Articles | Volume 18, issue 13
https://doi.org/10.5194/bg-18-4211-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-4211-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2021
Research article |
| 14 Jul 2021
| 14 Jul 2021
An improved process-oriented hydro-biogeochemical model for simulating dynamic fluxes of methane and nitrous oxide in alpine ecosystems with seasonally frozen soils
Wei Zhang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Zhisheng Yao
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Siqi Li
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Xunhua Zheng
CORRESPONDING AUTHOR
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
College of Earth and Planetary Sciences, University of the Chinese Academy
of Sciences, Beijing 100049, P. R. China
Han Zhang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
School of Geographic and Environmental Sciences, Tianjin Normal
University, Tianjin 300387, P. R. China
Lei Ma
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Institute of Meteorology and Climate Research, Atmospheric
Environmental Research (IMK-IFU), Karlsruhe Institute of Technology,
Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany
Kai Wang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Rui Wang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Chunyan Liu
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Shenghui Han
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Jia Deng
Complex Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, 39 College Road, Durham, NH
03824, USA
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, P. R. China
Related authors
Wei Zhang, Xunhua Zheng, Siqi Li, Shenghui Han, Chunyan Liu, Zhisheng Yao, Rui Wang, Kai Wang, Xiao Chen, Guirui Yu, Zhi Chen, Jiabing Wu, Huimin Wang, Junhua Yan, and Yong Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-141, https://doi.org/10.5194/gmd-2024-141, 2024
Revised manuscript not accepted
Short summary
Short summary
Process-oriented biogeochemical models are promising tools for estimating the carbon fluxes of forest ecosystems. In this study, the hydro-biogeochemical model of CNMM-DNDC was improved by incorporating a new forest growth module derived from the Biome-BGC. The updated model was validated using the multiple-year observed carbon fluxes and showed better performance in capturing the daily dynamics and annual variations. The sensitive eco-physiological parameters were also identified.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
Short summary
Short summary
Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Siqi Li, Wei Zhang, Xunhua Zheng, Yong Li, Shenghui Han, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, and Chong Zhang
Biogeosciences, 19, 3001–3019, https://doi.org/10.5194/bg-19-3001-2022, https://doi.org/10.5194/bg-19-3001-2022, 2022
Short summary
Short summary
The CNMM–DNDC model was modified to simulate ammonia volatilization (AV) from croplands. AV from cultivated uplands followed the first-order kinetics, which was jointly regulated by the factors of soil properties and meteorological conditions. AV simulation from rice paddy fields was improved by incorporating Jayaweera–Mikkelsen mechanisms. The modified model performed well in simulating the observed cumulative AV measured from 63 fertilization events in China.
Xiao Bai, Tom Cripps, João Serra, Klaus Butterbach-Bahl, and Zhisheng Yao
EGUsphere, https://doi.org/10.5194/egusphere-2025-5091, https://doi.org/10.5194/egusphere-2025-5091, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
This study examines the spatiotemporal variability of soil CH4, N2O and CO2 fluxes based on measurements across 56 spatial sites in an urban park. Our results show that soils in urban greenspaces function as sources of N2O and weak sinks of CH4. We developed random forest models to predict the probability of hot and cold spots of gas fluxes. Our study offers valuable insights into scaling gas fluxes in urban greenspaces, enabling a better assessment of how urbanization affects landscape fluxes.
Haoyuan Chen, Tao Song, Xiaodong Chen, Yinghong Wang, Mengtian Cheng, Kai Wang, Fuxin Liu, Baoxian Liu, Guiqian Tang, and Yuesi Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3931, https://doi.org/10.5194/egusphere-2024-3931, 2025
Short summary
Short summary
The methane leakage from natural gas may offset the reduced CO2 emissions from its combustion, To quantify its effect, we established the flux observation platform in the urban area of Beijing, the results showed that natural gas has become a common source of both after the transformation of energy structure, the natural gas could escape during storage and use. Although the natural gas leakage rate is not high (1.12 %), the greenhouse effect caused by natural gas leakage can not be ignored.
