Comment on “Field observations of soil moisture variability across scales” by James S. Famiglietti et al.
Comment on “Field observations of soil moisture variability across scales” by James S. Famiglietti et al.
复制标题
对 James S. Famiglietti 等人的“跨尺度土壤湿度变化的现场观察”的评论。
DOI：
10.1029/2008wr006911
复制
发表时间：
2008
影响因子：
5.4
通讯作者：
J. Vanderborght
中科院分区：
文献类型：
--
作者：
H. Vereecken;T. Kamai;Thomas Harter;R. Kasteel;J. Hopmans;J. Huisman;J. Vanderborght
[1]在最近的一篇论文中，Famiglietti等人[2008]分析了36，000多个基于地面的土壤水分测量结果，以描述从2.5米到50公里的空间尺度上的土壤水分变异性。他们的结论是，土壤水分标准差与平均含水量之间的关系，平方（hqi），有一个凸向上的行为与最大值发生在平均含水量为0.17厘米厘米3和0.19厘米厘米3的800米和50公里的规模，分别。在这些数据的基础上，他们推导出变异系数与平均土壤含水量之间的经验关系，以估计平均含水量实地观测的不确定性。作者为科学界提供了这一宝贵的数据库，值得赞扬。我们同意作者的观点，即这些数据对于提高我们对次网格水分变率在陆面过程参数化和模拟中的重要性的理解是重要的。然而，作者仅限于通过拟合平均含水量与变异系数（CV）数据的指数关系对观测数据进行经验描述。我们认为，这是一个错失的机会，并想认为，解释的基础上建立的理论和概念，土壤水文学和升级理论可以提供替代方法和新的见解解释这样的数据集。具体地说，从土壤物理概念可以看出，对于均质土壤，在任何特定的观测尺度上，水分保持曲线的形状都可以在很大程度上解释观测到的表层土壤水分变化。对于非均质土壤，随机尺度放大理论可用于将sq（hqi）与土壤水力特性的空间变异性联系起来。这些理论可以用来预测sq（hqi），并检查这个函数相对于土壤水力性质的敏感性。
[1] In a recent paper, Famiglietti et al. [2008] analyzed more than 36,000 ground-based soil moisture measurements to characterize soil moisture variability across spatial scales ranging from 2.5 m to 50 km. They concluded that the relationship between soil moisture standard deviation versus mean moisture content, sq (hqi), has a convex upward behavior with maximum values occurring at mean moisture contents of 0.17 cm cm 3 and 0.19 cm cm 3 for the 800-m and 50-km scale, respectively. On the basis of these data, they derived empirical relationships between the coefficient of variation and the mean soil moisture content in order to estimate the uncertainty in field observations of mean moisture content. The authors are to be commended for providing this valuable database to the scientific community. We agree with the authors that such data are important in improving our understanding about the importance of subgrid moisture variability in the parameterization and simulation of land surface processes. However, the authors limited themselves to an empirical description of the observed data by fitting exponential relationships to the mean moisture content versus coefficient of variation (CV) data. We feel that this is a missed opportunity and would like to argue that an interpretation based on established theories and concepts in soil hydrology and upscaling theories could provide alternative methods and new insights for interpreting such data sets. Specifically, it can be shown from soil physical concepts that for a homogeneous soil, the shape of the moisture retention curve can largely explain observed variations in surface soil moisture, at any specific observation scale. For heterogeneous soils, stochastic upscaling theories may be used to relate sq (hqi) to spatial variability in soil hydraulic properties. These theories can be used to predict sq (hqi) and to examine the sensitivity of this function with respect to soil hydraulic properties.
使用随机生成模型分析美国专利的引用情况
DOI：
--
发表时间：
2022
期刊：
影响因子：
--
作者：
Sawaki;D;Mizunaga,N;Ojima;T;Akamatsu;Y;Araki Y;成島康史;Takashi Yamanouchi;Yuichiro Yasui and Junji Nakano
通讯作者：
Yuichiro Yasui and Junji Nakano