil Nadu

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Figure 5. Values of pressure drop by return period for Tamil Nadu

3. MODEL SETUP 3.1 Description of ADCIRC Model A detailed description of the finite-element based hydrodynamic model ADCIRC-2DDI is available in Luettich et al (1992). The governing model equations comprise of the depth-integrated equations for mass and momentum conservation, subject to incompressibility, Boussinesq, and hydrostatic pressure approximations. The following set of conservation equations in primitive, non-conservative form expressed in a spherical coordinate system is incorporated in the model (Flather 1988; Kolar et al., 1994):

∂ζ ∂ ∂()VHcosφ  + 1  UH +  = 0 ∂ φλ∂ ∂φ (1) tRcos  

∂U 1 ∂U 1tan∂U  φ  + U + V −+ UfV = ∂tRcosφλ∂ R ∂ φ R  (2) 1 ∂  p  1 τ −  s ++−g ()ζαη +−sλ τ U φλρ∂ ρ * Rcos  0  HH0

∂V 1 ∂V 1 ∂V  tanφ  + U + V ++ UfU = ∂tRcosφλ∂ R ∂φ  R  (3) τ 1 ∂  p  1 φ −  s +−g ()ζαη ++−s τ V ∂φρ ρ * R  0  HH0 where, t = time, λ, φ = degrees longitude(east of Greenwich positive) and degrees latitude(north of the equator positive), ζ = free-surface elevation relative to the geoid, U,V = depth-averaged horizontal velocity, R = radius of the Earth, H = ζ+h = total water column, h = bathymetric depth relative to the φ geoid, f = 2Ωsin = Coriolis parameter, Ω = angular speed of the Earth, ps = atmospheric pressure at the free-surface g = acceleration due to gravity, η = effective Newtonian equilibrium tide potential, ρ α τ τ 0 = reference density of water, = Earth elasticity factor, sλ, sφ = applied free-surface stress.

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UV22+ τ = C = bottom stress, C = bottom friction coefficient. * f H f The effective Newtonian equilibrium tide potential as proposed by Reid (1990) is as follows:

 π −  2 ()tt0 ηλφ(),,tCftL= ∑ α() () φ cos  (4) jn jn jn0 j  ++λ () nj, Tjvjn jn t0 

where:

Cjn = Constant characterizing the amplitude of tidal constituent n of species j α jn = effective earth elasticity factor for tidal constituent n of species j fjn = time-dependent nodal factor vjn = time-dependent astronomical argument j = 0, 1, 2 = tidal species (j = 0, declinational; j = 1, diurnal; j = 2, semi-diurnal) 2φ L0 = 3 sin -1 φ L1 = sin (2 ) 2 φ L2 = cos ( ) t0 = reference time, Tjn = period of constituent n of species j.

The governing equations described above are discretized in space using linear finite elements and in time by a finite-difference scheme. The finite-element solution to the shallow water equations gives rise to spurious modes and numerical instabilities. Hence, it becomes necessary to reformulate the equations into a form that provides a stable solution in its finite-element representation. Therefore, ADCIRC-2D employs the Generalized Wave Continuity Equation (GWCE), together with the momentum conservation equations, to eliminate this problem (Westerink et al., 1994). The result is a noise-free solution which is used to solve the deviation from the geoid (ζ) and the resultant velocities in the x- and y- directions. Water levels along the open boundary are obtained from global tidal information and are represented by the six major constituents (M2, S2, N2, K1, O1 and P1) from Le Provost et al. (1995) FES95.2 database. This database was developed using a global tidal model and has been found to perform very well in deep waters.

3.2 Wind forcing module Two main forces, which generate storm surges on the sea surface, are surface wind stress and pressure gradient force. These act parallel and normal to the sea surface, respectively, and their relative importance depends on the water depth. In view of the strong associated winds, the forcing due to barometric changes is neglected. Thus, the surface wind field associated with a tropical cyclone is the primary requirement for modeling of storm surges. For this purpose, the wind field at the sea surface is derived by using a dynamic storm model (Jelesnianski and Taylor, 1973). To obtain a dynamic wind profile, initially a stationary symmetric model wind profile is taken, and then correction is applied to approximate the asymmetry due to storm motion. The vector equation which rules the horizontal motion of wind flow near the sea surface in the area of storm is dV 1 g =−grad pf +VkF × + (5) ρ g dt a ρ where, k is the vertical unit vector, Vg is the wind velocity, a is the density of air, f is Coriolis parameter, p is the pressure of atmosphere, F is the horizontal frictional force per unit mass. Assume that the pressure and the wind field move forward without change during forward motion of the storm. For a stationary symmetric storm, from Eq. 5 we get, at a distance r from the center of the cyclone (Myers and Malkin, 1961; Ueno, 1981)

