Spring Phenology Model Of Grassland Based On Soilmoisture And Air Temperature And Vegetation Reactions To Drought

As an important factor for human activities and material cycle, Net Primary Productivity (NPP) of terrestrial ecosystem is dramatically influenced by phenology change and drought, which are easily disturbed and induced by tendentious climate change and climate extremes. Soil moisture is an important variable that related to pehnology change and drought. Existing regional phenology models do not provide enough consideration on water conditions. Precipitation is frequently used instead of soil moisture which, however, is the more direct variable that the growth of vegetation depend on. By taking soil moisture as a critical environmental variable, based on regional hydrological model and remote sensing, a regional grassland phenology model and vegetation drought reconstruction model were built up, which will be a meaningful work on regional phenology model and vegetation drought research.A logarithmic model was used to identify the main phenomenon of grassland phenology in the study area. The model was based on the NDVI data retrieved from AVHRR. The main characteristics of phenology over Inner Mongolia and Qinghai-Tibetan Plateau grasslands over China were disclosed. Analyses were carried out on the nonstationarities of phenology and its impact factors. The applicability of the model was also discussed.Based on the analyses of phenology factors, Soil moisture was found to be a better element for phenology analysis. Inspired by the idea of TSO (Thermal Spring Onset), An index was made up for potential vegetation spring-up date controlled by soil moisture, SMSO(Soil Moisture Spring green-up Onset date) and PSO (Precipitation Spring green-up Onset date) to stand for the spring-up date controlled by precipitation. Results proved that the index based on soil moisture is superior to the precipitation index in regional phenology study.Based on the index proposed above, a grassland spring phenology model and the grassland spring phenology dominant factor model were established, and the models were then applied over Inner Mongolia and Qinghai-Tibetan Plateau grasslands. The grassland spring phenology model avoided the drawbacks of fixed accumulation span. The grassland spring phenology dominant factor model could depict the decadal shift of dominant factor and quantitatively describe the dominant role of factors. It could also be used to analyze the evolution of dominant factors with the projection of future climate change. Results showed that the dominant factor in both grasslands (Inner Mongolia and Qinghai-Tibetan Plateau) is water condition instead of thermal condition. The control of the current dominant factors is inclined to be reinforced under the SRES B2scenario.An index called NDVIP (NDVI Percentile) was proposed based on NDVI retrieved from MODIS, and a vegetation drought reconstruction model was established. The index was used to reconstruct the drought events over Colorado River Basin. Comparative studies showed that NDVIP is a more direct index for the description of drought. Resistance and recovery abilities of vegetation under drought were also defined and calculated. Different types of vegetations showed different responses to drought events.