Wei Zhang, Xunhua Zheng, Siqi Li, Shenghui Han, Chunyan Liu, Zhisheng Yao, Rui Wang, Kai Wang, Xiao Chen, Guirui Yu, Zhi Chen, Jiabing Wu, Huimin Wang, Junhua Yan, and Yong Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-141, https://doi.org/10.5194/gmd-2024-141, 2024
Revised manuscript not accepted
Short summary
Short summary
Process-oriented biogeochemical models are promising tools for estimating the carbon fluxes of forest ecosystems. In this study, the hydro-biogeochemical model of CNMM-DNDC was improved by incorporating a new forest growth module derived from the Biome-BGC. The updated model was validated using the multiple-year observed carbon fluxes and showed better performance in capturing the daily dynamics and annual variations. The sensitive eco-physiological parameters were also identified.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
Short summary
Short summary
Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Siqi Li, Wei Zhang, Xunhua Zheng, Yong Li, Shenghui Han, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, and Chong Zhang
Biogeosciences, 19, 3001–3019, https://doi.org/10.5194/bg-19-3001-2022, https://doi.org/10.5194/bg-19-3001-2022, 2022
Short summary
Short summary
The CNMM–DNDC model was modified to simulate ammonia volatilization (AV) from croplands. AV from cultivated uplands followed the first-order kinetics, which was jointly regulated by the factors of soil properties and meteorological conditions. AV simulation from rice paddy fields was improved by incorporating Jayaweera–Mikkelsen mechanisms. The modified model performed well in simulating the observed cumulative AV measured from 63 fertilization events in China.
Cited articles
Bechmann, M.: Long-term monitoring of nitrogen in surface and
subsurface runoff from small agricultural dominated catchments in Norway,
Agr. Ecosyst. Environ., 198, 13–24, 2014.
Bosch, N., Allan, J., Dolan, D., Han, H., and Richards, R.: Application of
the Soil and Water Assessment Tool for six watersheds of Lake Erie: Model
parameterization and calibration, J. Great Lakes Res., 37, 263–271, 2011.
Breuer, L., VachÉ, K., Julich, S., and Frede, H.: Current concepts in
nitrogen dynamics for mesoscale catchments, Hydrol. Sci. J.,
53, 1059–1074, 2010.
Canfield, D., Glazer, A., and Falkowski, P.: The evolution and future of
Earth's nitrogen cycle, Science, 330, 192–196, 2010.
Castellano, M., Lewis, D., and Kaye, J.: Response of soil nitrogen
retention to the interactive effects of soil texture, hydrology, and organic
matter, J. Geophys. Res.-Biogeo., 118, 280–290, 2013.
Chen, D., Li, Y., Grace, P., and Mosier, A.: N2O emissions from
agricultural lands: a synthesis of simulation approaches, Plant Soil, 309,
169–189, 2008.
Cheng, K., Ogle, S., Parton, W., and Pan, G.: Simulating greenhouse gas
mitigation potentials for Chinese Croplands using the DAYCENT ecosystem
model, Glob. Change Biol., 20, 948–962, 2014.
Collatz, G., Ribas-Carbo, M., and Berry, J.: Coupled
photosynthesis-stomatal conductance model for leaves of C4 plants,
Aust. J. Plant Physiol., 19, 519–538, 1992.
Collins, A., Zhang, Y., Winter, M., Inman, A., Jones, J., Johnes, P.,
Cleasby, W., Vrain, E., Lovett, A., and Noble, L.: Tackling agricultural
diffuse pollution: What might uptake of farmer-preferred measures deliver
for emissions to water and air?, Sci. Total Environ., 547, 269–281, 2016.
Congreves, K., Grant, B., Dutta, B., Smith, W., Chantigny, M., Rochette,
and Desjardins, R.: Prediction ammonia volatilization after field
application of swine slurry: DNDC model development, Agr. Ecosyst.
Environ., 219, 179–189, 2016.
