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Flood Assessment and Monitoring using RS and GIS WMO/FAO Training Workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for SADC.

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Presentation on theme: "Flood Assessment and Monitoring using RS and GIS WMO/FAO Training Workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for SADC."— Presentation transcript:

1 Flood Assessment and Monitoring using RS and GIS WMO/FAO Training Workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for SADC countries November 14-18, 2005 Tamuka Magadzire USGS/FEWSNET, SADC RRSU

2 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

3 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

4 Hydrological Cycle Source: Columbia university:

5 Hydrological Cycle The hydrological cycle is composed of a number of processes including –Evapotranspiration –Condensation and Cloud formation –Precipitation –Infiltration and Percolation –Runoff and stream flow –Subsurface interflow Different applications emphasize different components, based on the domain of interest

6 Hydrological Cycle

7 Flooding is as a result of complex interactions between rainfall and surface processes Generally, the more the rainfall, the greater the likelihood of flooding The amount of runoff generated plays a significant role in the flooding process

8 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

9 Topography & stream networks Some common hydrological knowledge –Water flows downhill –Water accumulates downstream, and water falling further from river will take longer to get there –Steeper areas are less likely to be flooded than flat areas –Areas nearer the river network are more likely to be flooded –Areas downstream in flood plains are more flood- prone than areas upstream nearer river source

10 Topography & stream networks In addition to this, water interactions in hydrological and flood analysis tend to be confined to river basins GIS analysis can help us define –the outline of the river basin –the stream networks –the topology of the streams and basins –the topography or terrain related characteristics of a basin that have a bearing on flooding processes A Digital Elevation Model (DEM) is required

11 Topography & stream networks A little more on DEMs –Can be defined as a digital representation of the elevation variations in the earth’s surface –Two models are common: A raster grid A Triangulated Irregular Network (TIN) –Many applications for hydrological analysis use raster grids –Sources of DEM include those made from: SRTM Data A combination of some or all of Contour, Spot height, River, Lake data *** [Recommended]

12 Using Arcview’s Terrain Analysis Functions with USGS 1 km DEM Flow Direction Flow Accumulation Flow Length Hill Length Slope Downstream Subbasin Subbasins Source: USGS

13 Theory behind flow analysis Flow Direction Flow Accumulation Source: ArcView Help System

14 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

15 Surface Conditions Surface conditions affect flooding by affecting the ratio of amount of rainfall to amount of water that infiltrates the soil Rainfall that does not infiltrate either becomes runoff or standing/ponded water.

16 Surface Conditions Surface conditions affecting flooding include: –Soil type (water holding capacity, hydraulic conductivity) –Land cover (imperviousness) –Antecedent moisture conditions SCS Curve Numbers are one way of quantifying the impact of rainfall on runoff

17 Surface Conditions Land Cover Soil Type

18 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

19 Historical flood risk An analysis of historical stream flows can help statistically determine probability of flooding at a point along the river network This is done using a cumulative distribution analysis of stream flow, to give historical return periods for different stream flows and stage heights This can be used to infer the severity associated with different flood return periods

20 Historical flood risk – an example Return Period (years)Discharge in m 3 /sHeight above the Bed level (m) Source: ZINWA

21 Topographic flood risk Areas closer to the river, and flatter areas, are more likely to be flooded by a specific rise in river level. GIS analysis can be used to estimate the area that will be flooded by a given rise in the river level. The main data input is a high-res DEM The flood area for different river levels can be calculated to map the flood risk zones for different flood severities

22 Topographic flood risk – an ArcINFO application Appropriate GIS software such as ArcINFO can be used to calculate the topographic flood risk ArcINFO AML example (K. Asante): –Raise the level of the DEM along the stream network –Use the Fill Function to fill the sinks that are generated by raising the stream level. –Subtract the original DEM from the filled DEM to identify the areas affected by stream rise

