高寒草甸生态系统表层土壤水分时间稳定性研究
发布时间：2018-09-13 13:40
【摘要】：选取西藏高原北部那曲地区一处典型的高寒草甸生态系统为研究对象,用TDR 300测量样地中2个样带共82个测点表层0~7.5 cm的土壤含水率,在2015年生长季中共测量14次。基于所测数据分析了土壤含水率的时空变异性和时间稳定性。结果表明,2015年生长季2个样带表层平均土壤含水率为26.0%,在空间上表现为弱变异性,在时间上表现为中等变异性,土壤含水率较高时,土壤水分的变异性也较高;82个测点土壤含水率的空间模式在7月份—8月初相似性较弱,在8月中旬—9月初相似性较强;土壤含水率的相对差分平均值在-11.5%~8.5%之间,相对差分标准差的平均值为8.6%,二者表现为开口向上的二次曲线关系,说明土壤含水率接近样地平均值的测点具有较高的时间稳定性,而在较干和较湿的测点,土壤含水率的时间稳定性相对较弱;时间稳定性指数、平均绝对偏差、均方根误差和最小相对差分标准差平衡法4种方法均能准确地判定土壤含水率时间稳定性最佳代表测点,利用最佳代表测点估算样带平均土壤含水率均具有较高的精度,相比较而言,最小相对差分标准差平衡法精度更高。
[Abstract]:A typical alpine meadow ecosystem in Naqu region of northern Tibet Plateau was selected as the research object. Soil moisture content of 0 ~ 7.5 cm in the surface layer of 82 samples was measured by TDR 300, and the soil moisture content was measured 14 times in 2015 growing season. The temporal and spatial variability and time stability of soil moisture content were analyzed based on the measured data. The results showed that the average soil moisture content in the surface layer of the two zones was 26.0 in the growth season of 2015, showing weak variability in space, moderate variability in time, and high soil moisture content. The spatial model of soil moisture content in 82 sites was weak in July and early August, and the similarity was stronger in mid-August and early September, and the relative difference average value of soil moisture content was -11.5% or 8.5%. The average value of the relative difference standard deviation is 8.6. The relationship between the two shows the conic relation of opening up, which indicates that the measuring point with soil moisture content close to the average value of the sample land has higher time stability, while at the dry and wet measuring points, The time stability of soil moisture content is relatively weak, the time stability index, mean absolute deviation, root mean square error and minimum relative difference standard deviation balance method can accurately determine the best time stability of soil moisture content. The precision of estimating the average soil moisture content by using the best representative measuring point is higher than that of the minimum relative difference standard deviation equilibrium method.
【作者单位】： 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室;中国科学院大学资源与环境学院;
【基金】：国家自然科学基金项目(41230746)
【分类号】：S152.7
本文编号：2241333
[Abstract]:A typical alpine meadow ecosystem in Naqu region of northern Tibet Plateau was selected as the research object. Soil moisture content of 0 ~ 7.5 cm in the surface layer of 82 samples was measured by TDR 300, and the soil moisture content was measured 14 times in 2015 growing season. The temporal and spatial variability and time stability of soil moisture content were analyzed based on the measured data. The results showed that the average soil moisture content in the surface layer of the two zones was 26.0 in the growth season of 2015, showing weak variability in space, moderate variability in time, and high soil moisture content. The spatial model of soil moisture content in 82 sites was weak in July and early August, and the similarity was stronger in mid-August and early September, and the relative difference average value of soil moisture content was -11.5% or 8.5%. The average value of the relative difference standard deviation is 8.6. The relationship between the two shows the conic relation of opening up, which indicates that the measuring point with soil moisture content close to the average value of the sample land has higher time stability, while at the dry and wet measuring points, The time stability of soil moisture content is relatively weak, the time stability index, mean absolute deviation, root mean square error and minimum relative difference standard deviation balance method can accurately determine the best time stability of soil moisture content. The precision of estimating the average soil moisture content by using the best representative measuring point is higher than that of the minimum relative difference standard deviation equilibrium method.
【作者单位】： 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室;中国科学院大学资源与环境学院;
【基金】：国家自然科学基金项目(41230746)
【分类号】：S152.7
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