Investigation of Sediment Budget and Mechanisms of Dynamic - PowerPoint PPT Presentation

Investigation of Sediment Budget and Mechanisms of Dynamic Morphology changes along the West coast of Sri Lanka Yoshimitsu TAJIMA Coastal Engineering Lab. The University of Tokyo GEOSS APS2014 Ryogoku, Tokyo 2014 May 27th

Local erosion & accumulations Erosion. sand rock severe erosion protects beach Groin & seawall protect beach

2001 Mar.9

2005 Oct.27

2010 Aug.9

Contents Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

Contents Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

Local erosion & accumulations Erosion. sand rock severe erosion protects beach Groin & seawall protect beach

What are the primary factors of erosions around the north of Kalpitiya? • Decreasing sediment supply from the south? • Local unbalance of the longshore sediment transport rate? • Temporal shoreline retreat due to stormy waves? We need more frequent monitoring of the shoreline change

2007.1 2009.12 Good PALSAR Relatively high resolution Shoreline is clearly detected Monitoring frequency Not so good •coarser resolution •Relatively low intensity of signal from the lower land like sand spit

Comparisons of GPS-log and PALSAR image • GPS-log data recorded in July 2010 (red lines) were compared with the PALSAR image. • Sandy beach sometime is “darker” than the swash zone. • PALSAR image can be a useful data sets to monitor shoreline changes.

( x c ,y c ,z c ) Shoreline Extraction y σ Procedures v u φ x Shoreline locations in pixel coordinates Shoreline locations on fixed XY-horizontal coordinate system Comparisons of shoreline locations at different time

Extracted Shorelines

Shoreline change since 2007 Jan 14th distance along the shoreline •severe erosion around time-series of shoreline change X~20km whereas significant accumulation at X~15km •Relatively stable shoreline at X<14km •Rapid shoreline change in each beginning of the year?

Contents Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

Estimated Bathymetry sand accumulation? • Wide shallower area is developed on the north side of Kalpitiya. • These accumulated sand can be a source of longshore sediment supply to the north • Further monitoring is essential for future estimation of the sediment budget

Contents Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

Thermoluminescence Temporal variation of natural grain TL signal Sand grain emits light (luminescence) when exposed to light (OSL: Optically Stimulated Luminescence) or heat (TL: Thermo Luminescence). Intensity of the luminescence depends on how long the grain was buried under the ground and how long it has been exposed to the sunlight. Luminescence signal Erosion Initial TL Sunlight Bleaching Luminescence signal decrease No light exposure Natural irradiation Initial OSL Signal accumulation Fast stage Laboratory Deposition TL Measurement Slow stage OSL Natural residual TL Time Sand buried under the ground bleaching Nearshore Sediment transport (long period) (short time) Natural residual TL signal ~ Solar exposure ~ Sediment transport 1. Travelling duration Nearshore Sediment Movement 2. Moving distance 3. Source identification

Results and Findings No major peak in the north of Nigombo > No major sand supply from land Small peak at the Kelani River mouth > relatively small sand supply from land Gradual decay toward north > Northward transport Clear peak around Kalu river > sand supply from the land

Contents Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

Numerical Models for.... • better understandings of the physical processes • Future predictions Wave wave observation • Phase-averaged EBM • Time-dependent non-linear wave model Current • Wave-induced nearshore currents • Tidal currents • Wave-current interactions • Tsunami inundation • Storm surge inundation Sediment transport / Topography change • shoreline model • 3D beach evolution model Observed shoreline/bathymetry change Future change of the LSST can be estimated.

Shoreline Model x wave breaking ∞ ∫ = Q q dx s y   ∂ x s ( ) θ b q y x   α = ( ) s arctan   ∝ θ − α ∂ EC sin   y g b x s b y shoreline dx dQ 1 = − s s + dt D R dy s u Assumption Old Shoreline New Shoreline y • Cross-shore beach profile stays the same. • Sand moves only where the water depth is shallower than the critical depth, D s . • Qs changes with the angle of shoreline, α . Q sOUT D s +R u • Qs is semi-empirically determined based D s on the assumption of long straight beach. Q sIN • No circulation current is accounted for. Δ y Δ x s

Wave information we need for the shoreline model Wave energy and Wave Directions along the Wave Breaking Point Phase-averaged energy balance equations are preferred accounting for both computational costs and minimum requirements of the wave information for the shoreline model.

Energy Balance Equation ( ) ∂ Momentum equation E = −∇ + − + E C E E time-average ∂ g in out Continuity equation t wave breaking wind friction loss ∂   E 1  + ∆  ∆ fx E x y   ∂ fx   2 x x ∂   ∂   E 1 E 1   − ∆ ∆  + ∆  ∆ fy  E y  x fy E y x   ∂ fy ∂   fy ∆ x 2 y   2 y E = EC f g ∆ y = θ E EC cos fx g θ wave crest line ∂   E 1  − ∆  ∆ fx E x y   ∂ fx   2 x = θ E EC sin y fy g

Wave Field Computation Shoreline Shoreline model Aerial photo & Satellite Coastal Structures Northward LSST Thermoluminescence Block of LSST at Colombo No sand supply from land in the north Offshore 0.1~1km wave height (m) Land Computed wave field North South 陸 Coastal Structures

Model representation of the S.L.-change from 1956 to 2000 •Coral reef around Kalpitiya caused local accumulation / erosion •While the shoreline is stable owing to coastal structures in the south of Chilaw, predicted water depth in front of the shoreline is kept increasing. meas. comp. Chilaw Kalpitiya Nigombo Colombo sea wall (b) HL HL S N 2km (c) (d) 0 Hs(m) 1.6

Extracted Shorelines

Rough estimation* of future budget of LSST * Numbers are subject to change with further detailed analysis Predicted time-series of LSST Kalpitiya カルピティア南部 S. Kalpitiya Chilaw チラウ LSST [m3/year] S. Kalpitiya カルピティア北部 Kalpitiya 1956 1988 100km 1988(cal.) Nigombo 10km Chilaw ニゴンボ 2000 2000(cal.) year after 1955 2050(cal.) Nigombo : rapid decay in first 50 yrs. followed 2100(cal.) by nearly no LSST Nigombo Chilaw : gradual decay is accelerated after 50 yrs. S. Kalpitiya: rapid decay after 100 yrs. 20km 1km Kalpitiya : No significant change

Summary Satellite-based observations of the Coast • Shoreline extractions • Bathymetry estimations • Wave observations Coupling monitoring techniques for better understandings of the coastal environments • Thermoluminescence (TL) • Numerical Model Preliminary findings of coastal morphological characteristics on the west coast of Sri Lanka

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