About the Project
Due to high computational demand and limited data availability, only a handful of global hydrological models have been developed. Current global models also suffer from a lack of regionalised model parameters and hence their simulation of streamflow can be unreliable [ii]. Regionalisation techniques can greatly improve model performance especially for the basins where streamflow data are unavailable or scarce. Many studies have applied regionalisation techniques for basin-scale hydrological models, but very few attempts have been made to apply these techniques to global-scale hydrological models and they have had limited success [ii].
The overarching aim of this PhD project is to develop a regionalised global hydrological model to assess impacts of climate change on flooding risks with three research objectives:
1. Collate and process geographical, meteorological and hydrological global datasets in a consistent gridded format for the hydrological model.
2. Develop a regionalised model parameterisation method for the model and improve its performance in different parts of the world by obtaining regional estimates of its parameters.
3. Model global flood hazards at present-day and under climate change using the latest climate reanalysis and global climate model outputs.
The prospective student will receive training in hydrology and climatology and acquire manifold skills in (1) processing of large datasets using computer programmes, (2) parameter calibration, validation and regionalisation of a hydrological model, and (3) statistical analysis. The student will also write peer-reviewed journal articles and participate in UK or international conferences.
For more information on the supervisor for this project, please go here: https://people.uea.ac.uk/en/persons/yi-he
The type of programme: PhD
The start date of the project: Oct 2019
The mode of study: Full-time
Acceptable first degree in a relevant subject area (Environmental Sciences, Physics, Maths, Statistics, Geography or a related discipline), an aptitude for research, numerate and a clear communicator. Minimum entry requirements is 2:1.
ii) Beck HE et al. 2016 Global-scale regionalization of hydrologic model parameters, Water Resour. Res., 52, 3599–3622.
iii) Hirabayashi Y. et al. 2013 Global flood risk under climate change. Nature Clim. Change 3, 816-821.
iv) Winsemius HC. et al. 2016 Global drivers of future river flood risk. Nat. Clim. Chang. 6, 381–385.
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