摘要:土壤水分是地表和大气循环的纽带，对植被生长和高效农业灌溉起着关键作用。以石羊河流域为研究区，采用植被覆盖度/表面反照率梯形特征空间散点图计算裸土反照率，减少植被对遥感获取土壤水分误差，以提高遥感土壤水分估算精度。同时通过稳定性、空间自相关和地理探测器等分析了SM的空间格局及其影响因素。结果表明：（1）裸土反照率模型在石羊河流域的SM反演精度较高，为流域尺度的SM计算提供了新的方法思考。（2） SM具有明显的空间自相关性，Moran's值为0.88（Z-score=1852.94，P<0.01），上游林地高-高聚集，下游荒漠低-低聚集，且SM与FVC显著相关（P<0.01）。（3）石羊河流域年内SM稳定性整体良好，其中稳定性好和较好区域占研究区88.34%。（4） SM空间分布受多因子影响，各因子解释能力存在显著差异，其中植被覆盖度 > 土壤类型 > 高程 > 土地利用，且因子间交互作用增强了对SM空间分异的解释力。（5）不同土地利用类型的SM差异较大，其中未利用地大部分SM小于7%；草地和耕地SM居于中等水平，SM值为7%-15%；林地水平最高，SM值大于25%。



Abstract:Soil moisture is the link between the surface and atmospheric circulation. It is an important part of hydrological cycle and water-heat balance. And it plays a key role in vegetation growth and efficiently agricultural irrigation. Therefore, accurate and fast soil moisture remote sensing inversion results are importantly basic data for agricultural production and ecological environment protection. The MODIS-MYD09A1 data with a spatial resolution of 500 meters and a temporal resolution of 8 days was used to calculate the surface albedo. The MODIS-MYD13A1 NDVI product data with a spatial resolution of 250 meters and a temporal resolution of 16 days was used to calculate vegetation coverage. In order to improve the estimation accuracy of the remote sensing soil moisture in the Shiyang River Basin, bare soil albedo was calculated by using vegetation coverage and surface albedo trapezoidal characteristics space scatter plot, this is to reduce the error of vegetation on soil moisture in remote sensing. The measured data was used to evaluate the accuracy of the inversion model. The inversion results of the bare soil albedo model were used to grade and map. At the same time, the spatial pattern of SM and its influencing factors were analyzed through stability analysis, spatial autocorrelation analysis and geographic detectors. The results show that: (1)The bare soil albedo model could yield more accurate soil moisture inversion accuracy in the Shiyang River Basin, which provided a new method for the SM calculation at the watershed scale. (2)Soil moisture had obviously spatial autocorrelation, Moran's value was 0.88 (Z-score=1852.94, P<0.01). Forest land in the upstream was high-high aggregation. Desert in the downstream was low-low aggregation. Soil moisture was significantly correlated with fractional vegetation coverage (P<0.01). (3) The annual overall stability of the soil moisture in the Shiyang River Basin being good, good stability and better stability area accounted for 88.34% of the study area. (4) The spatial distribution of soil moisture was affected by multifactor. And the explanatory ability of each factor was significantly different. Among these factors, vegetation coverage had the best interpretive ability. Soil type was in the second place. Elevation was in the third place and land use was at the end.The interaction between factors enhanced the explanatory ability of the spatial differentiation of soil moisture. (5) The soil moisture of different land use types was quite different. Among them, the soil moisture of most unused land was less than 7%; the soil moisture of grassland and cultivated land was at medium level, with soil moisture value of 7%-15%; the soil moisture level of woodland was the highest, and soil moisture value more than 25%.





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