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   dp 2 K 1 dV =−ρ V  s g   dr ag sinϕ V dr   g  (6) 2 1dp V 2 dϕ  cosϕ =+fV g cosϕ −+V sinϕ K V2  ρ g gng a dr rrd  ϕ where (r) is the inflow angle of wind, i.e., angle toward the storm center. Ks and Kn are empirically determined coefficients representing stress coefficients in the directions opposite and to the right of the wind, respectively. These stresses are given by the coefficient times the square of the wind speed. By eliminating pressure from Eq. 6, one can get

duuK s −− = fr K nV r (7) dr sinϕ g ϕ ϕ where u = Vg r cos . Equation 7 can be solved numerically to obtain distribution of u(r) or (r). On integrating the first part of Eq. of 6, we obtain the distribution of p(r) which can be known from the wind profile relation of Jelesnianski (1972):

2Rrm V ()r = R (8) g V 2 2 (Rm + r ) where, VR is the value of the maximum wind speed and Rm is the radial distance from the storm center where the maximum wind speed appears. The value of Rm is usually fixed from the synoptic map, while, the value of VR is determined by solving the Eqs. 6 and 7 numerically.

4. NUMERICAL EXPERIMENTS 4.1 Initial validation The analysis region of the model comprises the geographic domain from 79.5˚E to 82.5˚E and 11˚N to 14˚N. The finite-element mesh was constructed using the software package Surface Modeling System (SMS) (Westerink et al., 1994). The program automatically generates a grid with a low-resolution in the deeper region, and high resolution when approaching near the coast. The generated mesh in the entire analysis area is composed of 71180 nodes with 137839 elements. The node spacing varies between 50m near the coast and about 7km in the open ocean. The model mesh showing the variable grid resolution along with the bathymetry is shown in Figure 6. The landward boundary of the model is fixed from the coast based on 10m topo contour presuming that the surge would never exceed 10m in this region. The topography of the model domain is prescribed from the General Bathymetric Chart of the Oceans (GEBCO) with horizontal resolution of 1.8 km. It is to be noted that the high resolution bathymetry data surveyed off Kalpakkam region is blended with the GEBCO data. An explicit scheme is used in time discretization with a time-step of 6sec. The meteorological forcing (wind stress and pressure) are provided as input to the model at regular interval of 6 hours. Minimum depth of 0.5m is pre-set to delineate the wet and dry elements with a horizontal eddy viscosity coefficient of 5m2s-1. The ADCIRC model requires wind forcing as an essential input parameter. For this purpose, the wind field is first computed using a dynamic wind model of Jelesnianski and Taylor (1973). Here, a stationary symmetric wind profile is initially taken into the storm model, and then subsequent correction is applied to approximate the asymmetry due to forward motion of the storm. The dynamic storm model represents a balance between pressure gradient, centrifugal, Coriolis and surface frictional forces in case of a stationary storm. Wind speed in terms of surface stress is explicitly prescribed in the ADCIRC model, based on the relationship proposed by Garrett (1977). The value for the bottom friction coefficient is set to 0.0026. Further, the wind model provides the pressure gradient to the ADCIRC model. The conversion of pressure gradient to equivalent water column height is obtained ρ through the transformation P/ wg proposed by Blain et al. (1994). Finally, the wind stress and equivalent water column heights are linearly interpolated at each computational node of the finite- element mesh used in the model.

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Nellore

Chennai

Kalpakkam

15m topo land boundary

Pondicherry Cuddalore

Ocean boundary

Figure 6. The ADCIRC finite-element grid and bathymetry (m) of the model domain

The simulation experiment comprised of two parts; the first part is to assess the performance of ADCIRC for an extreme event of the November 2000 cyclone. After performing the validation for this case study, the model is further used to simulate for an event close to the Kalpakkam coast. Firstly, the model is used to compute the surges associated with November 2000 cyclone, which crossed approximately 20km south of Cuddalore. Storm surge simulations resulting from the application of wind, surface pressure and tidal constituents of K1, O1, P1, M2, S2, and N2 along the open ocean boundary, are consistent with the observations. The winds and associated surge height at the time of landfall is depicted in Figure 7(a,b) respectively. The maximum wind of the cyclone at the landfall time as seen from the Figure 7a was about 35ms-1. A peak surge of about 1.4m (Fig 7b) is simulated at Cuddalore, and surge heights of about 1m is simulated in the close vicinity between north of Cuddalore and Pondicherry. The development and advancement of peak surge as the cyclone moves towards the coast is shown in Figures 8(a,b). The maximum surge height (Figure 8a) of about 1.4m is simulated after one hour of the landfall. The model simulated surge envelope at two different locations on either side of

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the track (Figure-8b) shows that the piling of water initiates towards the coast (on the right side of the track) when the cyclone was positioned 20km away from the landfall location. The simulated peak surge agrees very well with Unisys (2006) observed value of about 1.2 -1.5m as shown in Table 1.

