Vol.30, NO.5, 2019
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Article Navigation >  Journal of Applied Meteorological Science  > 2019  >  30(5): 528-542
Ma Yuping, Huo Zhiguo, Wang Peijuan, et al. The construction and application of Chinese agrometeorological model(CAMM1.0). J Appl Meteor Sci, 2019, 30(5): 528-542. DOI:  10.11898/1001-7313.20190502.
Citation: Ma Yuping, Huo Zhiguo, Wang Peijuan, et al. The construction and application of Chinese agrometeorological model(CAMM1.0). J Appl Meteor Sci, 2019, 30(5): 528-542. DOI:  10.11898/1001-7313.20190502.
shu

The Construction and Application of Chinese AgroMeteorological Model(CAMM1.0)

DOI: 10.11898/1001-7313.20190502

  • Chinese Academy of Meteorological Sciences, Beijing 100081

  • Received Date: 2019-05-10
  • Rev Recd Date: 2019-07-24
  • Publish Date: 2019-09-30
    Abstract
  • In order to develop an agrometeorological model suitable for regional agricultural planting in China, China AgroMeteorological Model version 1.0(CAMM1.0) is established by improving and reconstructing the process and innovative application of existing oversea simulation methods.CAMM1.0 makes several improvements in process of agrometeorological model. It improves crop development process model by using average temperature intensity and soil moisture, improves crop leaf photosynthesis, dry matter distribution and leaf area expansion process model by using soil moisture, expands crop evapotranspiration process model by evaporation ratio method, establishes winter wheat plant height model based on development process. Based on the remote sensing information, the crop irrigation model, data assimilation model, crop growth and assessment model are also constructed. Main functions of CAMM1.0 include real-time crop growth simulation and customized user simulation. The former outputs real-time crop growth state variables, environmental variables and growth evaluation day by day. And the latter can produce customized products. CAMM1.0 can simulate the crop development, photosynthesis and plant height very well. However, the simulation is slightly weak on the process of soil moisture change, and the simulated yield is also slightly low. The assessed trend of summer maize in drought decreasing and waterlogging increasing by CAMM1.0 in Huaihe River Basin is consistent with the observation. Improving the key mechanism of crop growth enhances the response of CAMM1.0 to the environment. The construction of characteristic regional model improves its ability to simulate the growth process of Chinese crops, and realizes the regionalization of the model. The customized operation platform via the Internet is convenient for the agrometeorological application.CAMM1.0 constructs an online real-time operation platform to make the application and extension of the model and further development of the core module more convenient. Some of its sub-modules are constructed by multiple methods, which is more convenient for multi-model integration. The plugin method makes it easy for the model applicating, developing and updating. However, the mechanism of CAMM1.0 is still far from perfect, and the next step is to work on the response of agricultural production to climate change and various meteorological disasters. CAMM1.0 is expected to improve the theoretical level of agrometeorological simulation in China and provide technical solutions for related operational services.
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  • Fig. 1  Mechanisms of Chinese AgroMeteorological Model(CAMM1.0)

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    Fig. 2  Changes of dry matter partitioning coefficients of wheat with development stage(DVS)

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    Fig. 3  Trends of winter wheat plant height with accumulated heat unit(THU)

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    Fig. 4  The relationship of winter wheat plant height difference to average(AHU) and accumulated heat unit(THU)

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    Fig. 5  Running platform of Chinese AgroMeteorological Model(CAMM1.0)

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    Fig. 6  Relationship between measured and simulated winter wheat developments in China by CAMM1.0 from 2017 to 2018

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    Fig. 7  Relationship between measured and simulated photosynthetic rate of summer maize by three-leaf photosynthesis models

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    Fig. 8  Relationship between measured and simulated total aboveground dry weight of summer maize in Henan by remote sensing data assimilation model from 2010 to 2011

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    Fig. 9  Relationship between measured and simulated winter wheat yield and total dry weight aboveground in China by CAMM1.0 in 2018

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    Fig. 10  Evaluation of growth in time trend and spatial distribution of summer maize in North China by CAMM1.0 in 2013

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    Fig. 11  Assessment of summer maize drought and flood disasters in Huaihe River Basin by CAMM1.0

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    • Received : 2019-05-10
    • Accepted : 2019-07-24
    • Published : 2019-09-30
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