DREAM PhD PROJECT PROPOSAL for OCTOBER 2015 INTAKE RESEARCH PROJECT Title:

Predicting hydrological drought risk in Europe using big data of natural and socio-economic factors

Key words

hydrological drought risk, prediction, combining natural and social science data, statistical methods

Project details General project description Drought is one of the costliest natural hazards in Europe and drought risk is expected to increase in the future, partly due to changes in drought occurrence and severity, and partly due to increases in vulnerability. These changes are not uniform over Europe. In recent papers, spatial variability in drought impacts was found to be caused by both natural and anthropogenic factors. For example, differences in water storage (in groundwater, lakes, reservoirs, snow, and glaciers) result in spatial variation in the propagation of meteorological drought to hydrological drought. In addition, differences in water use for drinking, irrigation, or industry, result in spatial variation in the societal impacts of hydrological drought. However, drought risk predictions are based currently on precipitation which has little predictability beyond a week in Europe, and which also does not account for spatial variability in water storage or water use. This makes European-scale drought predictions of little use in local water management. The biggest barrier to including spatial variability in drought risk assessments is scattered and inconsistent data, e.g. river discharge and groundwater level observations are collected by a range of authorities in different ways, and satellite data on water storage have started to become available only recently. Additionally, drought impact information is locked up in national reports, and drought vulnerability is a complex issue characterised by a range of data, relating to exposure, sensitivity and adaptive capacity. Different studies have shown a link between drought vulnerability and various socio-economic factors (e.g. population density, crop patterns, right to water, access to water), but these links have never been applied in drought risk predictions on pan-European scale, Tools that translate the predictions of precipitation (meteorological drought) to the societal risk of hydrological drought are needed urgently to increase human preparedness and so lessen socioeconomic impacts. In this project, we will explore innovative ways to extract, combine, and analyse the natural and social science data needed to include spatial variability in hydrological drought risk analysis, with the aim to improve hydrological drought risk predictions and mitigate drought impacts. Alignment with core DREAM themes of Big Data, Risk and Mitigation This project combines the DREAM themes of Big Data, Risk and Mitigation by predicting drought risk across Europe based on combining multiple data sets. We focus on the development of new methodologies to include a variety of novel datasets in hydrological drought risk prediction to increase its usefulness on local to regional scale. With this project, we address the following NERC priorities for DREAM: - “Approaches and tools for the identification of sources of risks, their drivers and impacts within complex systems”: Hydrological drought risk is a highly complex issue with large spatial variability in both drivers and impacts. In this project we will quantify this spatial variability in drivers and impacts from a range of large-scale and local data sets; - “Robust methods to quantify and analyse risks and their drivers including sound mathematical and statistical approaches”: We will develop a new methodology to cleverly combine all data, both natural and social, from various sources and scales, based on statistical methods; Document v1.0

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- “Tools for developing, managing and analysing ‘Big Data’, to understand risk better, and to apply modern cloud computing approaches”: The tools we will be developing will combine and analyse a myriad of data, with the aim to not only understand, but also predict hydrological drought risk; - “New tools and approaches to multi-hazard assessment and interconnected risks (cascade effects)”: The new tool will feed into the European Drought Observatory, which is used by the European Union for multi-hazard assessment, and into local water management by water companies, which need to balance different risks. The integration of natural and social sciences is crucial for the success of this project, both in the data analysis aspect and in the assessment of the usefulness of the drought risk predictions for mitigation decision-making. Therefore, the project will additionally include reference to: - “New approaches to visualise and communicate risk, including the public, to enable decision-making”; and - “Risk perception, communication, decision making and management”. For both these themes we will collaborate closely with the European Drought Observatory and water companies. Project background, motivation and aims The prediction of hydrological drought risk to society is a highly complex issue that cuts across the natural and social sciences and hence requires an integrated, interdisciplinary research approach. The inclusion of spatial variability in both natural and anthropogenic factors is key to the application of drought risk mitigation in local water management. A lack of precipitation (i.e. a meteorological drought) can cause a hydrological drought immediately in regions with limited water storage; whereas a precipitation deficit is attenuated or occurs with a lag in regions with greater water storage (e.g. in snow pack or groundwater). Similarly, a hydrological drought can yield different societal impacts depending on location, i.e. in southern Europe water use for irrigation is vulnerable to drought and in northern Europe water use for energy is vulnerable to drought. This means that predictions of hydrological drought risk need to be tailor-made to a specific region; requiring new data and tools to underpin robust quantitative analyses. The approach that is followed in the natural sciences to translate meteorological drought into hydrological drought is by using complex large-scale modelling which introduces large uncertainties and results are rarely validated. Additionally, the lack of predictability of precipitation is an issue and it is a recent idea that the memory in the hydrological system and statistical links with other high-memory systems (like the oceans) can be used to improve hydrological drought predictions. In the social sciences, on the other hand, largescale information is commonly disregarded because of the large uncertainties and only local-scale drought vulnerability information is considered. Both approaches ignore the wealth of data that is available on both pan-European and local scales. Therefore, the aims of this specific project are: 1) to bridge the natural and social science research fields in drought risk prediction; 2) to develop new tools to combine various data sets quantifying spatial variability in drought hazard and drought vulnerability; 3) to include information from different scales, both quantitative and qualitative, from pan-European satellite data to local water storage observations or drought impact reports; 4) to provide a toolkit which improves the prediction of hydrological drought risk based on multiple data sources of natural hazard and vulnerability and which can be used for drought mitigation at local and regional scales. Proposed programme of research and methods For this project, we propose a range of interlinked, quantitative and qualitative methods with a focus on using existing data in innovative tools. The challenge is to find creative ways to combine data from various sources, in various formats, on various scales. This applies to both natural sciences and social sciences data. The natural science data are needed to make the translation from meteorological drought to hydrological drought, including the spatial variability in water storage. This will be achieved by combining satellite data with traditional local measurement data. NASA’s Gravity Recovery and Climate Experiment (GRACE) satellite remote sensing product provides a novel and timely opportunity to examine and observe changes in global terrestrial water storage. Combined with ground and other remotely sensed Document v1.0

