Articles | Volume 21, issue 9
https://doi.org/10.5194/hess-21-4629-2017
https://doi.org/10.5194/hess-21-4629-2017
Technical note
 | 
14 Sep 2017
Technical note |  | 14 Sep 2017

Technical note: A hydrological routing scheme for the Ecosystem Demography model (ED2+R) tested in the Tapajós River basin in the Brazilian Amazon

Fabio F. Pereira, Fabio Farinosi, Mauricio E. Arias, Eunjee Lee, John Briscoe, and Paul R. Moorcroft

Related authors

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description
Marcos Longo, Ryan G. Knox, David M. Medvigy, Naomi M. Levine, Michael C. Dietze, Yeonjoo Kim, Abigail L. S. Swann, Ke Zhang, Christine R. Rollinson, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4309–4346, https://doi.org/10.5194/gmd-12-4309-2019,https://doi.org/10.5194/gmd-12-4309-2019, 2019
Short summary
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Marcos Longo, Ryan G. Knox, Naomi M. Levine, Abigail L. S. Swann, David M. Medvigy, Michael C. Dietze, Yeonjoo Kim, Ke Zhang, Damien Bonal, Benoit Burban, Plínio B. Camargo, Matthew N. Hayek, Scott R. Saleska, Rodrigo da Silva, Rafael L. Bras, Steven C. Wofsy, and Paul R. Moorcroft
Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019,https://doi.org/10.5194/gmd-12-4347-2019, 2019
Short summary
Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation
Istem Fer, Ryan Kelly, Paul R. Moorcroft, Andrew D. Richardson, Elizabeth M. Cowdery, and Michael C. Dietze
Biogeosciences, 15, 5801–5830, https://doi.org/10.5194/bg-15-5801-2018,https://doi.org/10.5194/bg-15-5801-2018, 2018
Short summary
Assessing floods and droughts in the Mékrou River basin (West Africa): a combined household survey and climatic trends analysis approach
Vasileios Markantonis, Fabio Farinosi, Celine Dondeynaz, Iban Ameztoy, Marco Pastori, Luca Marletta, Abdou Ali, and Cesar Carmona Moreno
Nat. Hazards Earth Syst. Sci., 18, 1279–1296, https://doi.org/10.5194/nhess-18-1279-2018,https://doi.org/10.5194/nhess-18-1279-2018, 2018
Short summary
Variability of phenology and fluxes of water and carbon with observed and simulated soil moisture in the Ent Terrestrial Biosphere Model (Ent TBM version 1.0.1.0.0)
Y. Kim, P. R. Moorcroft, I. Aleinov, M. J. Puma, and N. Y. Kiang
Geosci. Model Dev., 8, 3837–3865, https://doi.org/10.5194/gmd-8-3837-2015,https://doi.org/10.5194/gmd-8-3837-2015, 2015
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023,https://doi.org/10.5194/hess-27-2989-2023, 2023
Short summary
Changes in Mediterranean flood processes and seasonality
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023,https://doi.org/10.5194/hess-27-2973-2023, 2023
Short summary
Can the combining of wetlands with reservoir operation reduce the risk of future floods and droughts?
Yanfeng Wu, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang
Hydrol. Earth Syst. Sci., 27, 2725–2745, https://doi.org/10.5194/hess-27-2725-2023,https://doi.org/10.5194/hess-27-2725-2023, 2023
Short summary
Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado
Peishi Jiang, Pin Shuai, Alexander Sun, Maruti K. Mudunuru, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 27, 2621–2644, https://doi.org/10.5194/hess-27-2621-2023,https://doi.org/10.5194/hess-27-2621-2023, 2023
Short summary
When best is the enemy of good – critical evaluation of performance criteria in hydrological models
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023,https://doi.org/10.5194/hess-27-2397-2023, 2023
Short summary

Cited articles

Albani, M., Medvigy, D., Hurtt, G. C., and Moorcroft, P. R.: The contributions of land-use change, CO2 fertilization, and climate variability to the Eastern US carbon sink, Glob. Change Biol., 12, 2370–2390, https://doi.org/10.1111/j.1365-2486.2006.01254.x, 2006.
Alsdorf, D. E., Rodríguez, E., and Lettenmaier, D. P.: Measuring surface water from space, Rev. Geophys., 45, RG2002, https://doi.org/10.1029/2006RG000197, 2007.
ANA: Plano Estratégico de Recursos Hídricos da Bacia Amazônica – Afluentes da Margem Direita, Brasilia, Brazil, Brazil, available at: http://margemdireita.ana.gov.br/ (last access: 7 September 2017), 2011 (in Portuguese).
ANA: Hidroweb –Sistema de informações hidrologicas, available from: http://www.snirh.gov.br/hidroweb/, (last access: 7 September 2017), 2016.
Anderson, E. A.: Calibration of Conceptual Models for Use in River Forecasting, available at: http://www.nws.noaa.gov/oh/hrl/calb/calibration1102/main.htm (last access: 7 September 2017), 2002.
Download
Short summary
ED2 is a terrestrial biosphere model (TBM) suited for investigating combined impacts of changes in climate, atmospheric CO2, and land cover on the water cycle. In this study, we describe the integration of ED2 with a hydrological routing scheme. The resulting ED2+R model calculates the lateral propagation of surface and subsurface runoff resulting from the TBM and determines spatiotemporal patterns of river flows. We successfully evaluated the ED2+R model in the Tapajós, Brazilian Amazon.