Guest Editorial: Special Issue on Global Hydrological Datasets for Local Water Management Applications
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Guest Editorial: Special Issue on Global Hydrological Datasets for Local Water Management Applications Geert Sterk 1 & Frederiek Sperna-Weiland 2 & Marc Bierkens 1 Published online: 11 May 2020 # Springer Nature B.V. 2020
1 Introduction The global water resources and flows are under pressure due to climate impacts and human interventions such as hydro-power dam operations and water abstractions for agriculture, industry, tourism and domestic use (Haddeland et al. 2014). In many areas the per-capita water availability is decreasing due to climate and demographic changes (Faures 2006). Projected climate change will aggravate hydrological extremes, notably floods and droughts (Patz et al. 2005), which in combination with continued population growth may enhance water scarcity (Hagemann et al. 2013). Management of water resources will become an increasing challenge in the twenty-first century, especially in those areas where large variations in the water availability occur. To assist operational water management activities, especially in those areas where in-situ measurements are lacking, new tools and hydrological datasets are required to test alternative management options to adapt to future hydrological conditions. To do so, it is important to have access to historical hydrological data, which can provide information about past hydrological extremes. These data can be used to test alternative water management decisions and provide probabilities of water resources availability under a variety of climatic conditions. In many developed countries with a good hydrological measurement network and long time series of data such water management evaluations can be easily made. On the other hand, there are many countries in the world where such time series of hydrological data are missing for most of their major watersheds. When good-quality data are missing, use can be made of re-analysis datasets of water resources. However, until recently only a few of such global re-analysis datasets were available (Schellekens et al. 2017). Examples are the Global Land Data Assimilation System (GLDAS) from NASA (Rodell et al. 2004) and ERA-Interim/Land, the ECMWF Re-Analysis product (Balsamo et al. 2015). The recently terminated project ‘Global Earth Observation for * Geert Sterk [email protected]
1
Department of Physical Geography, Utrecht University, P.O. Box 80.115, NL-3508 TC Utrecht, The Netherlands
2
Deltares, Rotterdamseweg 185, NL-2629 HD Delft, The Netherlands
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Sterk G. et al.
Integrated Water Resources Assessment’ (eartH2Observe), which was funded through the EU Framework 7 programme, has produced two new global water resources re-analysis (WRR) datasets, which cover the years 1979–2012.
2 eartH2Observe Products Compared to the previous re-analysis datasets, which were based on a single land surface model, the eartH2Observe WRR datasets are based on a multi-model ensemble consisting of ten global models (Table 1). The two WRR products from the eartH2Observe project are at different spatial resolutions. The Tier 1 WRR use
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