ASSESSMENT OF MORPHOLOGICAL CHANGES AND VULNERABILITY OF RIVER BANK EROSION ALONGSIDE THE RIVER JAMUNA USING REMOTE SENSING

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1 ASSESSMENT OF MORPHOLOGICAL CHANGES AND VULNERABILITY OF RIVER BANK EROSION ALONGSIDE THE RIVER JAMUNA USING REMOTE SENSING Kabir Uddin a *, Basanta Shrestha b and M. Shamsul Alam c a GIS and Remote Sensing Analyst, b Division Head, International Centre for Integrated Mountain Development (ICIMOD), GPO Box- 226, Khumaltar, Lalitpur, Kathmandu, Nepal. kuddin@icimod.org c Professor, Department of Geography & Environmental Studies, University of Rajshahi, Rajshahi, Bangladesh. md.alam@fulbrightmail.org KEY WORDS: Remote Sensing, GIS, Segmentation, Jamuna, River, Morphology ABSTRACT: River morphology is describe the shapes river channels and how they change over time. This study examine the morphology by the river Jamuna use of Remote Sensing (RS) and Geographic Information Systems (GIS) techniques. Vulnerability and morphological changes have been identified using 2010, 200, 1989, 1980 and 197 five different years Landsat Enhanced Thematic Mapper Plus (ETM+), Thematic Mapper (TM) and Multispectral Scanner (MSS) image and settlement identified using topographic maps Using ecognition/definiens object base image classification performed for river channel mapping and ArcGIS used for accurate information about recent river channel movement and bank erosion. The enumerated average bank erosion and siltation rates were found very high. Per year average erosion was Km 2 and siltation Km 2. Maximum river movement was 5847 meter in the year of 200 and minimum river movement was meter in the year of INTRODUCTION The river Jamuna is one of the three main rivers of Bangladesh. The river is a major contributor to the building up of the delta. There is evidence of severe bank erosion and rapid rates of bank line retreat along the Brahmaputra Jamuna River (Nasreen and Aminul, 200). Riverbank erosion is a natural process, but often anthropogenic activities can have significant impact on the rates of morphological change. River channel changes, such as bank erosion, down cutting and bank accretion, are natural processes for an alluvial river. Developments like sand mining, infrastructure building on the riverbank, artificial cutoffs, bank revetment, construction of reservoirs and land use alterations have changed the natural geomorphological dynamics of rivers (Lane and Richards, 1997; Surian, 1999; Fuller et al., 200; Rinaldi, 200; Li et al., 2007). As a consequence, channel stability is often threatened (Fuller et al., 200; Grant et al., 200; Kesel, 200; Rinaldi, 200). This happens to a channel due to morphological adjustments to accommodate the range of flows and sediment loads from upstream. (Khan et al., 200). The use of remotely sensed data in identify is the trends of river channel and as source of input data to determine river behavior study has became popular in recent years. With the availability of remotely sensed data from different sensors of various platforms with a wide range of *Corresponding author: Kabir Uddin.

2 spatiotemporal, radiometric and spectral resolutions have made remote sensing perhaps. One of the main characteristics of remote sensing is its capability of generating a large amount of information, frequently and spatially and thus studying river morphology. 2. THE STUDY RIVER The study Jamuna river in 1787 a tectonic movement followed by an abnormal flood led changes in the course of the Brahmaputra and started its flow through a new course known as the Jamuna. It is the main channel of the Brahmaputra River when it flows out of India into Bangladesh. Jamuna enters in Bangladesh from the north west side of Kurigram district and flows to south, ending its independent existence as it joins the Padma River near Goalundo Ghat. Bounding coordinates of the river area is W: 89.52, E: , N: , S: The climate of the study area is tropical monsoon. Figure 1. Location map of study area.1 Data Used. METHODOLOGY Based on satellite image quality and availability the primary data were used MMS, TM and ETM+ sensor of Landsat satellite for five different years.

