Abstract
Deep soil moisture is a highly important source of water for vegetation in the semiarid Loess Plateau of China, vegetation restoration reduced the deep soil moisture, but how to better quantify the impact of vegetation restoration on deep soil moisture is lack of certain understanding. To explore the impact exerted by different types of vegetation on deep layers of the soil moisture, the 0–10 m soil moisture content profile was measured before and after the rainy season in Armeniaca sibirica, Robinia pseudoacacia, Populus simonii, Pinus tabuliformis, Hippophae rhamnoides and in natural grassland in Wuqi County in Shannxi Province. These results showed that the highest soil moisture in the shallow layers (0–200 cm) was exhibited in the P. simonii forest, which was followed by that in the natural grassland. Both of these results were significantly higher than that those of the A. sibirica, P. tabuliformis, H. rhamnoides and R. pseudoacacia forests. The soil moisture in the deep layer (200–1000 cm) of the natural grassland was significantly higher than that of the other vegetation types. The annual precipitation that recharges the depth of soil moisture was the highest in natural grassland and the lowest in P. simonii. The inter-annual soil moisture replenishment is primarily affected by rainfall and vegetation types. Compared with the natural grassland, the CSWSD (the comparison of the soil moisture storage deficit) of different vegetation types varies. In the shallow soil layer, P. simonii is the lowest, and R. pseudoacacia is the highest. In the deep soil layer, R. pseudoacacia and P. simonii are the highest; H. rhamnoides is the second highest, and A. sibirica and P. tabuliformis are the lowest. These results indicate that vegetation restoration can significantly reduce the amount of water in the deep layers of the soil. In the future vegetation restoration, we suggest emphasizing natural development more strongly, since it can better maintain the local vegetation stability and soil moisture balance.
Funding Information
  • the 13th Five-year National Key Research and Development Project Funded by the Ministry of Science and Technology (MOST), P.R. China (No.2016YFC0501705)