Cui, F., Zheng, X., Liu, C., Wang, K., Zhou, Z., and Deng, J.: Assessing biogeochemical effects and best management practice for a wheat–maize cropping system using the DNDC model, Biogeosciences, 11, 91–107, https://doi.org/10.5194/bg-11-91-2014, 2014.
Cui, Z., Zhang, H., Chen, X., Zhang, C., Ma, W., Huang, C., Zhang, W., Mi,
G., Miao, Y., Li, X., Gao, Q., Yang, J., Wang, Z., Ye, Y., Guo, S., Lu, J.,
Huang, J., Lv, S., Sun, Y., Liu, Y., Peng, X., Ren, J., Li, S., Deng, X.,
Shi, X., Zhang, Q., Yang, Z., Tang, L., Wei, C., Jia, L., Zhang, J., He, M.,
Tong, Y., Tang, Q., Zhong, X., Liu, Z., Cao, N., Kou, C., Ying, H., Yin, Y.,
Jiao, X., Zhang, Q., Fan, M., Jiang, R., Zhang, F., and Dou, Z.: Pursuing
sustainable productivity with millions of smallholder farmers, Nature, 555,
363–366, 2018.
Cuo, L., Zhang, Y., Bohn, T., Zhao, L., Li, J., Liu, Q., and Zhou, B.:
Frozen soil degradation and its effects on surface hydrology in the northern
Tibetan Plateau, J. Geophys. Res.-Atmos., 120, 8276-8298, 2015.
de Bruijn, A.M.G., Butterbach-Bahl, K., Blagodatsky, S., and Grote, R.:
Model evaluation of different mechanisms driving freeze–thaw N2O
emissions, Agr. Ecosyst. Environ., 133, 196–207, 2009.
Deng, J., Li, C., Frolking, S., Zhang, Y., Bäckstrand, K., and Crill, P.: Assessing effects of permafrost thaw on C fluxes based on multiyear modeling across a permafrost thaw gradient at Stordalen, Sweden, Biogeosciences, 11, 4753–4770, https://doi.org/10.5194/bg-11-4753-2014, 2014.
Dong, Z., Hu, G., Yan, C., Wang, W., and Lu, J.: Aeolian desertification
and its causes in the Zoige Plateau of China's Qinghai–Tibetan Plateau,
Environ. Earth Sci., 59, 1731–1740, 2010.
Dubache, G., Li, S., Zheng, X., Zhang, W., and Deng, J.: Modeling ammonia
volatilization following urea application to winter cereal fields in the
United Kingdom by improving a biogeochemical model, Sci. Total Environ., 660,
1403–1418, 2019.
Farquhar, G., Caemmerer, S., and Berry, J.: A biochemical model of
photosynthetic CO2 assimilation in leaves of C3 species, Planta,
149, 78–90, 1980.
Fenner, N. and Freeman, C.: Drought-induced carbon loss in peatlands,
Nat. Geosci., 4, 895–900, 2011.
Foereid, B., Barthram, G., and Marriott, C.: The CENTURY model failed to
simulate soil organic matter development in an acidic grassland, Nutr. Cycl.
Agroecosyst., 78, 143–153, 2007.
Ford, T. W., Harris, E., and Quiring, S. M.: Estimating root zone soil moisture using near-surface observations from SMOS, Hydrol. Earth Syst. Sci., 18, 139–154, https://doi.org/10.5194/hess-18-139-2014, 2014.
Galloway, J., Dentenerd, F., Capone, D., Boyer, E., Howarth, R., Seitzinger,
S., Asner, G., Cleveland, C., Green, P., Holland, E., Karl, D., Michaels,
A., Porter, J., Townsend, A., and Vorosmarty, C.: Nitrogen Cycles: past,
present, and future, Biogeochemistry, 70, 153–226, 2004.
Galloway, J., Townsend, A., Erisman, J., Bekunda, M., Cai, Z., Freney, J.,
Martinelli, L., Seitzinger, S., and Sutton, M.: Transformation of the
nitrogen cycle: recent trends, questions, and potential solutions, Science,
320, 889–892, 2008.
