Estimating groundwater residence time using multiple regression model based on fluoride dissolution: an exploration of possibilities

High levels of fluoride concentration were observed in deep groundwater of the Mizunami area in Central Japan. Fluoride occurs mainly due to the reaction between granitic basement rock and groundwater. Granites were collected, crushed to powder, and then allowed to react with purified water for 80 days. Water–rock interaction results showed that the major factor affecting fluoride concentration is the residence time of the groundwater. Coexisting ions have also some contribution toward fluoride concentration. The groundwater residence time in the Mizunami area was estimated by applying results of water–rock interaction to correspond with field data. A regression model relating fluoride concentration, residence time, and coexisting ions was developed. The parameters of the regression model were determined using the genetic algorithms technique. Residence time was estimated by extrapolating experimental data to correspond with filed data. Near the recharge area, residence times in the potential fluoride source rock varied between 1 and 2,000 years, whereas near the discharge area residence times were in excess of tens of thousands of years. The groundwater residence time was also estimated by the groundwater particle-tracking-flow model. The estimates of groundwater residence time based on geochemical regression model were often larger than estimates of groundwater residence time developed by particle-tracking analysis using a groundwater flow model. There were large uncertainties—on the order of 10–10,000 years—in the estimates based on geochemical data.     

Impact area determination of pyroclastic deposits in Lascar volcano, eruptive process in the year 1993

By means of multi-temporal analysis of satellite images and statistical algorithms, the amount of pyroclastic material deposited on Lascar volcano walls after the gravitational collapse of the eruptive column caused by the eruption that occurred on April the 19th and the 20th in 1993 was determined and quantified. For this analysis, scenes corresponding to Landsat 4 TM in 1989 and Landsat 7 ETM+ in 2001 were used. By careful selection methods such as combination of bands, unsupervised classification, and the Karhunen–Loève transform, detailed analysis of zones of change that correspond to pyroclastic deposits were made. This analysis was complemented with in situ data in order to correct and calibrate the satellite images to identify zones of 1993s eruption pyroclastic deposits. Using Kittler’s and other thresholding algorithms, a search was performed for a proper threshold to binarize the images to determine the surface area covered by the eruptive process. Matlab™ software was used both for general programming and for digital image processing.     

Development of Productivity Models for the Northern Gulf of Mexico Based on Oxygen Concentrations and Stable Isotopes

Oxygen concentrations have been used for decades to estimate primary production (P) and respiration (R) in aquatic ecosystems. Yet, this approach cannot separate the effects of biological and physical processes affecting oxygen dynamics; therefore, it is now often complemented with the analysis of stable oxygen isotopes. Existing algorithms for calculating primary production and P/R have been developed for closed systems and steady-state open systems. None of these formulations are applicable to productive aquatic ecosystems where diurnal changes in oxygen concentrations and isotope values are usually large. Here, we describe a novel P/R model that includes algorithms for air–sea gas exchange and is not constrained by steady-state conditions. Our objective was to test model sensitivity to variations in input parameters for values commonly observed in coastal waters of the northern Gulf of Mexico. The model was highly sensitive to variations in fractionation factor for respiration (ε) but less sensitive to variations in wind speed, oxygen isotope values of source-water, or oxygen flux through the picnocline. This model is easily transferable to other coastal ecosystems, with a caveat that system-specific values for ε are needed to obtain realistic estimates of P/R.     

A comparison of estimated and calculated effective porosity

 Effective porosity in solute-transport analyses is usually estimated rather than calculated from tracer tests in the field or laboratory. Calculated values of effective porosity in the laboratory on three different textured samples were compared to estimates derived from particle-size distributions and soil–water characteristic curves. The agreement was poor and it seems that no clear relationships exist between effective porosity calculated from laboratory tracer tests and effective porosity estimated from particle-size distributions and soil–water characteristic curves. A field tracer test in a sand-and-gravel aquifer produced a calculated effective porosity of approximately 0.17. By comparison, estimates of effective porosity from textural data, moisture retention, and published values were approximately 50–90% greater than the field calibrated value. Thus, estimation of effective porosity for chemical transport is highly dependent on the chosen transport model and is best obtained by laboratory or field tracer tests. Received, March 1997 · Revised, August 1997 · Accepted, August 1997     

Kernel Principal Component Analysis for Efficient,Differentiable Parameterization of Multipoint Geostatistics

