Geology & Geophysics AGU News

Eric F. Wood Receives 2017 Robert E. Horton Medal

Eric F. Wood was awarded the 2017 Robert E. Horton Medal at the American Geophysical Union Fall Meeting Honors Ceremony, held on 13 December 2017 in New Orleans, La. The medal is for “outstanding contributions to hydrology.”



Eric F. Wood, 2017 Robert E. Horton Medal recipient
Eric F. Wood

The awarding of the Robert E. Horton Medal to Eric F. Wood recognizes him for major advances he has made toward process-based representation of global hydrology through developing hyperresolution models and enhancing them dynamically with remotely sensed observations using novel methods of data assimilation.

Eric was a pioneer in fundamental research on scaling and similarity of catchment hydrologic responses. He introduced the “representative elementary area” concept that showed that catchment response could be represented in terms of “building blocks” of some minimum size. This breakthrough launched him into the era of spatially distributed hydrologic modeling. Eric was the first to develop a distributed modeling framework that accounted for the effects of topography and land surface–atmosphere interactions involving coupled water–energy dynamics. Many of the distributed modeling concepts Eric pioneered found their way into the Variable Infiltration Capacity (VIC) macroscale hydrology model, which is the default land surface parameterization scheme in many global circulation models used in global change science.

Building on the success of distributed models at river basin scales, Eric Wood and his colleagues extended the modeling all the way to the globe and used the models to make predictions of river flows, floods, and droughts, discovering interesting regional and global patterns. At the continental and global scales, Eric made major contributions to increasing the predictability of streamflow by taking advantage of both soil moisture and precipitation data from satellites. He developed new conceptualizations of radiative transfer that allowed ingestion of radiation data directly into hydrologic models. Eric’s research also showed that knowledge of initial soil moisture provides the main source of forecasting skill and that the potential for improved forecasts was limited by the accuracy of precipitation estimates. Eric’s frameworks for improving predictability have been adopted by major weather forecasting centers around the world to routinely assimilate satellite estimates of land surface conditions into numerical weather prediction models. This enhanced forecast methodology has led to significantly improved drought forecasts.

Finally, through his leadership within global programs such as the World Climate Research Programme and the Global Water and Energy Experiment and his involvement with national organizations such as NASA and the National Oceanic and Atmospheric Administration (NOAA), Eric has steered global water research along his vision of global, distributed hydrology. The promise of global hydrology, deemed impossible only a few years ago, has now been realized through the efforts of Eric Wood, and he is therefore a deserving recipient of the Robert E. Horton Medal.

—Günter Blöschl, Vienna University of Technology, Vienna, Austria


I’m honored that AGU selected me to receive the Robert E. Horton Medal, and I thank Professor Günter Blöschl for the kind citation that provides a summary of my contributions. Over the past 40 years many people contributed to my research—over 30 Ph.D. students, 30 postdocs and research staff, and many collaborators. While space limitations preclude listing all of them and the ways they contributed, I would like to provide a perspective on the evolution of the research summarized in the citation. In the early 1980s, Keith Beven encouraged me to think about process-based hydrologic processes that led to my “Representative Elementary Area” concept. Understanding the impact of landscape variability on water and energy fluxes has been an unresolved research problem, but the work of M. Sivapalan, W. Crow, and C. Peters-Lidard indicated that ignoring such variability leads to biased surface fluxes. Including spatial variability in land surface models led to my 30-year collaboration with Dennis Lettenmaier in the development of the Variable Infiltration Capacity model, which started with Xu Liang’s Ph.D. dissertation in the early 1990s at the University of Washington. Twenty years later, I proposed the development of hyperresolution land surface modeling (LSM)—30 to 100 meters at continental scales—to capture this variability, which led to the development by my student Nathaniel Chaney of HydroBlocks, which we’ve run at 30 meters across the contiguous United States. In the mid-1990s a strategy was developed for using VIC and remote sensing from small-scale modeling (focusing on processes) to continental- to global-scale modeling (focusing on the global water cycle). With Dennis Lettenmaier and his group, we developed the first continental-scale, long-term forcing data set for LSM as part of the North American Land Data Assimilation System (NLDAS), which was used by Justin Sheffield to develop a VIC-based objective drought index and by Ming Pan to develop assimilation systems with remote sensing data. Within the NLDAS project we also used NOAA’s Climate Forecast System seasonal forecasting model to develop seasonal hydrological forecasting and, recently, a multimodel forecast system with my postdoc Niko Wanders. The experience over the United States allowed us to expand to a global domain, where we now run historical and real-time flood and drought monitors as a climate service to help users improve their decisions. I see my Robert Horton Medal as a medal shared with all of my students, research staff, and collaborators who contributed to the work and with the NASA and NOAA program managers who funded my research. I gratefully thank them all.

—Eric F. Wood, Princeton University, Princeton, N.J.

Citation: AGU (2017), Eric F. Wood receives 2017 Robert E. Horton Medal, Eos, 98, Published on 20 December 2017.
© 2017. The authors. CC BY-NC-ND 3.0