Articles | Volume 17, issue 2
https://doi.org/10.5194/hess-17-873-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-873-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Feb 2013
Research article |
| 28 Feb 2013
A new top boundary condition for modeling surface diffusive exchange of a generic volatile tracer: theoretical analysis and application to soil evaporation
J. Y. Tang
Earth Sciences Division, Lawrence Berkeley National Lab (LBL), Berkeley, CA, USA
W. J. Riley
Earth Sciences Division, Lawrence Berkeley National Lab (LBL), Berkeley, CA, USA
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Jinyun Tang and William J. Riley
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-233, https://doi.org/10.5194/bg-2016-233, 2016
Preprint retracted
J. Y. Tang and W. J. Riley
Biogeosciences, 13, 723–735, https://doi.org/10.5194/bg-13-723-2016, https://doi.org/10.5194/bg-13-723-2016, 2016
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We present a generic flux-limiting approach to simultaneously handle the availability limitation from many substrates, a problem common in all biogeochemical models. Our approach does not have the ordering problem like a few existing ad hoc approaches, and is straightforward to implement. Our results imply that significant uncertainties could have occurred in many biogeochemical models because of the improper handling of the substrate co-limitation problem.
Q. Zhu, W. J. Riley, J. Tang, and C. D. Koven
Biogeosciences, 13, 341–363, https://doi.org/10.5194/bg-13-341-2016, https://doi.org/10.5194/bg-13-341-2016, 2016
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Here we develop, calibrate, and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers based on enzyme kinetics theory. Our model provides an ecologically consistent representation of nutrient competition appropriate for land biogeochemical models integrated in Earth system models.
N. J. Bouskill, W. J. Riley, and J. Y. Tang
Biogeosciences, 11, 6969–6983, https://doi.org/10.5194/bg-11-6969-2014, https://doi.org/10.5194/bg-11-6969-2014, 2014
J. Y. Tang and W. J. Riley
Biogeosciences, 11, 3721–3728, https://doi.org/10.5194/bg-11-3721-2014, https://doi.org/10.5194/bg-11-3721-2014, 2014
W. J. Riley, F. Maggi, M. Kleber, M. S. Torn, J. Y. Tang, D. Dwivedi, and N. Guerry
Geosci. Model Dev., 7, 1335–1355, https://doi.org/10.5194/gmd-7-1335-2014, https://doi.org/10.5194/gmd-7-1335-2014, 2014
J. Y. Tang and W. J. Riley
Biogeosciences, 10, 8329–8351, https://doi.org/10.5194/bg-10-8329-2013, https://doi.org/10.5194/bg-10-8329-2013, 2013
C. D. Koven, W. J. Riley, Z. M. Subin, J. Y. Tang, M. S. Torn, W. D. Collins, G. B. Bonan, D. M. Lawrence, and S. C. Swenson
Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, https://doi.org/10.5194/bg-10-7109-2013, 2013
J. Y. Tang, W. J. Riley, C. D. Koven, and Z. M. Subin
Geosci. Model Dev., 6, 127–140, https://doi.org/10.5194/gmd-6-127-2013, https://doi.org/10.5194/gmd-6-127-2013, 2013
Kamal Nyaupane, Umakant Mishra, Feng Tao, Kyongmin Yeo, William J. Riley, Forrest M. Hoffman, and Sagar Gautam
Biogeosciences, 21, 5173–5183, https://doi.org/10.5194/bg-21-5173-2024, https://doi.org/10.5194/bg-21-5173-2024, 2024
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Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Using machine learning, we develop and compare predictive relationships in observations (Obs) and ESMs. We find different relationships between environmental factors and SOC stocks in Obs and ESMs. SOC prediction in ESMs may be improved by representing the functional relationships of environmental controllers in a way consistent with observations.
Jinyun Tang and William J. Riley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2282, https://doi.org/10.5194/egusphere-2024-2282, 2024
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A new mathematical formulation of the dynamic energy budget model is presented for the growth of biological organisms. The new theory combines mass conservation law and chemical kinetics theory, and is computationally faster than the standard formulation of dynamic energy budget model. In simulating the growth of Thalassiosira weissfloggi in a nitrogen-limiting chemostat, the new model is as good as the standard dynamic energy budget model using almost the same parameter values.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Xi Yi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1584, https://doi.org/10.5194/egusphere-2024-1584, 2024
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 per year in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter Raymond, Pierre Regnier, Joseph G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihito Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joel Thanwerdas, Hanquin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido van der Werf, Doug E. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-115, https://doi.org/10.5194/essd-2024-115, 2024
Revised manuscript under review for ESSD
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesize and update the budget of the sources and sinks of CH4. This edition benefits from important progresses in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
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Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
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We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Jing Tao, Qing Zhu, William J. Riley, and Rebecca B. Neumann
The Cryosphere, 15, 5281–5307, https://doi.org/10.5194/tc-15-5281-2021, https://doi.org/10.5194/tc-15-5281-2021, 2021
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We improved the DOE's E3SM land model (ELMv1-ECA) simulations of soil temperature, zero-curtain period durations, cold-season CH4, and CO2 emissions at several Alaskan Arctic tundra sites. We demonstrated that simulated CH4 emissions during zero-curtain periods accounted for more than 50 % of total emissions throughout the entire cold season (Sep to May). We also found that cold-season CO2 emissions largely offset warm-season net uptake currently and showed increasing trends from 1950 to 2017.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Robinson I. Negrón-Juárez, Jennifer A. Holm, Boris Faybishenko, Daniel Magnabosco-Marra, Rosie A. Fisher, Jacquelyn K. Shuman, Alessandro C. de Araujo, William J. Riley, and Jeffrey Q. Chambers
Biogeosciences, 17, 6185–6205, https://doi.org/10.5194/bg-17-6185-2020, https://doi.org/10.5194/bg-17-6185-2020, 2020
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The temporal variability in the Landsat satellite near-infrared (NIR) band captured the dynamics of forest regrowth after disturbances in Central Amazon. This variability was represented by the dynamics of forest regrowth after disturbances were properly represented by the ELM-FATES model (Functionally Assembled Terrestrial Ecosystem Simulator (FATES) in the Energy Exascale Earth System Model (E3SM) Land Model (ELM)).
Kuang-Yu Chang, William J. Riley, Patrick M. Crill, Robert F. Grant, and Scott R. Saleska
Biogeosciences, 17, 5849–5860, https://doi.org/10.5194/bg-17-5849-2020, https://doi.org/10.5194/bg-17-5849-2020, 2020
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Methane (CH4) is a strong greenhouse gas that can accelerate climate change and offset mitigation efforts. A key assumption embedded in many large-scale climate models is that ecosystem CH4 emissions can be estimated by fixed temperature relations. Here, we demonstrate that CH4 emissions cannot be parameterized by emergent temperature response alone due to variability driven by microbial and abiotic interactions. We also provide mechanistic understanding for observed CH4 emission hysteresis.