This paper describes a novel approach for creating an efficient, general, and differentiable parameterization of large-scale non-Gaussian, non-stationary random fields (represented by multipoint geostatistics) that is capable of reproducing complex geological structures such as channels. Such parameterizations are appropriate for use with gradient-based algorithms applied to, for example, history-matching or uncertainty propagation. It is known that the standard Karhunen–Loeve (K–L) expansion, also called linear principal component analysis or PCA, can be used as a differentiable parameterization of input random fields defining the geological model. The standard K–L model is, however, limited in two respects. It requires an eigen-decomposition of the covariance matrix of the random field, which is prohibitively expensive for large models. In addition, it preserves only the two-point statistics of a random field, which is insufficient for reproducing complex structures. In this work, kernel PCA is applied to address the limitations associated with the standard K–L expansion. Although widely used in machine learning applications, it does not appear to have found any application for geological model parameterization. With kernel PCA, an eigen-decomposition of a small matrix called the kernel matrix is performed instead of the full covariance matrix. The method is much more efficient than the standard K–L procedure. Through use of higher order polynomial kernels, which implicitly define a high-dimensionality feature space, kernel PCA further enables the preservation of high-order statistics of the random field, instead of just two-point statistics as in the K–L method. The kernel PCA eigen-decomposition proceeds using a set of realizations created by geostatistical simulation (honoring two-point or multipoint statistics) rather than the analytical covariance function. We demonstrate that kernel PCA is capable of generating differentiable parameterizations that reproduce the essential features of complex geological structures represented by multipoint geostatistics. The kernel PCA representation is then applied to history match a water flooding problem. This example demonstrates that kernel PCA can be used with gradient-based history matching to provide models that match production history while maintaining multipoint geostatistics consistent with the underlying training image.     

Monte Carlo simulation of permeability fields and reservoir performance predictions with SVD parameterization in RML compared with EnKF

In a previous paper, we developed a theoretical basis for parameterization of reservoir model parameters based on truncated singular value decomposition (SVD) of the dimensionless sensitivity matrix. Two gradient-based algorithms based on truncated SVD were developed for history matching. In general, the best of these “SVD” algorithms requires on the order of 1/2 the number of equivalent reservoir simulation runs that are required by the limited memory Broyden–Fletcher–Goldfarb–Shanno (LBFGS) algorithm. In this work, we show that when combining SVD parameterization with the randomized maximum likelihood method, we can achieve significant additional computational savings by history matching all models simultaneously using a SVD parameterization based on a particular sensitivity matrix at each iteration. We present two new algorithms based on this idea, one which relies only on updating the SVD parameterization at each iteration and one which combines an inner iteration based on an adjoint gradient where during the inner iteration the truncated SVD parameterization does not vary. Results generated with our algorithms are compared with results obtained from the ensemble Kalman filter (EnKF). Finally, we show that by combining EnKF with the SVD-algorithm, we can improve the reliability of EnKF estimates.     

Parameterization of sea surface drag under varying sea state and its dependence on wave age

Momentum and energy exchange at air–sea interface through wind stress is very important for air–sea interaction studies, ocean modeling, and climate studies. The accurate representation of wind stress, in terms of drag coefficient, is a key factor in estimating the momentum transfer at the interface. The drag coefficient, in general, estimated using bulk formulae does not take into account the influence of wave age. This study examines the dependence of wave age on computed surface drag coefficient obtained by combining the Toba 3/2-power law with Froude number scaling, resulting in a new drag formulation (hereafter referred as RP formulation). We demonstrate that our proposed formulation is in good conjunction with established theories for both young and mature waves. Our investigation shows the theoretical formulation advocated earlier by Guan and Xie (hereafter referred as GX) overestimated the surface drag for mature waves as wind speed tends to increase. In addition, the formulation by GX was not verified by observational data. In the present work, for validation purpose, we use time series measurement of meteorological and oceanographic data from a deep water location in the Indian Ocean which was tested with both RP and GX formulations. We find that the proposed RP formulation, which embeds the 3/2 power of wave-age, shows a better match for both young and mature waves with the results of Janssen compared to the hypothesis of conventional wave age used by GX.     

一种基于反距离加权方法的层状三维地质界面拟合算法

三维空间中地质曲面模拟是矿产勘查、大比例尺成矿预测等地学领域的重要研究内容之一.与地球化学、地球物理数据的曲面拟合相比,地质界面拟合更加复杂且具有一般性.从功能需求角度出发,地质界面拟合需要处理层状地层、不整合地层以及存在构造的地层等多种情况;从算法实现角度讲,该拟合过程不同于物化探数据通过某一属性值进行曲面拟合的情况,因为在地质界面模拟过程中,不存在这样的特征值进行曲面拟合,因此不能直接使用物化探数据等值面提取的思想模拟地质接触界面.针对上述问题,提出了一种基于反距离加权法移动立方格算法的层状地层曲面拟合算法.该方法模型适合绝大多数层状地学三维曲面模拟.     

