Using big data to detect and attribute global hydrological change
Lukas Gudmundsson1, Hong Xuan Do2, Simon Newland Gosling3, Michael Leonard4, Junguo Liu5, Hannes Mueller Schmied6, Jacob Schewe7, Sonia I Seneviratne1, Seth Westra8, Wim Thiery9, Xuebin Zhang10 and Fang Zhao11, (1)Institute for Atmospheric and Climate Science, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland, (2)University of Adelaide, School of Civil, Environmental and Mining Engineering, Adelaide, SA, Australia, (3)University of Nottingham, School of Geography, Nottingham, United Kingdom, (4)University of Adelaide, Adelaide, Australia, (5)North China University of Water Resources and Electric Power, Zhengzhou, China, (6)Goethe University Frankfurt, Senckenberg Biodiversity and Climate Research Centre, Institute of Physical Geography, Frankfurt am Main, Germany, (7)Potsdam Institute for Climate Impact Research, Potsdam, Germany, (8)University of Adelaide Water Research Centre, Adelaide, Australia, (9)ETH Swiss Federal Institute of Technology Zurich, Zurich, Switzerland, (10)Environment Canada Toronto, Toronto, ON, Canada, (11)University of Maryland, College Park, MD, United States