Haifan Liu, Heng Dai, Jie Niu, Bill X. Hu, Dongwei Gui, Han Qiu, Ming Ye, Xingyuan Chen, Chuanhao Wu, Jin Zhang, and William Riley
Hydrol. Earth Syst. Sci., 24, 4971–4996, https://doi.org/10.5194/hess-24-4971-2020, https://doi.org/10.5194/hess-24-4971-2020, 2020
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It is still challenging to apply the quantitative and comprehensive global sensitivity analysis method to complex large-scale process-based hydrological models because of variant uncertainty sources and high computational cost. This work developed a new tool and demonstrate its implementation to a pilot example for comprehensive global sensitivity analysis of large-scale hydrological modelling. This method is mathematically rigorous and can be applied to other large-scale hydrological models.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Haifan Liu, Heng Dai, Jie Niu, Bill X. Hu, Han Qiu, Dongwei Gui, Ming Ye, Xingyuan Chen, Chuanhao Wu, Jin Zhang, and William Riley
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-246, https://doi.org/10.5194/hess-2019-246, 2019
Manuscript not accepted for further review
Fushan Wang, Guangheng Ni, William J. Riley, Jinyun Tang, Dejun Zhu, and Ting Sun
Geosci. Model Dev., 12, 2119–2138, https://doi.org/10.5194/gmd-12-2119-2019, https://doi.org/10.5194/gmd-12-2119-2019, 2019
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The current lake model in the Weather Research and Forecasting system was reported to be insufficient in simulating deep lakes and reservoirs. We thus revised the lake model by improving its spatial discretization scheme, surface property parameterization, diffusivity parameterization, and convection scheme. The revised model was evaluated at a deep reservoir in southwestern China and the results were in good agreement with measurements.
Kuang-Yu Chang, William J. Riley, Patrick M. Crill, Robert F. Grant, Virginia I. Rich, and Scott R. Saleska
The Cryosphere, 13, 647–663, https://doi.org/10.5194/tc-13-647-2019, https://doi.org/10.5194/tc-13-647-2019, 2019
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Permafrost peatlands store large amounts of carbon potentially vulnerable to decomposition under changing climate. We estimated effects of climate forcing biases on carbon cycling at a thawing permafrost peatland in subarctic Sweden. Our results indicate that many climate reanalysis products are cold and wet biased in our study region, leading to erroneous active layer depth and carbon budget estimates. Future studies should recognize the effects of climate forcing uncertainty on carbon cycling.
Gautam Bisht, William J. Riley, Glenn E. Hammond, and David M. Lorenzetti
Geosci. Model Dev., 11, 4085–4102, https://doi.org/10.5194/gmd-11-4085-2018, https://doi.org/10.5194/gmd-11-4085-2018, 2018
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Most existing global land surface models used to study impacts of climate change on water resources routinely use different models for near-surface unsaturated soil and the deeper groundwater table. We developed a model that uses a unified treatment of soil hydrologic processes throughout the entire soil column. Using a calibrated drainage parameter, the new model is able to correctly predict deep water table depth as reported in an observationally constrained global dataset.
Xiyan Xu, William J. Riley, Charles D. Koven, and Gensuo Jia
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-257, https://doi.org/10.5194/bg-2018-257, 2018
Preprint withdrawn
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76, https://doi.org/10.5194/gmd-11-61-2018, https://doi.org/10.5194/gmd-11-61-2018, 2018
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The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
Gautam Bisht, Maoyi Huang, Tian Zhou, Xingyuan Chen, Heng Dai, Glenn E. Hammond, William J. Riley, Janelle L. Downs, Ying Liu, and John M. Zachara
Geosci. Model Dev., 10, 4539–4562, https://doi.org/10.5194/gmd-10-4539-2017, https://doi.org/10.5194/gmd-10-4539-2017, 2017
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A fully coupled three-dimensional surface and subsurface land model, CP v1.0, was developed to simulate three-way interactions among river water, groundwater, and land surface processes. The coupled model can be used for improving mechanistic understanding of ecosystem functioning and biogeochemical cycling along river corridors under historical and future hydroclimatic changes. The dataset presented in this study can also serve as a good benchmarking case for testing other integrated models.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Jin-Yun Tang and William J. Riley
Geosci. Model Dev., 10, 3277–3295, https://doi.org/10.5194/gmd-10-3277-2017, https://doi.org/10.5194/gmd-10-3277-2017, 2017
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We proposed the SUPECA kinetics to scale from single biogeochemical reactions to a network of mixed substrates and consumers. The framework for the first time represents single-substrate reactions, two-substrate reactions, and mineral surface sorption reactions in a scaling consistent manner. This new theory is theoretically solid and outperforms existing theories, particularly for substrate-limiting systems. The test with aerobic soil respiration showed its strengths for pragmatic application.
Sina Muster, Kurt Roth, Moritz Langer, Stephan Lange, Fabio Cresto Aleina, Annett Bartsch, Anne Morgenstern, Guido Grosse, Benjamin Jones, A. Britta K. Sannel, Ylva Sjöberg, Frank Günther, Christian Andresen, Alexandra Veremeeva, Prajna R. Lindgren, Frédéric Bouchard, Mark J. Lara, Daniel Fortier, Simon Charbonneau, Tarmo A. Virtanen, Gustaf Hugelius, Juri Palmtag, Matthias B. Siewert, William J. Riley, Charles D. Koven, and Julia Boike
Earth Syst. Sci. Data, 9, 317–348, https://doi.org/10.5194/essd-9-317-2017, https://doi.org/10.5194/essd-9-317-2017, 2017
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Waterbodies are abundant in Arctic permafrost lowlands. Most waterbodies are ponds with a surface area smaller than 100 x 100 m. The Permafrost Region Pond and Lake Database (PeRL) for the first time maps ponds as small as 10 x 10 m. PeRL maps can be used to document changes both by comparing them to historical and future imagery. The distribution of waterbodies in the Arctic is important to know in order to manage resources in the Arctic and to improve climate predictions in the Arctic.
Kathrin M. Keller, Sebastian Lienert, Anil Bozbiyik, Thomas F. Stocker, Olga V. Churakova (Sidorova), David C. Frank, Stefan Klesse, Charles D. Koven, Markus Leuenberger, William J. Riley, Matthias Saurer, Rolf Siegwolf, Rosemarie B. Weigt, and Fortunat Joos
Biogeosciences, 14, 2641–2673, https://doi.org/10.5194/bg-14-2641-2017, https://doi.org/10.5194/bg-14-2641-2017, 2017
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Xiyan Xu, William J. Riley, Charles D. Koven, Dave P. Billesbach, Rachel Y.-W. Chang, Róisín Commane, Eugénie S. Euskirchen, Sean Hartery, Yoshinobu Harazono, Hiroki Iwata, Kyle C. McDonald, Charles E. Miller, Walter C. Oechel, Benjamin Poulter, Naama Raz-Yaseef, Colm Sweeney, Margaret Torn, Steven C. Wofsy, Zhen Zhang, and Donatella Zona
Biogeosciences, 13, 5043–5056, https://doi.org/10.5194/bg-13-5043-2016, https://doi.org/10.5194/bg-13-5043-2016, 2016
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Wetlands are the largest global natural methane source. Peat-rich bogs and fens lying between 50°N and 70°N contribute 10–30% to this source. The predictive capability of the seasonal methane cycle can directly affect the estimation of global methane budget. We present multiscale methane seasonal emission by observations and modeling and find that the uncertainties in predicting the seasonal methane emissions are from the wetland extent, cold-season CH4 production and CH4 transport processes.