23 Topographic flood risk – an ArcINFO application /* Copy the instructions below into an aml (eg makedem.aml) and run from the arc command prompt /* eg *ARC: &run makedem.aml grid setwindow indem indem setcell indem /* strgrid is river grid with 1's in the rivercells and 0's elsewhere fill indem dem # # flowdir flowacc = flowaccumulation ( flowdir ) STRGRID = con ( flowacc >= , 1, 0 ) strlink = streamlink ( ( strgrid / strgrid ), flowdir ) strline = streamline ( ( strgrid / strgrid ), flowdir ) strgrid1 = strgrid &do ndepth := 1 &to 15 &by 1 newgrid%ndepth% = dem + (strgrid%ndepth%) fill newgrid%ndepth% dem%ndepth% # # flowdir%ndepth% &s ddd = %ndepth% + 1 tempgrid = dem%ndepth% - dem flowacc%ndepth% = flowaccumulation ( flowdir%ndepth% ) rivall%ndepth% = con(flowacc%ndepth% >= , 1, 0) /* I am assuming a threshold here of 100,000 cells each 30 x 30 m /* This is not automated if the main channel is the source of inundation area sgrid%ddd% = con(tempgrid > 0, (tempgrid + 1), 0) strgrid%ddd% = con((sgrid%ddd% == 0) and (rivall%ndepth% > 0), (sgrid%ddd% + 1), sgrid%ddd%) /* This ensures that any additional cells along the critical flow path /* are included in strgrid%ddd% before the next computation of flooded area. copy strgrid%ddd% flood%ndepth% kill flowdir%ndepth% all kill flowacc%ndepth% all kill rivall%ndepth% all kill sgrid%ddd% all kill tempgrid all kill strgrid%ndepth% all kill newgrid%ndepth% all &end Source: Kwabena Asante, USGS

24 Topographic flood risk – an ArcINFO application &do ndepth := 1 &to 15 &by 1 newgrid%ndepth% = dem + (strgrid%ndepth%) fill newgrid%ndepth% dem%ndepth% # # flowdir%ndepth% &s ddd = %ndepth% + 1 tempgrid = dem%ndepth% - dem flowacc%ndepth% = flowaccumulation ( flowdir%ndepth% ) rivall%ndepth% = con(flowacc%ndepth% >= , 1, 0) sgrid%ddd% = con(tempgrid > 0, (tempgrid + 1), 0) strgrid%ddd% = con((sgrid%ddd% == 0) and (rivall%ndepth% > 0), (sgrid%ddd% + 1), sgrid%ddd%) /* This ensures that any additional cells along the critical flow path /* are included in strgrid%ddd% before the next computation of flooded area. copy strgrid%ddd% flood%ndepth% kill flowdir%ndepth% all kill flowacc%ndepth% all kill rivall%ndepth% all kill sgrid%ddd% all kill tempgrid all kill strgrid%ndepth% all kill newgrid%ndepth% all &end Source: Kwabena Asante, USGS

25 Topographic flood risk – some results Such an analysis was done for Chokwe district to determine which settlements would be affected by different river rises. Similar analysis was done using SRTM DEM for Beitbridge

26 Example 1 CHOKWE

27 Topographic flood risk – some results Determinação de Área Inundada Usando DEM e Alturas Previstas Source: USGS & ARA-Sul, Mozambique

28 MAPA DE INUNDAÇÃO DO DISTRITO DE CHÒKWÉ, E35 Cidade: Macarretan e Aldeias: Conhane e Mapapa Alt. 4-6m

29 MAPA DE INUNDAÇÃO DO DSTRITO DE CHOKWE, E35 Alt 6-8m Cidade: Macarretane Aldeias : Muzumuia, Muianga, Conhane, Mapapa, Chiaquelane, Marranbandjane, Chiguidela, Malhazene, Chalucuane, Zuza e Chiduchine

30 MAPA DE INUNDAÇÃO DO DISTRITO DE CHÒKWÉ Altura: 8-10m Cidades: Macarretane, Chòkwè e Lionde Aldeias: Muzumuia, Massavasse, Nwachicoloane, Changulene, Muianga, Conhane, Mapapa, Chiaquelane,Marrambandjane,Chiguidela,Malhazene, Chalucuane, Zuza e Chiduachine

31 Example 2 BEITBRIDGE

32 SRTM DEM

33 Potential flood areas: 1m Source: SADC RRSU

34 Potential flood areas: 10m Source: SADC RRSU Notice the “line” down the centre of the flood map. Answer later

35 Potential flood areas: 15m Source: SADC RRSU

36 DEM Errors “DEM Errors” shown in brown. These are the areas that are filled during the Fill operation Source: SADC RRSU Reason for lines in flood areas analysis

37 Combining Statistical and Topographic Flood Risk The Beitbridge Study

38 Flood Risk

39

40

41

42 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

43 Rainfall Analysis When there is lots and lots of rain, result is often (not always) flooding. So a first step in analyzing unfolding flood risk is simple rainfall analysis A subjective analysis that benefits greatly from an enhanced knowledge of the area under analysis, of the recent rainfall history, as of the events upstream Daily rainfall observations over the last few days, and QPF are useful for heavy storms, while dekadal (10-day) sums are useful for persistent weather Encourage use of improved rainfall grids incorporating rain-gauge and satellite data

