近20年黄河流域夏季土壤水分时空变化特征及驱动因素分析OA北大核心CSTPCD
Temporal and spatial variation of summer soil moisture and its driving factors in Yellow River basin during the last 20 years
利用2001-2020年的中分辨率成像光谱仪产品和全球陆地数据同化系统气象数据,基于"植被指数-地表温度"梯形特征空间模型反演黄河流域夏季的土壤水分,并采用Sen斜率与Mann-Kendall法以及地理探测器进行黄河流域的土壤水分时空变化格局及驱动因素分析.研究结果表明:黄河流域土壤水分在空间上具有明显的空间异质性,黄河源区和下游地区较为湿润,黄河中游相对比较干旱;2001-2020年黄河流域土壤水分含量在空间上主要表现为不显著增加和不显著减少变化趋势,分别占全流域面积的39.54%和58.01%,其中上游地区土壤水分增长速度最快;降水是黄河流域土壤水分时间变化的主导要素,气温和高程是影响黄河上游土壤水分空间变化的主要因子,归一化植被指数和降水是黄河中游土壤水分变化的主要驱动因子.
Based on the moderate resolution imaging spectroradiometer products and global land data assimilation system meteorological data from 2001 to 2020,soil moisture in summer in the Yellow River basin was retrieved based on the vegetation index/land surface temperature trapezoid feature spatial model.The spatial-temporal pattern and driving factors of soil moisture in the Yellow River basin were analyzed using the Sen slope method,Mann-Kendall method,and geographical detector.The results showed that soil moisture in the Yellow River basin had apparent spatial heterogeneity.The source and lower reaches of the Yellow River are humid,while the middle reaches are relatively dry.From 2001 to 2020,soil moisture in the Yellow River basin showed an insignificant increase and an insignificant decrease in space,accounting for 39.54%and 58.01%of the regional area,respectively.The growth rate of soil moisture in the upper reaches was the fastest.Precipitation is the dominant factor of temporal variation of soil moisture in the Yellow River basin.Temperature and elevation are the main factors affecting the spatial variation of soil moisture in the upper reaches,and normalized difference vegetation index and precipitation are the main driving factors influencing soil moisture change in the middle reaches of the Yellow River.
张亚楠;宋小宁;冷佩;高亮;尹德伟
中国科学院大学资源与环境学院,北京 101408||中国科学院大学北京燕山地球关键带国家野外科学观测研究站,北京 101408中国农业科学院农业资源与农业区划研究所,北京 100081
计算机与自动化
黄河流域土壤水分时空变化梯形特征空间模型地理探测器
Yellow River basinsoil moisturespatial-temporal patterntrapezoid feature spatial modelgeographical detector
《中国科学院大学学报》 2024 (004)
477-489 / 13
国家自然科学基金(42041005)资助
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