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Monthly variation in soil moisture under Caragana intermedia stands grown in desert steppe.

SONG Nai-ping1,2**, YANG Ming-xiu1,2, WANG Lei1,2, WANG Xing1,2, XIAO Xu-pei1,2, QU Wen-jie1,2   

  1. (1State Key Laboratory Breeding Base of Land Degradation and Ecological Restoration of Northwest China, Yinchuan 750021, China; 2Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwest China of Ministry of Education, Ningxia University, Yinchuan 750021, China)
  • Online:2014-10-10 Published:2014-10-10

Abstract: Caragana shrub has been widely planted to prevent ecological deterioration in desert steppe. However, water capacity is the most important factor limiting the development of Caragana in this area. Annual variations of soil moisture in Caragana stands with different ages (9, 16 and 26 years old) and natural grassland in April, August, October in 2012 and March, April in 2013 were studied. The results showed that: (1) Similar soil moisture dynamic pattern was observed in the different Caragana stands in an annual cycle. Soil moisture was dramatically depleted from May to August and recovered in September. Soil water underwent slight depletion from October in 2012 to February in 2013. The depleting process of soil moisture was accelerated from March to April. (2) There was no significant difference in soil moisture between grassland and Caragana stands, while a significant difference in soil moisture was found between the Caragana stands with different ages. (3) The annual closure errors of soil moisture for the different Caragana stands were under deficit. The least soil water deficit was recorded for the 26-year-old Caragana stand, indicating its low water consumption and strong ability to keep soil water balance. (4) The precipitation distribution, soil texture and rooting character had profound effects on the soil moisture in desert steppe.

Key words: chlorophyll content, vegetation index, principal component analysis, red edge parameters, hyperspectral, BP neural network