of the area around the cross-dams in the Meghna Estuary Md. Sohel - PowerPoint PPT Presentation

Stakeholder Workshop on SAFE Prototype Activity in Bangladesh Investigation of sedimentation process and stability of the area around the cross-dams in the Meghna Estuary Md. Sohel Rana 1 and Mohammad Asad Hussain 2,3 1 Local Government Engineering Department, Bangladesh 2 Coastal Engineering Laboratory, The University of Tokyo, Japan 3 Bangladesh University of Engineering and Technology, Bangladesh 4 Geo Informatics Center, Asian Institute of Technology, Thailand

Outline of Presentation  Background  Objectives  Recent coastline changes at the north-eastern part of the Meghna Estuary  Seasonal variation of erosion-accretion around Urir Char Island of Meghna Estuary  Hydrodynamic and morphological modeling for cross dam impacts  Conclusions

The Ganges, the Brahmaputra, the Meghna River Systems Brahmaputra Basin Ganges Basin Meghna Basin Monthly water and sediment discharge into Meghna Estuary, Islam et al. J Mar Sys (2002) Meghna Estuary receives more than a billion tons of sediments every year. Meghna Estuary Sediment discharge into the Meghna Estuary is highest and water discharge Bay of Bengal is 3 rd highest in the world.

Dynamic Change of Coastline in the Study Area 1990 1990 2010 2010 Discharge from Meghna Tide 30km 30km Year Erosion ( SqKm) Accretion (SqKm) 1973 - 84 692 859 Such high rate of coastline movement can’t be found at any 1984 - 90 569 616 other parts of the world. (de Wilde, 2011) 1990 - 96 347 609 Significant and dynamic coastal morphology change has strong 1996 - 05 604 724 impacts on development of coastal area in Bangladesh 1973 - 05 1039 1792 For entire Meghna Estuary, (BWDB 2005) Lack of measured data makes it difficult to fully understand the Net annual accretion rate (de Wilde, 2011) phenomena. 1973~2000 2000~2008 Annual rate 18.8 25.0

Objectives The overall objective of the research work is to develop a monitoring system for large scale morphology change around the Meghna Estuary (MES) of Bangladesh The specific objectives are:  Analyze satellite data to identify the historic and recent morphology changes in the MES area as well as to distinguish the impact of cross dams.  Obtain hydrodynamic data and investigate the relationship between hydrodynamic events and observed morphology changes.  Apply numerical models to analyze morphological changes.  Assess impact of climate change on the morphology changes of MES area.

Methodology 90 0 40’ 91 0 20’ 92 0 00’ ¯ 22 0 50’ Noakhali Urir Char Bhola Char Jublee Chittagong Jahajjir Char Sandwip Hatiya 22 0 10’ Meghna Estuary Nijhum Dwip 0 12.5 25 km Study Area

Calculated TWL using WTWC Boon J (2007) Secrets of the Tide: Tide and Tidal Current Analysis and Applications, Storm surges and Sea Level Trends Horwood Publishing Chichester UK

Tidal phase difference (min) at three selected locations Year Date January 15 March 2 2007 (1005) (945) July 18 December 3 March 4 April 5 TWL (m) April 19 (960) 2008 June 4 July 20 October 20 January 20 March 7 2009 September 7 Time (min) December 8 January 23 2010 March 10 About one hour tidal phase January 12 difference at the selected three January 26 2011 locations February 27 April 14

10 Mar 2010 15 Jan 2007 Calculated TWL on the days 15 Jan 2007 10 Mar 2010 when images were selected PALSAR image dates: Year Date January 15 2007 March 10 2010 Time (hr) Time (hr) 12 Sep 2013 30 Oct 2013 12 Sep 2013 30 Oct 2013 Landsat image dates: Year Date September 12 2013 October 30 2013 Time (hr) Time (hr)

Sandwip Urir Char

Hatiya Jahajir Char

Area (km 2 ) on Area (km 2 ) on Area (km 2 ) of Islands 30 Oct 2013 12 Sep 2013 Intertidal Mudflat 118.82 128.36 9.54 Urir Char 210.66 242.30 31.64 Sandwip 217.50 247.45 29.95 Jahajir Char 431.41 483.14 51.72 Hatiya

Total area (km 2 ) Area change (km 2 ) Islands Jan 2007 Mar 2010 Oct 2013 ’07~’10 ’10~’13 102.40 115.05 118.82 12.65 3.77 Urir Char 222.66 221.93 210.66 -0.73 -11.27 Sandwip 101.77 189.63 217.50 87.86 27.88 Jahajir Char - - 431.41 - - Hatiya

Sandwip Urir Char

Jahajir Char Hatiya

Erosion area (km 2 ) Accretion area (km 2 ) Islands 2007~2010 2010~2013 2007~2010 2010~2013 3.31 5.63 15.92 10.26 Urir Char 9.08 11.49 8.62 1.46 Sandwip 4.16 16.36 90.77 45.90 Jahajir Char 3.12 4.73 - - North Hatiya Net: 2.6 km 2 per year From 2007~2011 3.4 km 2 from PALSAR (Taguchi et al. 2013)

• Annual rate of accretion of Urir Char island has decreased from 5.84 km 2 per year between 2007~2010 to 1.05 km 2 per year between 2010~2013. • Sandwip island has been eroding at a higher rate of 3.15 km 2 per year between 2010~2013 compared to 0.34 km 2 per year between 2007~2010.

