Research Themes

Global Water and Climate Risk

This research programme is led by Dr Philip Ward.

An understanding of water and climate risk at the global scale is essential for governments, development agencies, disaster planning and preparedness institutes, and the reinsurance industry. Our department is at forefront of the development of methods and tools to quantify global scale water and climate risks.

GLOFRIS and Aqueduct Global Flood Analyzer
Dr Philip Ward is a lead developer of the state-of-the-art global scale river flood risk model, GLOFRIS. GLOFRIS is constantly updated and improved, incorporating the newest scientific knowledge on natural hazards, exposure, and vulnerability, generated by our research group and collaborating partners. We focus on current risk, future risk under scenarios of climate change and socioeconomic development, and also temporal shifts in risk due to interannual climate variability. Using results from GLOFRIS, we recently developed and launched the Aqueduct Global Flood Analyzer, together with the World Resources Institute.

Dr Ward demonstrates theAqueduct Global Flood Analyzerto His Majesty King Willem-Alexander of the Netherlands

GLOFRIS and Aqueduct have been used in a large range projects with users and stakeholders, to develop risk-based information for use in policy and practice related studies. For example, we have worked with World Bank to assess risk hotspots in Nigeria and future risk trends and adaptation possibilities in Eastern Europe and Central Asia; with the Global Dialogue Project of OECD and GWP to map future trends in flood risk and assess risk reduction strategies; and in a project for a group of reinsurers (via the Risk Prediction Initiative 2.0) to assess interannual changes in flood risk.

Global Drought and Water Resources Modelling
By using global models and data, both available in-house and with partner institutes and universities, we developed and applied several techniques to asses drought and water scarcity at the global scale, disentangling the impact of driving forces such as long-term climate and socioeconomic changes, and climate variability. Using our expertise on risk assessments, we are now developing a risk-based framework for the assessment of global water scarcity risks. Such risk-based framework will offer water managers and policy makers a promising perspective to achieve higher water security under current and future conditions in a well-informed and adaptive manner. Current work is entitled to finalize this risk-based approach for the assessment of drought and water scarcity by the incorporation of economic exposure and vulnerability within the framework, and to allow for the evaluation of different adaptation options. We are using our global drought modelling framework together with several stakeholder, for example to assess the influence of climate change on poverty with the World Bank.

Methodological framework for the assessment of water scarcity risks

Global Tide and Storm Surge Modelling
We are developing the first global dynamically derived dataset of storm surges and extreme sea levels for the entire's world coastline. In collaboration with Deltares, we applied are applying the Global Tide and Surge Model (GTSM), a state-of-the-art hydrodynamic model, to derive timeseries of tides, surge and extreme sea levels for 1979-2014. Potential applications of the extreme sea levels are in coastal flood risk assessments and climate change adaptation.

Extreme sea levels with a return period of 1 in 100 years for the entire world's coastline

Nature Climate Change Publication on the Usefulness of Limitations of Global Flood Risk Models
In 2015, Philip Ward, Brenden Jongman and Sanne Muis, and colleagues from several international institutes, authored a paper in Nature Climate Change entitled Usefulness of Limitations of Global Flood Risk Models. The paper provides perspectives on this issue drawing from practical applications of global river flood risk models; demonstrates both the accomplishments in these examples, as well as limitations and gaps between user 'wish lists' and model capabilities; and presents a research agenda to address these issues and reduce the gaps. The paper is a result of a series of workshops at the Global Flood Partnership, Understanding Risk conferences, and the General Assembly of the European Geosciences Union.


Risk Modelling and e-Science

This research theme is coordinated by Dr Hans de Moel.

Our department is leading in developing computer based risk models for simulating water and climate risks. Dr Hans de Moel coordinates the development of these coupled models, integrating (1) climate-hydrological hazard models to simulate water and climate hazard extremes with (2)damage and catastrophe models. These models can be validated with empirical damage and loss data, for example from the (re-) insurance industry.

