The term management implies a systematic process under which resources are deployed in pursuit of an objective. In managing hydrologic information, the objective is to minimize the risk to hydrologic resources by effectively utilizing data and data analysis techniques. Recognition of the concept and procedures associated with quality assurance/quality control, as discussed in more detail in the Data Verification section below, is of utmost importance in this regard.
Managing water quality and quantity information to describe baseline conditions and predict potential impacts lends itself to automated computer techniques. These include data base management systems and geographic information systems that are linked to other automated analytical tools such as statistical and geochemical analysis packages, surface- and ground-water models, and other spatial analysis software.
With the growth in the use of micro-computers and high speed graphical scientific work stations, there is a large selection of software available that allows the management of hydrologic data and quantification of PHC and CHIA. Selection of a suite of software and optimization of specific hardware to store, manage and analyze hydrologic data involves the use of a "computer system". One such system available to both OSM and states with primacy under SMCRA is the OSM Technical Information Processing System (TIPS).
This chapter will cover the value of sorting regional and site-specific data in a data base management system and then using that data to determine baseline conditions and changes from baseline. Automated tools for determining levels of significance of these changes using standard geochemical and statistical procedures will be discussed along with software used for quantifying change by spatial and temporal analysis of data, including TIPS software applications for PHC and CHIA. There is no implication here that the specific TIPS software is the only methodology that can be used to accomplish these analyses.
Hydrologic data bases containing information for the entire United States are referred to as national data bases. The most significant of these are described in detail in the discussion about National Data Bases. The applicability of national data bases to a proposed coal mine operation is generally limited. As a result, it may be desirable for Regulatory Authorities (RA's) to consider establishing hydrologic data bases on a statewide, coal field, watershed, or aquifer basis from information commonly available in permit application files, inspection reports and monitoring reports.
A data base management system (DBMS) is a computer program for the manipulation of information. The information to be manipulated is the data base. Data may be retrieved in the form of reports, graphical displays, or statistical calculations. Data can be reduced to input files for other software applications.
The manipulations commonly used in a DBMS are sorting and filtering. Sorting is arranging the data by some order such as sample date, individual constituent concentration, or type of sampling location (such as an alluvial well, coal well, or overburden well). Sorting allows data to be arranged alphabetically or in ascending or descending numeric order. Filtering is the development of a subset of the data base. For example, if a data base has all hydrologic samples taken on a mine-site, a filter could be set to allow only the ground-water samples to be examined, or a report could be generated that lists only water samples that exceed water quality limits or postmining water quality land use constraints.
TIPS has two principal data base management systems by which users can enter data. These are Oracle DBMS and Reflex DBMS. The State of Wyoming in cooperation with OSM has developed a hydrologic data base shell to store baseline hydrologic data and hydrologic monitoring data for all of the coal mining operations in Wyoming. This is a generic data base shell and is partially based on a questionnaire sent to all RAs addressing their hydrologic data base needs. It was designed specifically to quantify and answer questions related to CHIA and evaluation of PHC. The system resides on the TIPS minicomputer in Denver, Colorado. Like all TIPS applications, the data base is menu driven to facilitate use.
This shell is available through OSM to all RA's so that they may enter State specific hydrologic data. This shell is also available to the public and industry users provided a current version of Oracle software is part of their system. Outputs from the DBMS can be transferred directly to other TIPS applications designed for quantifying hydrologic baseline conditions and quantifying/projecting change.
A generic Reflex DBMS file was set up to enter water quality data for CHIA and evaluating PHC. The shell has built-in calculated fields for TDS error and anion/cation error checking. Reflex is a "flat file" data base that does not allow linking of key fields. It is extremely user-friendly and often a subset of data from the Oracle DBMS is downloaded into reflex for detailed analysis. Standard report output files have been created so that data may be exported from Reflex to other TIPS applications.
Effective quality assurance and quality control (QA/QC) procedures are essential to ensure the validity of hydrologic data and ultimately the decisions utilizing hydrologic data in the coal mine permit process. QA/QC procedures commonly apply to sample collection, sample preservation, control and analysis, as well as the effectiveness of hydrologic data in monitoring a permitted operation.
Quality control refers to specific procedures used to achieve prescribed standards of performance. Quality assurance is an integrated planning process for assuring the reliability of hydrologic data so that it can be used with some definable degree of confidence. Quality assurance components commonly include:
Quality control procedures range from direct monitoring of intra-laboratory precision by using replicate samples or monitoring laboratory accuracy with reference samples, to indirect methods such as cation/anion balance error calculations.
TIPS has automated routines that perform indirect error checks rapidly within a Reflex shell. It is very helpful for the DBMS to be programmed to include tests for TDS error and ion balance error. With tests included in the DBMS, the data not passing the error test can be filtered from use. The error percentage used should generally be less than 10 percent as recommended by the EPA and USGS.
Water quality analyses should contain, at a minimum, the major cations and anions. These include calcium, magnesium, sodium, potassium, bicarbonate, chloride, sulfate, and carbonate. Without this minimum suite of parameters, the data cannot be tested for TDS or ion balance error. The minimum water quality parameters required by SMCRA are insufficient to test for laboratory error.
The methods selected for both the PHC process and the CHIA will depend upon the degree of risk the operation poses to the hydrologic balance and associated water resources and water use. The term "method" is very broad, but in the context of evaluating the hydrologic balance, it generally refers to three types of activities:
Sampling and measurement methods are used to observe and describe components of the hydrologic balance at a certain time or over a period of time. Often, components of the hydrologic balance cannot be directly observed. However, these components can be characterized by measured values of representative parameters. For example, in efforts to describe the status and recharge/discharge relationships of the ground-water quantity component of a hydrologic system, it is generally not possible to directly observe the entire potentiometric surface of the aquifer. However, measurements of its position at specific monitoring locations and times can be made. The value of the observed parameter, in this case the ground water level (and the associated time, date, etc.) represents a single data point. Further, because hydrologic systems usually vary spatially and temporally, several observation sites (wells in this case) are needed to allow characterization of this component of the hydrologic balance.
