Simulation Study Of Climate Change Impacts On Wetlands Productivity In Sanjiang Plain

This study statistics climate change facts in the past60years and predicts thetrends in the next90years, based on meteorological data (1951-2010) of nationalstandard weather station and simulation meteorological data (1951-2100) underA2/A1B/B1emission scenorios of global climate model groups. According to allabove, combinded with several climate-productivity models, this study constructs arisk rating system to assess response characteristics of vegetation productivity in Fujinand Xingkaihu wetlands.1. The heating rate of annual average temperature in Sanjiang Plain is about0.26℃/10a, which is higher than the national average trend(0.22℃/10a between1951and2001). The temperature of growing and non-growing season becomes higher andparticularly significant after1980s. Annual and seasonal maximum and minimumtemperature has an obvious upward trend. Annual precipitation decreases overall at arate of-13mm/10a. Seasonal precipitation increases in winter and spring whiledecreases in summer and autumn. The EOF analysis show that: temperature has largeramplitude in northwest and southeast while smaller in southern and central parts.Annual precipitation has contrary spatial phase distribution with temperature insouthwest, with increasing trend in northern, central and southern parts. The relativehumidity and wetness index reduce decadely, vegetation drying degree increase, andprecipitation days reduce. Extreme minimum temperature increases more significantlythan extreme maximum temperature.The temperature downscaling data of A2emission scenario in Sanjiang and Fujinverify the feasibility of the global simulation data. The average annual temperature ofSanjiang Plain in the next90years is likely to be more and more warm, temperatureanomalies of A2, A1B, B1emission scenarios is about4-5.4°C,3.5-4.5°C,2.5-3 °C, respectively, till the end of21st century. The warming amplitude of growingseason is slightly larger than that of non-growing season. Annual precipitation islikely to increase with rate10.98mm/10a,9.29mm/10a and5.41mm/10a respectivelyunder A2, A1B, B1emission scenarios.2001-2100, precipitation anomaly of spring,summer and fall is largest under A1B scenarios and that of winter is largest under A2.Vegetation dryness index continues to increase, A2, A1B and B1anomalies amountedto0.83°C/mm,0.53℃/mm and0.53°C/mm by the end of the21st century.2. Precipitation is the dominant constrained factor of NPP increasing in wetlands, andhydrothermal coincidence is an important environmental premise. NPP simulationresults under A2, A1B and B1emission scenarios show that: NPP in Fujin andXingkaihu wetlands increase overall between1951and2100, the order of NPP valueis forward> medium>recent. NPP of recent-term volatilities and decreases. Frommedium-term, NPP begin increasing and be stable after2040s. Compared withXingkaihu, Fujin has larger amplitude while smaller NPP value. In recent and forwardterm, A2scenario has better hydrothermal condition and largest NPP increase;Medium-term, the increase amplitude of temperature, precipitation and NPP is largestunder A1B. The NPP amplitude of Fujin is larger than that of Xingkaihu, which showsthe marsh can be impacted more by precipitation than lake wetlands.3. The risk level of NPP is higher with drought and not much affected bywaterlogging. With increasing temperature and precipatation, the amount ofhydrocephalus guaranteed and hydrothermal condition optimizes, which is conductiveto vegetation photosynthesis and increase organic matter, the risk level of NPP willdecrease and make wetlands healthy. Under A1B scenario, the growth of NPP is morestable in Fujin wetland with lower risk level. The NPP risk of Xingkaihu will enterlow level earlier under B1, showing that B1is more conductive to accumulation ofmatter.