Variations of precipitation over the eastern edge of the Tibetan Plateau are analyzed by using data over station Yaan including daytime, nighttime, and daily-mean precipitation and satellite-derived information. A comparison of some features over Yaan and other stations is also carried out. Over Yaan, light-moderate precipitation contributes significantly to both the number of rainy days (96.9%) and the amount (66.9%) of total precipitation. The light-moderate precipitation occurs more frequently at nighttime than at daytime (by 44.5 days, or 33.4%, and by 520.6 mm, or 134.4%, each year), and the nighttime precipitation is mainly in the form of light-moderate precipitation. The number of rainy days and the amount of total precipitation have decreased from the 1950s to the 1970s and during the recent 20 years, associated with negative trends of light-moderate precipitation. Similar features are also found in the Tropical Rainfall Measuring Mission satellite data. Local convective precipitation is the main form of the light-moderate precipitation over Yaan. The absorption of latent heat at the lower troposphere and the release of latent heat at the upper troposphere are larger at nighttime than at daytime by 1–2 times and 2–3 times, respectively. Both the peak value and the total release of latent heat over Yaan are significantly larger than those over the Tibetan Plateau, eastern China, and the western Pacific warm pool. These distinct local characteristics of the “rain city” Yaan are closely related to the interaction between the atmospheric circulation and the steep topography on the eastern edge of the Tibetan Plateau. 相似文献
Concentrations of suspended solids in lakes can affect the latter’s primary productivity and reflect changes in sediment deposition. Determining the temporal and spatial distribution of suspended solid concentrations has important significance in lake water environmental management; this is particularly urgent for Poyang Lake, the largest freshwater lake in China. In this study, suspended solid concentration inversion models for Poyang Lake were created using a semi-empirical method with regression analysis between continuously measured suspended solid concentration data and multi-band moderate-resolution imaging spectroradiometer images for spring, summer, autumn, and winter from 2009 to 2012. The coefficient of determination (R2) is from 0.6 to 0.9 and the average relative error for the accuracy verification was between 10 and 30%. The seasonal distributions of suspended solid concentrations in Poyang Lake from 2000 to 2013 were then obtained using optimal reversal models. The results showed that the seasonal variation in suspended solid concentrations had a “W” shape in which high spring and autumn and low summer and winter values. The suspended solid concentrations increased annually from 2000 to 2013 and were mainly distributed in the northern and central portions of the lake, with lower values along the shorelines. Further analysis indicated that the large difference in water level between the wet and dry seasons is an important factor in explaining these seasonal variations. Moreover, the suspended solid concentrations were poorly correlated with water temperature and chlorophyll-a concentration but more highly correlated with the deferred chlorophyll-a concentration. 相似文献
A self-organizing map (SOM) was used to cluster the water quality data of Xiangxi River in the Three Gorges Reservoir region.
The results showed that 81 sampling sites could be divided into several groups representing different land use types. The
forest dominated region had low concentrations of most nutrient variables except COD, whereas the agricultural region had
high concentrations of NO3N, TN, Alkalinity, and Hardness. The sites downstream of an urban area were high in NH3N, NO2N, PO4P and TP. Redundancy analysis was used to identify the individual effects of topography and land use on river water quality.
The results revealed that the watershed factors accounted for 61.7% variations of water quality in the Xiangxi River. Specifically,
topographical characteristics explained 26.0% variations of water quality, land use explained 10.2%, and topography and land
use together explained 25.5%. More than 50% of the variation in most water quality variables was explained by watershed characteristics.
However, water quality variables which are strongly influenced by urban and industrial point source pollution (NH3N, NO2N, PO4P and TP) were not as well correlated with watershed characteristics. 相似文献