Giltrap, D.L., Li, C., and Saggar, S.: DNDC: A process-based model of
greenhouse gas fluxes from agricultural soils, Agr. Ecosyst. Environ., 136,
292–300, 2010.
Gong, Y., Wu, J., Vogt, J., and Ma, W.: Greenhouse gas emissions from
peatlands under manipulated warming, nitrogen addition, and vegetation
composition change: a review and data synthesis, Environ. Rev., 28, 428–437, 2020.
Haas, E., Klatt, S., Fröhlich, A., Kraft, P., Werner, C., Kiese, R.,
Grote, R., Breuer, L., and Butterbach-Bahl, K.: LandscapeDNDC: a process
model for simulation of biosphere–atmosphere–hydrosphere exchange
processes at site and regional scale, Landsc. Ecol., 28, 615–636, 2012.
Hatano, R.: Impact of land use change on greenhouse gases emissions in
peatland: a review, Int. Agrophys., 33, 167–173, 2019.
Holzworth, D., Huth, N., deVoil, P., Zurcher, E., Herrmann, N., McLean, G.,
Chenu, K., van Oosterom, E., Snow, V., Murphy, C., Moore, A., Brown, H.,
Whish, J., Verrall, S., Fainges, J., Bell, L., Peake, A., Poulton, P.,
Hochman, Z., Thorburn, P., Gaydon, D., Dalgliesh, N., Rodriguez, D., Cox,
H., Chapman, S., Doherty, A., Teixeira, E., Sharp, J., Cichota, R., Vogeler,
I., Li, F., Wang, E., Hammer, G., Robertson, M., Dimes, J., Whitbread, A.,
Hunt, J., van Rees, H., McClelland, T., Carberry, P., Hargreaves, J.,
MacLeod, N., McDonald, C., Harsdorf, J., Wedgwood, S., and Keating, B.:
APSIM – Evolution towards a new generation of agricultural systems
simulation, Environ. Modell. Softw., 62, 327–350, 2014.
Houska, T., Kraus, D., Kiese, R., and Breuer, L.: Constraining a complex biogeochemical model for CO2 and N2O emission simulations from various land uses by model–data fusion, Biogeosciences, 14, 3487–3508, https://doi.org/10.5194/bg-14-3487-2017, 2017.
Huang, C.: Soil Science, China Agriculture Press, Beijing, 125 pp., 2000
(in Chinese).
Hugelius, G., Loisel, J., Chadburn, S., Jackson, R., Jones, M., MacDonald,
G., Marushchak, M., Olefeldt, D., Maara, P., Siewert, M., Treat, C.,
Turetsky, M., Voigt, C., and Yu, Z.: Large stocks of peatland carbon and
nitrogen are vulnerable to permafrost thaw, P. Natl. Acad. Sci. USA, 117, 20438–20446,
https://doi.org/10.1073/pnas.1916387117, 2020.
IPCC (Intergovernmental Panel on Climate Change): Climate Change 2013: The
Physical Science Basis, Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited by:
Stocker, T. F.,
Qin, D., Plattner, G.-K., Tignor, M. B., Allen, S. K., Boschung,J., Nauels, A., Xiao, Y., Bex, V., and Midgley, P. M., Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA, 2013.
Jiang, H., Yi, Y., Zhang, W., Yang, K., and Chen, D.: Sensitivity of soil
freeze/thaw dynamics to environmental conditions at different spatial scales
in the central Tibetan Plateau, Sci. Total Environ., 734, 139261, https://doi.org/10.1016/j.scitotenv.2020.139261, 2020.
Jiang, Z.: Analysis on the establishment conditions of the square sum
decomposition formular of regression model, J. Industr. Techn. Econ., 29,
116–119 , 2010 (in Chinese).
Johansen, O.: Thermal conductivity of soils, Ph.D. thesis, Univ. of
Trondheim, Trondheim, Norway, 1975.
