Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2917-2022
https://doi.org/10.5194/gmd-15-2917-2022
Development and technical paper
 | 
07 Apr 2022
Development and technical paper |  | 07 Apr 2022

Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x

Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe

Related authors

Reviews and Syntheses: Variable Inundation Across Earth’s Terrestrial Ecosystems
James Stegen, Amy Burgin, Michelle Busch, Joshua Fisher, Joshua Ladau, Jenna Abrahamson, Lauren Kinsman-Costello, Li Li, Xingyuan Chen, Thibault Datry, Nate McDowell, Corianne Tatariw, Anna Braswell, Jillian Deines, Julia Guimond, Peter Regier, Kenton Rod, Edward Bam, Etienne Fluet-Chouinard, Inke Forbrich, Kristin Jaeger, Teri O'Meara, Tim Scheibe, Erin Seybold, Jon Sweetman, Jianqiu Zheng, Daniel Allen, Elizabeth Herndon, Beth Middleton, Scott Painter, Kevin Roche, Julianne Scamardo, Ross Vander Vorste, Kristin Boye, Ellen Wohl, Margaret Zimmer, Kelly Hondula, Maggi Laan, Anna Marshall, and Kaizad Patel
EGUsphere, https://doi.org/10.5194/egusphere-2024-98,https://doi.org/10.5194/egusphere-2024-98, 2024
Short summary
Yakima River Basin Water Column Respiration is a Minor Component of River Ecosystem Respiration
Stephanie G. Fulton, Morgan Barnes, Mikayla A. Borton, Xingyuan Chen, Yuliya Farris, Brieanne Forbes, Vanessa A. Garayburu-Caruso, Amy E. Goldman, Samantha Grieger, Robert Hall Jr., Matthew H. Kaufman, Xinming Lin, Erin McCann, Sophia A. McKever, Allison Myers-Pigg, Opal C. Otenburg, Aaron C. Pelly, Huiying Ren, Lupita Renteria, Timothy D. Scheibe, Kyongho Son, Jerry Tagestad, Joshua M. Torgeson, and James C. Stegen
EGUsphere, https://doi.org/10.5194/egusphere-2023-3038,https://doi.org/10.5194/egusphere-2023-3038, 2024
Short summary
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023,https://doi.org/10.5194/gmd-16-4017-2023, 2023
Short summary
Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022,https://doi.org/10.5194/gmd-15-8809-2022, 2022
Short summary
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022,https://doi.org/10.5194/gmd-15-7879-2022, 2022
Short summary

Related subject area

Hydrology
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024,https://doi.org/10.5194/gmd-17-2141-2024, 2024
Short summary
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024,https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024,https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024,https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024,https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary

Cited articles

Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme, C., and Salamon, P.: A global streamflow reanalysis for 1980–2018, J. Hydrol. X, 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020. a
Bao, J., Zhou, T., Huang, M., Hou, Z., Perkins, W., Harding, S., Titzler, S., Hammond, G., Ren, H., Thorne, P., Suffield, S., Murray, C., and Zachara, J.: Modulating factors of hydrologic exchanges in a large‐scale river reach: Insights from three‐dimensional computational fluid dynamics simulations, Hydrol. Process., 32, 3446–3463, https://doi.org/10.1002/hyp.13266, 2018. a, b
Bao, J., Chen, Y., Fang, Y., Song, X., Perkins, W., Duan, Z., Shuai, P., Ren, H., Hou, Z., Richmond, M., He, X., and Scheibe, T.: Modeling framework for evaluating the impacts of hydrodynamic pressure on hydrologic exchange fluxes and residence time for a large-scale river section over a long-term period, Environ. Modell. Softw., 148, 105277, https://doi.org/10.1016/j.envsoft.2021.105277, 2022. a, b
Bates, P. D., Anderson, M. G., and Hervouet, J. M.: Initial comparison of two two-dimensional finite element codes for river flood simulation, P. I. Civil Eng.-Water, 112, 238–248, https://doi.org/10.1680/iwtme.1995.27886, 1995. a
Bates, P. D., Lane, S. N., and Ferguson, R. I.: Computational fluid dynamics: applications in environmental hydraulics, edited by: Bates, P. D., Lane, S. N., and Ferguson, R. I., John Wiley & Sons, Ltd, Chichester, UK, https://doi.org/10.1002/0470015195, 2005. a
Download
Short summary
Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.