Abstract:
Abstract: The alteration of water and carbon cycles can produce great influence on the terrestrial ecosystem, as far as to the whole earth. Vegetation water use efficiency (WUE) is the important variable on the contact of a carbon cycle and hydrological cycle in the vegetation ecosystem. In addition, study of vegetation WUE, in Yangtze and Yellow River Headwater Region, can provide important support for region ecological environment development. Therefore, in order to obtain the change characteristics of the hydrologic and carbon cycle within the terrestrial ecosystem under a data shortage condition, this manuscript, focused on the advantages and applicability of light energy utilization model (CASA model) and a FAO Penman-Monteith model, estimated the vegetation WUE and analyzed the dynamic change situation from year 2000 to 2010. Furthermore, test data which consisted of several vegetation types were subject to verification. The results revealed that a CASA model could reflect vegetation WUE distribution characteristics preferable in time and space. During the study phase, a decrease trend of vegetation WUE was obvious. Moreover, a changing rate of partition, in the Yellow River headwater Region and Yangtze headwater region, was relatively different. In terms of these two area, the alpine grassland in the Yellow River headwater Region showed more obvious expression to reducing than that of the Yangtze headwaters region. As far as the regulation was concerned within the year, continuous mono-peek distributions mainly appeared in the Yangtze headwaters region. In addition, changes by leaps and bounds turned up in the Yellow River Headwater Region. These cases showed that carbon sequestration capacity in the Yangtze headwaters region was much better during the calculation period. In addition, studies of principal component analysis indicated that the factors, such as NDVI, temperature, precipitation, solar radiation, and evaporation are closely related to vegetation WUE. Especially the NDVI, precipitation, and temperature were the main influencing factors in the study area.