IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i2p247-d1576524.html
   My bibliography  Save this article

Physical Parameterization Sensitivity of Noah-MP for Hydrothermal Simulation Within the Active Layer on the Qinghai–Tibet Plateau

Author

Listed:
  • Yongliang Jiao

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Ren Li

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Tonghua Wu

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Xiaodong Wu

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Shenning Wang

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jimin Yao

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Guojie Hu

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Xiaofan Zhu

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Jianzong Shi

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Yao Xiao

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

  • Erji Du

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yongping Qiao

    (Cryosphere Research Station on the Qinghai-Tibet Plateau, State Key Laboratory of Cryospheric Science, Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)

Abstract

The accurate modeling of complex freeze–thaw processes and hydrothermal dynamics within the active layer is challenging. Due to the uncertainty in hydrothermal simulation, it is necessary to thoroughly investigate the parameterization schemes in land surface models. The Noah-MP was utilized in this study to conduct 23,040 ensemble experiments based on 11 physical processes, which were aimed at improving the understanding of parameterization schemes and reducing model uncertainty. Next, the impacts of uncertainty of physical processes on land surface modeling were evaluated via Natural Selection and Tukey’s test. Finally, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used to identify the optimal combination of parameterization schemes for improving hydrothermal simulation. The results of Tukey’s test agreed well with those of Natural Selection for most soil layers. More importantly, Tukey’s test identified more parameterization schemes with consistent model performance for both soil temperature and moisture. Results from TOPSIS showed that the determination of optimal schemes was consistent for the simulation of soil temperature and moisture in each physical process except for frozen soil permeability (INF). Further analysis showed that scheme 2 of INF yielded better simulation results than scheme 1. The improvement of the optimal scheme combination during the frozen period was more significant than that during the thawed period.

Suggested Citation

  • Yongliang Jiao & Ren Li & Tonghua Wu & Xiaodong Wu & Shenning Wang & Jimin Yao & Guojie Hu & Xiaofan Zhu & Jianzong Shi & Yao Xiao & Erji Du & Yongping Qiao, 2025. "Physical Parameterization Sensitivity of Noah-MP for Hydrothermal Simulation Within the Active Layer on the Qinghai–Tibet Plateau," Land, MDPI, vol. 14(2), pages 1-24, January.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:247-:d:1576524
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/2/247/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/14/2/247/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lin Zhao & Qingbai Wu & S.S. Marchenko & N. Sharkhuu, 2010. "Thermal state of permafrost and active layer in Central Asia during the international polar year," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 21(2), pages 198-207, April.
    2. K. M. Hinkel & S. I. Outcalt & F. E. Nelson, 1990. "Temperature variation and apparent thermal diffusivity in the refreezing active layer, Toolik Lake, Alaska," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 1(3‐4), pages 265-274, July.
    3. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    4. Anna Galik & Monika Bąk & Katarzyna Bałandynowicz-Panfil & Giuseppe T. Cirella, 2022. "Evaluating Labour Market Flexibility Using the TOPSIS Method: Sustainable Industrial Relations," Sustainability, MDPI, vol. 14(1), pages 1-20, January.
    Full references (including those not matched with items on IDEAS)