3 Satellite Sensor Path/R ow Landsat5 TM 18/04 Landsat7 ETM+ 18/04 Landsat4 TM 18/04 Landsat MSS 148/04 Landsat1 MSS 148/04 Topographic maps Date/Year _01_ _02_ Data processing and analysis Table 1. List of satellite imagery The Enumerate for the river channel and associate land cover mapping were done is few steps. All the scene Landsat images were not acquired as rectified image. Topographic maps, Landsat MMS and TM image georeferenced into UTM and Zone 45 projection based on generated Ground Control Points (GCP) from Landsat ETM+ (200) image. All images were resample with the nearest neighbour method to a common resolution of 0m. Resample was chosen to a common resolution so that river of interest would be either equal to or larger than the pixel size. Landsat Image Image Georeference Image Rule Set Variable Execute Rule River Channel Map Changed Detected Map GIS GIS Analysis Analysis Generate Statistics River Centre Line Figure 2. Flow diagram of the whole study

4 After that Landsat images were processed in ecognition/definiens software for object-based image analysis (OBIA). Compared with pixel-based methods, this approach shows better classification results with higher accuracy as it uses both spectral and spatial information (Civco et al 2002; Yoon et al 2004; Harken and Sugumaran 2005; Gao et al 2007). The fundamental step of ecognition image analysis is a segmentation of a scene. Multiresolution segmentations were used for objectbased image analysis. Multiresolution Segmentation groups areas of similar pixel values into objects. Consequently homogeneous areas result in larger objects, heterogeneous areas in smaller ones. The most important issues in the context of an object-oriented classification is the accurate segmentation of the input images. A convenient approach was used to run segmentations with different parameters until the result was satisfactory. In the present analysis, the multiresolution algorithm was used; this algorithm locally minimized the average heterogeneity of image objects for a given resolution. For each segment, information on average NDVI, Land and Water Mask slope were derived. This information was used to develop suitable classification algorithms for individual classes. Image objects were linked to class objects and each classification link stored the membership value of the image object to the linked class. With each polygon assigned to a specific class, land cover map including river channel was generated for Jamuna river. After the classified data was exported to shape file format for further processing, such as the elimination of areas smaller than the defined minimum mapping units. Centre line of river from generated river channel. Within seven kilometers of river centre line 4401 settlement/landmark/building identified from topographic maps using ArcGIS. Threaten on settlements analysis based on number of time river flown particular settlement location. The comparison of the river channel location was carried out in the four phases, , , and , for both the riverbanks and the islands. GIS analysis and changed statistics calculated for results and discussion. 4. RESULTS One of the most serious problems in Bangladesh is erosion in river catchments. Analysis of a series of Landsat images, between 197 and 2010, exposed the dynamic nature of the river bank and, including channel migration, movement. The changes river channel from 197 to 2010 were very high and unstable. The river channel location changes during the period , , and are presented in Figure 5. The average bank erosion of was Km 2 and the bank Siltation was similar for both banks, around 24.9 Km2 on average. In 197 Maximum channel movement was 16875m and minimum 214m. In erosion and Siltation faintly increased but both amount was almost same. Figure 6 shows adjacent to Jamuna river settlement/landmark/building particular char land settlement due to the river channel changes several time flattened. Within the 4401 building 101 demolished from 197 to 1000 and 417 building demolished In the year of 1989 and 07 building demolished in 197. There is evidence of severe bank erosion and rapid rates of bank line retreat along the Brahmaputra Jamuna River. This happens to a channel due to morphological adjustments to accommodate the range of flows and sediment loads from upstream. (Khan et al., 200). In 197 to 2010 water area in the river was lot dissimilarity. Maximum water was in the river 1989 and the minimum water was in the water 197 Table 2. This variation could be because of seasonal deviation of satellite image or other region. The water level changes and fluctuation in the dry season would not cause frequent riverbank erosion compared to the same changes and fluctuations if in the wet season (Lu, 2006). The channel erosion and Siltation in was relatively increased when compared between the study periods and The average erosion rates have heavily increased that is Km2 and the annual channel Siltation rate has increased remarkably that t is Km2. In the year of 1980 and 1989 maximum channel