Ju, X., Xing, G., Chen, X., Zhang, S., Zhang, L., Liu, X., Cui, Z., Yin, B.,
Christie, P., Zhu, Z., and Zhang, F.: Reduing environmental risk by
improveing N mannagement in intensive Chinese agricultural systems, P.
Natl. Acad. Sci. USA, 106, 3041–3046, 2009.
Kandel, T., Lærke, P., and Elsgaard, L.: Annual emissions of CO2,
CH4 and N2O from a temperate peat bog: comparison of an undrained
and four drained sites under permanent grass and arable crop rotations with
cereals and potato, Agr. Forest Meteorol., 256/257, 470–481, 2018.
Kang, X., Li, Y., Wang, J., Yan, L., Zhang, X., Wu, H., Yan, Z., Zhang, K.,
and Hao, Y.: Precipitation and temperature regulate the carbon allocation
process in alpine wetlands: quantitative simulation, J. Soils Sediment., 20,
3300–3315, 2020.
Keiluweit, M., Wanzek, T., Kleber, M., Nico, P., and Fendorf, S.:
Anaerobic microsites have an unaccounted role in soil carbon stabilization,
Nat. Commun., 8, 1771, https://doi.org/10.1038/s41467-017-01406-6, 2017.
Klatt, S., Kraus, D., Kraft, P., Breuer, L., Wlotzka, M., Heuveline, V.,
Haas, E., Kiese, R., and Butterbach-Bahl, K.: Exploring impacts of
vegetated buffer strips on nitrogen cycling using a spatially explicit
hydro-biogeochemical modeling approach, Environ. Modell. Softw., 90, 55–67, 2017.
Li, B., Yu, Z., LIang, Z., Song, K., Li, H., Wang, Y., Zhang, W., and Acharya,
K.: Effects of climate variations and human activities on runoff in
the Zoige alpine wetland in the eastern edge of the Tibetan Plateau, J.
Hydrol. Eng., 19, 1026–1035, 2014.
Li, C.: Modeling trace gas emissions from agricutural ecosystems,
Nutr. Cycl. Agroecosyst., 58, 259–276, 2000.
Li, C.: Quantifying greenhouse gas emissions from soils: scientific
basis and modeling approach, Soil Sci. Plant Nutr., 53, 344–352, 2007.
Li, C.: Biogeochemistry: Scientific Fundamentals and Modelling
Approach, Tsinghua University Press, Beijing, 530 pp., 2016 (in Chinese).
Li, C., Frolking, S., and Butterbach-Bahl, K.: Carbon sequestration in
arable soils is likely to increase nitrous oxide emissions, offsetting
reductions in climate radiative forcing, Climatic Change, 72, 321–338, 2005.
Li, S., Zheng, X., Zhang, W., Han, S., Deng, J., Wang, K., Wang, R., Yao,
Z., and Liu, C.: Modeling ammonia volatilization following the application
of synthetic fertilizers to cultivated uplands with calcareous soils using
an improved DNDC biogeochemistry model, Sci. Total Environ., 660, 931–946, 2019.
Li, Y., White, R., Chen, D., Zhang, J., Li, B., Zhang, Y., Huang, Y., and Edis,
R.: A spatially referenced water and nitrogen management model (WNMM)
for (irrigated) intensive cropping systems in the North China Plain, Ecol.
Model., 203, 395–423, 2007.
Liu, C., Holst, J., Brüggemann, N., Butterbach-Bahl, K., Yao, Z., Yue,
J., Han, S., Han, X., Krümmelbein, J., Horn, R., and Zheng, X.:
Winter-grazing reduces methane uptake by soils of a typical semi-arid steppe
in Inner Mongolia, China, Atmos. Environ., 41, 5948–5958, 2007.
Liu, S., Xie, Z., Zeng, Y., Liu, B., Li, R., Wang, Y., Wang, L., Qin, P.,
Jia, B., and Xie, J.: Effects of anthropogenic nitrogen discharge on
dissolved inorganic nitrogen transport in global rivers, Glob. Change Biol.,
25, 1493–1513, 2019.
