THE EVOLUTION OF GLOBAL FLOOD HAZARD AND RISK [EVOFLOOD]
Lead Research Organisation:
University of Southampton
Department Name: Sch of Geography & Environmental Sci
Abstract
Flooding is the deadliest and most costly natural hazard on the planet, affecting societies across the globe. Nearly one billion people are exposed to the risk of flooding in their lifetimes and around 300 million are impacted by floods in any given year. The impacts on individuals and societies are extreme: each year there are over 6,000 fatalities and economic losses exceed US$60 billion. These problems will become much worse in the future. There is now clear consensus that climate change will, in many parts of the globe, cause substantial increases in the frequency of occurrence of extreme rainfall events, which in turn will generate increases in peak flood flows and therefore flood vast areas of land. Meanwhile, societal exposure to this hazard is compounded still further as a result of population growth and encroachment of people and key infrastructure onto floodplains.
Faced with this pressing challenge, reliable tools are required to predict how flood hazard and exposure will change in the future. Existing state-of-the-art Global Flood Models (GFMs) are used to simulate the probability of flooding across the Earth, but unfortunately they are highly constrained by two fundamental limitations. First, current GFMs represent the topography and roughness of river channels and floodplains in highly simplified ways, and their relatively low resolution inadequately represents the natural connectivity between channels and floodplains. This restricts severely their ability to predict flood inundation extent and frequency, how it varies in space, and how it depends on flood magnitude. The second limitation is that current GFMs treat rivers and their floodplains essentially as 'static pipes' that remain unchanged over time. In reality, river channels evolve through processes of erosion and sedimentation, driven by the impacts of diverse environmental changes (e.g., climate and land use change, dam construction), and leading to changes in channel flow conveyance capacity and floodplain connectivity. Until GFMs are able to account for these changes they will remain fundamentally unsuitable for predicting the evolution of future flood hazard, understanding its underlying causes, or quantifying associated uncertainties.
To address these issues we will develop an entirely new generation of Global Flood Models by: (i) using Big Data sets and novel methods to enhance substantially their representation of channel and floodplain morphology and roughness, thereby making GFMs more morphologically aware; (ii) including new approaches to representing the evolution of channel morphology and channel-floodplain connectivity; and (iii) combining these developments with tools for projecting changes in catchment flow and sediment supply regimes over the 21st century. These advances will enable us to deliver new understanding on how the feedbacks between climate, hydrology, and channel morphodynamics drive changes in flood conveyance and future flooding. Moreover, we will also connect our next generation GFM with innovative population models that are based on the integration of satellite, survey, cell phone and census data. We will apply the coupled model system under a range of future climate, environmental and societal change scenarios, enabling us to fully interrogate and assess the extent to which people are exposed, and dynamically respond, to evolving flood hazard and risk.
Overall, the project will deliver a fundamental change in the quantification, mapping and prediction of the interactions between channel-floodplain morphology and connectivity, and flood hazard across the world's river basins. We will share models and data on open source platforms. Project outcomes will be embedded with scientists, global numerical modelling groups, policy-makers, humanitarian agencies, river basin stakeholders, communities prone to regular or extreme flooding, the general public and school children.
Faced with this pressing challenge, reliable tools are required to predict how flood hazard and exposure will change in the future. Existing state-of-the-art Global Flood Models (GFMs) are used to simulate the probability of flooding across the Earth, but unfortunately they are highly constrained by two fundamental limitations. First, current GFMs represent the topography and roughness of river channels and floodplains in highly simplified ways, and their relatively low resolution inadequately represents the natural connectivity between channels and floodplains. This restricts severely their ability to predict flood inundation extent and frequency, how it varies in space, and how it depends on flood magnitude. The second limitation is that current GFMs treat rivers and their floodplains essentially as 'static pipes' that remain unchanged over time. In reality, river channels evolve through processes of erosion and sedimentation, driven by the impacts of diverse environmental changes (e.g., climate and land use change, dam construction), and leading to changes in channel flow conveyance capacity and floodplain connectivity. Until GFMs are able to account for these changes they will remain fundamentally unsuitable for predicting the evolution of future flood hazard, understanding its underlying causes, or quantifying associated uncertainties.
To address these issues we will develop an entirely new generation of Global Flood Models by: (i) using Big Data sets and novel methods to enhance substantially their representation of channel and floodplain morphology and roughness, thereby making GFMs more morphologically aware; (ii) including new approaches to representing the evolution of channel morphology and channel-floodplain connectivity; and (iii) combining these developments with tools for projecting changes in catchment flow and sediment supply regimes over the 21st century. These advances will enable us to deliver new understanding on how the feedbacks between climate, hydrology, and channel morphodynamics drive changes in flood conveyance and future flooding. Moreover, we will also connect our next generation GFM with innovative population models that are based on the integration of satellite, survey, cell phone and census data. We will apply the coupled model system under a range of future climate, environmental and societal change scenarios, enabling us to fully interrogate and assess the extent to which people are exposed, and dynamically respond, to evolving flood hazard and risk.
