Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

An approximate method for evaluating the shear band thickness in saturated soils

A formula for the thickness of a shear band formed in saturated soils under a simple shear or a combined stress state has been proposed. It is shown that the shear band thickness is dependent on the pore pressure properties of the material and the dilatancy rate, but is independent of the details of the combined stress state. This is in accordance with some separate experimental observations. Copyright © 2004 John Wiley & Sons, Ltd.     

GPS/LEO掩星观测的变分同化技术

在简单介绍GPS/LEO掩星探测大气的发展历史和科学意义之后,详细阐述了反演的基本原理;分析了标准反演中存在的问题,并说明一维变分同化(1DVAR)在反演方法中的重要性;给出了一维变分同化中价值函数的求解,以及各种同化因子;简单介绍了对当前气象学中普遍使用的四维变分同化(4DVAR);重点讨论了各种同化方法,以及使用各种同化因子的优缺点。最后,通过CHAMP卫星的观测实例分析,验证了GPS数据在数值天气预报(NWP)中的作用,以及相对于标准反演法一维变分对气象要素的改进。     

Optical monitoring of the quasar 4C 38.41

The results of a photometric monitoring of the quasar 4C 38.41, performed at the optical R and B bands in 2002 February–March, are presented. With a 60/90 cm Schmidt telescope at the Xinglong station of the National Astronomical Observatories of China, we observed the source exhibiting amplitude variations of up to 0.78 mag in both bands during the whole campaign. Intraday and even intranight variations are detected as well. A typical variability time-scale of about 36 d is derived from our 2-month observations at the optical bands, which is identical to that found at a radio wavelength of 92 cm, suggesting a common origin for the variations in 4C 38.41 from optical to radio bands.     

Three Super Active Regions in the Descending Phase of Solar Cycle 23

We analyze the magnetic configurations of three super active regions, NOAA 10484, 10486 and 10488, observed by the Huairou Multi-Channel Solar Telescope (MCST) from 2003 October 18 to November 4. Many energetic phenomena, such as flares (including a X-28 flare) and coronal mass ejections (CMEs), occurred during this period. We think that strong shear and fast emergence of magnetic flux are the main causes of these events. The question is also of great interest why these dramatic eruptions occurred so close together in the descending phase of the solar cycle.     

The FAST/SKA site selection in Guizhou province

Many karst depressions with diameters of 300 m to 500 m, suitable for constructing Arecibo-style radio telescopes, were identified in the south of Guizhou Province by Remote Sensing (RS) and Geographic Information System (GIS) technologies together with field investigations. Fundamental topography and landform databases were established for 391candidate depressions, and using GIS the3-dimensional images of depressions, at a scale of 1:10000, were then simulated to fit a spherical antenna. This revised version was published online in July 2006 with corrections to the Cover Date.     

ELECTROCHEMICAL CORROSION BEHAVIOR OF STEEL IN THE JUNCTURE AREA OF SEA CLAY AND SAND

Corrosion behavior of steel in the juncture area of sea clay and sand was studied. The results show that galvanic corrosion occurred between steel samples buried in sea clay and sand, and that the polarity of the galvanic cell reversed after some testing later. The cause of reversing of polarity is discussed.     

CHARACTERIZATION OF LACTATE DEHYDROGENASE ISOZYME PATTERN AND MORPHOLOGY OF THREE MARINE FISH CELL LINES

Three continuous marine fish cell lines of FG (i. e., Hounder Gill) from flounder (Paralichthys olivaceus) gill, SPH (i. e. , Sea Perch Heart) from sea perch (Lateolabrax japonicus) heart and RSBF (i.e., Red Sea Bream Fin) from red sea bream (Pagrosomus major) fin, were characterized by lactate dehydrogenase (LDH) isozyme and morphological analysis. The LDH isozyme patterns of these three cell lines and their corresponding tissues of origin were investigated and compared. The results showed: (1) No difference was found in the LDH isozyme patterns of FG and flounder gill tissue. However, the LDH isozyme patterns of SPH and RSBF were significantly different from their corresponding tissues of origin; (2) LDH isozyme patterns of FG, SPH and RSBF were markedly different from each other and could serve as genetic markers for species identification and detection of cross contamination. Morphological change analysis of these three cell lines in comparison to their original tissues indicated that FG cells still appeared epithelioid without morphological transformation. However, morphological changes were found in SPH and RSBF compared to their original tissues. Therefore, the cellular morphology was still plastic in the relatively stable culture conditions, and it was possible that change of LDH patterns wasrelated to morphological changes of fish cells in vitro.     

地倾斜台站数字化、模拟观测数据频率特性研究

分析了四川、云南的部分地倾斜数字化观测与模拟观测资料的特性，从频率范围，周期10天以上的FFT谱特性，固体潮波振幅，相位特征值等方面，论述了地倾斜数字化资料较模拟记录资料的信息组成变化，并对资料的分析与应用进行了初步探讨。