Nellore (a) (b)

PPondicherryondicherry

Thiruvallur

Chennai

Kanchipuram CCuddaloreuddalore

Kalpakkam

Pondicherry Cuddalore

Figure 7. (a) Computed wind field at landfall time for November 2000 cyclone (the track shown by a long arrow). Arrows indicate wind direction and magnitude in color (b) shown surge height in color and associated currents with arrows in the zoomed region

Figure 8a. Computed sea level variation Figure 8b. Computed peak surge (m) at two (m) at the location of the peak surge different latitudes

4.2 Application to Kalpakkam coast As our primary concern is for the coast of Kalpakkam, we have chosen the track 2 (as shown in Figure 4) which had its landfall in the coastal area of district. The track crossed the coast approximately about 40km south of Kalpakkam. Numerical experiments have been performed using ADCIRC model to simulate the maximum probable surge amplitudes and associated inland inundation

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along the coast. Based on a 50-year return period, the pressure-drop and radius of maximum winds used in the ADCIRC model is 66 hPa and 40km respectively. The model is integrated for about 36 hrs until the cyclone crossed the coast. Figures 9(a,b) depicts the cyclonic wind distribution at 24-hours before and at the landfall time respectively. The maximum wind associated with the cyclone was about 62ms-1. The model simulated surges and associated currents along with the inundation are shown in Figure10. In this illustration, the surge is shown only for the limited area (Figure 10a) which was affected by the cyclone. A maximum surge of 3.2m was computed about 40km to right of the landfall near Kovalam. It is evident from this figure that vast coastal stretch of approximately 30km is affected by surges greater than 2m which prevailed on the right-side of the track. The associated simulated currents are very strong in the order of about 2.0ms-1 along the affected coast. It is interesting to note that the currents are towards the coast where the maximum surges are occurred; elsewhere, it is southward to the right of the landfall. These onshore currents eventually lead to piling up of water near the coast. Figure 10b provides the surge and associated inundation in the zoomed region surrounding Kalpakkam. It is noted that the region is affected by surges of about 2.7 m and associated inland inundation of about 0.5km. In addition, it is critical to know details of the water levels associated with the surge development for emergency purpose and also evacuation of people along the vulnerable coast. Figure 11 gives the water levels along with inundation associated with combined effect of surges and tides. As the surges are computed from the mean sea level, the water levels are deduced by subtracting local topography from the surges as shown in Figure 11a. Accordingly, the water level simulated is about 2.6m near Kovalam and the associated extent of horizontal inundation is about 1.1km. Figure 11b depicts the water levels for the enlarged view encompassing the area within Kalpakkam region. It is to be noted that the coastal stretch between Kokilamedu and Kalpakkam is affected by water levels of about 2m. This suggests that the region is more vulnerable to inland inundation causing significant damage to the local development if the cyclone generated surges are more than 3.5m.

(a) Nellore (b) Nellore

Chennai Chennai

Kovalam Kovalam

Kalpakkam Kalpakkam

Pondicherry Pondicherry Cuddalore Cuddalore

Figure 9. Computed wind field (a) at 24 hours before and (b) at landfall time. Arrows indicate wind direction, color bar indicates magnitude

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!

(a) (b)

Figure 10. (a) Computed storm surges from the mean sea level along with associated currents and inundation based on 50-year return period (b) same as (a) except for zoomed portion of the southern region

(a) (b)

Bay of Bengal

Maximum inundation: 1.1 km Maximum water level: 2.6 m

Figure 11. (a) Water levels associated with inundation based on 50-year return period (b) same as (a) except for zoomed portion of the southern region

CONCLUSIONS An inventory of all major historical storms which had its landfall at various coastal destinations of Tamil Nadu had been compiled from which the relationship pertaining to the frequency of occurrence has been evaluated. A statistical based approach is used to determine the pressure drop for cyclones crossing each stretch of the Tamil Nadu coast for different return periods. A set of synthetic tracks is prepared for each affected coastal stretch based on information from actual tracks. A high resolution finite-element based ADCIRC model is then applied to simulate surges generated by the November 2000 cyclone. Preliminary analysis for the November 2000 event reveals that model computations are

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in good match with the observations. Based on legitimacy of model computed surges, an attempt is made to evaluate extreme water levels in the Kalpakkam coast. The maximum probable surge amplitudes and associated inland inundation along the coast of Kalpakkam for 50-year return period is computed. As the coastline geometry is modeled more accurately, the simulation of inland inundation from ADCIRC looks very realistic. The winds associated with 50-year return period correspond to 62ms-1 and hence the associated surges and inundation considered for this study is the threshold limit of this region. It is believed that this study would help the coastal authorities to develop a short and long-term disaster management and vulnerability reduction action plan and emergency response in the event of storm surge flooding.