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observations of river discharge, groundwater levels, lake and reservoir levels, soil moisture, snow accumulation and glacier mass balance, this large-scale product can be used to quantify spatial variability in water storage. GRACE data are freely available through NASA (grace.jpl.nasa.gov/) and the local water observations can be obtained through a variety of data providers, e.g. the Global Runoff Data Centre (GRDC; www.bafg.de/GRDC/EN/Home/homepage_node.html), International Groundwater Centre (IGRAC; www.un-igrac.org). The social science data are needed to make the translation from hydrological drought as a natural hazard to hydrological drought risk, including the spatial variability in vulnerability and water use. For this analysis the new European Drought Impact report Inventory (EDII) provides interesting opportunities. This online database (www.geo.uio.no/edc/droughtdb) for the first time consolidates qualitative information on the impacts of historical large-scale European drought events for a large range of sectors, allowing the assessment of vulnerability of different water uses in different parts of Europe. This information will be compared against more quantitative drought vulnerability data, e.g. crop yields and energy production from Eurostat (ec.europa.eu/eurostat). Finally these two steps will be combined in a total hydrological drought risk assessment that can be used to make the translation from predictions of drought drivers (e.g. precipitation or ocean factors like sea surface temperatures) to hydrological drought risk predictions. For this we need to develop new tools based on statistical approaches (see Figure 1). This methodology is purely data-based; it does not use complex modelling, but uses clever combinations of data. This makes communication of hydrological drought risk to stakeholders and the general public relatively easy. Training plan Besides the training provided by DREAM and the University of Birmingham, this project will provide additional training to the doctoral student. The student will develop skills in dealing with large datasets and will be trained in data analysis and visualisation techniques. S/he will interact and collaborate within an international network of scientists and will have the opportunity to present his/her research at international conferences, including interaction with the NERC Droughts programme of which Hayley Fowler is Co-I in the project IMPETUS. The supervisors are experienced in the fields of hydrological drought (Anne Van Loon, University of Birmingham), meteorological drought and climate change impacts (Hayley Fowler, Newcastle University), large-scale hydroclimatological analysis (David Hannah, University of Birmingham), and water governance (Julian Clark, University of Birmingham). Participation in the Young Scientists Summer Program of the International Institute for Applied Systems Analysis (IIASA) in Austria (www.iiasa.ac.at/web/home/education/yssp/about.html) is highly encouraged. Collaboration and impact beyond the supervisory team, interdisciplinary work, engagement activities or wider impact: The wider supervisory team on this project includes both natural and social scientists who are all familiar with interdisciplinary research and bridging the gap between science and policy. Besides the fact that this project addresses an interesting research question, it also aims to contribute to improved drought risk prediction. Therefore, close collaboration with Jürgen Vogt of the European Drought Observatory (EDO) of the European Joint Research Centre (JRC) is planned. The EDO (edo.jrc.ec.europa.eu/) provides real-time drought-relevant information such as maps of indicators derived from different data sources. EDO currently does not include any hydrological drought information and also lacks drought vulnerability maps. Furthermore, close links are established with the European Drought Centre (lead by Lena Tallaksen, University of Oslo), the UNESCO-FRIEND EURO-FRIEND Low Flow and Drought group (lead by Gregor Laaha, BOKU University Vienna), the IAHS Panta Rhei working group ‘Drought in the Anthropocene’ (lead by Anne Van Loon, University of Birmingham) and the GEWEX initiative – Hayley Fowler leads a cross-cut in this area, collaborating with Justin Sheffield and his Princeton group on droughts as part of her INTENSE ERC project. The results of this research will feed into these networks. Keywords for project hydrological drought risk, prediction, combining natural and social science data, statistical methods

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Figure 1: Proposed methodology to combine data sets of both natural and social science data and to use the relationship with drought drivers, with the aim to improve hydrological drought risk prediction for Europe. SUPERVISION Lead Supervisor Details: Names (first name, family name): Institution: Email:

Anne Van Loon University of Birmingham [email protected]

Second Supervisor Details: Names (first name, family name): Institution:

Hayley Fowler Newcastle University

Third Supervisor Details (if applicable): Names (first and last): Institution:

David M. Hannah University of Birmingham

Fourth Supervisor Details (if applicable): Names (first and last): Institution:

Julian Clark University of Birmingham

Eligibility. DREAM will use NERC rules regarding residency, you do not need to restate them here. Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Hydrology, Meteorology / climatology, Engineering, Geography, or Natural Sciences. Furthermore, applicants are expected to show evidence of proficiency in handling large data sets, programming and mathematical skills. Enquiries. For further details please contact Dr Anne Van Loon: [email protected].

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DREAM PROPOSAL FORM for OCTOBER 2015 INTAKE

factors is key to the application of drought risk mitigation in local water .... Justin Sheffield and his Princeton group on droughts as part of her INTENSE ERC ...

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