Hazard assessment for river flooding using flood maps

Hazard assessment for river flooding using flood maps#

A workflow from the CLIMAAX Handbook and FLOODS GitHub repository.
See our how to use risk workflows page for information on how to run this notebook.

In this workflow we will map the river flood hazard using widely available European and global datasets. For an overview of the datasets and their limitations please see the workflow description in the previous page or on GitHub.

In this hazard assessment workflow we will first access and analyze the JRC’s high-resolution flood maps to obtain the flood extents under extreme events with different statistical likelihood of occurence (available: 10, 20, 30, 40, 50, 75, 100, 200, 500 year return periods). We retrieve the relevant parts of the flood hazard dataset and explore it in more detail for the region of interest.

Secondly, we will check the likely impact of climate change on the river flood hazard under different climate scenarios by using the Aqueduct Floods coarse-resolution flood maps. By comparing flood maps under different climate scenarios we will get a qualitative indication of the effect of climate change on the extreme river dischages resulting in flooding.

Before proceeding with the hazard mapping, please take a moment to learn more about the background of the flood map datasets and learn what you should consider when using these datasets to assess flood risk in a local context:

JRC high-resolution flood hazard maps for Europe in historical climate

The high-resolution river flood maps from JRC come at a spatial resolution of 3 arc-seconds (30-75m in Europe depending on latitude). Flood maps are available for various return periods (10, 20, 30, 40, 50, 75, 100, 200, 500 years).

The methodology behind this dataset is documented and can be accessed through this article. We will use the most recently updated version of the dataset (v3) that became available in March 2024.

The dataset only includes the river basins larger than 150km2. The flood modelling in this dataset does not account for man-made protections that may already be in place in populated regions (e.g. dams, levees, dikes). Therefore, it is always important to survey the local circumstances when interpreting the flood maps.

Aqueduct Floods coarse-resolution flood maps - dataset of future river flood potential under climate change

This dataset has a resolution of 30 arc-seconds or 300-750m depending on the latitude (in Europe). This dataset includes flood maps for extreme flood events in the baseline climate (ca. 1980) and in the future climates (2030, 2050, 2080 for RCP4.5 and RCP8.5 climate scenarios). The methodology behind this dataset is available in the corresponding technical note.

This is a global dataset which on a local scale may lead to considerable uncertainty in the results. Please keep the following in mind when interpreting the data from this dataset:

The flood maps provide a first indicative estimate and should be interpreted with care.
Results of all scenarios and all models should be consulted before drawing any conclusions on the potential future changes in flood depth.
The underlying hydrological model and flood mapping method have a relatively coarse resolution and thus only include local characteristics up to this level of detail. Water management, weirs and sluices are not included in the model.
The analysis is based on time-series of limited length and thus extreme value analysis for high return periods (50 years and higher) is very uncertain.

Preparation work#

Select area of interest#

Before downloading the data, we will define the coordinates of the area of interest. Based on these coordinates we will be able to clip the datasets for further processing, and eventually display hazard and damage maps for the selected area.

To easily define an area in terms of geographical coordinates, you can go to the Bounding Box Tool to select a region and get the coordinates. Make sure to select ‘CSV’ in the lower left corner and copy the values in the brackets below. Next to coordinates, please specify a name for the area which will be used in plots and saved results. Note that the coordinates are specified in WGS84 coordinates (EPSG:4326).

## name the area for saving datasets and plots# specify the coordinates of the bounding box

# Examples:
bbox = [8.480702,52.959337,9.128896,53.216668]; areaname = 'Bremen_Germany'
# bbox = [-1.6,46,-1.05,46.4]; areaname = 'La_Rochelle' 
#bbox = [-8.946851,38.505622,-8.821409,38.563009]; areaname = 'Setubal_Portugal'
#bbox = [12.1,45.1,12.6,45.7]; areaname = 'Venice'
#bbox = [-9.250441,38.354403,-8.618666,38.604761]; areaname = 'Setubal'