ACKNOWLEDGEMENTS We acknowledge our sincere thanks to the Department of Atomic Energy, Indira Gandhi Centre for Atomic Research (IGCAR), Govt. of India, Kalpakkam, for granting the financial support to carry out this work. We also wish to thank India Meteorological Department for providing the historical cyclone data used in this study.

REFERENCES Blain, CA, Westerink JJ, and Luettich RA (1994) Domain and grid sensitivity studies for hurricane storm surge predictions. Computational Methods in Water Resources X, A. Peters et al., [eds], Heidelberg, July 1994. Dube SK, Chittibabu P, Rao AD, Sinha PC and Murty TS (2000) Sea levels and coastal inundation due to tropical cyclones in Indian coastal regions of Andhra and Orissa. Marine Geodesy 23, 65-73. Dube SK, Sinha PC, Rao AD, Jain I, Agnihotri N (2005) Effect of Mahanadi river on the development of storm surge along the Orissa coast of India: A numerical study. Pure and appl. geophys 162, 1673-1688 Flather, RA (1988) A numerical model investigation of tides and diurnal-period continental shelf waves along Vancouver island. J. Phys. Ocean. 18, 115-139. Garrett JR (1977) Review of the drag coefficients over oceans and continents. Monthly Weather Review, 105, 915-929. GEBCO, http://www.bodc.ac.uk/products/bodc_products/gebco/. Gumbel, EJ (1954) Statistics of extremes. Nat. Bureau of Stand. App. Math. Series. 33, Washington D.C. Jelesnianski CP and Taylor AD (1973) NOAA Technical Memorandum. ERL, WMPO-3, 33 pp. Jelesnianski, CP and Chen, J (1979) SLOSH (Sea Lake and Overland Surges from Hurricanes). Report of TDL, NWS, Silver Spring, MD., 16 pp. Johns, B, Dube, SK, Sinha, PC, Mohanty, UC and Rao, AD (1982) The simulation of continuously deforming lateral boundary in problems involving the shallow water equations. Comp. Fluids, 10, 105-116. Kalsi, SR, Jayanthi, N, Raj, YEA, Roy Bhomik, SK (2007) Probable maximum storm surge heights for the maritime districts of India. Met. Monograph No. Synoptic Meteorology 5/2007. Kolar, RL, Gray, WG, Westerink, JJ and Luettich, RA (1994) Shallow water modeling in spherical coordinates: equation formulation, numerical implementation, and application. J. Hydraul. Res. 32, 3-24. Le Provost, C, Bennett, AF and Cartwright, DE (1995) Ocean tides for and from TOPEX/Poseidon, Science, 267, 639-642. Luettich RA Jr., Westerink JJ and Scheffner NW (1992) ADCIRC: an advanced three dimensional circulation model for shelves coasts and estuaries, report 1: theory and methodology of ADCIRC- 2DDI and ADCIRC-3DL. Dredging Research Program Technical Report DRP-92-6, U.S. Army Engineers Waterways Experiment Station, Vicksburg, MS, 137 pp.

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Rao AD, Dube SK and Chittibabu P (1994) Finite difference techniques applied to the simulation of surges and currents around Sri Lanka and Southern Indian Peninsula. Computational Fluid Dynamics, 3, 71-77. Rao, AD, Indu Jain, Murthy, MVR, Murty, TS and Dube, SK (2008) Impact of cyclonic wind field on interaction of surge-wave computations using Finite-element and Finite-difference models, Natural Hazards DOI: 10.1007/s11069-008-9284-9. Reid, RO (1990) Water level changes-tides and storm surges. Hand book of coastal and ocean engineering, J.B.Herbich, ed., Gulf Publishing, Houston,Tex., 533-590. SMRC (1998) The impact of tropical cyclones on the coastal regions of SAARC countries and their influence in the region, SMRC-No.1, SAARC Meteorological Research Centre, Dhaka, Bangladesh, October 1998, 329 pp. Westerink JJ, Blain CA, Luettich RA, and Scheffner NW (1994) ADCIRC: an advanced three dimensional circulation model for shelves coasts and estuaries, report 2: Users manual for ADCIRC-2DDI. Dredging Research Program Technical Report DRP-92-6, U.S. Army Engineers Waterways Experiment Station, Vicksburg, MS., 156 pp. Unisys Hurricane Database, Unisys Corporation (2006). http://weather.unisys.com/hurricane/indian_oc/index.html.

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