Hazard models enable us to simulate flood extent- and depth, and periods of droughts and water shortage, and include HBV, STREAM, and GLOFRIS. For climate information, data is derived from RACMO or re-analysis data from ISIMIP. For our catastrophe models, we use advanced damage curves, showing the impacts of water and climate extremes on buildings, infrastructure and loss of life. In addition, we apply disaster impact models to model the economy-wide (indirect) effects of natural disasters and the economic consequences of failure of critical infrastructure due to a natural disaster.

Damage and catastrophe models combine the above data on natural hazard, such as maps of flood extent and water shortage, with socioeconomic data on aspects such as population, income, land use, and asset values to estimate the damage and losses associated with floods and droughts. Damage models include Damagescanner, which has already developed for several regions (e.g. The Netherlands, Ho Chi Minh City, New York City, Jakarta) and GLOFRIS for global scale studies.

Empirical data on actual damage and losses due to water and climate risk are very important; they can be used to validate our damage and catastrophe models. We therefore apply novel e-Science techniques for data assimilation in our damage and catastrophe models, for example using information from social media (Twitter, texting, etc). In our research, our close relations with the insurance industry are very important, and for example we apply the empirical loss data from the NatCatSERVICE database from Munich RE in our research. 


Risk-Based Decision Making and Adaptation

The research line ‘Risk Based Decision Making and Adaptation’ is coordinated by Prof. Jeroen Aerts and Dr Ralph Lasage.

Knowing the water and climate risk from our models and data, for the current and future situation, may serve as a basis for developing strategies or concrete measure to manage risk., and aims at assessing measures and/or strategies to manage or reduce risk. For example, flood risk can be reduced by many measures, such as building flood protection in the form of dikes and levees to reduce the chance of a flood, or by using spatial planning and building codes to reduce the impacts of floods if they do occur. Similarly, adaptation options are available to reduce drought risk, such as the development of water storage facilities, water pricing, and demand management. The department has international experience in analysing insurance schemes to cover residual risk from water and climate extremes. Research also addresses how insurance can be linked to risk reduction and management.

We apply two categories of techniques to support risk based decision making in adapting to water and climate extremes:

Measures are evaluated using cost benefit analysis, multi-criteria analysis, uncertainty assessment, and robust decision making techniques such as flexible pathways;

Agent based modelling techniques are often used in our projects to cover behavioural aspects of stakeholders in adapting to water and climate risk. For example, our models enable us to simulate the effects of investments in flood and drought management by the government, households and insurers, and how these investments and decisions interact. 


Climate Modelling and Extreme Events

This research line is led by Prof. Bart van den Hurk, who has a part-time position IVM on behalf of KNMI (Royal Netherlands Meteorological Institute), where he leads the R&D group on weather and climate modelling.

In the climate services research line, we develop and explore methods that translate the existing wealth of climate data and information into customised tools, products and information (‘climate services’) to address and assess the effects from global warming and other climate related processes and events. Climate modelling and scenario’s play a central role in these activities.

Climate modelling and climate data are essential for simulating hydrological extremes, such as floods and droughts, in our hazard and risk models In the research it is explored which climate information is optimally suited for decision making and risk analyses. For this, various types of climate scenarios, probabilistic weather forecasts and physical concepts are developed and tailored to the needs of stakeholder. For example, forecast based financing of disaster mitigation and response in a number of African countries is explored in cooperation with the Red Cross Climate Centre. Concepts of “Future Weather” and “Compounding Extremes” are developed that support the interpretation of climate change in terms of weather phenomena.

We use different sources of climate information: (1) historical climate data are often derived from re-analysis data such as ISIMIP; (2) climate change projections or scenarios of the future are derived from global climate models or regional climate models (e.g. RACMO), but must be processed to tailor the projections to the scale and resolutions needed for our risk and catastrophe models. We work at different scales, varying from the local city scale, to regional river basins, and our global flood and drought risk models.