Xiaofeng Xu, Fengming Yuan, Paul J. Hanson, Stan D. Wullschleger, Peter E. Thornton, William J. Riley, Xia Song, David E. Graham, Changchun Song, and Hanqin Tian
Biogeosciences, 13, 3735–3755, https://doi.org/10.5194/bg-13-3735-2016, https://doi.org/10.5194/bg-13-3735-2016, 2016
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Accurately projecting future climate change requires a good methane modeling. However, how good the current models are and what are the key improvements needed remain unclear. This paper reviews the 40 published methane models to characterize the strengths and weakness of current methane models and further lay out the roadmap for future model improvements.
Jinyun Tang and William J. Riley
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-233, https://doi.org/10.5194/bg-2016-233, 2016
Preprint retracted
J. Y. Tang and W. J. Riley
Biogeosciences, 13, 723–735, https://doi.org/10.5194/bg-13-723-2016, https://doi.org/10.5194/bg-13-723-2016, 2016
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We present a generic flux-limiting approach to simultaneously handle the availability limitation from many substrates, a problem common in all biogeochemical models. Our approach does not have the ordering problem like a few existing ad hoc approaches, and is straightforward to implement. Our results imply that significant uncertainties could have occurred in many biogeochemical models because of the improper handling of the substrate co-limitation problem.
Q. Zhu, W. J. Riley, J. Tang, and C. D. Koven
Biogeosciences, 13, 341–363, https://doi.org/10.5194/bg-13-341-2016, https://doi.org/10.5194/bg-13-341-2016, 2016
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Here we develop, calibrate, and test a nutrient competition model that accounts for multiple soil nutrients interacting with multiple biotic and abiotic consumers based on enzyme kinetics theory. Our model provides an ecologically consistent representation of nutrient competition appropriate for land biogeochemical models integrated in Earth system models.
C. D. Koven, J. Q. Chambers, K. Georgiou, R. Knox, R. Negron-Juarez, W. J. Riley, V. K. Arora, V. Brovkin, P. Friedlingstein, and C. D. Jones
Biogeosciences, 12, 5211–5228, https://doi.org/10.5194/bg-12-5211-2015, https://doi.org/10.5194/bg-12-5211-2015, 2015
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Terrestrial carbon feedbacks are a large uncertainty in climate change. We separate modeled feedback responses into those governed by changed carbon inputs (productivity) and changed outputs (turnover). The disaggregated responses show that both are important in controlling inter-model uncertainty. Interactions between productivity and turnover are also important, and research must focus on these interactions for more accurate projections of carbon cycle feedbacks.
U. Mishra and W. J. Riley
Biogeosciences, 12, 3993–4004, https://doi.org/10.5194/bg-12-3993-2015, https://doi.org/10.5194/bg-12-3993-2015, 2015
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
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We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
N. J. Bouskill, W. J. Riley, and J. Y. Tang
Biogeosciences, 11, 6969–6983, https://doi.org/10.5194/bg-11-6969-2014, https://doi.org/10.5194/bg-11-6969-2014, 2014
G. Bisht and W. J. Riley
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-12833-2014, https://doi.org/10.5194/hessd-11-12833-2014, 2014
Revised manuscript has not been submitted
G. S. H. Pau, G. Bisht, and W. J. Riley
Geosci. Model Dev., 7, 2091–2105, https://doi.org/10.5194/gmd-7-2091-2014, https://doi.org/10.5194/gmd-7-2091-2014, 2014
J. Y. Tang and W. J. Riley
Biogeosciences, 11, 3721–3728, https://doi.org/10.5194/bg-11-3721-2014, https://doi.org/10.5194/bg-11-3721-2014, 2014
W. J. Riley, F. Maggi, M. Kleber, M. S. Torn, J. Y. Tang, D. Dwivedi, and N. Guerry
Geosci. Model Dev., 7, 1335–1355, https://doi.org/10.5194/gmd-7-1335-2014, https://doi.org/10.5194/gmd-7-1335-2014, 2014
W. J. Riley and C. Shen
Hydrol. Earth Syst. Sci., 18, 2463–2483, https://doi.org/10.5194/hess-18-2463-2014, https://doi.org/10.5194/hess-18-2463-2014, 2014
I. N. Williams, W. J. Riley, M. S. Torn, S. C. Biraud, and M. L. Fischer
Atmos. Chem. Phys., 14, 1571–1585, https://doi.org/10.5194/acp-14-1571-2014, https://doi.org/10.5194/acp-14-1571-2014, 2014
J. Y. Tang and W. J. Riley
Biogeosciences, 10, 8329–8351, https://doi.org/10.5194/bg-10-8329-2013, https://doi.org/10.5194/bg-10-8329-2013, 2013
C. D. Koven, W. J. Riley, Z. M. Subin, J. Y. Tang, M. S. Torn, W. D. Collins, G. B. Bonan, D. M. Lawrence, and S. C. Swenson
Biogeosciences, 10, 7109–7131, https://doi.org/10.5194/bg-10-7109-2013, https://doi.org/10.5194/bg-10-7109-2013, 2013
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
J. H. Shim, H. H. Powers, C. W. Meyer, A. Knohl, T. E. Dawson, W. J. Riley, W. T. Pockman, and N. McDowell
Biogeosciences, 10, 4937–4956, https://doi.org/10.5194/bg-10-4937-2013, https://doi.org/10.5194/bg-10-4937-2013, 2013
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
S. C. Biraud, M. S. Torn, J. R. Smith, C. Sweeney, W. J. Riley, and P. P. Tans
Atmos. Meas. Tech., 6, 751–763, https://doi.org/10.5194/amt-6-751-2013, https://doi.org/10.5194/amt-6-751-2013, 2013
W. J. Riley
Geosci. Model Dev., 6, 345–352, https://doi.org/10.5194/gmd-6-345-2013, https://doi.org/10.5194/gmd-6-345-2013, 2013
J. R. Melton, R. Wania, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, D. J. Beerling, G. Chen, A. V. Eliseev, S. N. Denisov, P. O. Hopcroft, D. P. Lettenmaier, W. J. Riley, J. S. Singarayer, Z. M. Subin, H. Tian, S. Zürcher, V. Brovkin, P. M. van Bodegom, T. Kleinen, Z. C. Yu, and J. O. Kaplan
Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, https://doi.org/10.5194/bg-10-753-2013, 2013
J. Y. Tang, W. J. Riley, C. D. Koven, and Z. M. Subin
Geosci. Model Dev., 6, 127–140, https://doi.org/10.5194/gmd-6-127-2013, https://doi.org/10.5194/gmd-6-127-2013, 2013
Related subject area
Subject: Biogeochemical processes | Techniques and Approaches: Modelling approaches
Groundwater flow paths drive longitudinal patterns of stream dissolved organic carbon (DOC) concentrations in boreal landscapes
Water level variation at a beaver pond significantly impacts net CO2 uptake of a continental bog
A method for predicting hydrogen and oxygen isotope distributions across a region's river network using reach-scale environmental attributes
A new large-scale suspended sediment model and its application over the United States
Hydrological control of dissolved organic carbon dynamics in a rehabilitated Sphagnum-dominated peatland: a water-table based modelling approach
A systematic examination of the relationships between CDOM and DOC in inland waters in China
Effects of mountain tea plantations on nutrient cycling at upstream watersheds
Technical Note: Alternative in-stream denitrification equation for the INCA-N model
A generalized Damköhler number for classifying material processing in hydrological systems
Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem
Soil weathering rates in 21 catchments of the Canadian Shield
Parameterization of a coupled CO2 and H2O gas exchange model at the leaf scale of Populus euphratica
Anna Lupon, Stefan Willem Ploum, Jason Andrew Leach, Lenka Kuglerová, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 27, 613–625, https://doi.org/10.5194/hess-27-613-2023, https://doi.org/10.5194/hess-27-613-2023, 2023
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Discrete riparian inflow points (DRIPs) transport dissolved organic carbon (DOC) from large areas to discrete sections of streams, yet the mechanisms by which DRIPs affect stream DOC concentration, cycling, and export are still unknown. Here, we tested four models that account for different hydrologic and biological representations to show that DRIPs generally reduce DOC exports by either diluting stream DOC (snowmelt period) or promoting aquatic metabolism (summer).
