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Implementing Dynamic Rooting Depth for Improved Simulation of Soil Moisture and Land Surface Feedbacks in Noah‐MP‐Crop
Author(s) -
Liu Xing,
Chen Fei,
Barlage Michael,
Niyogi Dev
Publication year - 2020
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2019ms001786
Subject(s) - environmental science , water content , crop , soil science , moisture , agricultural engineering , atmospheric sciences , agronomy , meteorology , geology , geography , geotechnical engineering , engineering , biology
The study postulates that crop rooting depth representation plays a vital role in simulating soil‐crop‐atmospheric interactions. Rooting depth determines the water access for plants and alters the surface energy participation and soil moisture profile. The aboveground crop growth representation in land surface models continues to evolve and improve, but the root processes are still poorly represented. This limitation likely contributes to the bias in simulating soil‐crop‐related variables such as soil moisture and associated water and energy exchanges between the surface and the atmosphere. In Noah‐MP‐Crop, the rooting depth of crops is assumed as 1 m regardless of crop types and the length of growing seasons. In this study, a simple dynamic rooting depth formulation was integrated into Noah‐MP‐Crop. On comparing with soil moisture observations from the in situ Ameriflux, USDA Soil Climate Analysis Network, and the remote‐sensed Soil Moisture Active Passive data set, the results highlight the improved performance of Noah‐MP‐Crop due to modified rooting depth. The improvements were noted in terms of soil moisture and more prominently in terms of the energy flux simulations at both field scale and regional scale. The enhancements in soil moisture profiles reduce the biases in surface heat flux simulations. The impact of rooting depth representation appears to be particularly significant for improving model performance under drought‐like situations. Although it was not possible to validate the simulated rooting depth due to lack of observations, the overall performance of the model helps emphasize the importance of enhancing the representation of crop rooting depth in Noah‐MP‐Crop.

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