Multimodel Estimate of the Global Terrestrial Water Balance: Setup and First Results

Abstract

Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.58 spatial resolution for the global land areas for a 15-yr period (1985-99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr 21 (from 60 000 to 85 000 km 3 yr 21 ), and simulated runoff ranges from 290 to 457 mm yr 21 (from 42 000 to 66 000 km 3 yr 21 ). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degreeday approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).

Future discharge drought across climate regions around the world modelled with a synthetic hydrological modelling approach forced by three general circulation models

“…This large uncertainty in the GHMs was also found by Prudhomme et al (2014) for the CMIP5 climate projections in the ISI-MIP project. Prudhomme et al (2014) compared a large ensemble of GCM-GHM combinations and showed that the highest projection uncertainty could be related to the GHM runoff-generating processeswhich is supported by the work of Haddeland et al (2011) and Hagemann et al (2013). It was found by Alderlieste et al (2014) that the change in the projected characteristics of future drought is larger (climate signal) than the uncertainty in the GCM-GHM combinations.…”

“…Van Loon and Van Lanen, 2012), and the incapability of models to include all these processes (e.g. Gudmundsson et al, 2012;Haddeland et al, 2011;Prudhomme et al, 2011) reduce our ability to instil strong confidence in the assessment of past and future drought across the world. High-impact largescale droughts, like the recent droughts in Russia, United States and Africa, show the need to improve understanding of drought mechanisms on continental and global scales, which would lead to better drought adaptation and drought predictability.…”

“…Recently, the WATCH (WATer and global CHange) project concluded a comprehensive multimodel analysis (e.g. Haddeland et al, 2011) that tested GHM performance against historic low runoff (e.g. Gudmundsson et al, 2012;Stahl et al, 2012) and drought (e.g.…”

“…Moreover, the impact of GHMs on future drought projections is significant (e.g. Haddeland et al, 2011;Van Huijgevoort et al, 2014;Prudhomme et al, 2014), which makes a detailed impact assessment of the importance of climate and catchment structure even more complicated. To investigate the relative importance of climate and catchment structure on hydrological drought, used a synthetic hydrological modelling approach to study the effects of these factors on hydrological drought characteristics on a global scale.…”

“…The WFD were successfully used in multiple hydrological studies (e.g. Corzo Perez et al, 2011a;Haddeland et al, 2011;Harding et al, 2011;Prudhomme et al, 2011;Gudmundsson et al, 2012;Stahl et al, 2012;Van Vliet et al, 2012;Van Huijgevoort et al, 2013;Van Loon et al, 2014). In this study the WFD were used to identify the reference hydrological situation for every selected location, with the synthetic hydrological modelling approach.…”