Hongxing He, Tim Moore, Elyn R. Humphreys, Peter M. Lafleur, and Nigel T. Roulet
Hydrol. Earth Syst. Sci., 27, 213–227, https://doi.org/10.5194/hess-27-213-2023, https://doi.org/10.5194/hess-27-213-2023, 2023
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We applied CoupModel to quantify the impacts of natural and human disturbances to adjacent water bodies in regulating net CO2 uptake of northern peatlands. We found that 1 m drops of the water level at the beaver pond lower the peatland water table depth 250 m away by 0.15 m and reduce the peatland net CO2 uptake by 120 g C m-2 yr-1. Therefore, although bogs are ombrotrophic rainfed systems, the boundary hydrological conditions play an important role in regulating water storage and CO2 uptake.
Bruce D. Dudley, Jing Yang, Ude Shankar, and Scott L. Graham
Hydrol. Earth Syst. Sci., 26, 4933–4951, https://doi.org/10.5194/hess-26-4933-2022, https://doi.org/10.5194/hess-26-4933-2022, 2022
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Stable isotope ratios (isotope values) of surface water reflect hydrological pathways, mixing processes, and atmospheric exchange within catchments. We used a water-balance-based mapping method, which represents patterns of surface flow and mixing, and added a regression-based correction step using catchment environmental characteristics to map water isotope ratios across all the rivers of New Zealand.
Hong-Yi Li, Zeli Tan, Hongbo Ma, Zhenduo Zhu, Guta Wakbulcho Abeshu, Senlin Zhu, Sagy Cohen, Tian Zhou, Donghui Xu, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 665–688, https://doi.org/10.5194/hess-26-665-2022, https://doi.org/10.5194/hess-26-665-2022, 2022
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We introduce a new multi-process river sediment module for Earth system models. Application and validation over the contiguous US indicate a satisfactory model performance over large river systems, including those heavily regulated by reservoirs. This new sediment module enables future modeling of the transportation and transformation of carbon and nutrients carried by the fine sediment along the river–ocean continuum to close the global carbon and nutrient cycles.
Léonard Bernard-Jannin, Stéphane Binet, Sébastien Gogo, Fabien Leroy, Christian Défarge, Nevila Jozja, Renata Zocatelli, Laurent Perdereau, and Fatima Laggoun-Défarge
Hydrol. Earth Syst. Sci., 22, 4907–4920, https://doi.org/10.5194/hess-22-4907-2018, https://doi.org/10.5194/hess-22-4907-2018, 2018
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Peatlands are a major stock of carbon that can be released as dissolved organic carbon (DOC), affecting carbon balance and downstream water quality. This study investigates the impact of peatland restoration on water balance and DOC exports using a simple modelling approach. The results suggest that the restoration can affect the water balance and the dynamics of DOC in the peatland. However, there is no major impact in the quantity of DOC released in a short-term period (3 years).
Kaishan Song, Ying Zhao, Zhidan Wen, Chong Fang, and Yingxin Shang
Hydrol. Earth Syst. Sci., 21, 5127–5141, https://doi.org/10.5194/hess-21-5127-2017, https://doi.org/10.5194/hess-21-5127-2017, 2017
T.-C. Lin, P.-J. L. Shaner, L.-J. Wang, Y.-T. Shih, C.-P. Wang, G.-H. Huang, and J.-C. Huang
Hydrol. Earth Syst. Sci., 19, 4493–4504, https://doi.org/10.5194/hess-19-4493-2015, https://doi.org/10.5194/hess-19-4493-2015, 2015
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We summarize our findings as follows: (1) the mountain watersheds are vulnerable to agriculture expansion; (2) proper spatial configuration of agricultural lands in mountain watersheds can mitigate the impact of agriculture on NO3- output by 70%; and (3) the reconstructed element fluxes for the watersheds indicate excessive leaching of N and P, and additional loss of N to the atmosphere via volatilization and denitrification, which likely resulted from excessive fertilizer use.
J. R. Etheridge, F. Birgand, M. R. Burchell II, A. Lepistö, K. Rankinen, and K. Granlund
Hydrol. Earth Syst. Sci., 18, 1467–1473, https://doi.org/10.5194/hess-18-1467-2014, https://doi.org/10.5194/hess-18-1467-2014, 2014
C. E. Oldham, D. E. Farrow, and S. Peiffer
Hydrol. Earth Syst. Sci., 17, 1133–1148, https://doi.org/10.5194/hess-17-1133-2013, https://doi.org/10.5194/hess-17-1133-2013, 2013
S. H. Wu and P.-E. Jansson
Hydrol. Earth Syst. Sci., 17, 735–749, https://doi.org/10.5194/hess-17-735-2013, https://doi.org/10.5194/hess-17-735-2013, 2013
D. Houle, P. Lamoureux, N. Bélanger, M. Bouchard, C. Gagnon, S. Couture, and A. Bouffard
Hydrol. Earth Syst. Sci., 16, 685–697, https://doi.org/10.5194/hess-16-685-2012, https://doi.org/10.5194/hess-16-685-2012, 2012
G. F. Zhu, X. Li, Y. H. Su, and C. L. Huang
Hydrol. Earth Syst. Sci., 14, 419–431, https://doi.org/10.5194/hess-14-419-2010, https://doi.org/10.5194/hess-14-419-2010, 2010
Cited articles
Bachmann, J., Horton, R., Grant, S. A., and van der Ploeg, R. R.: Temperature dependence of water retention curves for wettable and water-repellent soils, Soil Sci. Soc. Am. J., 66, 44–52, 2002.