PART 2 Seasonal variation of erosion-accretion around Urir Char Island using PALSAR images

Topographic features Very Urir Char shallow 10km N 10km

21 images from Jan.2007 to Apr 2011 Analysis of PALSAR imagery Shoreline extraction based on local XY coordinates Target site Extracted shoreline change land sea Time-series of observed land area Urir-Char 20 Noakhali area change(km 2 ) 面積変化 (km 2 ) 0 2008.1 2009.1 2010.1 2011.1 2007.1

Challenge of this study • Observed shoreline change includes the change due to morphology change (erosion- accretion) and temporal shoreline change due to the difference in tidal water level when the PALSAR image was recorded. • Many parts of the target site has tidal flat and nearshore coast with very mild slopes. • Primary factors of the actual morphology change should be: (i) wind waves; (ii) tidal currents; (iii) sediment discharges from the river. • Most of these hydrodynamic data are not available around the target site. This study combines numerical model and available data for estimations of time-varying hydrodynamic conditions. Tidal flat around Urir Char Typical shoreline of Noakhali

Ocean tide model + non-linear shallow water model Tide Bathymetry: GEBCO(original) Ocean tide model(Nao.99b ） C -Assimilated to TOPEX/POSEIDON and provides accurate predictions of tides at arbitrary locations in the open ocean B -Influence of nearshore bathymetry is not accounted for and A thus loses accuracy near the shore 2 A B C 2 2 1 Nao.99b 0 0 0 -1 -2 (m) -2 Modified bathymetry 150 160 170 180 190 200 150 160 170 180 190 200 150 160 170 180 190 200 comparisons of Nao.99b (black line) and measured (red dot) tides at st. A, B and C Use Nao.99b to specify offshore BC and compute tidal response by non-linear wave model Bathymetry: Based on General Bathymetric Chart of Oceans (GEBCO). Modifications were needed for nearshore water depth and land-ocean boundaries. - PALSAR and J-SER were used to update the shorelines. - Unrealistic nearshore water depth was corrected so that it yields better predictive skills of tides. Modified bathymetry was consistent with previously measured bathymetry. (m)

Ocean tide model + non-linear shallow water model Tide 2 red dot ： meas. A B C blue line ： present model 2 2 1 0 0 0 Excellent predictive skills of nearshore -1 -2 tides around the target site! -2 150 160 170 180 190 200 150 160 170 180 190 200 150 160 170 180 190 200 (km 2 ) (m) Predicted tide when 10 4.00 PALSAR was recorded 8 3.00 Noakhali Urir-Char predicted tide, h ( t ) 6 2.00 Area change after removal 4 of linear regression trend 1.00 2 Urir-Char 0 0.00 Noakhali -2 -1.00 “Seasonal” trend of tide in -4 -2.00 recording timing of PALSAR h ( t ) -6 -3.00 -8 Tide and area change has strong correlations. -10 -4.00 01/01/2007 01/01/2008 01/01/2009 01/01/2010 01/01/2011

wave and river discharge Significant wave height(m): Jan.2007 ～ April2011 SMB curve 5 −2 4 1 2 𝑕𝐼 1 3 𝑕𝐺 = 0.30 1 − 1 + 0.004 2 2 𝑉 10 𝑉 10 3 −5 1 3 𝑕𝑈 1 3 𝑕𝐺 = 1.37 1 − 1 + 0.008 2 2 2𝜌𝑉 10 𝑉 10 SMB curves were used for estimations of 1 wave properties based on the wind data. 0 01/01/2007 01/01/2008 01/01/2009 01/01/2010 01/01/2011 River Discharge Monthly-averaged precipitation (Jan2007 - Apr2011. mm/day) -River discharge was related to the total 18 precipitation over the catchment area of the Meghna River. 15 - CMAP monthly-averaged precipitation was used. 12 -There should be a time lag among: (i) instantaneous precipitation; (ii) resulting 9 discharge at the river mouth and (iii) 6 sedimentation around the target site. 3 - Time lag was accounted for as one of calibration parameters of the following 0 fitting curves of the observed area change. Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 Jan-10 Jul-10 Jan-11

Impact of various factors on observed area change Fitting curve of the observed area change was proposed as functions of estimated parameters. 𝑢 𝑢 𝑢 𝑢 𝑒𝑢 + 𝑏 4 𝐼 2 (𝑢)𝑒𝑢 𝐵 𝑢 = 𝐵 0 + 𝑏 1 𝜃(𝑢) + 𝑏 2 𝑅 𝑢 − 𝜒 𝑒𝑢 + 𝑏 3 𝐼 0 0 0 A(t): Area change of Urir-Char and Noakhali h (t): tide, Q(t): precipitation, j : time lag, H(t): wave height - Least-square method was applied for estimation of the best-fit parameters of a1 ~ a4. - Time lag, 𝜒 was fixed in each analysis but the values of j was altered within 80< j (days) <120. - Time lag of j = 110days yielded the best fit curve. Area change ( observed and fitted ) observed 観測値 再現値 fitted