Overall, the project will deliver a fundamental change in the quantification, mapping and prediction of the interactions between channel-floodplain morphology and connectivity, and flood hazard across the world's river basins. We will share models and data on open source platforms. Project outcomes will be embedded with scientists, global numerical modelling groups, policy-makers, humanitarian agencies, river basin stakeholders, communities prone to regular or extreme flooding, the general public and school children.
Planned Impact
Almost one billion people are exposed to the risk of flooding during their lifetimes. This project will develop a suite of intuitive and predictive global scale flood models that will allow scientists and stakeholders to understand, illustrate and simulate how flood hazard and risk in rivers and their connected floodplains will respond to future environmental change.
Who could potentially benefit from the proposed research?
This project is aimed at seven groups of beneficiaries: (i) the scientific community in its broadest sense (e.g., researchers working on basin source:sink interrelationships including climate, land-use, hydrology, biogeochemistry); (ii) the global flood insurance industry (via a network of the world's 10 largest insurance companies); (iii) humanitarian organisations and disaster response agencies; (iv) government overseas aid distribution agencies and organisations who are responsible for facilitating societal resilience to floods and flood disaster management in response to events; (v) communities subject to regular flooding or prone to catastrophic and extreme flooding or drought (e.g., through links to regional and national governments, disaster relief agencies, hazard mitigation and NGO resilience teams); (vi) major civil engineering companies responsible for building resilient infrastructure and flood defences; and (vii) the general public and media via news reports, public debates, response to natural emergency events, production of resources for the school curriculum, and Learned Societies.
How might the identified stakeholders benefit?
Through: (i) provision of a suite of new open source computer programs and datasets made available through the NERC Environmental Information Data Centre, the project website and the specialist, NSF-funded, Community Surface Dynamics Modelling System (CSDMS) portal; (ii) production and sharing of flood risk and inundation maps for large river basins and regions of strategic value including cross-boundary/country zones; (iii) provision of advice to professional and public river basin users and managers (e.g., with and via Project Partners); (iv) sharing of expertise, software and data (via agreed secondments and participation as Project Partners); (v) advice that better targets aid investment and more efficient emergency disaster management including a better projection of population migration and impact by floods; (vi) provision of news feeds, interaction with short film production, and dissemination to schools and the general public (e.g., British Science Festival), social media and website resources.
Who could potentially benefit from the proposed research?
This project is aimed at seven groups of beneficiaries: (i) the scientific community in its broadest sense (e.g., researchers working on basin source:sink interrelationships including climate, land-use, hydrology, biogeochemistry); (ii) the global flood insurance industry (via a network of the world's 10 largest insurance companies); (iii) humanitarian organisations and disaster response agencies; (iv) government overseas aid distribution agencies and organisations who are responsible for facilitating societal resilience to floods and flood disaster management in response to events; (v) communities subject to regular flooding or prone to catastrophic and extreme flooding or drought (e.g., through links to regional and national governments, disaster relief agencies, hazard mitigation and NGO resilience teams); (vi) major civil engineering companies responsible for building resilient infrastructure and flood defences; and (vii) the general public and media via news reports, public debates, response to natural emergency events, production of resources for the school curriculum, and Learned Societies.
How might the identified stakeholders benefit?
Through: (i) provision of a suite of new open source computer programs and datasets made available through the NERC Environmental Information Data Centre, the project website and the specialist, NSF-funded, Community Surface Dynamics Modelling System (CSDMS) portal; (ii) production and sharing of flood risk and inundation maps for large river basins and regions of strategic value including cross-boundary/country zones; (iii) provision of advice to professional and public river basin users and managers (e.g., with and via Project Partners); (iv) sharing of expertise, software and data (via agreed secondments and participation as Project Partners); (v) advice that better targets aid investment and more efficient emergency disaster management including a better projection of population migration and impact by floods; (vi) provision of news feeds, interaction with short film production, and dissemination to schools and the general public (e.g., British Science Festival), social media and website resources.