Load libraries#

Find more info about the libraries used in this workflow here

In this notebook we will use the following Python libraries:

os - Provides a way to interact with the operating system, allowing the creation of directories and file manipulation.
pooch - A data retrieval and storage utility that simplifies downloading and managing datasets.
logging - event logging system for libraries.
numpy - A powerful library for numerical computations in Python, widely used for array operations and mathematical functions.
pandas - A data manipulation and analysis library, essential for working with structured data in tabular form.
rasterio - A library for reading and writing geospatial raster data, providing functionalities to explore and manipulate raster datasets.
rioxarray - An extension of the xarray library that simplifies working with geospatial raster data in GeoTIFF format.
xarray - library for working with labelled multi-dimensional arrays.
damagescanner - A library designed for calculating flood damages based on geospatial data, particularly suited for analyzing flood impact.
matplotlib - A versatile plotting library in Python, commonly used for creating static, animated, and interactive visualizations.
contextily A library for adding basemaps to plots, enhancing geospatial visualizations.

These libraries collectively enable the download, processing, analysis, and visualization of geospatial and numerical data, making them crucial for this risk workflow.

# Package for downloading data and managing files
import os
import pooch

# Packages for working with numerical data and tables
import numpy as np
import pandas as pd

# Packages for handling geospatial maps and data
import rioxarray as rxr
import xarray as xr
import rasterio

# Ppackages used for plotting maps
import matplotlib.pyplot as plt
import contextily as ctx

Create the directory structure#

In order for this workflow to work even if you download and use just this notebook, we need to set up the directory structure.
Next cell will create the directory called ‘FLOOD_RIVER_hazard’ in the same directory where this notebook is saved.

# Define the folder for the flood workflow
workflow_folder = 'FLOOD_RIVER_hazard'

# Check if the workflow folder exists, if not, create it
if not os.path.exists(workflow_folder):
    os.makedirs(workflow_folder)

general_data_folder = os.path.join(workflow_folder, 'general_data')

# Check if the general data folder exists, if not, create it
if not os.path.exists(general_data_folder):
    os.makedirs(general_data_folder)

# Define directories for data and plots within the previously defined workflow folder
data_dir = os.path.join(workflow_folder, f'data_{areaname}')
plot_dir = os.path.join(workflow_folder, f'plots_{areaname}')

if not os.path.exists(data_dir):
    os.makedirs(data_dir)
if not os.path.exists(plot_dir):
    os.makedirs(plot_dir)

Conclusions#

In this hazard workflow we learned:

How to retrieve high-resolution river flood maps from JRC portal for your specific region.
Understanding the differences between river flood maps under extreme events with different return periods in the present-day scenario.
How to retrieve and compare the Aqueduct Floods coarse-resolution flood maps for your specific region to assess the change in flood hazard potential under different climate scenarios.

The river flood hazard maps that were retrieved and saved locally in this workflow will be further used in the river flood risk workflow (part of the risk toolbox).

Contributors#

Applied research institute Deltares (The Netherlands)

Institute for Environmental Studies, VU Amsterdam (The Netherlands)

Authors of the workflow:
Natalia Aleksandrova (Deltares) Ted Buskop (Deltares, VU Amsterdam)

Hazard assessment for river flooding using flood maps

Contents

Hazard assessment for river flooding using flood maps#

Preparation work#

Select area of interest#

Load libraries#

Create the directory structure#

Flood hazard mapping based on the JRC’s high-resolution river flood map dataset for present-day scenario#

Download and view the JRC flood map dataset#

Combining all high-resolution flood maps with different return periods into one dataset#

Visualize JRC’s river flood hazard dataset for the present scenario and different return periods#

Save dataset of present-day flood hazard maps to a local directory for future access#

Estimating the effect of climate scenarios on the river flood hazard using the Aqueduct Floods river flood maps#

Load and explore dataset for baseline scenario (ca. 1980) from the Aqueduct Floods dataset#

Load flood maps for all models and future scenarios from the Aqueduct Floods dataset#

Compare flood maps for different years and climate scenarios#

Conclusions#

Contributors#