River size representation in global flood models: a geospatial investigation Mark Bernhofen PhD Student - University of Leeds cn13mvb@leeds.ac.uk GFP Conference, Guangzhou. Session 3 – 12 June, 2019
Overview • Follows on from the global flood model intercomparison work (Trigg et al, 2016). • Study found 30-40% agreement between 6 global flood models in Africa. • Difficult to quantify the significance of river size representation on model disagreement using different global flood models. • Need some independent (from GFMs) measure of flood extent. How do the Global Flood Model river size thresholds affect exposure estimates? Slide 1/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC Slide 2/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC 5000 km 2 threshold Slide 2/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC 1000 km 2 threshold Slide 2/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC 500 km 2 threshold Slide 2/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC 50 km 2 threshold Slide 2/12
Global Model Thresholds: Nigeria Drainage Thresholds Global Model 50 km 2 Fathom 500 km 2 U-Tokyo, ECMWF 1000 km 2 CIMA-UNEP 5000 km 2 JRC 5 km 2 threshold Slide 2/12
Height Above Nearest Drainage (H (HAND) • Terrain model developed by Nobre et al. (2011) • Needs only terrain derived datasets as inputs: • Digital Elevation Model (DEM) • Drainage directions • River upstream drainage area • Has been successfully used in studies as a quasi or (0 dimensional) flood model. • Quick to run at large-scales. • Easily produce an auxiliary dataset of river size (upstream drainage area) from Nobre et al. (2011) Slide 3/12
HAND Model Setup Strahler Stream Order HAND height 1 2 m • Using MERIT Hydro data 2 2 m • HAND heights were “calibrated” using 100y flood 3 3 m maps in Nigeria and the UK. 4 4 m • For rivers with Strahler Stream Orders >=6, JRC’s 5 5 m 100 year flood map was used in Nigeria. 6 6 m 7 7 m • JRC’s model was the best of the GFMs in a previous validation study in Nigeria (Bernhofen et al, 2018) 8 8 m 9 10 m • For smaller rivers with stream orders <=7 the 10 12 m Environment Agency’s 100 year flood zone map for the UK was used. 11 12 m Slide 4/12
HAND Model Quality Models in HAND Height Agreement 1m 12m HAND Model Aggregated GFMs (from Trigg et al, 2015) Slide 5/12
HAND Model Quality Good Fairly good Fair Fairly poor Poor Koppen-Geiger Climate Classifications HAND Model Performance Slide 5/12
Exposure Data HRSL availability • Using Facebook and Columbia University’s High Resolution Settlement Layer (HRSL) (30m resolution) in the 22 countries it is available. • Use WorldPop data (100m resolution) in all countries. • Can compare results to see how population data affects the exposure estimates. Slide 6/12
Flood Exposure - Afr frica Population Exposed to Flooding (WorldPop) 250 Millions 19% 200 15% 150 Population 11% 9% 100 7% 50 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) “%” relates to total population Slide 7/12
Flood Exposure - Afr frica Population Exposed to Flooding (WorldPop) 100 Millions 12% 80 9% 60 Population 6% 5% 40 4% 20 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) “%” relates to total population Slide 7/12
HRSL vs. . WorldPop Percentage change in exposure estimates when using HRSL vs. WorldPop River Drainage Area Thresholds (km 2 ) 5-50 50-500 500-1000 1000-5000 5000< 0% -5% -10% -12% Percentage Change -15% -20% -25% -28% -30% Results correspond with Smith et al (2019) -29% -31% Nature Comms. -35% -35% -40% Slide 8/12
Flood Exposure – HRSL Population Exposed to Flooding (HRSL) 60 Millions 11% 50 8% 40 Population 6% 30 5% 4% 20 10 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) “%” relates to total population Slide 9/12
In Interesting Countries Population Exposed to Flooding (HRSL) Madagascar 3 Millions 11% 2.5 2 8% Population 1.5 5% 4% 1 0.5 1% 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) Slide 10/12
Interesting Countries In Population Exposed to Flooding (HRSL) Benin 1.4 Millions 12% 1.2 10% 9% 9% 1 Population 0.8 0.6 0.4 3% 0.2 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) Slide 10/12
Interesting Countries In Population Exposed to Flooding (HRSL) Ivory Coast 2 Millions 8% 1.8 7% 1.6 6% 6% 6% 1.4 1.2 Population 1 0.8 0.6 0.4 0.2 0 5< 50< 500< 1000< 5000< Minimum Drainage Area Threshold (km 2 ) Slide 10/12
Conclusions • Different GFM minimum threshold river sizes result in significantly different exposure estimates (on average, up to a factor of 2.0). • Certain country’s exposure estimates are more sensitive to river size representation than others. • Improving river representation beyond current GFM limits could incorporate an additional 30% of potential exposed population into the modelling frameworks • WorldPop population data overestimates exposure compared to Facebook High Resolution Settlement Layer, especially on smaller rivers. Slide 11/12
Next xt Steps • Fine tune the HAND model calibration to include different climate zones. • Expand study globally • Global picture of flood exposure from different size rivers. • Can inform global flood modelling community about where it’s important to consider river size representation and which countries would benefit from improved representation Slide 12/12
Thanks for listening.
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