Skip to main content
SpringerLink
Log in

Method development for estimating soil organic carbon content in an alpine region using soil moisture data

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

The high soil organic carbon (SOC) content in alpine meadow can significantly change soil hydrothermal properties and further affect the soil temperature and moisture as well as the surface water and energy budget. Therefore, this study first introduces a parameterization scheme to describe the effect of SOC content on soil hydraulic and thermal parameters in a land surface model (LSM), and then the SOC content is estimated by minimizing the difference between observed and simulated surface-layer soil moisture. The accuracy of the estimated SOC content was evaluated using in situ observation data at a soil moisture and temperature-measuring network in Naqu, central Tibetan Plateau. Sensitivity experiments show that the optimum time window for stabilizing the estimation results cannot be shorter than three years. In the experimental area, the estimated SOC content can generally reflect the spatial distribution of the measurements, with a root mean square error of 0.099 m3 m−3, a mean bias of 0.043 m3 m−3, and a correlation coefficient of 0.695. The estimated SOC content is not sensitive to the temporal frequency of the soil moisture data input. Even if the temporal frequency is as low as that of current soil moisture products derived from passive microwave satellites, the estimation result is still stable. Therefore, by combining a high-quality satellite soil moisture product and a parameter optimization method, it is possible to obtain grid-scale effective parameter values, such as SOC content, for an LSM and improve the simulation ability of the LSM.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bi H, Ma J, Wang F. 2015. An improved particle filter algorithm based on ensemble kalman filter and markov chain monte carlo method. IEEE J Sel Top Appl Earth Obser Remote Sens, 8: 447–459

    Article  Google Scholar 

  • Chen Y Y, Yang K, Tang W J, Qin J, Zhao L. 2012. Parameterizing soil organic carbon’s impacts on soil porosity and thermal parameters for Eastern Tibet grasslands. Sci China Earth Sci, 55: 1001–1011

    Article  Google Scholar 

  • Chen Y Y, Yang K, He J, Qin J, Shi J C, Du J Y, He Q. 2011. Improving land surface temperature modeling for dry land of China. J Geophys Res, 116: D20104

    Article  Google Scholar 

  • Chen Y Y, Yang K, Qin J, Zhao L, Tang W J, Han M L. 2013. Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau. J Geophys Res-Atmos, 118: 4466–4475

    Article  Google Scholar 

  • Chen Y Y, Yang K, Qin J, Cui Q, Lu H, La Z, Han M L, Tang W J. 2017. Evaluation of SMAP, SMOS, and AMSR2 soil moisture retrievals against observations from two networks on the Tibetan Plateau. J Geophys Res-Atmos, 122: 5780–5792

    Article  Google Scholar 

  • Corbari C, Mancini M. 2014. Calibration and validation of a distributed energy-water balance model using satellite data of land surface temperature and ground discharge measurements. J Hydrometeorol, 15: 376–392

    Article  Google Scholar 

  • Corbari C, Mancini M, Li J, Su Z. 2015. Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration? Hydrol Sci J, 60: 202–217

    Article  Google Scholar 

  • Dai Y J, Shangguan W, Duan Q Y, Liu B Y, Niu G Y. 2013. Development of a china dataset of soil hydraulic parameters using pedotransfer functions for land surface modeling. J Hydrometeorol, 14: 869–887

    Article  Google Scholar 

  • Duan Q Y, Gupta V K, Sorooshian S. 1993. Shuffled complex evolution approach for effective and efficient global minimization. J Optim Theor Appl, 76: 501–521

    Article  Google Scholar 

  • Fang J Y, Liu G H, Xu S L. 1996. Soil carbon pool in China and its global significance. J Environ Sci-China, 8: 249–254

    Google Scholar 

  • FAO/IIASA/ISRIC/ISS-CAS/JRC. 2012. Harmonized World Soil Database (ver. 1.2), FAO, Rome

  • Gao Y H, Li K, Chen F, Jiang Y S, Lu C G. 2015. Assessing and improving Noah-MP land model simulations for the central Tibetan Plateau. J Geophys Res-Atmos, 120: 9258–9278