    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. Yongming Song & Jun Hu, 2017. "Vector similarity measures of hesitant fuzzy linguistic term sets and their applications," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-13, December.
    2. Yi Peng, 2015. "Regional earthquake vulnerability assessment using a combination of MCDM methods," Annals of Operations Research, Springer, vol. 234(1), pages 95-110, November.
    3. Hae-Yeol Kang & Seung Taek Chae & Eun-Sung Chung, 2023. "Quantifying Medium-Sized City Flood Vulnerability Due to Climate Change Using Multi-Criteria Decision-Making Techniques: Case of Republic of Korea," Sustainability, MDPI, vol. 15(22), pages 1-20, November.
    4. Zheng, Guozhong & Wang, Xiao, 2020. "The comprehensive evaluation of renewable energy system schemes in tourist resorts based on VIKOR method," Energy, Elsevier, vol. 193(C).
    5. Lin, Sheng-Hau & Zhao, Xiaofeng & Wu, Jiuxing & Liang, Fachao & Li, Jia-Hsuan & Lai, Ren-Ji & Hsieh, Jing-Chzi & Tzeng, Gwo-Hshiung, 2021. "An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    6. Milad Zamanifar & Seyed Mohammad Seyedhoseyni, 2017. "Recovery planning model for roadways network after natural hazards," 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. 87(2), pages 699-716, June.
    7. Pedro Ponce & Citlaly Pérez & Aminah Robinson Fayek & Arturo Molina, 2022. "Solar Energy Implementation in Manufacturing Industry Using Multi-Criteria Decision-Making Fuzzy TOPSIS and S4 Framework," Energies, MDPI, vol. 15(23), pages 1-19, November.
    8. Mohit Jain & Gunjan Soni & Deepak Verma & Rajendra Baraiya & Bharti Ramtiyal, 2023. "Selection of Technology Acceptance Model for Adoption of Industry 4.0 Technologies in Agri-Fresh Supply Chain," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    9. Chen, Lisa Y. & Wang, Tien-Chin, 2009. "Optimizing partners' choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR," International Journal of Production Economics, Elsevier, vol. 120(1), pages 233-242, July.
    10. Wenyao Niu & Yuan Rong & Liying Yu & Lu Huang, 2022. "A Novel Hybrid Group Decision Making Approach Based on EDAS and Regret Theory under a Fermatean Cubic Fuzzy Environment," Mathematics, MDPI, vol. 10(17), pages 1-30, August.
    11. Deb, Madhujit & Debbarma, Bishop & Majumder, Arindam & Banerjee, Rahul, 2016. "Performance –emission optimization of a diesel-hydrogen dual fuel operation: A NSGA II coupled TOPSIS MADM approach," Energy, Elsevier, vol. 117(P1), pages 281-290.
    12. Kuang-Hua Hu & Wei Jianguo & Gwo-Hshiung Tzeng, 2017. "Risk Factor Assessment Improvement for China’s Cloud Computing Auditing Using a New Hybrid MADM Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 737-777, May.
    13. Wabukala, Benard M. & Bergland, Olvar & Mukisa, Nicholas & Adaramola, Muyiwa S. & Watundu, Susan & Orobia, Laura A. & Rudaheranwa, Nichodemus, 2024. "Electricity security in Uganda: Measurement and policy priorities," Utilities Policy, Elsevier, vol. 91(C).
    14. Fernando Rojas & Peter Wanke & Víctor Leiva & Mauricio Huerta & Carlos Martin-Barreiro, 2022. "Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    15. Maghsoodi, Abtin Ijadi, 2023. "Cryptocurrency portfolio allocation using a novel hybrid and predictive big data decision support system," Omega, Elsevier, vol. 115(C).
    16. Hisham Alidrisi, 2021. "An Innovative Job Evaluation Approach Using the VIKOR Algorithm," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    17. Büsing, Christina & Goetzmann, Kai-Simon & Matuschke, Jannik & Stiller, Sebastian, 2017. "Reference points and approximation algorithms in multicriteria discrete optimization," European Journal of Operational Research, Elsevier, vol. 260(3), pages 829-840.
    18. Abbas Keramati & Fatemeh Shapouri, 2016. "Multidimensional appraisal of customer relationship management: integrating balanced scorecard and multi criteria decision making approaches," Information Systems and e-Business Management, Springer, vol. 14(2), pages 217-251, May.
    19. Beata Bieszk-Stolorz & Krzysztof Dmytrów, 2022. "Assessment of the Similarity of the Situation in the EU Labour Markets and Their Changes in the Face of the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    20. Xiaodong Li & Haibo Kuang & Yan Hu, 2019. "Carbon Mitigation Strategies of Port Selection and Multimodal Transport Operations—A Case Study of Northeast China," Sustainability, MDPI, vol. 11(18), pages 1-17, September.

    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:gam:jlands:v:14:y:2025:i:2:p:247-:d:1576524. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.