2000~2016年太湖流域植被NPP与土壤水文要素的时空耦合研究

Spatiotemporal Coupling Between Vegetation NPP and Soil Hydrological Elements in Taihu Lake Basin from 2000 to 2016

陆地生态系统碳水循环的耦合关系是当前全球变化研究的热点之一。但目前的研究主要集中在干旱与半干旱地区,湿润地区陆域碳水耦合机制尚不明晰。以太湖流域为研究区,基于遥感与GIS技术定量分析2000~2016年流域内植被净初级生产力(Net Primary Productivity,NPP)、土壤水分与蒸散发之间的时空耦合关系。结果表明,NPP与水文要素在不同时空尺度上的耦合关系显著不同:整时段月尺度内,流域蒸散发与NPP均为显著正相关关系,99.86%区域的土壤水分与NPP为负相关关系;年际尺度内,三者之间的相关性均减弱;季尺度内,82%区域土壤水分与NPP在春、夏、秋季为负相关关系,其中春季最为显著,这主要与土地覆被、植物生长期等的差异有关。此外,三者之间的相关性与地形因子关系密切,具体表现为随着坡度或海拔增加而减弱的趋势。最后,研究还发现基于整时段月尺度水文气象要素逐像元建立的随机森林模型(RF_All模型)能够对流域NPP进行较好地估算与预测(R^(2)=0.97,RMSE=4.16 gC m^(-2)a^(-1),Bias=0.37 gC m^(-2)a^(-1))。研究结论对于制定全球变化背景下太湖流域生态建设与可持续发展政策具有重要的理论指导意义。

The coupling relationship between carbon and water cycles in terrestrial ecosystems is one of the hot spots of global change research.However,the current research is mainly in arid and semi-arid areas,and the coupling mechanism of terrestrial carbon and water in humid regions is still unclear.Based on Remote Sensing and GIS,the coupling relationship between vegetation net primary productivity(NPP),soil moisture and evapotranspiration in Taihu Lake Basin was analyzed at different spatial and temporal scales.The results showed that the coupling relationships between NPP and hydrological elements were significantly different at different spatial and temporal scales:Based on all monthly data during the study period,evapotranspiration and NPP were significantly positively correlated,while soil moisture in 99.86%regions was negatively correlated with NPP.In the interannual scale,the correlation between the three was weakened.At the seasonal scale,soil moisture and NPP were negatively correlated in 82%of regions in spring,summer and autumn,among which spring was the most significant,which was mainly related to the difference of land cover and plant growth period.The study further found that the correlation between the three was closely related to topographic factors,which was manifested as a trend of weakening with the increase of slope or altitude.Finally,it was found that the Random forest model(RF_All model)based on the whole period monthly scale hydro-meteorological elements could estimate and predict the NPP of the basin well(R~2=0.97,RMSE=4.16 gC m~(-2)a~(-1),Bias=0.37 gC m~(-2)a~(-1)).The conclusion of this study has important theoretical significance for formulating the policy of ecological construction and sustainable development of Taihu basin under the background of global change.