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Soil moisture is an essential climate variable (ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year (2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Mainland China was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature (TB) data into a land surface model (LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau. The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons (spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center. [ABSTRACT FROM AUTHOR]

Summary: Alpine meadow soil is an important ecosystem component of the Qinghai-Tibetan Plateau. However, the alpine meadow soil is undergoing serious degradation mainly due to global climate change, overgrazing, human activities and rodents. In this paper, spatial sequencing was chosen over time succession sequencing to study the changes of soil hydraulic properties under different degrees of alpine meadow degradation. Soil saturated hydraulic conductivity (Ks) and Gardner α both at the surface and at 40–50cm depth were investigated in the field using tension infiltrometers. Soil physical and chemical properties, together with the root index at 0–10cm and 40–50cm soil layer depths were also analyzed. Pearson correlations were adopted to study the relationships among the investigated factors and principal component analysis was performed to identify the dominant factor. Results show that with increasing degree of degradation, soil sand content increased while soil Ks and Gardner α as well as soil clay content, soil porosity decreased in the 0–10cm soil layers, and organic matter and root gravimetric density decreased in both the 0–10cm and 40–50cm soil layers. However, soil moisture showed no significant changes with increasing degradation. With decreasing pressure head, soil unsaturated hydraulic conductivity reduced more slowly under degraded conditions than non-degraded conditions. Soil Ks and Gardner α were significantly correlated (P =0.01) with bulk density, soil porosity, soil organic matter and root gravimetric density. Among these, soil porosity is the dominant factor explaining about 90% of the variability in total infiltration flow. Under non-degraded conditions, the infiltration flow principally depended on the presence of macropores. With increasing degree of degradation, soil macropores quickly changed to mesopores or micropores. The proportion of total infiltration flow through macropores and mesopores significantly decreased with the most substantial decrease observed for the macropores in the 0–10cm soil layer. The substantial decrease of macropores caused a cut in soil moisture and hydraulic conductivity. This study improves the understanding and prediction of alpine meadow soil and ecosystem changes and provides guidelines for improving water flow modeling under the background of global climate change over the Qinghai-Tibetan Plateau and similar regions. [Copyright &y& Elsevier]