In scientific measurement, there are three main attributes that describe the quality of the resulting information: precision, bias, and accuracy. The 17th edition of Standard Methods for the Examination of Water and Waste-Water (edited by L. S. Clesceri and others, 1989) defines them as follows:
A single measurement of a hydrologic parameter at a particular site indicates only the value of that hydrologic parameter at one instant in time. It does not represent how the parameter varies with time or how it relates to other variables. At the other extreme, continuous measurements over a period of years may precisely represent the parameter variability, but because of measurement error, would still be only an approximation of the parameter's true value.
Predictive methods are used to estimate the degree and kind of changes from the initial condition of a component of the hydrologic balance caused by mining activities. Both the PHC and CHIA include quantitative determinations that are based on the results of analytical and predictive methods. The selection of methods is dictated by the level of detail needed for the applicant to:
It may be adequate to express some impacts qualitatively if it can be demonstrated that mitigative measures used in a similar setting have been effective. However, most situations require a quantitative approach that includes numerical estimates of impacts for all important components of the hydrologic balance of the permit and adjacent areas. Where high environmental risks to valuable hydrologic resources are associated with a proposed mining operation, the applicant and RA should select measurement techniques and methods that will result in appropriate levels of precision and accuracy. Conversely, where risks are known to be minimal, less precise methodologies may be appropriate.
The most important conditions determining the validity of predictions are:
The validity and therefore, the usefulness of the results will be determined by how closely these conditions are met.
There are several considerations that can help determine how detailed the data base for the PHC and CHIA must be. These are:
The hydrologic balance should be described in as much detail as is necessary to determine whether there will be material damage. For example, most coal preparation plants have very little potential to affect ground-water resources, and this component of the hydrologic balance might be adequately evaluated with relative ease. On the other hand, mining in acid-forming overburden in an area where poorly buffered receiving streams support important fisheries, would justify a more intensive evaluation.
There is no simple answer as to how detailed a PHC must be. The information and analyses should be adequate to make the necessary findings, namely that:
Significant advances have been made in recent years in applying artificial intelligence to the complicated engineering and scientific problems. Expert systems such as the one developed by OSM, utilize artificial intelligence. An expert system is comprised of a knowledge base and an inference engine. The knowledge base contains the accumulated knowledge of specialists in a narrowly defined area. The contents of the knowledge base are accessed and acted upon by the inference engine which generates heuristic solution strategies. Heuristic is an exploratory problem-solving strategy which can deal with inexact or incompletely formulated axioms or rules of thumb. Expert systems are capable of utilizing these rules of thumb to arrive at reasonable solutions to specific problems.
OSM has developed a prototype expert system named Surface Mining And Reclamation Task Expert System Technology (SMARTEST). SMARTEST addresses the probable impacts from surface mining in the Appalachian Coal Basin. It contains a knowledge base derived from interviews with numerous hydrogeologists who are acknowledged to possess expertise both in the hydrogeology of the Appalachian Region and the hydrologic impacts of coal mining.
SMARTEST assists both inexperienced, and experienced hydrogeologists in both defining the hydrologic system at any given mine site and in developing predictions of PHC. SMARTEST operates in an interactive mode and asks the user numerous questions concerning site location, geologic data, baseline hydrologic data, proposed mining and reclamation techniques, and proposed postmining land uses. SMARTEST tests input data and generates warnings to the user when errors or inconsistencies are indicated. A "worst case" PHC is then generated which represents the unmitigated impacts of mining. The user then enters the HRP data including, but not limited to, drainage controls, erosion and sediment controls, and special material handling plans. A final PHC determination is then generated that addresses the likely hydrologic impacts of mining on the aquifer in the permit and adjacent areas. It also generates predictions of possible changes in surface- and ground-water quality and quantity, and an assessment of the potential for the development of acid mine drainage. These predictions can be printed as a report submitted with the permit application. For more information on SMARTEST, contact Robert Evans of OSM by telephone at (412) 937-2895 or by E-mail.
Statistical procedures are excellent tools for quantifying change and statistically comparing postmining data from a nearby watershed with baseline water quality in the CIA. This is most often done by comparing summary statistics for pre and postmining data for performing a two-sample test on the baseline versus postmining data for ground-water quality within a given aquifer or specific surface-water monitoring site resulting from mining. Regression analysis may be performed for a given surface-water quality monitoring station to determine what changes have occurred over time. All of these types of analyses can be performed with Statgraphics.
Multi-Dimensional Spatial Analysis, Volumetrics and Simulation (earthVision from Dynamic Graphics, Inc.)
This state of the art software package is used to analyze a wide variety of multi-dimensional spatial information and will accept drill log information, coal and overburden quality data, toxic material distribution data, coal-crop information, cross-section data or digitized information. EarthVision will then display this information spatially in real time, geo-referenced to the earth's surface. EarthVision's uses include: analysis of approximate original contour (AOC); hydrologic impact assessment; subsidence control planning; volumetrics; ground water contaminant distribution; three-dimensional toxic- and acid-forming material distribution; verification of special handling plans and geostatistical analysis. Output includes generation of complex, camera-ready geo-referenced, maps, graphics, and tables related to volumetrics of resources, overburden, and toxic materials.
The full version of MODFLOW resides on the OSM minicomputer in Denver.
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