Urban Poverty & Climate Change in Dar es Salaam, Tanzania:

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Flood Modeling 128 Annex 5 A flood modeling exercise was undertaken by Ardhi University to map potential changes in rainfall regime and sea level rise on the flood extent and depth in the at-risk areas that were covered in the socio-economic surveys. A combined 1D-2D hydrodynamic model known as SOBEK was used (developed by Delft Hydraulics Software). The flood propagation model required spatial data (including a digital elevation model (DEM) and surface roughness estimates) and temporal data (such as initial water level, and downstream and upstream boundary conditions). Digital Elevation Model (DEM) Aster Digital Elevation model (DEM) with 30m resolution was used in this study and the 30m grid size was resampled to 15m. The DEM was then converted to standard Arc Info ASCII (.asc) format, required by SOBEK. Surface Roughness Surface roughness is another important spatial data parameter, indicating resistance to the flow of water on a floodplain. The surface roughness map was derived from a land-use map and was generated at the same resolution as the DEM to ensure that for each cell, both elevation information and roughness values were available (Alkema et al., 2007). Initial and boundary conditions The initial condition describes the initial state of the system, in this case water levels and fluxes at the start of the computation. In this study the restart file was used to define initial condition of the model. The restart file was created by running the model starting with dry conditions until the hydraulically stable starting point of simulation was reached (Alkema et al., 2007). Boundary conditions for flood model were applied to define the inflow and outflow elements of the model domain. In this study, there were a number of upper boundary conditions in which discharge data was used and one downstream boundary where a constant water level was used. Model schematization Schematization involved adding the flood model components using a network editor known as NETTER available in SOBEK. The model components added include: river cross-section, flow calculation points, 1D boundary nodes (upstream and downstream), 1D-2D-internal boundary node, connection nodes, measurement stations, and hydraulic structures (bridges). NETTER offers a way to assign attribute values for various added nodes. The schematization starts by importing the 2D network, which represents the terrain elevation in ASCII data format. For quick assessment of the model performance, history boundaries (where water depth, and water velocity are recorded for a specific pixel) were placed for selected areas. A 1D flow was represented by a series of crosssections perpendicular to the direction of the river flow. The river is defined by reaches
connected together by connection nodes. In the 1D model the flow of water is characterized by the channel characteristics defined by the cross section, bed and surface level as well as the roughness coefficient Model calibration and scenario simulations The model was calibrated in order to find the optimal set of roughness values that would result in acceptable differences between the model outputs and observed field data. After calibration of the1D-2D flood model, the effects of changes in rainfall and sea level on flood characteristics in Dar es Salaam city were analyzed, with various sets of values used. In the Report, Figure 28 shows a map of Dar es Salaam with the case study area that was modeled, while Figures 29 (a), (b) and (c) shows flood extents for a 5, 10, and 50 year flood return period with varying rainfall magnitudes and sea level rise set at 2m. 129
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Final Report Urban Poverty & Climat
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5.2 Relevant policies..............
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List of Boxes Box 1 Flood Early War
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NLFEP NSSCP NTD PMI PMORALG PRB PRE
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over coming decades in Dar es Salaa
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1 Introduction 1.1 Background to th
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water is unsafe for household use.
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Figure 1(a) shows Dar es Salaam’s
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For each location, the area leader
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displays the major zones. Natural v
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Figure 5: Trend of mean minimum tem
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Figure 9: Number of rain days per y
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Table 2: Information on significant
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Figure 12: Projected mean annual te
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Figure 15: Projections of monthly p
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Table 3 Population and assets expos
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climatic events (e.g., the droughts
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Bank, 2002). IFPRI (2006) also show
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quality. Olvera et al. (2002) state
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Several agencies are engaged in hou
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water table and poor drainage syste
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Figure 20: Illnesses and diseases s
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158 cases of cholera in 2009 (6 bel
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providing a suitable breeding groun
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asked about strategies used to comb
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From Table 5, it may be seen that a
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contaminated rivers that not only c
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The link between climate and income
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4 The Urban Poverty - Climate Chang
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(vi) Kunduchi and Bahari Beach Thes
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Figure 25: Flood hazard zone map ov
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Photo 3 Waste-dumping along storm-w
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disease incidence. Prolonged drough
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Figure 28 (b) Modeled flood extent
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4.3 Poverty, pollution and GHG emit
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households) and gas (3 percent). Ta
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Box 3: Roles of the City Council an
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5.3 Programs and projects 5.3.1 Red
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Page 83 and 84: 4 GEF Trust Fund - Climate Change f
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Page 87 and 88: change, so that they could formulat
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Page 91 and 92: Kyessi, S and Kyessi, A. (2007). Re
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Page 95 and 96: Table 2: Construction Materials Wal
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Page 99 and 100: 31. How does your water taste: 1.Go
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Page 107 and 108: water drainage channel 2.1 Assessme
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Page 111 and 112: No 1 Name of City Program Instituti
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Page 115 and 116: 3 Environmental Monitoring 4 Beach
Page 117 and 118: No Type of poverty alleviation supp
Page 119 and 120: KEY INFORMANT INTERVIEW CHECKLIST 1
Page 121 and 122: Dar Es Salaam Administrative Struct
Page 123 and 124: CITY COUNCIL Officials Interviewed
Page 125 and 126: Ubungo Kibangu Paul Thomas Tabata-M
Page 127: A simplified flowchart of the metho
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