Barnes, C. J. and Allison, G. B.: Tracing of water-movement in the unsaturated zone using stable isotopes of hydrogen and oxygen, J. Hydrol., 100, 143–176, 1988.
Bear, J.: Dynamics of fluids in porous media, Elsevier, N.Y., 1972.
Beljaars, A. C. M., Viterbo, P., Miller, M. J., and Betts, A. K.: The anomalous rainfall over the United States during July 1993: Sensitivity to land surface parameterization and soil moisture, Mon. Weather Rev., 124, 362–383, 1996.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Bittelli, M., Ventura, F., Campbell, G. S., Snyder, R. L., Gallegati, F., and Pisa, P. R.: Coupling of heat, water vapor, and liquid water fluxes to compute evaporation in bare soils, J. Hydrol., 362, 191–205, https://doi.org/10.1016/J.Jhydrol.2008.08.014, 2008.
Braud, I., Bariac, T., Gaudet, J. P., and Vauclin, M.: SiSPAT-Isotope, a coupled heat, water and stable isotope (HDO and H218O) transport model for bare soil. Part I. Model description and first verifications, J. Hydrol., 309, 277–300, https://doi.org/10.1016/J.Jhydrol.2004.12.013, 2005.
Brutsaert, W.: A model for evaporation as a molecular diffusion process into a turbulent atmosphere, J. Geophys. Res., 70, 5017–5024, https://doi.org/10.1029/JZ070i020p05017, 1965.
Brutsaer, W.: A Model for Evaporation as a Molecular Diffusion Process into a Turbulent Atmosphere, J. Geophys. Res., 70, 5017–5024, 1965.
Budyko, M. I.: Evaporation under natural conditions, GIMIZ, Leningrad, 1948 (English translation Israel Progr. Sci. Transl., Jerusalem, 1963).
Camillo, P. J. and Gurney, R. J.: A resistance parameter for bare-soil evaporation models, Soil Sci., 141, 95–105, 1986.
Campbell, G. S. and Shiozawa S.: Prediction of hydraulic properties of soils using particle size distributions and bulk density data, in: International Workshop on Indirect Methods for Estimating the Hydraulic, Properties of Unsaturated Soils, University of Calif. Press, Berkeley, 1992.
Clapp, R. B. and Hornberger, G. M.: Empirical equations for some soil hydraulic-properties, Water Resour. Res., 14, 601–604, 1978.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A statistical exploration of the relationships of soil-moisture characteristics to the physical-properties of soils, Water Resour. Res., 20, 682–690, 1984.
Daamen, C. C. and Simmonds, L. P.: Measurement of evaporation from bare soil and its estimation using surface resistance, Water Resour. Res., 32, 1393–1402, 1996.
Davidson, E. A., Savage, K. E., Trumbore, S. E., and Borken, W.: Vertical partitioning of CO2 production within a temperate forest soil, Global Change Biol., 12, 944–956, https://doi.org/10.1111/J.1365-2486.2005.01142.X, 2006.
Deardorff, J. W.: Efficient prediction of ground surface-temperature and moisture, with inclusion of a layer of vegetation, J. Geophys. Res.-Atmos., 83, 1889–1903, 1978.
Fang, C. and Moncrieff, J. B.: A model for soil CO2 production and transport 1: Model development, Agr. Forest Meteorol., 95, 225–236, 1999.
Foken, T.: The energy balance closure problem: An overview, Ecol. Appl., 18, 1351–1367, 2008.
Frensch, J. and Steudle, E.: Axial and radial hydraulic resistance to roots of maize (Zea-Mays-L), Plant Physiol., 91, 719–726, 1989.
Gardner, W. R. and Fireman, M.: Laboratory studies of evaporation from soil columns in the presence of a water table, Soil Sci.., 85, 244–249, 1958.
Gerke, H. H.: Preferential flow descriptions for structured soils, J. Plant Nutr. Soil Sci., 169, 382–400, https://doi.org/10.1002/Jpln.200521955, 2006.
Goss, K. U.: Adsorption of organic vapors on ice and quartz sand at temperatures below 0 °C, Environ. Sci. Technol., 27, 2826–2830, https://doi.org/10.1021/Es00049a024, 1993.
Goss, K. U. and Madliger, M.: Estimation of water transport based on in situ measurements of relative humidity and temperature in a dry Tanzanian soil, Water Resour. Res., 43, W05433, https://doi.org/10.1029/2006wr005197, 2007.
Grant, S. A.: Extension of a temperature effects model for capillary pressure saturation relations, Water Resour. Res., 39, 1003, https://doi.org/10.1029/2000wr000193, 2003.
Green, P. J.: Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, 82, 711–732, 1995.
Grifoll, J., Gasto, J. M., and Cohen, Y.: Non-isothermal soil water transport and evaporation, Adv. Water Resour., 28, 1254–1266, https://doi.org/10.1016/J.Advwatres.2005.04.008, 2005.
Gut, A., Scheibe, M., Rottenberger, S., Rummel, U., Welling, M., Ammann, C., Kirkman, G. A., Kuhn, U., Meixner, F. X., Kesselmeier, J., Lehmann, B. E., Schmidt, W., Muller, E., and Piedade, M. T. F.: Exchange fluxes of NO2 and O3 at soil and leaf surfaces in an Amazonian rain forest, J. Geophys. Res.-Atmos., 107, 8060, https://doi.org/10.1029/2001jd000654, 2002.
Hanks, R. J., Gardner, H. R., and Fairbour.Ml: Evaporation of water from soils as influenced by drying with wind or radiation, Soil Sci. Soc. Am. Pro., 31, 593–598, 1967.
Heideger, W. J. and Boudart, M.: Interfacial resistance to evaporation, Chem. Eng. Sci., 17, 1–10, 1962.
Huntington, T. G.: Evidence for intensification of the global water cycle: Review and synthesis, J. Hydrol., 319, 83–95, https://doi.org/10.1016/J.Jhydrol.2005.07.003, 2006.
Insam, H. and Seewald, M. S. A.: Volatile organic compounds (VOCs) in soils, Biol. Fert. Soils, 46, 199–213, https://doi.org/10.1007/S00374-010-0442-3, 2010.
Jacobs, A. F. G., Heusinkveld, B. G., and Berkowicz, S. M.: Force-restore technique for ground surface temperature and moisture content in a dry desert system, Water Resour. Res., 36, 1261–1268, 2000.