    Article  Google Scholar 

  • Guo D L, Wang H J. 2013. Simulation of permafrost and seasonally frozen ground conditions on the Tibetan Plateau, 1981–2010. J Geophys Res-Atmos, 118: 5216–5230

    Article  Google Scholar 

  • Gutmann E D, Small E E. 2005. The effect of soil hydraulic properties vs. soil texture in land surface models. Geophys Res Lett, 32: L02402

    Article  Google Scholar 

  • He J, Yang K. 2011. China Meteorological Forcing Dataset. Third Pole Environment Database, Beijing, China, doi: https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file

  • Henderson-Sellers A, Pitman A J, Love P K, Irannejad P, Chen T H. 1995. The project for intercomparison of land surface parameterization schemes (PILPS): Phases 2 and 3. Bull Amer Meteorol Soc, 76: 489–503

    Article  Google Scholar 

  • Lawrence D M, Slater A G. 2008. Incorporating organic soil into a global climate model. Clim Dyn, 30: 145–160

    Article  Google Scholar 

  • Li X. 2014. Characterization, controlling, and reduction of uncertainties in the modeling and observation of land-surface systems. Sci China Earth Sci, 57: 80–87

    Article  Google Scholar 

  • Liu J G, Xie Z H. 2013. Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach. Hydrol Earth Syst Sci, 17: 3355–3369

    Article  Google Scholar 

  • Liu Y Q, Gupta H V, Sorooshian S, Sastidas L A, Shuttleworth W J. 2005. Constraining land surface and atmospheric parameters of a locally coupled model using observational data. J Hydrometeorol, 6: 156–172

    Article  Google Scholar 

  • Luo S Q, Fang X W, Lyu S, Zhang Y, Chen B L. 2017. Improving CLM4.5 simulations of land-atmosphere exchange during freeze-thaw processes on the Tibetan Plateau. J Meteorol Res, 31: 916–930

    Article  Google Scholar 

  • Pinnington E, Quaife T, Black E. 2018. Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model. Hydrol Earth Syst Sci, 22: 2575–2588

    Article  Google Scholar 

  • Qin J, Yang K, Lu N, Chen Y Y, Zhao L, Han M L. 2013. Spatial upscaling of in-situ soil moisture measurements based on MODIS-derived apparent thermal inertia. Remote Sens Environ, 138: 1–9

    Article  Google Scholar 

  • Reynolds C A, Jackson T J, Rawls W J. 2000. Estimating soil waterholding capacities by linking the food and agriculture organization soil map of the world with global pedon databases and continuous pedotransfer functions. Water Resour Res, 36: 3653–3662

    Article  Google Scholar 

  • Sellers P J, Randall D A, Collatz G J, Berry J A, Field C B, Dazlich D A, Zhang C, Collelo G D, Bounoua L. 1996. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. J Clim, 9: 676–705

    Article  Google Scholar 

  • Shangguan W, Dai Y J, Liu B Y, Zhu A X, Duan Q Y, Wu L Z, Ji D Y, Ye A Z, Yuan H, Zhang Q, Chen D D, Chen M, Chu J T, Dou Y J, Guo J X, Li H Q, Li J J, Liang L, Liang X, Liu H P, Liu S Y, Miao C Y, Zhang Y Z. 2013. A China data set of soil properties for land surface modeling. J Adv Model Earth Syst, 5: 212–224

    Article  Google Scholar 

  • Shi J C, Jiang L M, Zhang L X, Chen K S, Wigneron J P, Chanzy A. 2005. A parameterized multifrequency-polarization surface emission model. IEEE Trans Geosci Remote Sens, 43: 2831–2841

    Article  Google Scholar 

  • Shi Z, Wang Q L, Peng J, Ji W J, Liu H J, Li X, Viscarra Rossel R A. 2014. Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations. Sci China Earth Sci, 57: 1671–1680

    Article  Google Scholar 

  • Tao Z, Shen C D, Gao Q Z, Sun Y M, Yi W X, Li Y N. 2007. Soil organic carbon storage and soil CO2 flux in the alpine meadow ecosystem. Sci China Ser D-Earth Sci, 50: 1103–1114

    Article  Google Scholar 

  • Wang G X, Qian J, Cheng G D, Lai Y M. 2002. Soil organic carbon pool of grassland soils on the Qinghai-Tibetan Plateau and its global implication. Sci Total Environ, 291: 207–217

    Article  Google Scholar 

  • Yang K, Qin J, Zhao L, Chen Y Y, Tang W J, Han M L, La Z, Chen Z Q, Lv L, Ding B H, Wu H, Lin L G. 2013. A multiscale soil moisture and freeze-thaw monitoring network on the Third Pole. Bull Amer Meteorol Soc, 94: 1907–1916

    Article  Google Scholar 

  • Yang K, Watanabe T, Koike T, Li X, Fuji H, Tamagawa K, Ma Y M, Ishikawa H. 2007. Auto-calibration system developed to assimilate AMSR-E data into a land surface model for estimating soil moisture and the surface energy budget. J Meteorol Soc Jpn, 85A: 229–242

    Article  Google Scholar 

  • Yang K, Koike T, Ye B, Luis B. 2005. Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition. J Geophys Res, 110: D08101

    Google Scholar 

  • Yang K, Koike T, Kaihotsu I, Qin J. 2009. Validation of a dual-pass microwave land data assimilation system for estimating surface soil moisture in semiarid regions. J Hydrometeorol, 10: 780–793

    Article  Google Scholar 

  • Yang K, Zhu L, Chen Y Y, Zhao L, Qin J, Lu H, Tang W J, Ding B H, Fang N. 2016. Land surface model calibration through microwave data as-similation for improving soil moisture simulations. J Hydrol, 533: 266–276

    Article  Google Scholar 

  • Yang Y H, Fang J Y, Tang Y H, Ji C J, Zheng C Y, He J S, Zhu B. 2008. Storage, patterns and controls of soil organic carbon in the Tibetan grasslands. Glob Change Biol, 14: 1592–1599

    Article  Google Scholar 

  • Yang Y H, Fang J Y, Pete S, Tang Y H, Chen A P, Ji C J, Hu H F, Rao S, Tan K, He J S. 2009. Changes in topsoil carbon stock in the Tibetan grasslands between the 1980s and 2004. Glob Change Biol, 15: 2723–2729

    Article  Google Scholar 

  • Zeng J Y, Li Z, Chen Q, Bi H Y, Qiu J X, Zou P F. 2015. Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations. Remote Sens Environ, 163: 91–110

    Article  Google Scholar 

  • Zhang Y Q, Tang Y H, Jiang J, Yang Y H. 2007. Characterizing the dynamics of soil organic carbon in grasslands on the Qinghai-Tibetan Plateau. Sci China Ser D-Earth Sci, 50: 113–120

    Article  Google Scholar 

  • Zhao L, Yang K, Qin J, Chen Y Y, Tang W J, Montzka C, Lu H, Lin C G, Han M L, Vereecken H. 2013. Spatiotemporal analysis of soil moisture observations within a Tibetan mesoscale area and its implication to regional soil moisture measurements. J Hydrol, 482: 92–104

    Article  Google Scholar 

  • Zhao L, Yang K, Qin J, Chen Y Y, Tang W J, Lu H, Yang Z L. 2014. The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau. Remote Sens Environ, 152: 345–355

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Key Research and Development Project (Grant No. 2018YFA0605400), the National Natural Science Foundation of China (Grant No. 41471286), the Frontier Science Project of Chinese Academy of Sciences (Grant No. QYZDY-SSW-DQC011-03), and the Special Project of Information Construction of the 13th Five-Year Plan of the Chinese Academy of Sciences (Grant No. XXH13505-06).

Author information

Authors and Affiliations

  1. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China

    Qi Luo, Kun Yang, Yingying Chen & Xu Zhou

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Qi Luo

  3. Department of Earth System Science, Tsinghua University, Beijing, 100084, China

    Kun Yang

  4. CAS Center for Excellence in Tibetan Plateau Earth System, Beijing, 100101, China

    Kun Yang & Yingying Chen

Authors
  1. Qi Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yingying Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xu Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kun Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, Q., Yang, K., Chen, Y. et al. Method development for estimating soil organic carbon content in an alpine region using soil moisture data. Sci. China Earth Sci. 63, 591–601 (2020). https://doi.org/10.1007/s11430-019-9554-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-019-9554-8

Keywords

Search

Navigation