Program disk to accompany MAGMIX (Computers & Geosciences, 1988, v. 14, p. 213-228)for IBM PC/AT (or compatible) computers
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Open-File Report↗
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Earthcasting: Geomorphic forecasts for society
Over the last several decades, the study of Earth surface processes has progressed from a descriptive science to an increasingly quantitative one due to advances in theoretical, experimental, and computational geosciences. The importance of geomorphic forecasts has never been greater, as technological development and global climate change threaten to reshape the landscapes that support human societies and natural ecosystems. Here we explore best practices for developing socially relevant forecasts of Earth surface change, a goal we are calling “earthcasting”. We suggest that earthcasts have the following features: they focus on temporal (∼1–∼100 years) and spatial (∼1 m–∼10 km) scales relevant to planning; they are designed with direct involvement of stakeholders and public beneficiaries through the evaluation of the socioeconomic impacts of geomorphic processes; and they generate forecasts that are clearly stated, testable, and include quantitative uncertainties. Earthcasts bridge the gap between Earth surface researchers and decision-makers, stakeholders, researchers from other disciplines, and the general public. We investigate the defining features of earthcasts and evaluate some specific examples. This paper builds on previous studies of prediction in geomorphology by recommending a roadmap for (a) generating earthcasts, especially those based on modeling; (b) transforming a subset of geomorphic research into earthcasts; and (c) communicating earthcasts beyond the geomorphology research community. Earthcasting exemplifies the social benefit of geomorphology research, and it calls for renewed research efforts toward further understanding the limits of predictability of Earth surface systems and processes, and the uncertainties associated with modeling geomorphic processes and their impacts.
Earth's Future↗
Modules based on the geochemical model PHREEQC for use in scripting and programming languages
The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server—for example, Excel®, Visual Basic®, Python, or MATLAB". PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations.
Computers & Geosciences↗
A BASIC program for locating references cited in geoscience manuscripts
[No abstract available]
Computers & Geosciences↗
Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing
Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.
Computers & Geosciences↗
3D semantic mapping of surface geological features
Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.
Computers & Geosciences↗
Analytical model for screening potential CO2 repositories
Assessing potential repositories for geologic sequestration of carbon dioxide using numerical models can be complicated, costly, and time-consuming, especially when faced with the challenge of selecting a repository from a multitude of potential repositories. This paper presents a set of simple analytical equations (model), based on the work of previous researchers, that could be used to evaluate the suitability of candidate repositories for subsurface sequestration of carbon dioxide. We considered the injection of carbon dioxide at a constant rate into a confined saline aquifer via a fully perforated vertical injection well. The validity of the analytical model was assessed via comparison with the TOUGH2 numerical model. The metrics used in comparing the two models include (1) spatial variations in formation pressure and (2) vertically integrated brine saturation profile. The analytical model and TOUGH2 show excellent agreement in their results when similar input conditions and assumptions are applied in both. The analytical model neglects capillary pressure and the pressure dependence of fluid properties. However, simulations in TOUGH2 indicate that little error is introduced by these simplifications. Sensitivity studies indicate that the agreement between the analytical model and TOUGH2 depends strongly on (1) the residual brine saturation, (2) the difference in density between carbon dioxide and resident brine (buoyancy), and (3) the relationship between relative permeability and brine saturation. The results achieved suggest that the analytical model is valid when the relationship between relative permeability and brine saturation is linear or quasi-linear and when the irreducible saturation of brine is zero or very small.
Computational Geosciences↗
Linear complementarity formulation for 3D frictional sliding problems
Frictional sliding on quasi-statically deforming faults and fractures can be modeled efficiently using a linear complementarity formulation. We review the formulation in two dimensions and expand the formulation to three-dimensional problems including problems of orthotropic friction. This formulation accurately reproduces analytical solutions to static Coulomb friction sliding problems. The formulation accounts for opening displacements that can occur near regions of non-planarity even under large confining pressures. Such problems are difficult to solve owing to the coupling of relative displacements and tractions; thus, many geomechanical problems tend to neglect these effects. Simple test cases highlight the importance of including friction and allowing for opening when solving quasi-static fault mechanics models. These results also underscore the importance of considering the effects of non-planarity in modeling processes associated with crustal faulting.
Computational Geosciences↗
Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations
In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.
North Carolina↗
Q-mode factor analysis of compositional data
An extended form of the method of Q-mode factor analysis may be used if the rows of the data matrix sum to a constant. The constant row-sum provides a means for scaling the factor model to conform to the units of the original data in such forms as proportions, percentages, or parts per million. The scale factors for an m-factor model are used to derive composition scores and loadings, which lead to the same reproduced data regardless of the choice of reference axes (end-members). Factor-variance diagrams may be constructed to show the proportion of the variance that will be accounted for in each compositional variable by models containing various numbers of end-members. The method may be used to develop a petrologic mixing model by searching for end-members that are geologically plausible. ?? 1976.
