Gravity Delineation of a Buried Valley in Quartzite

A gravity survey was conducted in a 94-square-mile area of northeastern Hanson County, South Dakota. The 340 measured gravity values, together with test-hole data, were used to approximately delineate a buried valley eroded into the Sioux Quartzite of Precambrian age. This valley contains, in places, an aquifer composed of quartzose sand of pre-Cretaceous age derived from the Sioux Quartzite. The bottom of the valley is approximately 450–600 ft below land surface. Simple Bouguer values were determined from measured gravity data, referenced to a local base station, and interpolated to a 0.5- by 0.5-mile grid. The interpolated simple Bouguer values of residual gravity were determined using a five-ring, inverse-weighted filtering method. The second derivative of the interpolated gravity values, as well as their downward continuation, did not delineate the buried valley as well. Subsequent drilling of nine test holes showed that the gravity method can be used for approximately delineating subsurface features     

Aquifer Testing, Mathematical Modeling, and Regulatory Risk

Mathematical modeling founded on a strong field data base can be a valuable tool for the analysis of ground-water contamination problems. The purposes of this paper are threefold: (1) we demonstrate the dilemma of a knowledgeable ground-water quality regulator whose regulatory decision-making process is confronted with the output of a mathematical model that is based on very limited field test data; (2) we demonstrate a method available to a knowledgeable regulator for assessing approximately a range of possible performances of a contaminated ground-water recovery well field using a range of input data derived from a very limited data base; and (3) we present a strong case for presenting mathematical model outputs as ranges of values rather than as unique solutions. A range is determined by an examination of the level of sophistication of the field data base. Our experience with 12 field sites wherein ground-water contamination has occurred has led us to conclude that field data are seldom, if ever, adequate to defend a unique solution from a mathematical model. Regulatory decisions generally can be reduced to minimization of risks based on the smallest range of model outputs that can be defended on the basis of the field data base. The more limited the field data base, the greater must be the range of defensible model outputs, and consequently, the greater the risk inherent in subsequent regulatory decisions. The knowledgeable regulator can assess the risks in the regulatory decision-making process only if he is able to assess the extent to which the field data base for the mathematical model output reflects state-of-the-art data collection and analysis technologies and methodologies. If an applicant for a permit or license submits a less than adequate data base and concomitantly a broad range of defensible model outputs, he inherently requests that the knowledgeable regulator accept a risk greater than that required if adequate aquifer testing techniques had been employed.     

A Coastal Aquifer Study Using Magnetotelluric and Gravity Methods in Abo Zenema, Egypt

Magnetotelluric (MT) soundings and gravity methods were employed to study the deep freshwater aquifer in the area north of Abo Zenema city on the eastern side of the Gulf of Suez, Egypt. Seven MT sites and 48 gravity stations were surveyed along northeast–southwest profiles as close as possible to a line perpendicular to the coast of the Gulf of Suez. The MT survey was conducted using high and low frequencies to investigate shallow and deep areas, respectively. One-dimensional inversion was conducted using a heuristic inversion scheme of the Bostick algorithm. The MT data were also inverted with a 2-D smooth model inversion routine using the nonlinear conjugate gradient method to infer variation in vertical and lateral resistivity inside the Earth. A 100-Ohm-m homogeneous half-space initial model was used to invert the TE mode data only. Then, the inverted model obtained from the TE mode data was used as an initial model for inversion of the TM mode data. The inverted model thus obtained from the TM mode data inversion was used as an initial model for the inversion of the joint TE and TM responses. Two-dimensional (2-D) forward modeling of the gravity data was conducted using the 2-D polygon method of Talwani’s algorithm for an arbitrarily shaped body and was based on the subsurface information from the MT survey and the available information about the geological structure of the study area. This method enabled us to obtain the basement structure of the coastal aquifer in the study area. The results from the analysis and the interpretation of MT and gravity data were used to detect and delineate the groundwater coastal aquifer in the study area.     

Ground Water Quality In the Aquifer of the Upper Mad River Valley 1940 to 1983

More than 40 years of ground water quality monitoring data from the aquifer of the Upper Mad River Valley have been accumulated by various agencies in Ohio. The data consist of concentrations for more than 30 chemical substances found in the ground water. Evaluation of this data using statistical analysis, tables and graphs indicates that there have been moderate increases in total dissolved solids, sulfate, fluoride, calcium, magnesium and potassium. More significant increases were discovered for chloride and sodium. Iron and zinc show a general decline in concentration. The metals arsenic, barium and lead also show increases in recent years. However, large variations in the concentrations and limited data for these metals limit the reliability of the apparent trends shown in the tabulated data.
The increases in chloride and sodium are attributed to the use of road de-icing salt. Increases in sulfate and potassium may be due to use of fertilizers in a region which is largely agricultural. The most recent data may indicate that the ground water quality is improving in terms of these two parameters. Although most of the data indicate increases in concentrations with time, inconsistencies in sampling procedures and difficulties in assessing many factors which affect ground water quality preclude the broad conclusion that urbanization and industrialization have caused regional ground water quality degradation.
The inability to interpret much of the data underlies the need for an integrated environmental monitoring program. Such a program should provide a data base for assessing factors such as air and river quality and historical land use practices so that their impact on ground water quality in the Mad River Valley can be better understood.     

以乡镇为单元评估云南省建水县地震灾害风险

基于云南省建水县的建筑物、人口数量、生命线工程、地形地貌等数据,选取地震灾害损失风险评估因子,利用评估模型对设定烈度下可能造成的人员死亡、房屋破坏、滑坡密度等进行计算,给出地震灾害损失定量评估结果。在传统风险评估方法基础上,对无法建立灾害损失关系的承灾体用风险暴露量来代替灾害损失量进行风险评估。最后应用极差变换法对地震灾害损失的不同因子进行标准化,通过综合赋权划分地震灾害风险等级。结果表明:建水县地震灾害高风险的乡镇有5个,主要分布在建水北部的曲江,南部的南庄、西庄、临安、官厅一带;中风险乡镇有6个,低风险乡镇有3个。