THE EVOLUTION OF GLOBAL FLOOD HAZARD AND RISK [EVOFLOOD]
THE EVOLUTION OF GLOBAL FLOOD HAZARD AND RISK [EVOFLOOD]
批准号:
NE/S015817/1
负责人:
Stephen Darby
金额:
$87.26万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Beyond just floodwater
不仅仅是洪水
DOI:
10.1038/s41893-022-00929-1
发表时间:
2022
期刊:
Nature Sustainability
影响因子:
27.6
作者:
[Best J]
通讯作者:
Best J
Global scale evaluation of precipitation datasets for hydrological modelling
用于水文建模的降水数据集的全球尺度评估
DOI:
10.5194/hess-2023-251
发表时间:
2023
期刊:
影响因子:
--
作者:
[Gebrechorkos S]
通讯作者:
Gebrechorkos S
VIET NAM: Slow Onset Hazard Interactions with Enhanced Drought and Flood Extremes in an At-Risk Mega-Delta
-
批准号:NE/S002847/1
-
项目类别:Research Grant
-
资助金额:$50.79万
-
财政年份:2019
-
负责人:Stephen Darby
-
依托单位:
Deciphering the dominant drivers of contemporary relative sea-level change: Analysing sediment deposition and subsidence in a vulnerable mega-delta
-
批准号:NE/P008100/1
-
项目类别:Research Grant
-
资助金额:$4.87万
-
财政年份:2017
-
负责人:Stephen Darby
-
依托单位:
Sustainable Intensification of Rice Agriculture in Vulnerable Mega-Deltas: A Global Challenge
-
批准号:BB/P022693/1
-
项目类别:Research Grant
-
资助金额:$77.09万
-
财政年份:2017
-
负责人:Stephen Darby
-
依托单位:
Climatic and Autogenic Controls on the Morphodynamics of Mega-Rivers: Modelling Sediment Flux in the Alluvial Transfer Zone
-
批准号:NE/J021970/1
-
项目类别:Research Grant
-
资助金额:$50.16万
-
财政年份:2012
-
负责人:Stephen Darby
-
依托单位:
Flow dynamics and sedimentation in an active submarine channel: a process-product approach
-
批准号:NE/F020120/1
-
项目类别:Research Grant
-
资助金额:$31.18万
-
财政年份:2010
-
负责人:Stephen Darby
-
依托单位:
The Characteristics of Turbulent Flows on Forested Floodplains
-
批准号:NE/E009832/1
-
项目类别:Research Grant
-
资助金额:$6.14万
-
财政年份:2007
-
负责人:Stephen Darby
-
依托单位:
国内基金
海外基金
Identification and quantification of primary phytoplankton functional types in the global oceans from hyperspectral ocean color remote sensing
-
批准号:--
-
项目类别:--
-
资助金额:160万元
-
批准年份:2022
-
负责人:李忠平
-
依托单位:
磁层亚暴触发过程的全球(global)MHD-Hall数值模拟
-
批准号:40536030
-
项目类别:重点项目
-
资助金额:120.0万元
-
批准年份:2005
-
负责人:马志为
-
依托单位: