IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v220y2009i18p2121-2136.html
   My bibliography  Save this article

Optimization of ecosystem model parameters using spatio-temporal soil moisture information

Author

Listed:
  • Zhu, Lin
  • Chen, Jing M.
  • Qin, Qiming
  • Li, Jianping
  • Wang, Lianxi

Abstract

Parameters in process-based terrestrial ecosystem models are often nonlinearly related to the water flux to the atmosphere, and they also change temporally and spatially. Therefore, for estimating soil moisture, process-based terrestrial ecosystem models inevitably need to specify spatially and temporally variant model parameters. This study presents a two-stage data assimilation scheme (TSDA) to spatially and temporally optimize some key parameters of an ecosystem model which are closely related to soil moisture. At the first stage, a simplified ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS), is used to obtain the prior estimation of daily soil moisture. After the spatial distribution of 0–10cm surface soil moisture is derived from remote sensing, an Ensemble Kalman Filter is used to minimize the difference between the remote sensing model results, through optimizing some model parameters spatially. At the second stage, BEPS is reinitialized using the optimized parameters to provide the updated model predictions of daily soil moisture. TSDA has been applied to an arid and semi-arid area of northwest China, and the performance of the model for estimating daily 0–10cm soil moisture after parameter optimization was validated using field measurements. Results indicate that the TSDA developed in this study is robust and efficient in both temporal and spatial model parameter optimization. After performing the optimization, the correlation (r2) between model-predicted 0–10cm soil moisture and field measurement increased from 0.66 to 0.75. It is demonstrated that spatial and temporal optimization of ecosystem model parameters can not only improve the model prediction of daily soil moisture but also help to understand the spatial and temporal variation of some key parameters in an ecosystem model and the corresponding ecological mechanisms controlling the variation.

Suggested Citation

  • Zhu, Lin & Chen, Jing M. & Qin, Qiming & Li, Jianping & Wang, Lianxi, 2009. "Optimization of ecosystem model parameters using spatio-temporal soil moisture information," Ecological Modelling, Elsevier, vol. 220(18), pages 2121-2136.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:18:p:2121-2136
    DOI: 10.1016/j.ecolmodel.2009.04.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380009003196
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2009.04.042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Piñeiro, Gervasio & Perelman, Susana & Guerschman, Juan P. & Paruelo, José M., 2008. "How to evaluate models: Observed vs. predicted or predicted vs. observed?," Ecological Modelling, Elsevier, vol. 216(3), pages 316-322.
    2. Naud, Cédric & Makowski, David & Jeuffroy, Marie-Hélène, 2007. "Application of an interacting particle filter to improve nitrogen nutrition index predictions for winter wheat," Ecological Modelling, Elsevier, vol. 207(2), pages 251-263.
    3. Fischer, Björn & Goldberg, Valeri & Bernhofer, Christian, 2008. "Effect of a coupled soil water–plant gas exchange on forest energy fluxes: Simulations with the coupled vegetation–boundary layer model HIRVAC," Ecological Modelling, Elsevier, vol. 214(2), pages 75-82.
    4. McVicar, Tim R. & Jupp, David L. B., 1998. "The current and potential operational uses of remote sensing to aid decisions on drought exceptional circumstances in Australia: a review," Agricultural Systems, Elsevier, vol. 57(3), pages 399-468, July.
    5. Mo, Xingguo & Chen, Jing M. & Ju, Weimin & Black, T. Andrew, 2008. "Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 217(1), pages 157-173.
    6. Chen, Baozhang & Chen, Jing M. & Ju, Weimin, 2007. "Remote sensing-based ecosystem–atmosphere simulation scheme (EASS)—Model formulation and test with multiple-year data," Ecological Modelling, Elsevier, vol. 209(2), pages 277-300.
    7. Hanson, J. D. & Ahuja, L. R. & Shaffer, M. D. & Rojas, K. W. & DeCoursey, D. G. & Farahani, H. & Johnson, K., 1998. "RZWQM: Simulating the effects of management on water quality and crop production," Agricultural Systems, Elsevier, vol. 57(2), pages 161-195, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. He, Liming & Chen, Jing M. & Liu, Jane & Mo, Gang & Bélair, Stéphane & Zheng, Ting & Wang, Rong & Chen, Bin & Croft, Holly & Arain, M.Altaf & Barr, Alan G., 2014. "Optimization of water uptake and photosynthetic parameters in an ecosystem model using tower flux data," Ecological Modelling, Elsevier, vol. 294(C), pages 94-104.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. He, Liming & Chen, Jing M. & Liu, Jane & Mo, Gang & Bélair, Stéphane & Zheng, Ting & Wang, Rong & Chen, Bin & Croft, Holly & Arain, M.Altaf & Barr, Alan G., 2014. "Optimization of water uptake and photosynthetic parameters in an ecosystem model using tower flux data," Ecological Modelling, Elsevier, vol. 294(C), pages 94-104.
    2. Ojeda, Jonathan J. & Volenec, Jeffrey J. & Brouder, Sylvie M. & Caviglia, Octavio P. & Agnusdei, Mónica G., 2018. "Modelling stover and grain yields, and subsurface artificial drainage from long-term corn rotations using APSIM," Agricultural Water Management, Elsevier, vol. 195(C), pages 154-171.
    3. Wu, Zhangsheng & Li, Yue & Wang, Rong & Xu, Xu & Ren, Dongyang & Huang, Quanzhong & Xiong, Yunwu & Huang, Guanhua, 2023. "Evaluation of irrigation water saving and salinity control practices of maize and sunflower in the upper Yellow River basin with an agro-hydrological model based method," Agricultural Water Management, Elsevier, vol. 278(C).
    4. Booth, Shawn & Walters, William J & Steenbeek, Jeroen & Christensen, Villy & Charmasson, Sabine, 2020. "An Ecopath with Ecosim model for the Pacific coast of eastern Japan: Describing the marine environment and its fisheries prior to the Great East Japan earthquake," Ecological Modelling, Elsevier, vol. 428(C).
    5. Luca Piciullo & Vittoria Capobianco & Håkon Heyerdahl, 2022. "A first step towards a IoT-based local early warning system for an unsaturated slope in Norway," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3377-3407, December.
    6. X. Zhang & Y. Yamaguchi, 2014. "Characterization and evaluation of MODIS-derived Drought Severity Index (DSI) for monitoring the 2009/2010 drought over southwestern China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(3), pages 2129-2145, December.
    7. Chantal M. J. Hendriks & Harry S. Gibson & Anna Trett & André Python & Daniel J. Weiss & Anton Vrieling & Michael Coleman & Peter W. Gething & Penny A. Hancock & Catherine L. Moyes, 2019. "Mapping Geospatial Processes Affecting the Environmental Fate of Agricultural Pesticides in Africa," IJERPH, MDPI, vol. 16(19), pages 1-22, September.
    8. Chen, Weiping & Hou, Zhenan & Wu, Laosheng & Liang, Yongchao & Wei, Changzhou, 2010. "Evaluating salinity distribution in soil irrigated with saline water in arid regions of northwest China," Agricultural Water Management, Elsevier, vol. 97(12), pages 2001-2008, November.
    9. Sergio Vicente-Serrano, 2007. "Evaluating the Impact of Drought Using Remote Sensing in a Mediterranean, Semi-arid Region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 40(1), pages 173-208, January.
    10. Ma, Shaoxiu & Churkina, Galina & Wieland, Ralf & Gessler, Arthur, 2011. "Optimization and evaluation of the ANTHRO-BGC model for winter crops in Europe," Ecological Modelling, Elsevier, vol. 222(20), pages 3662-3679.
    11. Majid Majzoubi & Eric Yanfei Zhao, 2023. "Going beyond optimal distinctiveness: Strategic positioning for gaining an audience composition premium," Strategic Management Journal, Wiley Blackwell, vol. 44(3), pages 737-777, March.
    12. Shuang Liu & David I Stern, 2008. "A Meta-Analysis of Contingent Valuation Studies in Coastal and Near-Shore Marine Ecosystems," Socio-Economics and the Environment in Discussion (SEED) Working Paper Series 2008-15, CSIRO Sustainable Ecosystems.
    13. Sepaskhah, Ali Reza & Fahandezh-Saadi, Saghar & Zand-Parsa, Shahrokh, 2011. "Logistic model application for prediction of maize yield under water and nitrogen management," Agricultural Water Management, Elsevier, vol. 99(1), pages 51-57.
    14. Michael Gbenga Ogungbuyi & Juan P. Guerschman & Andrew M. Fischer & Richard Azu Crabbe & Caroline Mohammed & Peter Scarth & Phil Tickle & Jason Whitehead & Matthew Tom Harrison, 2023. "Enabling Regenerative Agriculture Using Remote Sensing and Machine Learning," Land, MDPI, vol. 12(6), pages 1-25, May.
    15. Sileshi, Gudeta & Hailu, Girma & Nyadzi, Gerson I., 2009. "Traditional occupancy–abundance models are inadequate for zero-inflated ecological count data," Ecological Modelling, Elsevier, vol. 220(15), pages 1764-1775.
    16. Gergs, André & Ratte, Hans Toni, 2009. "Predicting functional response and size selectivity of juvenile Notonecta maculata foraging on Daphnia magna," Ecological Modelling, Elsevier, vol. 220(23), pages 3331-3341.
    17. Blal, Mohamed & Benatiallah, Ali & NeÇaibia, Ammar & Lachtar, Salah & Sahouane, Nordine & Belasri, Ahmed, 2019. "Contribution and investigation to compare models parameters of (PEMFC), comprehensives review of fuel cell models and their degradation," Energy, Elsevier, vol. 168(C), pages 182-199.
    18. Bagnara, Maurizio & Van Oijen, Marcel & Cameron, David & Gianelle, Damiano & Magnani, Federico & Sottocornola, Matteo, 2018. "Bayesian calibration of simple forest models with multiplicative mathematical structure: A case study with two Light Use Efficiency models in an alpine forest," Ecological Modelling, Elsevier, vol. 371(C), pages 90-100.
    19. Della Nave, Facundo N. & Ojeda, Jonathan J. & Irisarri, J. Gonzalo N. & Pembleton, Keith & Oyarzabal, Mariano & Oesterheld, Martín, 2022. "Calibrating APSIM for forage sorghum using remote sensing and field data under sub-optimal growth conditions," Agricultural Systems, Elsevier, vol. 201(C).
    20. Lutz, Femke & Stoorvogel, Jetse J. & Müller, Christoph, 2019. "Options to model the effects of tillage on N2O emissions at the global scale," Ecological Modelling, Elsevier, vol. 392(C), pages 212-225.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:220:y:2009:i:18:p:2121-2136. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.