Catalogue Search | MBRL
Search Results Heading
Explore the vast range of titles available.
MBRLSearchResults
-
DisciplineDiscipline
-
Is Peer ReviewedIs Peer Reviewed
-
Item TypeItem Type
-
SubjectSubject
-
YearFrom:-To:
-
More FiltersMore FiltersSourceLanguage
Done
Filters
Reset
3
result(s) for
"Uhlemann-Elmer, Steffi"
Sort by:
Comparison of estimates of global flood models for flood hazard and exposed gross domestic product: a China case study
2020
Over the past decade global flood hazard models have been developed and
continuously improved. There is now a significant demand for testing
global hazard maps generated by these models in order to understand their
applicability for international risk reduction strategies and for
reinsurance portfolio risk assessments using catastrophe models. We expand
on existing methods for comparing global hazard maps and analyse eight global
flood models (GFMs) that represent the current state of the global flood
modelling community. We apply our comparison to China as a case study and,
for the first time, include industry models, pluvial flooding, and flood
protection standards in the analysis. In doing so, we provide new insights
into how these components change the results of this comparison. We find
substantial variability, up to a factor of 4, between the flood hazard maps in
the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods
(ranging from 5 to 1500 years) and in expected annual exposed GDP. The
inclusion of industry models, which currently model flooding at a higher
spatial resolution and which additionally include pluvial flooding,
strongly improves the comparison and provides important new benchmarks. We
find that the addition of pluvial flooding can increase the expected annual
exposed GDP by as much as 1.3 percentage points. Our findings strongly highlight
the importance of flood defences for a realistic risk assessment in
countries like China that are characterized by high concentrations of
exposure. Even an incomplete (1.74 % of the area of China) but locally
detailed layer of structural defences in high-exposure areas reduces the
expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.
Journal Article
The Need for Mapping, Modeling, and Predicting Flood Hazard and Risk at the Global Scale
by
Safaie, Sahar
,
Perez, Erin Coughlan
,
Uhlemann‐Elmer, Steffi
in
floods
,
Global flood hazard modeling
,
global flood risk modeling
2018
The socioeconomic impacts of flooding are huge. Between 1980 and 2013, flood losses exceeded $1 trillion globally, and resulted in approximately 220,000 fatalities. To reduce these negative impacts of floods, effective flood risk management is required. Reducing risk globally is at the heart of two recent international agreements: the Sendai Framework for Disaster Risk Reduction and the Warsaw International Mechanism for Loss and Damage Associated with Climate Change Impacts. Prerequisites for effective risk reduction are accurate methods to assess hazard and risk, based on a thorough understanding of underlying processes. Due to the paucity of local scale hazard and risk data in many regions, several global flood hazard and flood risk models have been developed in recent years. More and more, these global models are being used in practice by an ever‐increasing range of users and practitioners. In this chapter, we provide an overview of recent advances in global flood hazard and risk modeling. We then discuss applications of the models in high‐level advocacy in disaster risk management activities, international development organizations, the reinsurance industry, and flood forecasting and early warning. The chapter concludes with several remarks on limitations in global flood risk models and the way forward for the future.
Book Chapter