Organisations
Publications
Best J
(2022)
Beyond just floodwater
in Nature Sustainability
Gebrechorkos S
(2023)
Global scale evaluation of precipitation datasets for hydrological modelling
Gebrechorkos S
(2023)
A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses.
in Scientific data
Gebrechorkos S
(2024)
Global-scale evaluation of precipitation datasets for hydrological modelling
in Hydrology and Earth System Sciences
Guth P
(2024)
Ranking of 10 Global One-Arc-Second DEMs Reveals Limitations in Terrain Morphology Representation
in Remote Sensing
Liu Y
(2024)
First global estimation of bankfull river discharge
| Title | Global River BankFull Discharge (GQBF) - Siberia(SI) & South Pacific/Australia(SP) |
| Description | The GQBF is the estimated bankfull discharge across ~2.87 million km (length) of global river reaches. The bankfull discharge here is defined as the maximum flow rate contained within a river just before inundation occurs in the surrounding floodplain. We based our river bankfull discharge estimation on a newly developed river network, Global RIver Topology (GRIT), using GRIT's river reaches as the spatial scale to represent the variation in bankfull discharge. We included all GRIT river reaches that coincided with the Global River Width from Landsat (GRWL) river masks (with overlapping ratio >=0.5). This selects river reaches with satellite-derived width measurements >=30 m, resulting in a total length of ~2.87 million km. Here, the GQBF represents the time-averaged bankfull discharge at <1 km (river length) spatial resolution. Regions Added regions SI, SP Vector files. SI - Siberia SP - South Pacific/Australia The subcontinental catchment groups (vector, polygons) can be found at GRIT domain polygon (GRITv06_domain_GLOBAL.gpkg.zip). They allow for more fine-grained subsetting of data . Vector files are provided in geographic WGS84 coordinates (EPSG:4326). Change log v0.1 - 2024-09-29 First globally complete dataset published v0.1 - 2024-11-19 Add vector files for regions SI, SP |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | This dataset will allow Global Flood Models to be parameterised more accurately. |
| URL | https://zenodo.org/doi/10.5281/zenodo.13855370 |
| Title | Global River Topology (GRIT) |
| Description | The Global River Topology (GRIT) is a vector-based, global river network that not only represents the tributary components of the global drainage network but also the distributary ones, including multi-thread rivers, canals and delta distributaries. It is also the first global hydrography (excl. Antarctica and Greenland) produced at 30m raster resolution. It is created by merging Landsat-based river mask (GRWL) with elevation-generated streams to ensure a homogeneous drainage density outside of the river mask (rivers narrower than approx. 30m). Crucially, it uses a new 30m digital terrain model (FABDEM, based on TanDEM-X) that shows greater accuracy over the traditionally used SRTM derivatives. After vectorisation and pruning, directionality is assigned by a combination of elevation, flow angle, heuristic and continuity approaches (based on RivGraph). The network topology (lines and nodes, upstream/downstream IDs) is available as layers and attribute information in the GeoPackage files (readable by QGIS/ArcMap/GDAL). A map of GRIT segments labelled with OSM river names is available here: https://michelwortmann.com/research/gritv05-segments-river-names/ Regions Vector files are provided in 7 regions with the following codes: AF - Africa AS - Asia (excl. Siberia) EU - Europe NA - North America SA - South America SI - Siberia SP - South Pacific/Australia The domain polygons (GRITv06_domain_GLOBAL.gpkg.zip) provide 60 subcontinental catchment groups that are available as vector attributes. They allow for more fine-grained subsetting of data (e.g. with ogr2ogr --where and the domain attribute). Vector files are provided both in the original equal-area Equal Earth Greenwich projection (EPSG:8857) as well as in geographic WGS84 coordinates (EPSG:4326). Change log v0.6 - 2024-05-30 Rivers/streams outside of the GRWL mask forced by all OSM water lines (not only those with waterway=river/canal) Some manual directions in the Irrawaddy delta and fixed erronous sink in the Volga delta v0.5 - 2024-02-14 Cyclicity and discontinuities resolved through improved algorithms, bug fixes, more sophisticated cycle solving algorithms and some manually forced directions. Only insignificant cycles (non-sinks, less than 50) were removed. Added segment and reach attributes Computational domain fixes Segments include OSM river names Asia domain split into Siberia and rest of Asia Vector files available in EPSG:8857 and EPSG:4326 v0.4 - 2023-03-11 First globally complete dataset published Network segments Lines between inlet, outlet, confluence and bifurcation nodes. Files have lines and nodes layers. Attribute description of lines layer Name Data type Description cat integer domain internal feature ID global_id integer global river segment ID, same as FID catchment_id integer global catchment ID upstream_node_id integer global segment node ID at upstream end of line downstream_node_id integer global segment node ID at downstream end of line upstream_line_ids text comma-separated list of global river segment IDs connecting at upstream end of line downstream_line_ids text comma-separated list of global river segment IDs connecting at downstream end of line direction_algorithm float code of RivGraph method used to set the direction of line width_adjusted float median river width in m without accounting for width of segments connecting