Integrated flood Management Kampala 1D/2Dmodelling and scale issues Victor Jetten, Richard Sliuzas, Janneke Ettema Shuaib Luaise (Makerere University) DISASTER RISK MANAGEMENT @ ITC Somewhat based on: IPCC SREX report, 2012 INTEGRATED FLOOD MANAGEMENT KAMPALA 1. City-wide assessment of flood risks & climate change impacts 2. Detailed flood risk assessment in flood ‘hotspot’ 3. Develop a strategy and action plan for improved and integrated flood management. Partners: UN-HABITAT Cities and Climate Change Initiative (CCCI) Counterpart: KCCA – Kampala Capital City Authorities Makerere University, Hydroc Consultants, Local NGO’s MONTHLY FLASH FLOODS DRIVER 1: ONE OF THE FASTEST GROWING CITIES IN AFRICA 2010 Modeled density 2020 DRIVER 2: CLIMATE CHANGE Temperature: significantly warmer by a few degrees in 2090. Very little change up to 2030. Impacts unknown: drought, lake Victoria water balance, local weather systems? Rainfall there is already a large variability Extremes: possibly larger proportion of rainfall in large events (statistically not significant, but best to be prepared!) “Inconvenient truth”: cities are not “climate proof” now, used often as an excuse for management/planning problems Tyndall Centre for Climate Change Research, McSweeny et al. (2011) KAMPALA RAINFALL DATA… Detailed rainfall data not available Two sources: Outspan Primary School in Bwaise III area Automatic weather station at Makarere University campus RAINFALL LEADING TO FLASH FLOODS Design discharge based on 1:10 year event = 100 mm/day. We do NOT know what this rainstorm looks like. We measured a 1:2 year rainstorm with 66.2 mm and intensities > 100 mm/h, and scaled this event up Important: the Kampala drainage master plan uses a design rainstorm infiltration based on a USDA-SCS method that generates aAverage longer, lessrates intense than measured. openLISEM model system Spatial, event based, high resolution Rainfall data Gauge areas Rainfall Runoff, erosion, flooding Vegetation Buildings Rain harvesting INTERCEPTION opensource, freeware http://blogs.itc.nl/lisem INFILTRATION SPLASH DETACHMENT SURFACE STORAGE Soil cohesion Texture D50 Roads, Structures DETACHMENT / DEPOSITION SEDIMENT TRANSPORT OVERLAND FLOW 1D Channel cohesion Texture D50 DETACHMENT / DEPOSITION SEDIMENT TRANSPORT CHANNEL FLOW 1D Sediment Discharge Channel Discharge Soil properties Land use Roads Buildings DEM Roughness Obstructions FLOODING 2D Flood Discharge DEM Channel properties Culverts ORDER OF FLOW PROCESSES kw 1 kw 2 sv kw kw 3 4 kw sv sv kw = kinematic wave sv = Saint Venant kw kw 2D ‘FULLSWOF’ SHALLOW FLOOD SIMULATION Freeware open-source University of Orleans Finite volume solution of saint Venant equations, with “Modified Upwind Scheme for Conservation Laws” (MUSCL) scheme and to avoid oscillations “Harten, Lax, van Leer” scheme for “shock proof” differential equation solutions Fast and stable: 2-step iteration with varying timesteps to ensure stability (~10-0.1 sec) Olivier Delestre, Stéphane Cordier, Francois James, Frédéric Darboux COUPLING 1D AND 2D Two moments of coupling: a. 1D runoff reaching the 2D flood zone Mixing principle (turbulence): runoff continues in the floodzone but the velocity decreases rapidly: Manning’s n resistance increases with flood depth: n = n*exp(-ah) b. Flood zone emptying through the channel : Each timestep make one water level between channel and surroundings => THE REAL PROBLEM: DATA ON URBAN HYDROLOGY Rooftop some interception no infiltration max runoff Vegetation, bare soil interception infiltration less runoff Drain no interception some infiltration guided runoff Murrum road no interception min. infiltration less runoff Dealing with sub-pixel information Combine into one infiltration/runoff response Channel information: Dimensions, flow network Road information: Cover, flow resistance, impermeable Building information: Cover, roof storage, raindrums Vegetation information: Cover, canopy storage, flow resistance Soil structure: Crusting, Compaction (infiltration) Soil physical information: Ksat, porosity, suction, moisture content FROM SATELLITE IMAGE TO FRACTIONS OF SURFACE PROPERTY PER PIXELS 1m land use map 10 m 10m Vegetation fraction 10m Bare surface fraction 0.5 m resolution Worldview image Worldview 2 is out, 0.2m resolution 8 bands 800 US$ for 20 km2 10m House fraction ACCURATE DRAINAGE SYSTEM NETWORK Tertiary secondary primary drains Tertiary drains badly maintained, blocked by sediment/garbage Secondary drains are being cleaned Primary drain is being improved SCENARIO 1 - PRIMARY DRAIN IMPROVED, 1:10 YEAR EVENT Include Simulation here Simulation here culverts SOME KEY GOVERNANCE FACTS People living in slums (former wetlands) are there partly illegally (but they rent land from the King of Kampala so there is some form of tenancy) Complicated tenancy system between “traditional” Buganda land board and Kampala municipality, 4 tenure systems exist next to each other Unplanned, unregistered development Slums are extremely dynamic, people live there from a day to a few months, day time/nighttime and no recorded figures for that, no statistics Some good schools in slums (twinning with UK nand US schools)! One of the reasons for migration to the city, apart from economics Many NGO’s, people know exactly the required answers to questionnaires Key question: are people upstream prepared to take action for people downstream (who are there illegally in their view) WHAT ABOUT RISK? There is hardly any physical damage, there are no physical vulnerability curves to be made There is social vulnerability in the slums: poverty, health, environment FULL RISK ANALYSIS WAS NOT DONE Risk as “expected losses” is almost impossible: No direct physical damage health problems related to standing water, waste management, social disruption etc. poor methodology for that 3 Stakeholder meetings throughout the project (“slum dwellers”, authorities, engineers, planners etc) to identify “quick wins” and long term strategies, and identify who is responsible and can take action TWO SOLUTIONS TO DECREASE VULNERABILITY Improve drainage system City engineering larger drainage channels Community self-help cleaning Increase resilience at house level Elevate houses Small dikes surrounding house Bricked-up doorways DRAINAGE SYSTEM ASPECTS RESILIENCE STRATEGIES CITY GROWTH, MODELED HOUSING DENSITIES 2020 Growth will take place in the vicinity of existing buildings 6.5% 4.2% growth per year Infiltration with 1:10 year rainfall (100 mm) 2013 situation Infil = 63.31 mm (1,775,000 m3) 2020 trend growth Infil = 51.86 mm (1,453,000 m3 = -22%) SUSTAINABLE URBAN DRIANAGE SYSTEMS (SUDS) Advantages: Infiltration and slow down flow, Avoid erosion Filter function for groundwater (leading to wells and sources) Double function: grazing, agriculture, recreation? Buffers as temporary storage ESTIMATED SCENARIO EFFECTS now Master plan Grassed waterway Flood zonation Structures in the Flood zone to be removed IMPLICATIONS FOR PHYSICAL PLANNING Improve drainage with “more concrete”, wider channels, will only evacuate water faster from the slopes to the valley Grassed waterways will work city repsosibility Construction and maintenance Displacement of people, eviction, possibly many lawsuits Not all land is owned by the municipality, so major planning requires agreement between all parties Water harvesting at house level people’s responsibility Behavioral change, maintenance of grass in plots Subsidy for water tanks needed Awareness programme CONCLUSIONS Integrated Flood Management is really needed here: upstream-downstream Because of the high infiltration capacity, avoid surface sealing at all cost contrary to planning policy that wants densification Risk as a central concept expected losses or potential damages, but hard to establish because no direct damages, we need research and better methods (social risk) Every solution needs a mix of engineering and planning, and has major planning and governance implications THANK YOU
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