Jamet, D., Chandesris, M., and Goyeau, B.: On the equivalence of the discontinuous one- and two-domain approaches for the modeling of transport phenomena at a fluid/porous interface, Transport Porous. Med., 78, 403–418, https://doi.org/10.1007/S11242-008-9314-9, 2009.
Jia, Y. W., Ni, G. H., Kawahara, Y., and Suetsugi, T.: Development of WEP model and its application to an urban watershed, Hydrol. Process., 15, 2175–2194, 2001.
Johnson, M. T.: A numerical scheme to calculate temperature and salinity dependent air-water transfer velocities for any gas, Ocean Sci., 6, 913–932, https://doi.org/10.5194/os-6-913-2010, 2010.
Jury, W. A., Russo, D., Streile, G., and Elabd, H.: Evaluation of volatilization by organic-chemicals residing below the soil surface, Water Resour. Res., 26, 13–20, 1990.
Katata, G., Nagai, H., Ueda, H., Agam, N., and Berliner, P. R.: Development of a land surface model including evaporation and adsorption processes in the soil for the land-air exchange in arid regions, J. Hydrometeorol., 8, 1307–1324, https://doi.org/10.1175/2007jhm829.1, 2007.
Kirkman, G. A., Gut, A., Ammann, C., Gatti, L. V., Cordova, A. M., Moura, M. A. L., Andreae, M. O., and Meixner, F. X.: Surface exchange of nitric oxide, nitrogen dioxide, and ozone at a cattle pasture in Rondonia, Brazil, J. Geophys. Res.-Atmos., 107, 8083, https://doi.org/10.1029/2001jd000523, 2002.
Komatsu, T. S.: Toward a robust phenomenological expression of evaporation efficiency for unsaturated soil surfaces, J. Appl. Meteorol, 42, 1330–1334, 2003.
Kondo, J. and Saigusa, N.: Modeling the evaporation from bare soil with a formula for vaporization in the soil pores, J. Meteorol. Soc. Jpn, 72, 413–421, 1994.
Kondo, J., Saigusa, N., and Sato, T.: A parameterization of evaporation from bare soil surfaces, J. Appl. Meteorol., 29, 385–389, 1990.
Kondo, J., Saigusa, N., and Sato, T.: A model and experimental-study of evaporation from bare-soil surfaces, J. Appl. Meteorol., 31, 304–312, 1992.
Koster, R. D., Dirmeyer, P. A., Guo, Z. C., Bonan, G., Chan, E., Cox, P., Gordon, C. T., Kanae, S., Kowalczyk, E., Lawrence, D., Liu, P., Lu, C. H., Malyshev, S., McAvaney, B., Mitchell, K., Mocko, D., Oki, T., Oleson, K., Pitman, A., Sud, Y. C., Taylor, C. M., Verseghy, D., Vasic, R., Xue, Y. K., Yamada, T., and Team, G.: Regions of strong coupling between soil moisture and precipitation, Science, 305, 1138–1140, 2004.
Lawrence, D. M., Oleson, K. W., Flanner, M. G., Thornton, P. E., Swenson, S. C., Lawrence, P. J., Zeng, X. B., Yang, Z. L., Levis, S., Sakaguchi, K., Bonan, G. B., and Slater, A. G.: Parameterization improvements and functional and structural advances in version 4 of the Community Land Model, J. Adv. Model. Earth Syst., 3, M03001, https://doi.org/10.1029/2011ms000045, 2011.
Lebeau, M. and Konrad, J. M.: A new capillary and thin film flow model for predicting the hydraulic conductivity of unsaturated porous media, Water Resour. Res., 46, W12554, https://doi.org/10.1029/2010wr009092, 2010.
Lebeau, M. and Konrad, J. M.: An extension of the capillary and thin film flow model for predicting the hydraulic conductivity of air-free frozen porous media, Water Resour. Res., 48, W07523, https://doi.org/10.1029/2012WR011916, 2012.
Lee, T. J. and Pielke, R. A.: Estimating the soil surface specific-humidity, J. Appl. Meteorol., 31, 480–484, 1992.
Lefer, B. L., Talbot, R. W., and Munger, J. W.: Nitric acid and ammonia at a rural northeastern US site, J. Geophys. Res.-Atmos., 104, 1645–1661, 1999.
Lehmann, P., Assouline, S., and Or, D.: Characteristic lengths affecting evaporative drying of porous media, Phys. Rev. E, 77, 056309, https://doi.org/10.1103/Physreve.77.056309, 2008.
Leighly, J.: A note on evaporation, Ecology, 18, 180–198, 1937.
Lemon, E. R.: The potentialities for decreasing soil moisture evaporation loss, Soil Sci. Soc. Am. J., 20, 120–125, https://doi.org/10.2136/sssaj1956.03615995002000010031x, 1956.
Li, C. S., Aber, J., Stange, F., Butterbach-Bahl, K., and Papen, H.: A process-oriented model of N2O and NO emissions from forest soils: 1. Model development, J. Geophys. Res.-Atmos., 105, 4369–4384, 2000.
Liss, P. S.: Processes of gas-exchange across an air-water interface, Deep-Sea Res., 20, 221–238, 1973.
Liss, P. S. and Slater, P. G.: Flux of gases across air-sea interface, Nature, 247, 181–184, 1974.
Mathieu, R. and Bariac, T.: A numerical model for the simulation of stable isotope profiles in drying soils, J. Geophys. Res.-Atmos., 101, 12685–12696, 1996.
Merlin, O., Al Bitar, A., Rivalland, V., Beziat, P., Ceschia, E., and Dedieu, G.: An analytical model of evaporation efficiency for unsaturated soil surfaces with an arbitrary thickness, J. Appl. Meteorol. Climatol., 50, 457–471, https://doi.org/10.1175/2010jamc2418.1, 2011.
Miller, J. B., Yakir, D., White, J. W. C., and Tans, P. P.: Measurement of 18O/16O in the soil-atmosphere CO2 flux, Global Biogeochem. Cy., 13, 761–774, 1999.
Milly, P. C. D.: Moisture and heat-transport in hysteretic, inhomogeneous porous-media - a matric head-based formulation and a numerical-model, Water Resour. Res., 18, 489–498, 1982.
Moldrup, P., Olesen, T., Komatsu, T., Yoshikawa, S., Schjonning, P., and Rolston, D. E.: Modeling diffusion and reaction in soils: X. A unifying model for solute and gas diffusivity in unsaturated soil, Soil Sci., 168, 321–337, https://doi.org/10.1097/00010694-200305000-00002, 2003.
Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D. E.: Three-porosity model for predicting the gas diffusion coefficient in undisturbed soil, Soil Sci. Soc. Am. J., 68, 750–759, 2004.
Montgomery, R. B.: Viscosity and thermal conductivity of air and diffusivity of water vapor in air, J. Meteorol., 4, 193–196, 1947.
Mosthaf, K., Baber, K., Flemisch, B., Helmig, R., Leijnse, A., Rybak, I., and Wohlmuth, B.: A coupling concept for two-phase compositional porous-medium and single-phase compositional free flow, Water Resour. Res., 47, W10522, https://doi.org/10.1029/2011wr010685, 2011.