Computers & Geosciences↗
Extended cabfac and Qmodel computer programs for Q-mode factor analysis of compositional data
The computer program CABFAC for Q-mode factor analysis of geologic data has been extended for use with data having constant row-sums. Another program, QMODEL, reads an output file from CABFAC and can be used to develop a variety of Q-mode models. The models serve to reproduce estimates of the original data rather than of the data in normalized form. ?? 1976.
Computers & Geosciences↗
A method and fortran program for quantitative sampling in paleontology
The Unit Sampling Method is a binomial sampling method applicable to the study of fauna preserved in rocks too well cemented to be disaggregated. Preliminary estimates of the probability of detecting each group in a single sampling unit can be converted to estimates of the group's volumetric abundance by means of correction curves obtained by a computer simulation technique. This paper describes the technique and gives the FORTRAN program. ?? 1976.
Computers & Geosciences↗
Interactive computer programs for petrologic modeling with extended Q-mode factor analysis
An extended form of Q-mode factor analysis may be used if the row-sums of the data matrix are constant and can be helpful especially in developing and testing petrologic-mixing models for igneous systems. The first step is to represent the sample compositions as unit vectors in M-dimensional space and then to project them into space of fewer dimensions (m) as determined to be appropriate from a factor-variance diagram. Compositions thought to be those of possible end-members in the petrologic system then are represented as vectors in the M-dimensional space and projected into the same space as the sample vectors. If these vectors remain close to unity in length after projection, the corresponding compositions can serve as end-member compositions for the model. After m suitable end-member compositions have been identified, each sample composition is expressed as a mixture of the end-members by computation of the composition loadings. The interactive computer programs presented are useful in these procedures because of the trial-and-error nature of the modeling procedures. ?? 1976.
Computers & Geosciences↗
Resource data bases-Resource assessment
The U.S. Geological Survey's Office of Resource Analysis is developing computer methods for the handling of mineral-resources data in order to provide improved means for addressing and manipulating data. These methods include: computerized data files and predictive resource models. Data files contain the raw or disaggregated information on mineral deposits and commodities. One operational data file is CRIB (Computerized Resources Information Bank) which is a general purpose inventory and reference file on metallic and nonmetallic mineral deposits. A computer file on resources should contain detailed information on the following main categories: record identification, name and location, description of deposit, analytical data, and production/reserves. A resource model employs postulates and inferences in conjunction with the data to make predictions about resources-as key variables concerning a mineral commodity are changed. The objective is to estimate the availability of minerals including: geological availability (occurrence models), technological availability (exploration and beneficiation models), and economic availability (economics models). ?? 1976.
Computers & Geosciences↗
The national coal-resources data system of the U.S. geological survey
The National Coal Resources Data System (NCRDS) was designed by the U.S. Geological Survey (USGS) to meet the increasing demands for rapid retrieval of information on coal location, quantity, quality, and accessibility. An interactive conversational query system devised by the USGS retrieves information from the data bank through a standard computer terminal. The system is being developed in two phases. Phase I, which currently is available on a limited basis, contains published areal resource and chemical data. The primary objective of this phase is to retrieve, calculate, and tabulate coal-resource data by area on a local, regional, or national scale. Factors available for retrieval include: state, county, quadrangle, township, coal field, coal bed, formation, geologic age, source and reliability of data, and coal-bed rank, thickness, overburden, and tonnage, or any combinations of variables. In addition, the chemical data items include individual values for proximate and ultimate analyses, BTU value, and several other physical and chemical tests. Information will be validated and deleted or updated as needed. Phase II is being developed to store, retrieve, and manipulate basic point source coal data (e.g., field observations, drill-hole logs), including geodetic location; bed thickness; depth of burial; moisture; ash; sulfur; major-, minor-, and trace-element content; heat value; and characteristics of overburden, roof rocks, and floor rocks. The computer system may be used to generate interactively structure-contour or isoline maps of the physical and chemical characteristics of a coal bed or to calculate coal resources. ?? 1976.
Computers & Geosciences↗
RESIN, a FORTRAN IV program for determining the area of influence of samples or drill holes in resource target search
A FORTRAN IV program that calculates the area of influence of drill holes or samples with respect to the size and shape of elliptical or circular resource targets is presented. Program options include determination of the degree to which areas within a region have been explored and estimation of probabilities that points are centers of undiscovered deposits. Errors of recognition can be utilized in the program input. ?? 1976.
Computers & Geosciences↗
Binorm-a fortran subroutine to calculate the percentiles of a standardized binormal distribution
BINORM is a FORTRAN subroutine for calculating the percentiles of a standardized binormal distribution. By using a linear transformation, the percentiles of a binormal distribution can be obtained. The percentiles of a binormal distribution are useful for plotting purposes, for establishing confidence intervals, and for sampling from a mixed population that consists of two normal distributions. ?? 1977.
Computers & Geosciences↗