Ma, L., Yao, Z., Zheng, X., Zhang, H., Wang, K., Zhu, B., Wang, R., Zhang,
W., and Liu, C.: Increasing grassland degradation stimulates the
non-growing season CO2 emissions from an alpine meadow on the
Qinghai-Tibetan Plateau, Environ. Sci. Pollut. Res., 25, 26576–26591, 2018.
McClain, M., Boyer, E., Dent, C., Gergel, S., Grimm, N., Groffman, P., Hart,
S., Harvey, J., Johnston, C., and Mayorga, E.: Biogeochemical hot spots
and hot moments at the interface of terrestrial and aquatic ecosystems,
Ecosystems, 6, 301–312, 2003.
Moriasi, D., Arnold, J., Van Liew, M., Bingner, R., Harmel, R., and Veith, T.: Model evaluation guidelines for systematic quantification of accuracy
in watershed simulation, T. Am. Soc. Agr. Biol. Eng., 50, 885–900,
2007.
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual
models: part I – a discussion of principles, J. Hydrol., 10, 282–290, 1970.
Pansu, M., Sarmiento, L., Rujano, M., Ablan, M., Acevedo, D., and Bottner, P.: Modelling Organic transformations by Micro-Organisms of Soils in six
contrasting ecosystems: validation of the MOMOS model, Global Biogechem.
Cy., 24, GB1008, https://doi.org/10.1029/2009GB003527,
2010.
Pansu, M., Machado, D., Bottner, P., and Sarmiento, L.: Modelling microbial exchanges between forms of soil nitrogen in contrasting ecosystems, Biogeosciences, 11, 915–927, https://doi.org/10.5194/bg-11-915-2014, 2014.
Piao, S., Fang, J., Ciais, P., Peylin, P., Huang, Y., Sitch, S., and Wang, T.: The carbon balance of terrestrial ecosystems in China, Nature, 458,
1009–1013,
2009.
Pohlert, T., Huisman, J., Breuer, L., and Frede, H.: Integration of a
detailed biogeochemical model into SWAT for improved nitrogen
predictions – Model development, sensitivity, and GLUE analysis, Ecol.
Model., 203, 215–228, 2007.
Pollack, H. and Chapman, D.: On the regional variation of heat
flow,geotherms,and lithospheric thickness, Teclonophysics, 38, 279–296, 1977.
Schroeck, A., Gaube, V., Haas, E., and Winiwarter, W.: Estimating nitrogen
flows of agricultural soils at a landscape level – A modelling study of the
Upper Enns Valley, a long-term socio-ecological research region in Austria,
Sci. Total Environ., 665, 275–289, 2019.
Schuur, E., McGuire, A., Schadel, C., Grosse, G., Harden, J., Hayes, D.,
Hugelius, G., Koven, C., Kuhry, P., Lawrence, D., Natali, S., Olefeldt, D.,
Romanovsky, V., Schaefer, K., Turetsky, M., Treat, C., and Vonk, J.:
Climate change and the permafrost carbon feedback, Nature, 520, 171–179, 2015.
Seitzinger, S.: Nitrogen cycle – Out of reach, Nature, 452, 162–163, 2008.
Song, L., Yao, Y., Lin, L., Gao, W., Cai, T., Liang, H., and Gao, D.: The
potential source of nitrous oxide in the pristine riparian marsh during
freeze-thaw cycles, case study in Northeast China, Ecol. Eng., 134, 18–25, 2019.
Tan, L., Ge, Z., Zhou, X., Li, S., Li, X., and Tang, J.: Conversion of
coastal wetlands, riparian wetlands, and peatlands increases greenhouse gas
emissions: a global meta-analysis, Glob. Change Biol., 26, 1638–1653, 2020.
Todd-Brown, K., Hopkins, F., Kivlin, S., Jennifer, M., Talbot, J., and Allison,
S.: A framework for representing microbial decomposition in coupled
climate models, Biogeochemistry, 109, 19–33, 2012.