Nassar, I. N. and Horton, R.: Transport and fate of volatile organic chemicals in unsaturated, nonisothermal, salty porous media: 1. Theoretical development, J. Hazard. Mater., 69, 151–167, 1999.
Novak, M. D.: Dynamics of the near-surface evaporation zone and corresponding effects on the surface energy balance of a drying bare soil, Agr. Forest Meteorol., 150, 1358–1365, https://doi.org/10.1016/J.Agrformet.2010.06.005, 2010.
Novak, M. D.: Comment on "Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium and nonequilibrium based approaches," by Kathleen M. Smits, Abdullah Cihan, Toshihiro Sakaki, and Tissa H. Illangasekare, Water Resour. Res., 48, W05549, https://doi.org/10.1029/2011wr011393, 2012.
Oberbauer, S. F., Tweedie, C. E., Welker, J. M., Fahnestock, J. T., Henry, G. H. R., Webber, P. J., Hollister, R. D., Walker, M. D., Kuchy, A., Elmore, E., and Starr, G.: Tundra CO2 fluxes in response to experimental warming across latitudinal and moisture gradients, Ecol. Monogr., 77, 221–238, 2007.
Oleson, K. W., Niu, G. Y., Yang, Z. L., Lawrence, D. M., Thornton, P. E., Lawrence, P. J., Stockli, R., Dickinson, R. E., Bonan, G. B., Levis, S., Dai, A., and Qian, T.: Improvements to the Community Land Model and their impact on the hydrological cycle, J. Geophys. Res.-Biogeo., 113, G01021, https://doi.org/10.1029/2007jg000563, 2008.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., DIckinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J. F., Mahowald, N., Niu, G. Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stockli, R., Wang, A., Yang, Z. L., Zeng, X., and Zeng, X.: Technical description of version 4.0 of the Community Land Model. NCAR Tech. Note NCAR/TN-478+STR, 257 pp., 2010.
Pan, H. L. and Mahrt, L.: Interaction between soil hydrology and boundary-layer development, Bound.-Lay. Meteorol., 38, 185–202, 1987.
Pastor, J. and Post, W. M.: Influence of climate, soil-moisture, and succession on forest carbon and nitrogen cycles, Biogeochem., 2, 3–27, 1986.
Philip, J. R.: Evaporation, and moisture and heat fields in the soil, J. Meteorol., 14, 354–366, 1957.
Pietikainen, J., Vaijarvi, E., Ilvesniemi, H., Fritze, H., and Westman, C. J.: Carbon storage of microbes and roots and the flux of CO2 across a moisture gradient, Can. J. Forest Res., 29, 1197–1203, 1999.
Prat, M.: Recent advances in pore-scale models for drying of porous media, Chem. Eng. J., 86, 153–164, 2002.
Qiu, G. Y., Momii, K., Yano, T., and Lascano, R. J.: Experimental, verification of a mechanistic model to partition evapotranspiration into soil water and plant evaporation, Agr. Forest Meteorol., 93, 79–93, 1999.
Reichman, R., Yates, S. R., Skaggs, T. H., and Rolston, D. E.: Effects of soil moisture on the diurnal pattern of pesticide emission: Numerical simulation and sensitivity analysis, Atmos. Environ., 66, 41–51, https://doi.org/10.1016/j.atmosenv.2012.10.002, 2013.
Riley, W. J., Still, C. J., Torn, M. S., and Berry, J. A.: A mechanistic model of H218O and CO18O fluxes between ecosystems and the atmosphere: Model description and sensitivity analyses, Global Biogeochem. Cy., 16, 1095, https://doi.org/10.1029/2002gb001878, 2002.
Riley, W. J., Subin, Z. M., Lawrence, D. M., Swenson, S. C., Torn, M. S., Meng, L., Mahowald, N. M., and Hess, P.: Barriers to predicting changes in global terrestrial methane fluxes: analyses using CLM4Me, a methane biogeochemistry model integrated in CESM, Biogeosciences, 8, 1925–1953, https://doi.org/10.5194/bg-8-1925-2011, 2011.
Ritchie, J. T.: Model for predicting evaporation from a row crop with incomplete cover, Water Resour. Res., 8, 1204–1213, 1972.
Roderick, M. L., Hobbins, M. T., and Farquhar, G. D.: Pan evaporation trends and the terrestrial water balance. II. Energy balance and interpretation, Geogr. Compass, 3, 761–780, https://doi.org/10.1111/j.1749-8198.2008.00214.x, 2009.
Rose, D. A.: Water movement in porous materials: Part 1 – Isothermal vapour transfer, Br. J. Appl. Phys., 14, 256–262, 1963.
Ruiz, J., Bilbao, R., and Murillo, M. B.: Adsorption of different VOC onto soil minerals from gas phase: Influence of mineral, type of VOC, and air humidity, Environ. Sci. Technol., 32, 1079–1084, https://doi.org/10.1021/Es9704996, 1998.
Saito, H., Simunek, J., and Mohanty, B. P.: Numerical analysis of coupled water, vapor, and heat transport in the vadose zone, Vadose Zone J., 5, 784–800, https://doi.org/10.2136/Vzj2006.0007, 2006.
Sakaguchi, K. and Zeng, X. B.: Effects of soil wetness, plant litter, and under-canopy atmospheric stability on ground evaporation in the Community Land Model (CLM3.5), J. Geophys. Res.-Atmos., 114, D01107, https://doi.org/10.1029/2008jd010834, 2009.
Salvucci, G. D.: Soil and moisture independent estimation of stage-two evaporation from potential evaporation and albedo or surface temperature, Water Resour. Res., 33, 111–122, 1997.
Salvucci, G. D. and Entekhabi, D.: Equivalent steady soil-moisture profile and the time compression approximation in water-balance modeling, Water Resour. Res., 30, 2737–2749, 1994.
Saravanapavan, T. and Salvucci, G. D.: Analysis of rate-limiting processes in soil evaporation with implications for soil resistance models, Adv. Water Resour., 23, 493–502, 2000.
Schaap, M. G. and Bouten, W.: Forest floor evaporation in a dense Douglas fir stand, J. Hydrol., 193, 97–113, 1997.
Sellers, P. J., Heiser, M. D., and Hall, F. G.: Relations between surface conductance and spectral vegetation indexes at intermediate (100 m2 to 15 km$^{2})$ length scales, J. Geophys. Res.-Atmos., 97, 19033–19059, 1992.
Shahraeeni, E. and Or, D.: Pore-scale analysis of evaporation and condensation dynamics in porous media, Langmuir, 26, 13924–13936, https://doi.org/10.1021/La101596y, 2010.
Shahraeeni, E. and Or, D.: Pore scale mechanisms for enhanced vapor transport through partially saturated porous media, Water Resour. Res., 48, W05511, https://doi.org/10.1029/2011wr011036, 2012.
