Relict mountain slope deposits of northern Portugal: facies,sedimentogenesis and environmental implications

This paper deals with the formation processes and the palaeoenvironmental significance of relict slope deposits located on the uppermost part of the north Portugal mountains. For this purpose, seven key sites representative of the different lithofacies have been selected and analysed in detail. The data show that three main dynamic processes are responsible for the emplacement of regional fossil slope deposits: runoff, debris flows and dry grain flows. The ubiquity of these processes and the lack of frost‐related features or landforms do not support the existence of severe Pleistocene climates in this part of the lberian Peninsula as postulated by previous work. Pedological data gathered at one of the study sites show that a subalpine environment was probably present at 700–800 m altitude between 29 and 14 kyr. Using data from the Pyrenees Mountains, a 6.5 to 12°C depression in mean annual temperature has been tentatively postulated for this Pleniglacial period. Copyright © 2003 John Wiley & Sons, Ltd.     

The grain-size characteristics of Quaternary deposits at Xingshan near Siping in Jilin province, China

This research paper analyses the grain-size characteristics of the Quaternary deposits at Xingshan near Siping, Jilin province in China by employing graphic measures to study the grain size distribution and its mode of transport and deposition. The Quaternary deposits at Xingshan lie unconformable on Cretaceous rocks made of siltstone, mudstone and sandstone. The average grain size is between 8.06 to 8.55Φ (0.002 6 ～0.003 7 mm). The Quaternary deposits at Xingshan mainly compose of very fine silt to clay. The compositions of the grade are clay 63% and silt 37%. The clay size components are weathered debris transported and deposited by flowing water from the SE highlands or hills to the low lying NW Xingshan plains whereas the silty components accumulated by aoelian process. The Quaternary deposits at Xingshan accumulated in the middle and late Pleistocene interglacial periods from (459.12～39.03) ka to (88.92～7.56) ka. The standard deviation ranged from 0.96 to 1.36Φ, indicating that the sediments are moderately to poorly sorted, Coefficient of skewness ranged from 0.16～0.31 with an average skewness of 0.218, (Positively skewed towards fine). Kurtosis values (0.84～1.05) from the grain size distribution and visual inspection of the frequency curves indicate platykurtic to mesokurtic curves and unimodal to bimodal grain-size distribution. The type of deposit formation is sand dune and the source is at a distal from its provenance.     

Effect of spatial variation characteristics on contouring of design storm depth

The ordinary kriging method, a geostatistical interpolation technique, was applied for developing contour maps of design storm depth in northern Taiwan using intensity–duration–frequency (IDF) data. Results of variogram modelling on design storm depths indicate that the design storms can be categorized into two distinct storm types: (i) storms of short duration and high spatial variation and (ii) storms of long duration and less spatial variation. For storms of the first category, the influence range of rainfall depth decreases when the recurrence interval increases, owing to the increasing degree of their spatial independence. However, for storms of the second category, the influence range of rainfall depth does not change significantly and has an average of approximately 72 km. For very extreme events, such as events of short duration and long recurrence interval, we do not recommend usage of the established design storm contours, because most of the interstation distances exceed the influence ranges. Our study concludes that the influence range of the design storm depth is dependent on the design duration and recurrence interval and is a key factor in developing design storm contours. Copyright © 2003 John Wiley & Sons, Ltd.     

Optimization of grid-drilling using computer simulation

A computer simulation method has been developed to find efficient drilling grids for mineral deposits. A well-known ore deposit is used as a model to develop an efficient pattern for undiscovered ore bodies in the same area or in other prospects where similar geometry is suspected. The model for this study is the Austinville, Virginia deposit, a Mississippi Valley-type deposit composed of 17 ore bodies totaling 34 million short tons (30 million metric tons). The method employs a computer program that simulates drilling the model deposit with different patterns, including various levels of follow-up drilling. Follow-up holes are drilled in fences at one half the original spacing around holes in the grid that show ore-grade mineralization. Each pattern is drilled 100 times from random starting locations to provide a range of outcomes of drilling, including the best, worst, and most likely. For this study, patterns of 100 drill holes were composed of 10 fences spaced 1000–5000 feet (305–1524 m) apart, each with 10 holes spaced 200–1000 feet (61–305 m) apart. In all, 25 grids were used with zero to three levels of follow-up drilling. The 600/2000 grid, with drill holes spaced 600 feet (183 m) apart in fences spaced 2000 feet (610 m) apart, was compared with the 200/5000 grid because they represented contrasting outcomes. The 600/2000 grid penetrated many ore bodies consistently but with few multiple hits to individual ore bodies; whereas the 200/5000 grid inconsistently penetrated few ore bodies with many multiple hits. The 600/2000 grid was more efficient than the 200/5000 grid at hitting large ore bodies of 1,000,000 short tons or greater (900,000 metric tons or greater) and was made more effective by adding one cycle of follow-up drilling. The 600/2000 grid had a 97% chance of hitting one or more large ore bodies with at least one drill hole per ore body, and the 200/5000 grid had a 64% chance. Once hit, there was an 82% chance that the largest ore body would be penetrated by three or more holes when using the 600/2000 grid and an 88% chance using the 200/5000 grid.     

Contribution of storms to groundwater recharge in the semi‐arid region of Karnataka,India

This paper describes the application of environmental isotopes and injected tracer techniques in estimating the contribution of storms as well as annual precipitation to groundwater recharge and its circulation, in the semi‐arid region of Bagepalli, Kolar district, Karnataka. Environmental isotopes ²H, ¹⁸O and ³H were used to study the effect of storms on the hydrological system, and an isotope balance was used to compute the contribution of a storm component to the groundwater. Some of the groundwater samples collected during the post‐storm periods were highly depleted in stable isotope content with higher deuterium excess relative to groundwater from the pre‐storm periods. Significant variation in deuterium excess in groundwater from the same area, collected in two different periods, indicates the different origin of air masses. The estimated recharge component of a storm event of 600 mm to the groundwater was found to be in the range of 117–165 mm. There was no significant variation in environmental tritium content of post‐storm and pre‐storm groundwater, indicating the fast circulation of groundwater in the system. After completion of the environmental isotope work, an injected radiotracer ³H technique was applied to estimate the direct recharge of total precipitation to the groundwater. The estimated recharge to the groundwater is 33 mm of the 550 mm annual precipitation during 1992. Copyright © 2003 John Wiley & Sons, Ltd.     

Design of stable drainage networks in upland forestry plantations

Erosion of man-made, forestry drainage channels occurs when the plough cuts through the surface peat layer into the underlying erodible mineral soil. A procedure is developed, based on hydraulic considerations, which will allow the drainage engineer to design stable drainage networks in upland forestry plantations. An example design chart is given for an erodible sandy loam type soil.     

青岛港风暴潮经验统计预报

本文利用青岛港多年实测资料,分析了该港风暴潮概况。而后通过多元回归技术,求取了该港极值增减水的预报公式。经非独立和独立检验,结果令人满意。     

阿尔金地区构造应力场及其对金属矿产分布的控制作用

构造应力场研究可以为区域矿产预测提供依据。主要根据节理、擦痕的测试分析，结合区域构造解析，确定阿尔金山东西向拉配泉－－红柳沟构造带经历了三期不同方向的应力作用：印支期以前的南北向挤压作用，印支－燕山期的北西－南东向的挤压和中生代晚期－新生代北东东－南南西向的挤压；并利用有限元数值模拟前两期构造应力场的演变过程，进而讨论了区域构造应力场对内生金属矿产分布规律的控制作用指出了区域寻找大型内生金属矿产的有利地段。     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.