upstream/downstream length_adjusted float segment length in m without accounting for width of segments connecting upstream/downstream in m is_mainstem integer 1 if widest segment of bifurcated flow or no bifurcation upstream, otherwise 0 strahler_order integer Strahler order of segment, can be used to route in topological order length float segment length in m azimuth float direction of line connecting upstream-downstream nodes in degrees from North sinuousity float ratio of Euclidean distance between upstream-downstream nodes and line length, i.e. 1 meaning a perfectly straight line drainage_area_in float drainage area at beginning of segment, partitioned by width at bifurcations, in km2 drainage_area_out float drainage area at end of segment, partitioned by width at bifurcations, in km2 drainage_area_mainstem_in float drainage area at beginning of segment, following the mainstem, in km2 drainage_area_mainstem_out float drainage area at end of segment, following the mainstem, in km2 bifurcation_balance_out float (drainage_area_out - drainage_area_mainstem_out) / max(drainage_area_out, drainage_area_mainstem_out), dimensionless ratio grwl_overlap float fraction of the segment overlapping with the GRWL river mask grwl_value integer dominant GRWL value of segment name text river name from Openstreetmap where available, English preferred name_local text river name from Openstreetmap where available, local name n_bifurcations_upstream integer number of bifurcations upstream of segment domain text catchment group ID, see domain index file Attribute description of nodes layer Name Data type Description cat integer domain internal feature ID global_id integer global river node ID, same as FID catchment_id integer global catchment ID upstream_line_ids text comma-separated list of global river segment IDs flowing into node downstream_line_ids text comma-separated list of global river segment IDs flowing out of node node_type text description of node, one of bifurcation, confluence, inlet, coastal_outlet, sink_outlet, grwl_change grwl_value integer GRWL code at node grwl_transition text GRWL codes of change at grwl_change nodes cycle integer >0 if segment is part of an unresolved cycle, 0 otherwise continuity_violated integer 1 if flow continuity is violated, otherwise 0 drainage_area float drainage area, partitioned by width at bifurcations, in km2 drainage_area_mainstem float drainage area, following the mainstem, in km2 n_bifurcations_upstream integer number of bifurcations upstream of node domain text catchment group, see domain index file Network reaches Segment lines split to not exceed 1km in length, i.e. these lines will be shorter than 1km and longer than 500m unless the segment is shorter. A simplified version with no vertices between nodes is also provided. Files have lines and nodes layers. Attribute description of lines layer Name Data type Description cat integer domain internal feature ID segment_id integer global segment ID of reach global_id integer global river reach ID, same as FID catchment_id integer global catchment ID upstream_node_id integer global reach node ID at upstream end of line downstream_node_id integer global reach node ID at downstream end of line upstream_line_ids text comma-separated list of global river reach IDs connecting at upstream end of line downstream_line_ids text comma-separated list of global river reach IDs connecting at downstream end of line grwl_overlap float fraction of the reach overlapping with the GRWL river mask grwl_value integer dominant GRWL value of node grwl_width_median float median width of the GRWL river mask, meters grwl_width_std float standard deviation of width of the GRWL river mask, meters length float length of reach in meters sinuousity float ratio of eucledian distance betwen upstream-downstream nodes and line length, i.e. 1 meaning a perfectly straight line azimuth float direction of line connecting upstream-downstream nodes in degrees from North domain text catchment group, see domain index file Attribute description of nodes layer Name Data type Description cat integer domain internal feature ID segment_node_id integer global ID of segment node at segment intersections, otherwise blank n_segments integer number of segments attached to node global_id integer global river reach node ID, same as FID upstream_line_ids text comma-separated list of global river reach IDs flowing into node downstream_line_ids text comma-separated list of global river reach IDs flowing out of node domain text catchment group, see domain index file Catchments Catchment outlines for entire river basins (network components, including coastal drainage areas). Catchments for segments (aka. subbasins) and reaches are also available on request. Attribute description Name Data type Description cat integer domain internal feature ID global_id integer global catchment ID, same as global_id of segment/reach ID if is_coastal == 0 for respective catchments or the catchment_id for component_catchments, same as FID area float catchment area in km2 is_coastal integer 1 for coastal drainage areas, 0 otherwise domain text catchment group, see domain index file Raster Upstream drainage area and other raster-based products are also available upon request. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2024 |
| Provided To Others? | Yes |
| Impact | This dataset is a new global river hydrography that accounts for river bifurcations. It will allow better characterisation of the global river network, for use in hydrological, geomorphological and ecological studies. |
| URL | https://zenodo.org/doi/10.5281/zenodo.7629907 |