The runoff generated from mountainous regions is recognized as the main water source for inland river basins in arid environments. Thus, the mechanisms by which catchments retain water in soils are to be understood. The water storage capacity of soil depends on its depth and capacity to retain water under gravitational drainage and evapotranspiration. The latter can be studied through soil water retention curve (SWRC), which is closely related to soil properties such as texture, bulk density, porosity, soil organic carbon content, and so on. The present study represented SWRCs using HYDRUS-1D. In the present study, we measured physical and hydraulic properties of soil samples collected from Sabina przewalskii forest (south-facing slope with highest solar radiation), shrubs (west-facing slope with medium radiation), and Picea crassifolia forest (north-facing slope with lowest radiation), and analyzed the differences in soil water storage capacity of these soil samples. Soil water content of those three vegetation covers were also measured to validate the soil water storage capacity and to analyze the relationship between soil organic matter content and soil water content. Statistical analysis showed that different vegetation covers could lead to different soil bulk densities and differences in soil water retention on the three slope aspects. Sand content, porosity, and organic carbon content of the P. crassifolia forest were relatively greater compared with those of the S. przewalskii forest and shrubs. However, silt content and soil bulk density were relatively smaller than those in the S. przewalskii forest and shrubs. In addition, there was a significant linear positive relationship between averaged soil water content and soil organic matter content (P<0.0001). However, this relationship is not significant in the P. crassifolia forest. As depicted in the SWRCs, the water storage capacity of the soil was 39.14% and 37.38% higher in the P. crassifolia forest than in the S. przewalskii forest and shrubs, respectively, at a similar soil depth.
Understanding the response mechanism of ecosystems to climate change and human disturbance can be improved by analyzing the spatial patterns of vegetation phenology and its influencing factors. Because the diverse phenological patterns are impacted by cloud cover contamination issues in the satellite observations, there are few remote sensing phenological research data in subtropical monsoon climate regions. To better understand the horizontal and vertical changes of vegetation phenology in these regions and how it may be affected by climatic factors and topographical features, we first extracted vegetation phenological information (such as start of growth season (SOS), end of growth season (EOS) and length of growth season (LEN)) from a reconstructed MODIS EVI time-series data. We then used geographic detectors to identify the influencing factors of phenology in different elevation zoning areas. We have found that in the Xiangjiang River Basin: 1) gradual changes in the longitudinal or latitudinal gradient of vegetation phenology were not obvious. Instead of horizontal changes, the variation pattern of phenology was similar to the striped river network of the Xiangjiang River. Earlier SOS mainly appeared in the areas far away from the river; later SOS appeared in the midstream and downstream reaches.2) Elevation played an important role in the regional differentiation of phenology. Boundaries at elevations of 320 m and 520 m distinctly separated the region into plain, hilly, and mountain vegetation phenological characteristics. 3) The impacts of climatic factors were quite different in the three vertical zoning areas. Precipitation was the most crucial factor affecting SOS both in plain and mountain areas. There was no significant factor affecting EOS in the plain area, but temperature had an essential effect on EOS in the mountain area. The hilly areas had a concentrated growth period with no significant factors affecting phenology. These findings highlight the importance of elevation in phenology at a watershed scale, enhance our understanding of the impact of climate changes on subtropical ecosystems, and provide a reference for further land-use change monitoring.
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