Review of the neotectonics of the Eastern Turkish–Armenian Plateau by geomorphic analysis of digital elevation model imagery

Digital elevation model (DEM) images provide synoptic views of the Earth’s surface allowing the analysis of landforms of still active tectonic and volcanic structures at regional scale. A DEM at 250 m pixel size constitutes regional scale data particularly efficient to investigate the late Miocene–Quaternary deformation of the Eastern Turkish–Armenian Plateau in the Arabian–Eurasian area of convergence. Geomorphic analysis of the DEM image associated with review of fault-plane solutions of earthquakes show that faults are mostly strike-slip with small vertical component. Here we show that the orientations of the tectonic and volcanic structures fit with a tectonic regime characterized by N–S shortening and E–W lengthening, consistent with westward escape of Anatolia perpendicular to the direction of the Arabia–Eurasia shortening. The uniform uplift of the plateau, the predominance of strike-slip faulting, the lack of major thrusts and the occurrence of normal faults do not support a model of going-on crustal thickening due to intracontinental convergence. On the contrary, our observations can be better interpreted in terms of lithospheric thinning and mantle upwelling related to gravity escape of Anatolia.     

Investigation of the effect of specific interfacial area on strength of unsaturated granular materials by X-ray tomography

This paper studies the effect of interfacial areas (air–water interfaces and solid–water interfaces) on material strength of unsaturated granular materials. High-resolution X-ray computed tomography technique is employed to measure the interfacial areas in wet glass bead samples. The scanned 3D images are trinarized into three phases and meshed into representative volume elements (RVEs). An appropriate RVE size is selected to represent adequate local information. Due to the local heterogeneity of the material, the discretized RVEs of the scanned samples actually cover a very large range of degree of saturation and porosity. The data of RVEs present the relationship between the specific interfacial areas and degree of saturation and gives boundaries where the interfacial area of a whole sample should fall in. In parallel, suction-controlled direct shear tests have been carried out on glass beads and the material strength has been corroborated with two effective stress definitions related to the specific air–water interfacial areas and fraction of wetted solid surface, respectively. The comparisons show that the specific air–water interfacial area reaches the peak at about 25% of saturation and contributes significantly to the material strength (up to 60% of the total capillary strength). The wetted solid surface obtained from X-ray CT is also used to estimate Bishop’s coefficient χ based on the second type of effective stress definition, which shows a good agreement with the measured value. This work emphasizes the importance to include interface terms in effective stress formulations of unsaturated soils. It also suggests that the X-ray CT technique and RVE-based multiscale analysis are very valuable in the studies of multiphase geomaterials.

     

Short-time-scale features of the Earth’s polar motion

The fundamental astrometric problem of high-accuracy interpolation and forecasting of the Earth’s polar motion on short time scales from 1–2 to 10–30 days is studied. Hierarchies of interval length and parameter accuracy are established using appropriate models for the process. Filtering algorithms are adjusted using a weighted least squares fit of measurements of the International Earth Rotation Service (IERS). Best-fit estimates for the main features of the motion are obtained for various time intervals; interpolations and forecasts are compared with the IERS measurements.     

Utility of DMSP-SSM/I for integrated water vapour over the Indian seas

Recent algorithms for Special Sensor Microwave/Imager (DMSP-SSM/I) satellite data are used for estimating integrated water vapour over the Indian seas. Integrated water vapour obtained from these algorithms is compared with that derived from radiosonde observations at Minicoy and Port Blair islands. Algorithm-3 of Schlussel and Emery (1990) performed best. On the basis of this algorithm, distribution of integrated water vapour is determined during the monsoon depression (22nd–27th July, 1992) that formed over the Bay of Bengal.     

Estimation of colored dissolved organic matter and salinity fields in case 2 waters using SeaWiFS: Examples from Florida Bay and Florida Shelf

Estimates of water quality variables such as chlorophylla concentration (Chl), colored dissolved organic matter (CDOM), or salinity from satellite sensors are of great interest to resource managers monitoring coastal regions such as the Florida Bay and the Florida Shelf. However, accurate estimates of these variables using standard ocean color algorithms have been difficult due to the complex nature of the light field in these environments. In this study, we process SeaWiFS satellite data using two recently developed algorithms; one for atmospheric correction and the other a semianalytic bio-optical algorithm and compare the results with standard SeaWiFS algorithms. Overall, the two algorithms produced more realistic estimates of Chl and CDOM distributions in Florida Shelf and Bay waters. Estimates of surface salinity were obtained from the CDOM absorption field assuming a conservative mixing behavior of these waters. A comparison of SeaWiFS-derived Chl and CDOM absorption with field measurements in the Florida Bay indicated that although well correlated, CDOM was underestimated, while Chl was overestimated. Bottom reflectance appeared to affect these estimates at the shallow central Bay stations during the winter. These results demonstrate the need for new bio-optical algorithms or tuning of the parameters used in the bio-optical algorithm for local conditions encountered in the Bay.     