Shahraeeni, E., Lehmann P., and Or, D.: Coupling of evaporative fluxes from drying porous surfaces with air boundary layer: Characteristics of evaporation from discrete pores, Water Resour. Res., 48, W09525, https://doi.org/10.1029/2012WR011857, 2012.
Shao, Y. P. and Irannejad, P.: On the choice of soil hydraulic models in land-surface schemes, Bound.-Lay. Meteorol., 90, 83–115, 1999.
Shaw, T. M.: Drying as an immiscible displacement process with fluid counterflow, Phys. Rev. Lett., 59, 1671–1674, 1987.
Shavit, U.: Special Issue on "Transport Phenomena at the Interface Between Fluid and Porous Domains", Transport Porous Med., 78, 327–330, https://doi.org/10.1007/S11242-009-9414-1, 2009.
Shokri, N., Lehmann, P., Vontobel, P., and Or, D.: Drying front and water content dynamics during evaporation from sand delineated by neutron radiography, Water Resour. Res., 44, W06418, https://doi.org/10.1029/2007wr006385, 2008.
Shokri, N., Lehmann, P., and Or, D.: Critical evaluation of enhancement factors for vapor transport through unsaturated porous media, Water Resour. Res., 45, W10433, https://doi.org/10.1029/2009wr007769, 2009.
Shokri, N. and Or, D.: What determines drying rates at the onset of diffusion controlled stage-2 evaporation from porous media? Water Resour. Res., 47, W09513, https://doi.org/10.1029/2010wr010284, 2011.
Silva, O. and Grifoll, J.: A soil-water retention function that includes the hyper-dry region through the BET adsorption isotherm, Water Resour. Res., 43, W11420, https://doi.org/10.1029/2006wr005325, 2007.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Ny\'iri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, \'A., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Smits, K. M., Cihan, A., Sakaki, T., and Illangasekare, T. H.: Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium- and nonequilibrium-based approaches, Water Resour. Res., 47, W05540, https://doi.org/10.1029/2010wr009533, 2011.
Smits, K. M., Cihan, A., Ngo, V. V., and Illangasekare, T. H.: Reply to comment by Michael D. Novak on "Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium and nonequilibrium based approaches", Water Resour. Res., 48, W05550, https://doi.org/10.1029/2011wr011609, 2012.
Stockli, R., Lawrence, D. M., Niu, G. Y., Oleson, K. W., Thornton, P. E., Yang, Z. L., Bonan, G. B., Denning, A. S., and Running, S. W.: Use of FLUXNET in the community land model development, J. Geophys. Res.-Biogeo., 113, G01025, https://doi.org/10.1029/2007jg000562, 2008.
Su, H., Cheng, Y. F., Oswald, R., Behrendt, T., Trebs, I., Meixner, F. X., Andreae, M. O., Cheng, P., Zhang, Y., and Poschl, U.: Soil nitrite as a source of atmospheric HONO and OH radicals, Science, 333, 1616–1618, https://doi.org/10.1126/Science.1207687, 2011.
Suleiman, A. A. and Ritchie, J. T.: Modeling soil water redistribution during second-stage evaporation, Soil Sci. Soc. Am. J., 67, 377–386, 2003.
Sun, S. F.: Moisture and heat transport in a soil layer forced by atmospheric conditions, M.Sc. thesis, University of Connecticut, 1982.
Tang, J. Y. and Zhuang, Q.: Equifinality in parameterization of process-based biogeochemistry models: A significant uncertainty source to the estimation of regional carbon dynamics, J. Geophys. Res., 113, G04010, https://doi.org/10.1029/2008JG000757, 2008.
Tang, J. Y., Zhuang, Q., Shannon, R. D., and White, J. R.: Quantifying wetland methane emissions with process-based models of different complexities, Biogeosciences, 7, 3817–3837, https://doi.org/10.5194/bg-7-3817-2010, 2010.
Tang, J. Y., Riley, W. J., Koven, C. D., and Subin, Z. M.: CLM4-BeTR, a generic biogeochemical transport and reaction module for CLM4: model development, evaluation, and application, Geosci. Model Dev., 6, 127–140, https://doi.org/10.5194/gmd-6-127-2013, 2013.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experiment design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/Bams-D-11-00094.1, 2012.
Tokunaga, T. K.: Hydraulic properties of adsorbed water films in unsaturated porous media, Water Resour. Res., 45, AW06415, https://doi.org/10.1029/2009wr007734, 2009.
Tuller, M. and Or, D.: Hydraulic conductivity of variably saturated porous media: Film and corner flow in angular pore space, Water Resour. Res., 37, 1257–1276, 2001.
van de Griend, A. A. and Owe, M.: Bare soil surface-resistance to evaporation by vapor diffusion under semiarid conditions, Water Resour. Res., 30, 181–188, 1994.
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Walko, R. L., Band, L. E., Baron, J., Kittel, T. G. F., Lammers, R., Lee, T. J., Ojima, D., Pielke, R. A., Taylor, C., Tague, C., Tremback, C. J., and Vidale, P. L.: Coupled atmosphere-biophysics-hydrology models for environmental modeling, J. Appl. Meteorol., 39, 931–944, 2000.
Walter, B. P. and Heimann, M.: A process-based, climate-sensitive model to derive methane emissions from natural wetlands: Application to five wetland sites, sensitivity to model parameters, and climate, Global Biogeochem. Cy., 14, 745–765, 2000.
Xiu, A. J. and Pleim, J. E.: Development of a land surface model. Part I: Application in a mesoscale meteorological model, J. Appl. Meteorol., 40, 192–209, 2001.
Yamanaka, T. and Yonetani, T.: Dynamics of the evaporation zone in dry sandy soils, J. Hydrol., 217, 135–148, 1999.
Yamanaka, T., Takeda, A., and Sugita, F.: A modified surface-resistance approach for representing bare-soil evaporation: Wind tunnel experiments under various atmospheric conditions, Water Resour. Res., 33, 2117–2128, 1997.
Yashiro, H., Sudo, K., Yonemura, S., and Takigawa, M.: The impact of soil uptake on the global distribution of molecular hydrogen: chemical transport model simulation, Atmos. Chem. Phys., 11, 6701–6719, https://doi.org/10.5194/acp-11-6701-2011, 2011.
Yeh, G. T. and Tripathi, V. S.: A model for simulating transport of reactive multispecies components – model development and demonstration, Water Resour. Res., 27, 3075–3094, 1991.
Zeng, X. B., Zhao, M., and Dickinson, R. E.: Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO data, J. Climate, 11, 2628–2644, 1998.
Zhuang, Q., Melillo, J. M., Kicklighter, D. W., Prinn, R. G., McGuire, A. D., Steudler, P. A., Felzer, B. S., and Hu, S.: Methane fluxes between terrestrial ecosystems and the atmosphere at northern high latitudes during the past century: A retrospective analysis with a process-based biogeochemistry model, Global Biogeochem. Cy., 18, Gb3010, https://doi.org/10.1029/2004gb002239, 2004.
