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土壤水分是地表过程的核心变量之一,强烈影响着陆表—植被—大气间的能量和水分交换。当前基于星载被动微波遥感的土壤水分产品的空间分辨率普遍较粗(25~40km),无法满足流域尺度水文气象、生态水文模拟及水资源管理等研究和应用的需求,而土壤水分降尺度是目前较为可行的解决方案之一。通过对不同降尺度指标的研究,分析确定每种降尺度指标的适用条件,为土壤水分的降尺度研究奠定基础。利用2013年5月1日~9月30日黑河中游人工绿洲试验区大满超级站的气象数据驱动SiB2模型,分别模拟了土壤水分、土壤表层温度、植被冠层温度以及地表蒸散发、土壤蒸发等变量,利用Penman-Monteith公式计算了地表潜在蒸散发;利用SiB2模拟结果与P-M公式计算结果估算获得常用的土壤水分降尺度指标:表观热惯量(ATI)、土壤蒸发(E)、土壤蒸发/实际蒸散发(E/ETa)、蒸发比(EF)、实际蒸发比(AEF)。通过对降尺度指标与土壤水分之间相关性分析可知,在植被的整个生长季,5种指标与土壤水分之间都具有较好的相关性。其中ATI、E、E/ETa以及EF这4种指标与土壤水分之间的相关性都随着土壤深度的增加而逐渐减弱;而AEF与植被根区土壤水分的相关性最好,更能反映根区土壤水分的动态变化。从可决系数来看,各降尺度指标与土壤水分的相关性排序如下:2cm:E/ETa>EF>E>AEF>ATI;10cm:AEF>EF>E/ETa>E>ATI;80cm:EF>AEF>E/ETa>E>ATI。
Soil moisture is one of the core variables in the surface processes that strongly influence the exchange of energy and moisture between the land surface-vegetation-atmosphere. At present, the spatial resolution of soil moisture products based on spaceborne passive microwave remote sensing is generally coarse (25 ~ 40km), which can not meet the needs of research and application such as hydrology and meteorology, eco-hydrology and water resources management in watersheds. However, Is one of the more feasible solutions. Through the research on different downgrade indexes, the suitable conditions of each downgrade index are analyzed and analyzed, which lays the foundation for the research on the downscaling of soil moisture. The SiB2 model was driven by meteorological data from Dayan Super Station in artificial oasis test area in Mid-Heihe River from May 1, 2013 to September 30, 2013 to simulate soil moisture, soil surface temperature, vegetation canopy temperature and surface evapotranspiration respectively. Soil evaporation The potential evapotranspiration of the surface was calculated by Penman-Monteith formula. The commonly used index of soil moisture reduction was estimated by SiB2 simulation and PM formula. Apparent thermal inertia (ATI), soil evaporation (E), soil evaporation / Actual evapotranspiration (E / ETa), evaporation ratio (EF), actual evaporation ratio (AEF). By analyzing the correlation between downscaling index and soil moisture, we can see that there is a good correlation between the five indexes and soil moisture throughout the growing season. The correlations of ATI, E, E / ETa and EF with soil moisture decreased with the increase of soil depth. However, the correlation between AEF and soil moisture in the vegetation root zone was the best Dynamic Changes of Soil Moisture in the Root Zone. In terms of the coefficient of determination, the correlation between the downscaling index and soil moisture is as follows: 2cm: E / ETa> EF> E> AEF> ATI; 10cm: AEF> EF> E / ETa> EF> AEF> E / ETa> E> ATI.