Fulco Ludwig

Prof. Dr. Fulco Ludwig

Water Systems and Global Change, Department of Environmental Sciences, Wageningen University

Research Focus & Metrics

Academic Career Length

30Years (1997-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2005 in Nature
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Journal Article
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MSMahesh Sankaran
Mahesh Sankaran
NHNiall Hanan
Niall Hanan
RSRobert Scholes
Robert Scholes
JRJayashree Ratnam
Jayashree Ratnam
DADavid Augustine
David Augustine
NZNick Zambatis
Nick Zambatis

16 December 2013 in Proceedings of the National Academy of Sciences
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Journal Article
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IHIngjerd Haddeland
Ingjerd Haddeland
JHJens Heinke
Jens Heinke
HBHester Biemans
Hester Biemans
SEStephanie Eisner
Stephanie Eisner
MFMartina Flörke
Martina Flörke
DWDominik Wisser
Dominik Wisser
Significance: Humans alter the water cycle by constructing dams and through water withdrawals. Climate change is expected to additionally affect water supply and demand. Here, model analyses of climate change and direct human impacts on the terrestrial water cycle are presented. The results indicate that the impact of man-made reservoirs and water withdrawals on the long-term global terrestrial water balance is small. However, in some river basins, impacts of human interventions are significant. In parts of Asia and the United States, the effects of human interventions exceed the impacts expected for moderate levels of global warming. This study also identifies areas where irrigation water is currently scarce, and where increases in irrigation water scarcity are projected.

16 December 2013 in Proceedings of the National Academy of Sciences
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JEJoshua Elliott
Joshua Elliott
DDDelphine Deryng
Delphine Deryng
CMChristoph Müller
Christoph Müller
KFKatja Frieler
Katja Frieler
MKMarkus Konzmann
Markus Konzmann
DWDominik Wisser
Dominik Wisser
We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. Significance Freshwater availability is relevant to almost all socioeconomic and environmental impacts of climate and demographic change and their implications for sustainability. We compare ensembles of water supply and demand projections driven by ensemble output from five global climate models. Our results suggest reasons for concern. Direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–2,600 Pcal (8–43% of present-day total). Freshwater limitations in some heavily irrigated regions could necessitate reversion of 20–60 Mha of cropland from irrigated to rainfed management, and a further loss of 600–2,900 Pcal. Freshwater abundance in other regions could help ameliorate these losses, but substantial investment in infrastructure would be required.

1 April 2013 in Global Environmental Change
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MVMichelle T.H. van Vliet
Michelle T.H. van Vliet
WFWietse H.P. Franssen
Wietse H.P. Franssen
JYJohn R. Yearsley
John R. Yearsley
Fulco LudwigFulco Ludwig
Fulco Ludwig
IHIngjerd Haddeland
Ingjerd Haddeland
PKPavel Kabat
Pavel Kabat

1 October 2011 in Journal of Hydrometeorology
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IHIngjerd Haddeland
Ingjerd Haddeland
DCDouglas B. Clark
Douglas B. Clark
WFWietse Franssen
Wietse Franssen
Fulco LudwigFulco Ludwig
Fulco Ludwig
FVFrank Voß
Frank Voß
PYPat Yeh
Pat Yeh
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 0.5° 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−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). 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 degree-day 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).

3 June 2012 in Nature Climate Change
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MVMichelle T. H. van Vliet
Michelle T. H. van Vliet
JYJohn R. Yearsley
John R. Yearsley
Fulco LudwigFulco Ludwig
Fulco Ludwig
Stefan VögeleStefan Vögele
Stefan Vögele
DLDennis P. Lettenmaier
Dennis P. Lettenmaier
PKPavel Kabat
Pavel Kabat