I will reflect on some of Eric’s major accomplishments, and my own experiences from having worked with him for over 40 years.  This will go back to our first professional meeting, at a meeting of the AGU Committee on Network Design in the late 1970s.  It will also include early consulting work, including Love Canal in particular, his leave at the (then) UK Institute of Hydrology in 1984, and work with the late James R Wallis.  I will focus especially on development of the Variable Infiltration Capacity (VIC) model starting in the early 1990s, and its many applications by his group over the last two plus decades.  I’ll finish with reflections on his approach to hydrologic research, and some messages our younger colleagues can take away from his life and contributions.

How to cite: Lettenmaier, D.: Some reflections on Eric Wood’s career, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3054, https://doi.org/10.5194/egusphere-egu22-3054, 2022.

This presentation will briefly review the scaling and similarity concepts developed by Eric Wood and evaluate their impact on the development of the hydrological science, in particular distributed hydrological modeling.

Eric Wood was a pioneer in fundamental research on scaling and similarity of catchment hydrologic response. 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 thinking 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 has become a common land surface parameterization scheme in global circulation models used in global change science.

How to cite: Blöschl, G.: Eric Wood’s contributions to Scaling in Hydrology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1900, https://doi.org/10.5194/egusphere-egu22-1900, 2022.

Eric F. Wood was a pioneer in large-domain hydrologic modeling. Building on his work on hydrologic scaling in the 1980s, in the 1990s and 2000s Eric led the community in process-based approaches to hydrologic modeling across large geographical domains. Together with Dennis Lettenmaier, Eric developed the open-source Variable Infiltration Capacity (VIC), which became a leading large-domain hydrologic model used by dozens of research groups around the world. The capabilities of VIC advanced by Eric and Dennis' students and postdocs included improved representation of hydrologic scaling relationships, advanced representation of cold region hydrologic processes, new capabilities for large-domain streamflow forecasting, and understanding the sensitivity of large river basins to climate variability and change. Eric's work in leading community model inter-comparison projects (PILPS) and community large-domain modeling studies (GEWEX/GCIP and GEWEX/GAPP) advanced understanding of the limitations of large-domain hydrologic models and helped identify effective strategies for model improvement. It is clear that most large-domain hydrologic models that are in use today are heavily influenced by the legacy of VIC. As the community continues to advance in developing interdisciplinary approaches to Earth System modeling (integrating advances from terrestrial and aquatic ecology and the social sciences), explicitly representing a broader range of natural and human processes, it is increasingly clear that the community is indebted to the contributions of Eric F. Wood.

How to cite: Clark, M.: Celebrating Eric Wood's advances in large domain hydrologic modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5238, https://doi.org/10.5194/egusphere-egu22-5238, 2022.

One of Eric Wood’s latest contributions was to set forth the needs and challenges for developing hyper-resolution LSMs in the order of ~100-m to 1-km spatial resolution. This expanded the applicability of land surface models (LSMs), to address critical challenges in monitoring terrestrial water.  Particularly, by representing the spatial variability of physical processes and their interactions with water, energy, and carbon fluxes at the fine-scale that are critical to advance monitoring and understanding of processes linked to freshwater dynamics, hydrologic extremes (floods and droughts), food security, water quality, among others. Over the past 10 years, Eric’s visions on hyper-resolution along with the ever-increasing availability of high-resolution environmental datasets, satellite and in-situ observations, computing resources, and the development of novel modeling frameworks provided a fertile environment for hyper-resolution land surface models to flourish. This presentation will review the community’s efforts towards the development of models, processes representation, and supporting datasets. In particular, it will highlight recent advances on leveraging big environmental datasets and machine learning for developing hyper-resolution LSMs’ sub-grid tiling schemes; the role of data assimilation in hyper-resolution LSMs to bridge spatial scale mismatch between satellite and in-situ observations; and applications of hyper-resolution LSM for understanding soil moisture spatial scaling.

How to cite: Vergopolan, N.: Eric Wood’s contributions and recent advances on hyper-resolution land surface modeling , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9726, https://doi.org/10.5194/egusphere-egu22-9726, 2022.

Eric F. Wood will be remembered as a visionary scientist and mentor to many hydrologists. As a master student, I had the good fortune to read one of his thought-provoking questions: What modelling experiments need to be performed to resolve the scale question? [1]. Further reading of his scientific contributions led me to appreciate the usefulness of the representative elementary area concept (REA) [2] for developing meso- or macro-scale hydrological models that benefit from the subgrid variability of model paramterizations to derive hydrological fluxes at multiple scales. Eric's scientific writings intrigued us so much that they lead to the development of the multiscale parameter regionalization (MPR) [3] technique originally implemented in the mesoscale hydrological model [4] and now applicable to any land surface model to derive seamless parameter fields at continental or global scales [5].

Eric was an early advocate of hyperresolution global land surface modeling and continental drought monitoring and forecasting initiatives [6,7]. His support and motivation were key to devising a project to demonstrate, for the first time, the feasibility of a high-resolution seasonal forecasting and projection system for Europe using a multi-model approach that use the same hyperresolution physiographic datasets and a common river routing model to reduce the predictive uncertainty of the target variables. We called this project the End to End Demonstrator for Improved Decision Making in Europe (EDgE) [8]. This proof-of-concept constitutes now a blueprint for several follow-up projects at national or global scales [e.g., 9].

Eric F. Wood's scientific legacy will shape future developments in land surface modeling and his contributions will keep guiding generations of hydrologists. I was one of the fortunate ones who had the opportunity to know him as a mentor, project partner and friend. In this presentation, I will attempt to synthesize some of his key contributions that are the cornerstone for developing a Digital Twin [11] of the Earth's water cycle.

References

[1] Wood, E. (Ed.): Land Surface, atmosphere interactions for climate modelling: observations, models, and analysis, Kluwer, 1990.
[2] Wood, E. F. et al. https://doi.org/10.1016/0022-1694(88)90090-X 1988.
[3] Samaniego, L. et al. https://doi.org/10.1029/2008WR007327, 2010b.
[4] mhm-ufz.org
[5] Schweppe, R et al. https://doi.org/10.5194/gmd-2021-103. 2021.
[6] Wood, E.F. et al. https://doi.org/10.1029/2010WR010090 2010.
[7] Sheffield, J., Wood, E. F. et al. https://doi.org/10.1175/BAMS-D-12-00124.1, 2014.
[8] Samaniego, L. et al. https://doi.org/10.1175/BAMS-D-17-0274.1 2019
[9] https://www.ufz.de/ulysses
[10] Bauer, P. et al. https://doi.org/10.1038/s41558-021-00986-y 2021

How to cite: Samaniego, L.: From the REA Concept to a High Resolution Digital Twin of the Earth's Water Cycle, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8072, https://doi.org/10.5194/egusphere-egu22-8072, 2022.