5 movement was 15252m and 17251m near the Kurigram district and minimum channel movement was 28410m and 5518m near the Sirajganj. Minimum river channel movement in Sirajganj due to artificial flow obstacle due to the bridge construction. Figure. Map of Jamuna river channel ( ) with associated land cover Figure 4. Erosion and Siltation rate

6 Year Channel Area(Km2) Table 2. Water area within the River Channel Northing (Km) Table. Eastward channel movement from 197 to 2010 River normally gets silted during their course of flow. Every river carries certain amount of sediment load. The sediment particles try to settle down to the river bottom due to the gravitational force, but may be kept in suspension due to the upward currents in the turbulent flow which may overcome the gravity force. Due to these reasons, the river carries the fine sediment in suspension as suspended load. Whenever the flow velocity in the channel reduces, the silt carried by the water in suspension gets deposited on the bed and sides of the canal.(alam et al., 2008). In the year of erosion and Siltation gone down. The average bank erosion of was Km2 and Siltation was Km2 in this erosion rate gone less Siltation rate.

7 Figure 5. Chanel movement from 197 to 2010 and Threaten Settlements

8 5. CONCLUSIONS This study demonstrates efficient way to determine river channel and understanding river erosion and siltation and how it has trended on settlement alongside the Jamuna river using remote sensing and GIS from medium resolution Landsat images and topographic maps. This type of study is obliging for further planning of river and river adjacent to settlement management an effective manner as it could be incorporated the long time changes of the river morphology. GIS analysis result shown 197 to 2010 significant changed occurred in Jamuna river. Erosion and siltation was regular process and large area of upper Jamuna river it is occurred more and Jamuna bridge area river movement has been reduced from the year Different amount water area identified from satellite images may have different month of imagery. For better scenario of Jamuna river satellite imagery will have same date with same sensor and Radar image more potential due to cloudy weather of study area.. 6. ACKNOWLEDGEMENTS We are gratefully acknowledged MENRIS division of ICIMOD and obliged for helpful discussion with Dr. Amarnath Giriraj. 7. REFERENCES Alam, J. B., and Uddin, M., Ahmed,J.U., Cacovean,. H. Rahman, M.H. Banik, B.K.Yesmin,N. Study of Morphological Change of River Old Brahmaputra And Its Social Impacts By Remote Sensing: Geographia Technica, no.2, 7, 7-8. Benz, U. C., Hoffmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58, Blaschke T., Lang S., Lorup E., Strobl J., Zeil P., Object-oriented image processing in an integrated GIS/remote sensing environment and perspectives for environmental applications. In: Cremers A, Greve K, editors. Umwel tinformation fu r Planung, Politik und O ffentlichkeit/environmental Information for Planning, Politics and the Public. Vol 2. Marburg, Germany: Metropolis Verlag, pp Civco D.L, Hurd J.D., Wilson E.H., Song M., Zhang Z., A comparison of land use and land cover change detection methods. In: Proceedings, 2002 ASPRS-ACSM Annual Conference and FIG XXII Congress,Washington, DC, April Bethesda, MD: American Society for Photogrammetry & Remote Sensing, pp Definiens Definiens Professional 5 User Guide. Munich, Germany: Definiens AG. Fuller, I.C., Large, A.R.G., Milan, D.J., 200. Quantifying channel development and sediment transfer following chute-off in a wandering gravel-bed river. Geomorphology 54, Gao Y, Mas JF, Niemeyer I, Marpu PR, Palacio JL Object based image analysis for forest area land cover mapping. In: Proceedings, International Symposium for Spatial Data Quality (ISSDQ). Enschede, the Netherlands, 1 15 June, Enschede, the Netherlands: ISSDQ 2007 Secretariat. accessed on 21 April Grant, G.E., Schmidt, J.C., Lewis, S.L., 200. A geological framework for interpreting downstream effects of dams on Rivers. In: O Connor, J.E., Grant, G.E. (Eds.), A Peculiar River. American Geophysical Union,

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