44 Rainfall Analysis Every day, NOAA CPC produces Rainfall Estimates for the FEWSNET activity. These RFE, as well as QPF are put on the USGS FEWSNET website as graphics: –http://earlywarning.usgs.gov/addshttp://earlywarning.usgs.gov/adds The actual data can also be downloaded: –http://edcwww.cr.usgs.gov/pub/edcuser/fewsips/africa/http://edcwww.cr.usgs.gov/pub/edcuser/fewsips/africa/

45 Rainfall Analysis

46 Rainfall Analysis of potential flood situation March 2001

47 There was much flooding in 2001, which was analyzed, tracked and reported on in the Regional Flood Watch The following analysis shows how rainfall estimates, rainfall proxies, and rainfall forecasts were used to track the flood likelihood Rainfall Analysis – an example

48 Daily Rainfall Estimates Cold Cloud Duration Quantitative Precipitation Forecasts

49 Rainfall Analysis of potential flood situation March 2003

50 Rainfall Analysis – an example Example of rainfall analysis that was done to support the Regional Flood Watch in anticipation of Cyclone Japhet in March The following example illustrates the use of rainfall estimates and the incorporation of antecedent moisture conditions in the analysis

51 Rainfall Analysis – an example Rainfall associated with Cyclone Japhet

52 Rainfall Analysis – an example Antecedent moisture conditions have an influence on flooding

53 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

54 Basin Excess Rainfall Maps One large advantage of rainfall analysis is its simplicity Rainfall analysis has it’s limitations – very subjective, and does not consider basin characteristics or climatology of basin Rainfall that falls within a basin [is converted to runoff, and] accumulates within a basin, affecting flooding downstream within the basin Analysis of basin-specific rainfall is therefore useful for flood analysis

55 Basin Excess Rainfall Maps Basin Excess Rainfall Maps (BERMs) are one solution. USGS produces and updates BERMs operationally (http://earlywarning.usgs.gov/adds)http://earlywarning.usgs.gov/adds BERMs are maps which highlight: –basins experiencing above-average rainfall in the previous ten-day period –river reaches with potentially higher-than-average stream flow BERM products reveal basins and streams experiencing sustained heavy regional rains with increased likelihood of flooding at locations within the basin

56 Basin Excess Rainfall Maps For basin analysis, process is as follows: –Sum RFE over each basin for: 3 day period Dekad Cumulatively for the season –Divide the basin sums by the corresponding long-term average –Assign excess rainfall scores to basins and rivers –Make maps of basins with color codes indicating the excess rainfall score for each basin. This is the BERM

57 Basin Excess Rainfall Maps Source: USGS/FEWSNET

58 Basin Excess Rainfall Maps Two types of maps are produced: –The basin (or catchment) map highlights subbasins locally (i.e. rain falling in sub-basin only) receiving above-average precipitation by color coding the relevant polygons. –The stream map highlights reaches of river [regionally] receiving above-average amounts of precipitation from all areas upstream of them Thus, a subbasin may not be highlighted if only light rain is occurring locally, while the stream passing through may be highlighted, due to heavy rains in upstream catchments

59 Basin Excess Rainfall Maps Source: USGS/FEWSNET

60 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

61 Hydrological Modelling Advantages of BERMs is that –they are simple to produce and do not require much extra information or calculation –They account for basin, and upstream rainfall Disadvantage is that –they do not account for basin characteristics such as soil type, landcover, and antecedent moisture conditions –they do not explicitly account for transport time of water from upstream basins Full-fledged hydrological modelling should take all these factors into account

62 Hydrological Modelling The USGS has developed a geo-spatial Stream Flow Model that uses daily evapotranspiration and precipitation data to predict stream flow, and consequently, flood risk

63 FEWS Flood Risk Monitoring System Flow Diagram Preprocessing MAP MAE Basin Linkage Routing Parameters Soil Parameters Flood Inundation Mapping Landsat 7SPOT Output / Decision Support System Data RFE PET Soil LU/LC DEM QPF Stream Flow Model Water Balance Lumped Routing Dist. Routing Updating Source: USGS

