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"# EU JRC global flood depth-damage functions\n",
"\n",
"This data set comprises a set of global flood depth-damage functions. Damage curves are specified along with a measure of the uncertainty of the curves. Both the paper and data set itself are available via the link: \n",
"\n",
"https://publications.jrc.ec.europa.eu/repository/handle/JRC105688\n",
"\n",
"## Notes\n",
"Data from `copy_of_global_flood_depth-damage_functions__30102017.xlsx` has been converted into CSV format in `raw.csv` for easier processing. Previously, this was ingested into the vulnerability model as JSON, but now as vulnerability config. The example below generates the configuration and plots this out.\n",
"\n",
"From the paper Huizinga et al. 2017: \"The database collects the fractional damage functions which allow to determine the percentage of the asset being damaged at specific flood depth.\" This is taken to be the same as the total insurable value (TIV) of the asset.\n",
"\n",
"The paper makes use of FEMA Hazus data in North America, which leads to a non-zero damage at zero flood depth for the residential curve. Hazus allows for negative flood depths, corresponding to flooding of a basement. However this convention conflicts with that of various hazard indicators where a zero 1-in-100 year flood depth would be taken to mean no flood risk for those return periods. The configuration builder therefore zeros fractional damage <= 1cm."
]
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"source": [
"import plotly.graph_objs as go\n",
"import plotly.io\n",
"from plotly.subplots import make_subplots\n",
"from physrisk.vulnerability_models.configuration.config_builders import ConfigBuilderJRCFlood\n",
"plotly.io.renderers.default = \"notebook\"\n",
"\n",
"builder = ConfigBuilderJRCFlood()\n",
"config_items = builder.build_config()"
]
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"cell_type": "code",
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"source": [
"fig1 = make_subplots(rows=1, cols=1)\n",
"for item in config_items:\n",
" fig1.add_scatter(x=item.points_x, y=item.points_y, row=1, col=1, name=item.asset_identifier)\n",
"fig1.update_xaxes(title=\"Flood depth (m)\", title_font={\"size\": 14}, row=1, col=1)\n",
"fig1.update_yaxes(title=\"Damage as fraction of TIV\", title_font={\"size\": 14}, row=1, col=1)\n",
"fig1.update_layout(legend=dict(orientation=\"h\", y=-0.25))\n",
"fig1.update_layout(margin=dict(l=20, r=20, t=20, b=20))"
]
}
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