PROGRESS IN GEOGRAPHY ›› 2022, Vol. 41 ›› Issue (2): 289-303.doi: 10.18306/dlkxjz.2022.02.009

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Comparative study of DLM and CLM5 model simulations at winter wheat-summer maize rotation stations in the North China Plain

WANG Fei1(), CHEN Baozhang1,3,*(), CHEN Jing2, ZHANG Huifang1, GUO Lifeng1   

  1. 1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Beijing Meteorological Service, Beijing 100089, China
    3. Collaborative Innovation Center of Geographical Information Resources Development and Utilization in Jiangsu Province, Nanjing 210023, China
  • Received:2021-01-19 Revised:2021-08-11 Online:2022-02-28 Published:2022-04-28
  • Contact: CHEN Baozhang E-mail:fei1226h@126.com;baozhang.chen@igsnrr.ac.cn
  • Supported by:
    National Key R&D Program of China(2018YFA0606001);National Key R&D Program of China(2017YFA0604302);National Natural Science Foundation of China(41771114);National Natural Science Foundation of China(4197740)

Abstract:

The interaction between crop growth and climate is one of the key issues in climate change studies. As an important research tool, land surface models can be used for distinct simulations with different model frameworks, algorithms, or parameterization schemes. In order to investigate the differences of the Dynamic Land Model (DLM) and Community Land Model (CLM5) in estimating crop growth and farmland heat flux and the causes of the differences, model comparisons were conducted at the agricultural stations with summer maize and winter wheat rotation in the North China Plain (NCP). The results show that the estimated leaf area index and gross primary production of DLM for summer maize were better, while for winter wheat, the opposite results were obtained. Nonetheless, DLM performed better in simulating latent heat flux, which may reflect that the Penman formula and two-leaf strategy in DLM is better than the mass conservation algorithm based on water potential gradient and big-leaf strategy in CLM5. However, the capacity of yield prediction was poor. In conclusion, with the default settings, the simulations of the two models can basically reflect the growth characteristics of summer maize and winter wheat in the study area, but there remains certain deviation from the observations. The applicability of the models for the NCP may need to be further improved through the addition of farmland management measures, algorithm optimization, and parameter localization.

Key words: summer maize and winter wheat rotation, DLM model, CLM5 model, growth simulation, model comparison and evaluation, North China Plain