PhD research: Hydrological climate change impact assessment - addressing the uncertainties
Some of the most significant effects of climate change are expected to impact hydrological processes, such as snowmelt and timing of discharge. Therefore, it is of growing importance to create accurate projections of streamflow whilst understanding and reducing biases in climate model projections. Streamflow is controlled by a wide range of hydrometeorological processes. When streamflow is simulated, the realism of the simulations reflects how well those processes are represented in models. Therefore, within our first project, we use hydrological modeling to evaluate the atmospheric forcing provided by GCM-RCM combinations (climate models).
Our second project is a more collaborative effort, which entails the creation of an encyclopedia chapter 'Hydrological climate change impact modeling: from basics to applications'. Within this chapter, we provide background knowledge on the subject, descriptions of best practices, we outline common mistakes and provide scripts for those who wish to carry out such research. This chapter also provides information for faculty to custom-design their own course packs for interdisciplinary water-related courses.
In our third project, we aim to improve decision making by hydropower managers by providing them with projections of streamflow for their catchments. The projections and visualizations we provide will include uncertainty decomposition so that decisions can be made in light of all uncertainties involved.
Besides my main research projects described above, I am also currently involved in studies related the use of multivariate bias correction for glaciated Swiss catchments and the impact of potential evapotranspiration estimation on streamflow in Tunisia.
Project management and contacts
Prof. Dr. Jan Seibert (firstname.lastname@example.org)
Dr. Nans Addor (N.Addor@uea.ac.uk)
Kirsti Hakala (email@example.com)
Meyer, Judith; Kohn, Irene; Stahl, Kerstin; Hakala, Kirsti; Seibert, Jan; Cannon, Alex J. (in review). Effects of univariate and multivariate bias correction on hydrological impact projections in alpine catchments. Hydrological and Earth System Sciences, doi: 10.5194/hess-2018-317.
Dahklaoui, Hamouda; Seibert, Jan; Hakala, Kirsti (in review). Sensitivity of discharge projections to potential evapotranspiration in Northern Tunisa. Regional Environmental Change.
Hakala, Kirsti; Addor, Nans; Teutschbein, Claudia; Vis, Marc; Dakhlaoui, Hamouda; Seibert, Jan (in press). Hydrological climate change impact modeling. Encyclopedia of Water: Science, Technology, and Society.
Hakala, Kirsti; Addor, Nans, Seibert, Jan (2018). Hydrological modeling to evaluate climate model simulations and their bias correction. Journal of Hydrometeorology, doi: 10.1175/jhm-d-17-0189.1.
Wang, S.-Y. (Simon); Lin, Yen-Heng; Gillies, Robert R.; Hakala, Kirsti (2016). Indications for protracted groundwater depletion after drought over the Central Valley of California. Journal of Hydrometeorology, doi: 10.1175/JHM-D-15-0105.1.
Archfield, Stacey; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew; Wagener, Thorsten; Farmer, William H.; Andréassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas (2015). Accelerating advances in continental domain hydrologic modeling. Water Resources Research, doi: 10.1002/2015WR017498.
Wang, Shih-Yu; Hakala, Kirsti; Gillies, Robert R.; Capehart, William J. (2014). The Pacific quasi-decadal oscillation (QDO): An important precursor toward anticipating major flood events in the Missouri River Basin? Geophysical Research Letters, doi: 10.1002/2013GL059042.