0 E 50 N 30 E Slum Slum Slum 3 Slum 4 Slum 5 Slum 6 Slum 7 Slum 8 Slum 9 Slum 0 40 N CASE CASE CASE CASE 3 4 ~~
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1 Study on sensitivity analysis of main factors for inundation in Dhaka city, Bangladesh Masakazu HASHIMOTO, Tadashi SUETSUGI, Kengo SUNADA Yutaka ICHIKAWA, Naoki KONDO and Kei NISHIDA Bangladesh is one of the most flood-prone countries in the world. Especially, in Dhaka city, capital of Bangladesh, inundation problem is very serious. To prevent the social problem caused by inundation, such as traffic jam and health risk in low lying slum areas, it is important to evaluate the influence of inundations for plan to develop the city. In such a developing country, dataset about hydrology is not enough to perform inundation analysis. Therefore sensitivity analysis was performed for ) DEM, ) embankment, 3) building occupied ratio and 4) rivers as beginning step to evaluate the inundation condition. From the result, it was found that inundation in city areas is not only caused by elevation deference. Especially the influence of building ratio is remarkable as a cause of inundation, secondary, embankment is effective. As a further extent, sewerage network should be considered to simulate the inundation with more high accuracy at overestimated area in this study. Key Words: internal inundation analysis, sensitivity analysis, numerical model
2 0 E 50 N 30 E Slum Slum Slum 3 Slum 4 Slum 5 Slum 6 Slum 7 Slum 8 Slum 9 Slum 0 40 N CASE CASE CASE CASE 3 4 ~~
3 ) (x ) (y ) h () t + M x + N y = q rain M um vm + + t x y H = gh x N un vn H + + = gh t x y y () h(m), M, Nx, y (m/s), M=uh, N=vh, u, vx, y (m/s), xb, yb x, y, H (m)q rain τ xor y(b) = gn (u or v) u + v ρ 3 h τ xb τ yb (3) (4) ρ ρ (5) 3) (6), (7) 3) m M, N = 0.35h gh " h M, N = 0.35h gh % $ ' (6) # h 3& " M, N = 0.9h g(h h ) h > % $ ' (7) h # 3& h (m), h (m) m (4) 4) (9) A n 3 (5)
4 Difference of inundation depth (m) m m Difference of inundation depth (m) / n n = n θ 4 θ h 3 (8) 0 n = n =0.060, n =0.047, n 3 = ) 3 ( ) n=0.04 (8), (9)= () 0.80() n=0.03 A + n Slum number A + A AquaMODIS A + n + A 3 3 A3 (9) Slum number 5) a) b) 6,, 7, 8, 9 ( 7, 9) ( 8)( ) 7,
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6 Mollah ) 7, 8, 9 ( 4, 7, 8, 9) ),, 6 ) ) 3) 4) 5) ) Khondoker Golam Tawhid, Jan-Erik Gustafsson: Causes and Effects of Water Logging in Dhaka City, Bangladesh (M. Eng.), KTH Royal Institute of Technology, 004. ) MoEF, UNEP, BCAS, Dhaka City State of Environment 005 (006). 3) JICA, Master Plan Study for Greater Dhaka Protection Project, FAP 8A (99). 4) So Kazama, Tatsuhito Kono, Kengo Kakiuchi, Masaki Sawamoto: Evaluation of flood control and inundation conservation in Cambodia using flood and economic growth models, Hydrological Processes, Vol.3, No.4, pp.63, ),,, : 00,, Vol.68, No.4, pp.498, 0. 6) FFWC: Flood Forecasting and Warning Centre, Bangladesh HP, ( ) 7) Ole Mark, C. Wennberg, T. van Kalken, F. Rabbi, B. Albinsson: Risk analyses for sewer systems based on numerical modeling and GIS, Safety Science, Vol.30, pp.06, ) Ole Mark, Sutat Weesakul, Chusit Apirumanekul, Surajate Boonya Aroonnet, Slobodan Djordjević: Potential and limitations of D modelling of urban flooding, Journal of Hydrology, Vol.99, No.3-4, pp.99, ),,,, :,, Vol.67, pp.990, 0. 0),, :,, pp.94, 00. ) Kabirul Ahsan Mollah, Kei Nishida, Naoki Kondo, Zentaro Yamagata: Children s Health Deficits due to Diarrhoea: Effects of Water Supply and Sanitation Systems in Slums with Different Water Logging Conditions, Journal of Water and Environment Technology, Vol.7, No.4, pp.9-77, 009. ),, :,, pp.37, ) :,, ) : ()--,, Vol.3400, ) G. PRIESTNALL, J. Jaafar, A. Duncan: Extracting urban features from LiDAR digital surface models, Computers, Environment and Urban Systems, Vol.4, pp.78, ) :,, Vol.700, No.-54, pp.,
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