利用1992年沃希托试验流域的微波遥感资料，对100 m ~ 10 km尺度的土壤水分变化进行了功率谱分析。功率谱S（k）与波数k近似呈幂律关系，指数为-1.8。这种行为是一致的随机微分方程的土壤水分在一个点的行为。这种行为对滑坡的频率-规模分布有重要影响。我们提出了累积频率的大小分布的滑坡在日本和玻利维亚的降水，以及滑坡引发的1994年北岭，加利福尼亚州地震。尽管这些地区的大型滑坡是由不同的机制触发的，但其累积频率-规模分布与面积呈幂律关系，指数范围为-1.5至-2。我们使用土壤水分场与上述统计数据结合边坡稳定性分析来模拟滑坡的频率-大小分布。在我们的模型中，当超过取决于粘聚力、孔隙压力、内摩擦力和坡角的阈值剪应力时，发生滑坡。这意味着阈值依赖于土壤水分和坡度，因为这些因素主要取决于土壤水分。摘要继续在纸上。
英文摘要：
Power spectral analyses of soil moisture variability are carried out from scales of 100 m to 10 km on the microwave remotely-sensed data from the Washita experimental watershed during 1992. The power spectrum S(k) has an approximately power-law dependence on wave number k with exponent -1.8. This behavior is consistent with the behavior of a stochastic differential equation for soil moisture at a point. This behavior has important consequences for the frequency-size distribution of landslides. We present the cumulative frequency-size distributions of landslides induced by precipitation in Japan and Bolivia as well as landslides triggered by the 1994 Northridge, California earthquake. Large landslides in these regions, despite being triggered by different mechanisms, have a cumulative frequency-size distribution with a power-law dependence on area with an exponent ranging from -1.5 to -2. We use a soil moisture field with the above statistics in conjunction with a slope stability analysis to model the frequency-size distribution of landslides. In our model landslides occur when a threshold shear stress dependent on cohesion, pore pressure, internal friction and slope angle is exceeded. This implies a threshold dependence on soil moisture and slope angle since these factors are primarily dependent on soil moisture. Abstract continued in paper.
Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院）
In this contribution, we investigate the potential of hyperspectral data combined with either simulated ground penetrating radar (GPR) or simulated (sensor-like) soil-moisture data to estimate soil moisture. We propose two simulation approaches to extend a given multi-sensor dataset which contains sparse GPR data. In the first approach, simulated GPR data is generated either by an interpolation along the time axis or by a machine learning model. The second approach includes the simulation of soil-moisture along the GPR profile. The soil-moisture estimation is improved significantly by the fusi…
Inversion methodology has been used to obtain, from multi-layer soil probes records, a complete soil parametrisation, namely water retention curve, unsaturated conductivity curve and bulk density at 4 depths. The approach integrates water dynamics, hysteresis and the effect of bulk density on conductivity to extract soil parameters required from most simulation models. The method is applied to sub-sets of data collection, allowing to understand that not every data-sets contains the information required for method convergence. A comparison with experimental bulk-density values show that inversi…
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach has the potential to be one of the best space-time trade-off methods, representing a joining link between punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is theoretically derived taking into account a non-c…
The proper determination of soil moisture on different scales is important for applications in a variety of fields. We aim to develop a high-level soil moisture product with high temporal and spatial resolution by assimilating the multilayer soil moisture product SCATSAR-SWI (Scatterometer Synthetic Aperture Radar Soil Water Index) into the surface model SURFEX. In addition, we probe the impact of the findings on the Numerical Weather Prediction (NWP) in Austria. The data assimilation system consists of the NWP model AROME and the SURFEX Offline Data Assimilation, which provide atmospheric for…
Most of the damaging geo-hazards recorded in modern history are caused by soil swelling or expansion. Therefore, proper evaluation of a soils capacity to swell is very crucial for the achievement of a secure and safe foundation for civil infrastructure. Hence, in this brief, a dataset of standardised one-dimensional soil swelling on laboratory engineered and natural soils is reported. Corresponding properties of these soils such as moisture content, void ratio, specific gravity, unit weight, Atterberg limits, size fractions, soil activity index including the state of compaction of the soils wh…
Modeling water flow in unsaturated soils is vital for describing various hydrological and ecological phenomena. Soil water dynamics is described by well-established physical laws (Richardson-Richards equation (RRE)). Solving the RRE is difficult due to the inherent non-linearity of the processes, and various numerical methods have been proposed to solve the issue. However, applying the methods to practical situations is challenging because they require well-defined initial and boundary conditions. Here, we present a physics-informed neural networks (PINNs) method that approximates the solution…
Warming-driven rise in soil moisture entropy signals destabilization of the Asian Water Tower
Beijing Normal University（北京师范大学）；Technical University of Munich（慕尼黑工业大学）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Chinese Academy of Meteorological Sciences（中国气象科学研究院）；Tsinghua University（清华大学）；Kunming University of Science and Technology（昆明理工大学）
An application of the Soil Moisture Agricultural Drought Index (SMADI) at the global scale is presented. The index integrates surface soil moisture from the SMOS mission with land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS and allows for global drought monitoring at medium spatial scales (0.05 deg).. Biweekly maps of SMADI were obtained from year 2010 to 2015 over all agricultural areas on Earth. The SMADI time-series were compared with state-of-the-art drought indices over the Iberian Peninsula. Results show a good agreement between SMADI and the Cr…
