Peak discharge of a Pleistocene lava-dam outburst flood in Grand Canyon, Arizona, USA

The failure of a lava dam 165,000 yr ago produced the largest known flood on the Colorado River in Grand Canyon. The Hyaloclastite Dam was up to 366 m high, and geochemical evidence linked this structure to outburst-flood deposits that occurred for 32 km downstream. Using the Hyaloclastite outburst-flood deposits as paleostage indicators, we used dam-failure and unsteady flow modeling to estimate a peak discharge and flow hydrograph. Failure of the Hyaloclastite Dam released a maximum 11 × 10⁹ m³ of water in 31 h. Peak discharges, estimated from uncertainty in channel geometry, dam height, and hydraulic characteristics, ranged from 2.3 to 5.3 × 10⁵ m³ s⁻¹ for the Hyaloclastite outburst flood. This discharge is an order of magnitude greater than the largest known discharge on the Colorado River (1.4 × 10⁴ m³ s⁻¹) and the largest peak discharge resulting from failure of a constructed dam in the USA (6.5 × 10⁴ m³ s⁻¹). Moreover, the Hyaloclastite outburst flood is the oldest documented Quaternary flood and one of the largest to have occurred in the continental USA. The peak discharge for this flood ranks in the top 30 floods (>10⁵ m³ s⁻¹) known worldwide and in the top ten largest floods in North America.     

Comparison of methods to model the gravitational gradients from topographic data bases

A number of methods have been developed over the last few decades to model the gravitational gradients using digital elevation data. All methods are based on second-order derivatives of the Newtonian mass integral for the gravitational potential. Foremost are algorithms that divide the topographic masses into prisms or more general polyhedra and sum the corresponding gradient contributions. Other methods are designed for computational speed and make use of the fast Fourier transform (FFT), require a regular rectangular grid of data, and yield gradients on the entire grid, but only at constant altitude. We add to these the ordinary numerical integration (in horizontal coordinates) of the gradient integrals. In total we compare two prism, two FFT and two ordinary numerical integration methods using 1" elevation data in two topographic regimes (rough and moderate terrain). Prism methods depend on the type of finite elements that are generated with the elevation data; in particular, alternative triangulations can yield significant differences in the gradients (up to tens of Eötvös). The FFT methods depend on a series development of the topographic heights, requiring terms up to 14th order in rough terrain; and, one popular method has significant bias errors (e.g. 13 Eötvös in the vertical–vertical gradient) embedded in its practical realization. The straightforward numerical integrations, whether on a rectangular or triangulated grid, yield sub-Eötvös differences in the gradients when compared to the other methods (except near the edges of the integration area) and they are as efficient computationally as the finite element methods.     

内蒙古中部重、磁场特征与地壳密度结构

中亚造山带中的古生代——中生代花岗岩普遍具有正εNd值，在世界上是十分独特的。美国西部加利福尼亚中生代-新生代花岗岩同样具有正εNd值，并且其地壳的速度分布特征与内蒙古中部十分相似。本文通过与美国加利福尼亚的地球物理研究成果进行对比，来研究内蒙古中部的地壳密度结构，特别是下地壳的组成，试图探讨产生正￡。值花岗岩的深部地质原因。研究结果表明，在大兴安岭-内蒙古造山带下地壳中可能存在与美国加里福尼亚类似的洋壳物质。此外，还对重、磁异常进行了处理，以确定蛇绿岩带的延展情况。由于在西拉木伦河附近存在切割至莫霍面的深断裂，结合地表出现的蛇绿岩带，故提出温都尔庙-西拉木伦河一线可能是内蒙古中部最重要的地质构造界线。     

Outlier detection algorithms and their performance in GOCE gravity field processing

The satellite missions CHAMP, GRACE, and GOCE mark the beginning of a new era in gravity field determination and modeling. They provide unique models of the global stationary gravity field and its variation in time. Due to inevitable measurement errors, sophisticated pre-processing steps have to be applied before further use of the satellite measurements. In the framework of the GOCE mission, this includes outlier detection, absolute calibration and validation of the SGG (satellite gravity gradiometry) measurements, and removal of temporal effects. In general, outliers are defined as observations that appear to be inconsistent with the remainder of the data set. One goal is to evaluate the effect of additive, innovative and bulk outliers on the estimates of the spherical harmonic coefficients. It can be shown that even a small number of undetected outliers (<0.2 of all data points) can have an adverse effect on the coefficient estimates. Consequently, concepts for the identification and removal of outliers have to be developed. Novel outlier detection algorithms are derived and statistical methods are presented that may be used for this purpose. The methods aim at high outlier identification rates as well as small failure rates. A combined algorithm, based on wavelets and a statistical method, shows best performance with an identification rate of about 99%. To further reduce the influence of undetected outliers, an outlier detection algorithm is implemented inside the gravity field solver (the Quick-Look Gravity Field Analysis tool was used). This results in spherical harmonic coefficient estimates that are of similar quality to those obtained without outliers in the input data.