The project AVOSS "Impact-based forecasting of heavy rain and flash floods at different scales: potentials, uncertainties and limitations" investigates the process chain of flash floods starting from meteorology via hydrology and hydraulics up to damage and risk assessment.
Flooding events in urban and non-urban settings represent a major cause of insured losses, with costs of several billion US$/year globally (e.g., US$ 60 billion in 2016).
Terrestrial Environmental Observatories
CAOS - catchments as organised systems
In hydrological models, the complexity of hydrological systems is represented by simplified model structures. The differences between model structures, e.g. in the type and accuracy of process representation, lead to differences in model performance and could be explained by deficits in the representation of hydrological processes.
The overarching goal is to undertake a novel investigation of compound drought and hot event driver’s quantification, and prediction at various spatial and temporal scales by integrating statistical physics, wavelet analysis, complex networks and artificial intelligence-based machine learning.
Compound events receive increasing attention in recent years with the aim of better understanding how climate variables combine to produce extreme impacts. Actually, many disastrous floods are compound events, where multiple sources of flooding overlap or interact in such a way that the flood impact is aggravated.
Regulators and industries are challenged by the difficulty to analyze and predict the impact of nonlinear environmental processes on short-term and long-term responses of ecosystems to environmental change.
The effect of water storage variations on in-situ gravity measurements and their use for hydrology
This project aims at acquisition, processing and interdisciplinary analysis of high-quality geodetic and hydrological data
GFZ Section 5.4 is involved in MOSES with the modules "Monitoring of water storage changes" and "Water and sediment monitorin" in the event chains "Hydrological extremes" and "Heat waves".
The G3P consortium combines key expertise from science and industry across Europe that optimally allows to (1) capitalize from the unique capability of GRACE and GRACE-FO satellite gravimetry
Regional Research Network “Water in Central Asia” The research network “Water in Central Asia” is primarily focused on improving the scientific and technical basis of the transboundary water resources management through conducting the state-of-the-art research works, fostering collaboration and experience exchange among the Central Asian and foreign partners.
The aim of this project is to develop a modelling system to produce a coherent regional flood risk assessment covering the whole of Germany.
DFG Research Training Group NatRiskChange - Natural Hazards and Risks in a Changing World
The overall goal of SPATE is a better understanding of relevant processes and causes leading to the occurrence of extreme floods.
Extreme, large-scale river floods typically affect more than one river basin.
Human activities and climate change are rapidly changing the Earth’s surface.
Towards SMART Monitoring and Inegrated Data Exploration of the Earth System - Implementing the Data Science Paradigm
Das Projekt H2020|Insurance hat das Ziel die Verbreitung eines neuen Standards zur Risikokalkulation zu unterstützen....
Improvement of forecasting and management of hydrological extremes
The overall objective of the Catch-Mekong project is to provide innovative research and technologies for a sustainable and transboundary management of the natural water and land resources in the Mekong Delta.
RIESGOS - Multi-risk analysis and information system components for the Andes region
The H2020|Insurance project therefore aims to advance the use of the standardized risk calculation software
Joint research initiative between GFZ, German Research Centre for Geosciences, Potsdam, Germany and AXA Global P&C.
The Future Danube model is a multi-hazard and risk model suite for the Danube region that is currently developed comprising of modules for