64 Water Balance Conceptual Model

65 Runoff Response Function Flow time from cell to s outlet Aggregate flow times for each day

66 Outlet Sub-basin 3 Main channel Sub-basin 2 Sub-basin Sub-basin 1 Flood Routing Network Main channel

67 ArcView Interface

68 Stream Flow Model Some Derived Model Inputs

69 Flow direction Flow AccumulationFlow Length Hill Length HYDRO1K DEM Derivatives Terrain slopeSub-basin Linkage

70 USGS Global Land Cover Characteristics

71 FAO Digital Soil Map of the World

72 Soil and Land Cover Data Soil Depth Soil WHC Texture SCS Curve No. Hydraulic Conductivity Maximum Impervious

73 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

74 Flood Mapping Using RS Satellites are often used for flood mapping Optical and radar sensors have varied advantages and disadvantages Optical –Many optical sensors available at varying spatial resolution, providing high temporal resolution to monitor flood evolution –Are affected by cloud cover Radar –Are not affected by cloud cover –Difficult to get, often expensive, and need to be ordered in advance

75 Flood Mapping Using RS Freely available data can be downloaded from internet, e.g. MODIS Disadvantage: internet speeds in much of Africa are often prohibitive for downloading these large datasets. Disadvantage 2 is that some of the images are not available in near-real time and so are not useful for flood monitoring One alternative is to download smaller, pre-processed graphics from the internet, and these can be geo- referenced for further analysis Data can also be purchased, or requested from appropriate partners, or through Disaster Management EO Charter

76 Flood Mapping Using RS Processing of optical data to produce flood map: –Water generally has the lowest reflectance in many of the ranges of the optical spectrum –This property can be used to identify water using a simple classification procedure –Disadvantage: water is easily confused with shade (e.g. cloud shadow), so classification cannot be completely automated

77 Flood mapping using Remote Sensing Some Examples

78 Example 1 ERS SAR image Tropical Storm Russ China, 1994 Source: DFO:

79 Example 2 Source: DFO:

80 Example 3 Landsat 7 Browse Image of Luangwa River and western end of Cabora Bassa Reservoir from Dec 19, 2000 Landsat 7 Browse Image of Luangwa River and western end of Cabora Bassa Reservoir from Jan 20, 2001 Source: DFO:

81 Example 4 Source: DFO: Landsat 7 Browse Image from Dec 30, 2000 of the confluence of the Zambizi and Shire rivers in Mozambique and Malawi

82 Example 4 Source: DFO: Geocorrected Modis 250 Image of the confluence of the Zambizi and Shire rivers in Mozambique and Malawi from Feb 25, 2001

83 Example 4 Source: DFO: Inundation map of the Zambezi and Shire Rivers based upon Modis 250 data from Feb 25, 2001

84 Example 5 Geocorrected Modis 250 Image of the lower Zambezi River in Mozambique from Feb 25, Source: DFO:

85 Flood Mapping Using RS So why Do-It-Yourself when you can get all these good maps on the web? Some good reasons include: –Timeliness –Incorporation of locally available relevant datasets (cities, population, infrastructure etc)

86 Outline Introduction: understanding flood processes –Hydrological Cycle –Topography and stream networks –Surface conditions (landcover, soils, antecedence etc) Analyzing historical and topographic flood risk Analyzing current/unfolding flood risk –Rainfall analysis –Basin Excess Rainfall Mapping –Hydrological modeling Flood mapping using RS Incorporating GIS overlays

87 Incorporating GIS Overlays Which geo-spatial datasets are useful for analyzing flood information and producing overlays? What are the sources of the data, and is it readily available? How is the integration done practically? What useful end products can be produced from these overlays? Who are the likely users of these information products (overlays)?

88 Incorporating GIS Overlays Which geo-spatial datasets are useful for analyzing flood information and producing overlays? e.g. –Population, settlements, agriculture fields, transport networks, infrastructure What are the sources of the data, and is it readily available? How is the integration done practically? e.g. –Overlaying the vector datasets of interest on the flood polygon –Intersecting population grid with flood polygon to determine how many people affected What useful end products can be produced from these overlays? –Affected/flooded settlements –Estimate of number of affected people –Estimate of crop hectarage lost due to flooding –Affected transportation routes, and clear transportation routes –Inaccessible (marooned) settlements –Affected infrastructure Who are the likely users of these information products (overlays)? –Potentially affected communities –Disaster Management Authorities and related agencies –Agriculture and crop estimate authorities

89 End-of-File Thank You


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