Effect of varied atmospheric stability on sea surface drag in shallow seas and its impact on wind-wave growth

This work reports an efficient bulk formulation of sea surface drag that incorporates effect of dynamic stability under varied atmospheric forcing. The proposed formulation exhibits a polynomial dependence of wind speed on air–sea temperature difference based on statistical analysis. Quality checked meteorological and oceanographic data from four shallow water buoys located off Korean seas having measurements at an interval of every 1 h were used for this study. The analyses of in situ records for this region suggest stability ranging from highly stable to very unstable conditions. Importance of this proposed formulation is better reflected during unstable condition where other popular bulk formulations fail. In addition, importance and impact of such a study on wind-wave growth using the state-of-art wave model was also investigated. Finally, we advocate a new drag formulation, which accounts for varied atmospheric stability and suggest that this should be considered as an essential pre-requisite for ocean modeling studies.     

Temporal and spatial variations in the magnitude of completeness for homogenized moment magnitude catalogue for northeast India

Northeast India region is one of the most seismically active areas in the world. Events data for the period 1897–2010, used in this study has been largely compiled from global ISC, NEIC and GCMT databases. Historical seismicity catalogue of Gupta et al (1986) and some events data from the bulletins of India Meteorological Department are also used. Orthogonal regression relations for conversion of body and surface wave magnitudes to M _w,HRVD based on events data for the period 1978–2006 have been derived. An Orthogonal Standard Regression (OSR) relationship has also been obtained for scaling of intensity estimates to M _w,NEIC using 126 global intensity events with intensity VI or greater during the period 1975–2010.     

Impacts of coal mining subsidence on the surface landscape in Longkou city,Shandong Province of China

Coal mining subsidence is a common human geological disaster that was particularly conspicuous in China. It seriously restricts the sustainable development of mining areas, and it not only damages land resources but also triggers a series of ecological and environmental problems that may result in social and economic issues. This report studied the coal mining subsidence area of Longkou in Shandong province and uses digital elevation data (DEM) of the mining area before subsidence in 1978 as the baseline elevation. Through image algorithms, we obtained coal mining subsidence region data for 1984, 1996, 2000, and 2004. And with spatial data sources of the same period of TM/ETM⁺ and SPOT5 remote sensing images, BP artificial neural network (BPNN) classification is used to extract surface landscape information in the subsidence area. With the support of GIS technology, superimposing subsidence area on the surface landscape—using the largest landscape ecology patch index, landscape shape index, landscape condensation index, and the index of landscape distribution—report analyzes the mining landscape changes before and after subsidence. This study also carries on exploratory research with the landscape changes, thereby providing a scientific basis for integrated prevention and treatment.     

Physicochemical simulation of the evolution of small lakes in a cold climate

The paper presents a generalized algorithm for the simulation of multiyear cycles in variations of the chemical composition of lake waters with regard for the seasonal specifics of hydrogeochemical processes. Data were obtained on the behavior of the hydrogeological system during a time span of 500–1000 years. Each of the simulated model cycles involved a successively alternating “summer-winter” time periods. Terrestrial exchange fluxes between reservoirs, groundwater inflow, falls of atmospheric precipitate, and the evaporation of lake water were taken into account for summer periods, whereas winter conditions were simulated as corresponding to the development of the ice phase, the absence of water exchange fluxes, a change from oxidizing to reducing conditions, and the burial of solid phases in the sediments. The results of our physicochemical simulations with the use of data on the composition of natural hydrogeological systems are in good agreement with natural observations and make it possible to realistically predict the evolution of small lakes in the Ol’khon area.     

Analysis of optimal strategies for soft landing on the Moon from lunar parking orbits

Optimal trajectory design of a probe for soft landing on the Moon from a lunar parking orbit by minimizing the fuel required is obtained. The problem is formulated as an optimal control problem with the thrust direction being the control variable. Using the maximum principle of Pontryagin, the control variable is expressed as a function of co-state variables and the problem is converted into a two-point boundary value problem. The two-point boundary value problem is solved using an optimization technique, i.e., controlled random search. The strategies such as