Treseder, K., Balser, T., Bradford, M., Brodie, E., Dubinsky, E., Eviner,
V., Hofmockel, K., Lennon, J., Levine, U., MacGregor, B., Pett-Ridge, J.,
and Waldrop, M.: Integrating microbial ecology into ecosystem models:
challenges and priorities, Biogeochemistry, 109, 7–18, 2011.
Vereecken, H., Schnepf, A., Hopmans, J., Javaux, M., Or, D., Roose, T.,
Vanderborght, J., Young, M., Amelung, W., Aitkenhead, M., Allison, S.,
Assouline, S., Baveye, P., Berli, M., Brüggemann, N., Finke, P., Flury,
M., Gaiser, T., Govers, G., Ghezzehei, T., Hallett, P., Hendricks Franssen,
H., Heppell, J., Horn, R., Huisman, J., Jacques, D., Jonard, F., Kollet, S.,
Lafolie, F., Lamorski, K., Leitner, D., McBratney, A., Minasny, B., Montzka,
C., Nowak, W., Pachepsky, Y., Padarian, J., Romano, N., Roth, K., Rothfuss,
Y., Rowe, E., Schwen, A., Šimůnek, J., Tiktak, A., Van Dam, J., van
der Zee, S., Vogel, H., Vrugt, J., Wöhling, T., and Young, I.:
Modeling Soil Processes: Review, Key Challenges, and New Perspectives,
Vadose Zone J., 15, vzj2015.09.0131, https://doi.org/10.2136/vzj2015.09.0131, 2016.
Wania, R., Ross, I., and Prentice, I.: Integrating peatlands and
permafrost into a dynamicglobal vegetation model: 1. Evaluation and
sensitivity of physical land surface processes, Global Biogechem. Cy., 23,
GB3014, https://doi.org/10.1029/2008GB003412, 2009.
Wigmosta, M., Vail, L., and Lettenmaier, D.: A distributed
hydrology-vegetation model for complex terrain, Water Resour. Res., 30,
1665–1679, 1994.
Willmott, C. and Matsuurra, K.: Advantages of the mean aboslute error
(MAE) over the root mean square error (RMSE) in assessing average model
performance, Clim. Res., 30, 79–82, 2005.
Wolf, B., Kiese, R., Chen, W., Grote, R., Zheng, X., and Butterbach-Bahl, K.: Modelling N2O emissions from steppe in Inner Mongolia, China,
with consideration of spring thaw and grazing intensity, Plant Soil, 350,
297–310,
2011.
Wu, Y., Liu, S., Qiu, L., and Sun, Y.: SWAT-DayCent coupler: An
integration tool for simultaneous hydro-biogeochemical modeling using SWAT
and DayCent, Environ. Modell. Softw., 86, 81–90, 2016.
Xiang, S., Guo, R., Wu, N., and Sun, S.: Current status and future
prospects of Zoige Marsh in Eastern Qinghai-Tibet Plateau, Ecol. Eng., 35,
553–562, 2009.
Yao, Z., Ma, L., Zhang, H., Zheng, X., Wang, K., Zhu, B., Wang, R., Wang,
Y., Zhang, W., Liu, C., and Butterbach-Bahl, K.: Characteristics of annual
greenhouse gas flux and NO release from alpine meadow and forest on the
eastern Tibetan Plateau, Agr. Forest Meteorol., 272/273, 166–175, 2019.
Zhang, H., Yao, Z., Wang, K., Zheng, X., Ma, L., Wang, R., Liu, C., Zhang,
W., Zhu, B., Tang, X., Hu, Z., and Han, S.: Annual N2O emissions
from conventionally grazed typically alpine grass meadows in the eastern
QInghai-Tibetan Plateau, Sci. Total Environ., 625, 885–899, 2018.
Zhang, H., Yao, Z., Ma, L., Zheng, X., Wang, R., Wang, K., Liu, C., Zhang,
W., Zhu, B., Tang, X., Hu, Z., and Han, S.: Annual methane emissions from
degraded alpine wetlands in the eastern Tibetan Plateau, Sci. Total Environ.,
657, 1323–1333, 2019.
