Search Results

You are looking at 1 - 10 of 13 items for :

  • Water and Global Change (WATCH) Special Collection x
  • All content x
Clear All
Christel Prudhomme, Simon Parry, Jamie Hannaford, Douglas B. Clark, Stefan Hagemann, and Frank Voss

1. Introduction and background There is growing evidence that the hydrological cycle is intensifying (e.g., Huntington 2006 ; Stott et al. 2010 ) as a result of anthropogenically forced climatic change. Generally speaking, at regional to continental scales, two contrasting approaches are used to examine the influence of climate change on the hydrological cycle: through analysis of historical data, to detect emerging trends (e.g., in Europe by Stahl et al. 2010 , in North America by Douglas

Full access
Lukas Gudmundsson, Lena M. Tallaksen, Kerstin Stahl, Douglas B. Clark, Egon Dumont, Stefan Hagemann, Nathalie Bertrand, Dieter Gerten, Jens Heinke, Naota Hanasaki, Frank Voss, and Sujan Koirala

Europe based on daily data. They concluded that the model captured average annual low and high flows reasonably well, but had a tendency to overestimate the return periods of extreme events. Similarly, Hirabayashi et al. (2008) compared the estimated return periods of seven disastrous floods around the globe to the results from a global offline simulation with daily resolution and concluded that the return period of the simulated events compared reasonably well to the observed values. However

Full access
Wai Kwok Wong, Stein Beldring, Torill Engen-Skaugen, Ingjerd Haddeland, and Hege Hisdal

relevance to the water industry when investigating environmental demands on river systems. Climate change has the potential to alter hydrological conditions and these changes could have a large adverse effect on the availability of the water resources. Few studies have examined climate change impacts on future droughts. A study by Calanca (2007) stated that the frequency of soil moisture droughts will increase in summer in the Alpine region in Europe. Blenkinsop and Fowler (2007) used six regional

Full access
Kerstin Stahl, Lena M. Tallaksen, Lukas Gudmundsson, and Jens H. Christensen

. Examples of global or continental-scale mapping of recent and predicted hydrological change include changes in mean streamflow globally (e.g., Milly et al. 2005 ; Dai et al. 2009 ) and extremes (floods and low flows) in Europe ( Lehner et al. 2006 ) and globally ( Hirabayashi et al. 2008 ). To assess the limits of interpretability of model simulations, evaluation against observational data is crucial. Such comparisons are usually carried out in the model development phase—for example, for parameter

Full access
Philippe Lucas-Picher, Jens H. Christensen, Fahad Saeed, Pankaj Kumar, Shakeel Asharaf, Bodo Ahrens, Andrew J. Wiltshire, Daniela Jacob, and Stefan Hagemann

. (2009) showed that the implementation of an irrigation scheme reduces the warm bias of the Max Planck Institute Regional Model (REMO) for the north of India and improves the precipitation distribution. Recently, Dobler and Ahrens (2010) performed RCM simulations with the Consortium for Small-Scale Modelling (COSMO) Climate Local Model (CLM) RCM over South Asia, using the ECHAM5–Max Planck Institute Ocean Model (MPIOM) GCM and the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re

Full access
Richard Harding, Martin Best, Eleanor Blyth, Stefan Hagemann, Pavel Kabat, Lena M. Tallaksen, Tanya Warnaars, David Wiberg, Graham P. Weedon, Henny van Lanen, Fulco Ludwig, and Ingjerd Haddeland

Northern Hemisphere tropics (West and East Africa and southern Asia) with distinct upward trends at high latitudes. Zhang et al. (2007) conclude that anthropogenic forcing has contributed significantly to these observed zonal changes in precipitation. There is some evidence for the increased intensity of precipitation in Europe ( Klein Tank and Konnen 2003 ; Zolina et al. 2010 ) and worldwide ( Groisman et al. 2005 ). The increase in heavy rainfall is more than the percentage average and is

Full access
Aristeidis G. Koutroulis, Aggeliki-Eleni K. Vrohidou, and Ioannis K. Tsanis

, during the corresponding 48-month previous period (October 1989–September 1993). This example presents the shortcoming of the SPI in providing relative information related to the water resources of a region. Although the period 1990–95 is severely dry for each of the 3 hypothetical basins, water excess from wet watershed C could be used to cover the water shortage of dry watershed A. The recently adopted European Water Framework Directive (WFD) 2000/60/EC ( EUR-Lex 2000 ) establishes a new

Full access
D. Gerten, J. Heinke, H. Hoff, H. Biemans, M. Fader, and K. Waha

than in northern Europe ( Liu et al. 2007 ; Fader et al. 2010 ). Hence, using the global average threshold would underrate water scarcity for regions where in fact >1300 cubic meters per capita per year is needed for producing the specified diet, and vice versa. This study quantifies the GW and BW availabilities for each country of the world and directly compares these to the water requirements for producing a diet of 3000 kilocalories per capita per day (with 80% vegetal products) calculated from

Full access
Manuel Punzet, Frank Voß, Anja Voß, Ellen Kynast, and Ilona Bärlund

temperatures were used as data input. Water temperature data were compiled from 935 U.S. Geological Survey (USGS) water gauging stations, 570 stations of United Nations Environmental Programme (UNEP) Global Environment Monitoring System (GEMS), and 154 additional gauging stations situated at various European main streams ( Table 1 ). The measured water temperatures are monthly means of single values available for the period 1965–2001. For gridded monthly air temperatures, the new global meteorological

Full access
Stefan Hagemann, Cui Chen, Jan O. Haerter, Jens Heinke, Dieter Gerten, and Claudio Piani

dataset covers the period 1958–2001 and is based on the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40; Uppala et al. 2005 ). The ERA-40 data were interpolated to 0.5° and only considered over land points using the land–sea mask from the Climate Research Unit dataset TS2.1 (CRU; Mitchell and Jones 2005 ). A correction for elevation differences between ERA-40 and CRU was applied. For 2-m temperatures, a correction of the monthly means with CRU data was performed

Full access