Remote Sens. 2013, 5(11), 5514-5529; doi:10.3390/rs5115514
Article

Evaluation of the Effects of Soil Layer Classification in the Common Land Model on Modeled Surface Variables and the Associated Land Surface Soil Moisture Retrieval Model

1 University of Chinese Academy of Sciences, Beijing 100049, China 2 ICube, UdS, CNRS, Boulevard Sebastien Brant, BP10413, Illkirch 67412, France 3 Key Laboratory of Agri-Informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
* Author to whom correspondence should be addressed.
Received: 23 August 2013; in revised form: 15 October 2013 / Accepted: 15 October 2013 / Published: 28 October 2013
(This article belongs to the Special Issue Hydrological Remote Sensing)
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Abstract: Land surface soil moisture (SSM) is crucial in research and applications in hydrology, ecology, and meteorology. A novel SSM retrieval model, based on the diurnal cycles of land surface temperature (LST) and net surface shortwave radiation (NSSR), has recently been reported. It suggests a promising avenue for the retrieval of regional SSM using LST and NSSR derived from geostationary satellites in a future development. As part of a further improvement of previous work, effects of soil layer classification in the Common Land Model (CoLM) on modeled LST, NSSR and the associated SSM retrieval model in particular, have been evaluated. To address this issue, the soil profile has been divided in to three layers, named upper layer (0–0.05 m), root layer (0.05–1.30 m) and bottom layer (1.30–2.50 m). By varying the number of soil layers with the three layer zones, nine different soil layer classifications have been performed in the CoLM to produce simulated data. Results indicate that (1) modeled SSM is less sensitive to soil layer classification while modeled LST and NSSR are sensitive, especially under wet conditions and (2) the simulated data based SSM retrieval model is stable for a fixed upper layer with varying classifications of root and bottom layers. It also concludes an optimal soil layer classification for the CoLM while producing simulated data to develop the SSM retrieval model.
Keywords: soil layer classification; surface soil moisture (SSM) retrieval model; Common Land Model (CoLM)

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MDPI and ACS Style

Leng, P.; Song, X.; Li, Z.-L.; Wang, Y. Evaluation of the Effects of Soil Layer Classification in the Common Land Model on Modeled Surface Variables and the Associated Land Surface Soil Moisture Retrieval Model. Remote Sens. 2013, 5, 5514-5529.

AMA Style

Leng P, Song X, Li Z-L, Wang Y. Evaluation of the Effects of Soil Layer Classification in the Common Land Model on Modeled Surface Variables and the Associated Land Surface Soil Moisture Retrieval Model. Remote Sensing. 2013; 5(11):5514-5529.

Chicago/Turabian Style

Leng, Pei; Song, Xiaoning; Li, Zhao-Liang; Wang, Yawei. 2013. "Evaluation of the Effects of Soil Layer Classification in the Common Land Model on Modeled Surface Variables and the Associated Land Surface Soil Moisture Retrieval Model." Remote Sens. 5, no. 11: 5514-5529.

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