Zhang, W., Liu, C., Zheng, X., Fu, Y., Hu, X., Cao, G., and Butterbach-Bahl, K.: The increasing distribution area of zokor mounds weaken greenhouse gas
uptakes by alpine meadows in the Qinghai–Tibetan Plateau, Soil Biol.
Biochem., 71, 105–112,
2014.
Zhang, W., Liu, C., Zheng, X., Zhou, Z., Cui, F., Zhu, B., Haas, E., Klatt,
S., Butterbach-Bahl, K., and Kiese, R.: Comparison of the DNDC,
LandscapeDNDC and IAP-N-GAS models for simulating nitrous oxide and nitric
oxide emissions from the winter wheat-summer maize rotation system, Agr.
Syst., 140, 1–10, 2015.
Zhang, W., Li, Y., Zhu, B., Zheng, X., Liu, C., Tang, J., Su, F., Zhang, C.,
Ju, X., and Deng, J.: A process-oriented hydro-biogeochemical model
enabling simulation of gaseous carbon and nitrogen emissions and hydrologic
nitrogen losses from a subtropical catchment, Sci. Total Environ., 616/617,
305–317, 2018.
Zhang, W., Liu, C., Zheng, X., Wang, K., Cui, F., Wang, R., Li, S., Yao, Z., and Zhu, J.: Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China, Biogeosciences, 16, 2905–2922, https://doi.org/10.5194/bg-16-2905-2019, 2019.
Zhang, W., Wang, J., Hu, Z., Li, Y., Yan, Z., Zhang, X., Wu, G., Yan, L.,
Zhang, K., and Kang, X.: The primary drivers of greenhouse gas emissions
along the water table gradient in the Zoige apline peatland, Water Air Soil
Pollut., 231, 224, https://doi.org/10.1007/s11270-020-04605-y, 2020.
Zhang, Y., Chen, W., and Cihlar, J.: A process-based model for quantifying
the impact of climate change on permafrost thermal regimes, J. Geophys.
Res.-Atmos., 108, 4695, https://doi.org/10.1029/2002JD003354, 2003.
Zhang, Y., Sachs, T., Li, C., and Boike, J.: Upscaling methane fluxes from
closed chambers to eddy covariance based on a permafrost biogeochemistry
integrated model, Glob. Change Biol., 18, 1428–1440, 2012.
Zhang, Y. Y., Shao, Q. X., Ye, A. Z., Xing, H. T., and Xia, J.: Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration, Hydrol. Earth Syst. Sci., 20, 529–553, https://doi.org/10.5194/hess-20-529-2016, 2016.
Zhu, Q., Schmidt, J. P., and Bryant, R.: Hot moments and hot spots of
nutrient losses from a mixed land use watershed, J. Hydrol. Eng., 414,
393–404, 2012.
Zhu, Q., Castellano, M., and Yang, G.: Coupling soil water processes and
the nitrogen cycle across spatial scales: potentials, bottlenecks and
solutions, Earth-Sci. Rev., 187, 248–258, 2018.
Zhuang, Q., Romanovsk, V., and McGuire, A.: Incorporation of a permafrost
model into a large-scale ecosystem model: Evaluation of temporal and spatial
scaling issues in simulating soil thermal dynamics, J. Geophys. Res., 106,
33649–33670, 2001.
Zhuang, Q., Melillo, J., Kicklighter, D., Prinn, R., McGuire, A., Steudler,
P., Felzer, B., 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
Biogechem. Cy., 18, GB3010, https://doi.org/10.1029/2004GB002239, 2004.
Short summary
The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) is improved by incorporating a soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model is validated at a seasonally frozen catchment with typical alpine ecosystems (wetland, meadow and forest). The simulated aggregate emissions of methane and nitrous oxide are highest for the wetland, which is dominated by the methane emissions.
The hydro-biogeochemical model Catchment Nutrient Management Model –...
Altmetrics
Final-revised paper
Preprint