1、Designation: D6312 17Standard Guide forDeveloping Appropriate Statistical Approaches forGroundwater Detection Monitoring Programs at WasteDisposal Facilities1This standard is issued under the fixed designation D6312; the number immediately following the designation indicates the year oforiginal adop
2、tion or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope*1.1 This guide covers the context of groundwater monitor-ing at waste dispo
3、sal facilities. Regulations have requiredstatistical methods as the basis for investigating potentialenvironmental impact due to waste disposal facility operation.Owner/operators must typically perform a statistical analysison a quarterly or semiannual basis. A statistical test is per-formed on each
4、 of many constituents (for example, 10 to 50 ormore) for each of many wells (5 to 100 or more). The result ispotentially hundreds, and in some cases, a thousand or morestatistical comparisons performed on each monitoring event.Even if the false positive rate for a single test is small (forexample, 1
5、 %), the possibility of failing at least one test on anymonitoring event is virtually guaranteed. This assumes youhave performed the statistics correctly in the first place.1.2 This guide is intended to assist regulators and industryin developing statistically powerful groundwater monitoringprograms
6、 for waste disposal facilities. The purpose of thisguide is to detect a potential groundwater impact from thefacility at the earliest possible time while simultaneouslyminimizing the probability of falsely concluding that thefacility has impacted groundwater when it has not.1.3 When applied inapprop
7、riately, existing regulation andguidance on statistical approaches to groundwater monitoringoften suffer from a lack of statistical clarity and often imple-ment methods that will either fail to detect contamination whenit is present (a false negative result) or conclude that the facilityhas impacted
8、 groundwater when it has not (a false positive).Historical approaches to this problem have often sacrificed onetype of error to maintain control over the other. For example,some regulatory approaches err on the side of conservatism,keeping false negative rates near zero while false positive ratesapp
9、roach 100 %.1.4 The purpose of this guide is to illustrate a statisticalgroundwater monitoring strategy that minimizes both falsenegative and false positive rates without sacrificing one for theother.1.5 This guide is applicable to statistical aspects of ground-water detection monitoring for hazardo
10、us and municipal solidwaste disposal facilities.1.6 It is of critical importance to realize that on the basis ofa statistical analysis alone, it can never be concluded that awaste disposal facility has impacted groundwater. A statisti-cally significant exceedance over background levels indicatesthat
11、 the new measurement in a particular monitoring well for aparticular constituent is inconsistent with chance expectationsbased on the available sample of background measurements.1.7 Similarly, statistical methods can never overcome limi-tations of a groundwater monitoring network that might arisedue
12、 to poor site characterization, well installation and location,sampling, or analysis.1.8 It is noted that when justified, intra-well comparisonsare generally preferable to their inter-well counterparts becausethey completely eliminate the spatial component of variability.Due to the absence of spatia
13、l variability, the uncertainty inmeasured concentrations is decreased, making intra-well com-parisons more sensitive to real releases (that is, false negatives)and false positive results due to spatial variability are com-pletely eliminated.1.9 Finally, it should be noted that the statistical method
14、sdescribed here are not the only valid methods for analysis ofgroundwater monitoring data. They are, however, currently themost useful from the perspective of balancing site-wide falsepositive and false negative rates at nominal levels. A morecomplete review of this topic and the associated literatu
15、re ispresented by Gibbons (1).21.10 The values stated in SI units are to be regarded asstandard. No other units of measurement are included in thisstandard.1This guide is under the jurisdiction ofASTM Committee D18 on Soil and Rockand is the direct responsibility of Subcommittee D18.21 on Groundwate
16、r andVadose Zone Investigations.Current edition approved Jan. 1, 2017. Published January 2017. Originallyapproved in 1998. Last previous edition approved in 2012 as D6312 98 (2012)1.DOI: 10.1520/D6312-17.2The boldface numbers given in parentheses refer to a list of references at theend of the text.*
17、A Summary of Changes section appears at the end of this standardCopyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United StatesThis international standard was developed in accordance with internationally recognized principles on standardization estab
18、lished in the Decision on Principles for theDevelopment of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.11.11 This standard does not purport to address all of thesafety concerns, if any, associated with its use
19、. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.1.12 This guide offers an organized collection of informa-tion or a series of options and does not recommend a specific
20、course of action. This document cannot replace education orexperience and should be used in conjunction with professionaljudgment. Not all aspects of this guide may be applicable in allcircumstances. This ASTM standard is not intended to repre-sent or replace the standard of care by which the adequa
21、cy ofa given professional service must be judged, nor should thisdocument be applied without consideration of a projects manyunique aspects. The word “Standard” in the title of thisdocument means only that the document has been approvedthrough the ASTM consensus process.2. Referenced Documents2.1 AS
22、TM Standards:3D653 Terminology Relating to Soil, Rock, and ContainedFluids3. Terminology3.1 Definitions:3.1.1 For common definitions of terms in this standard, referto Terminology D653.3.2 Definitions of Terms Specific to This Standard:Defini-tions of Terms from D653 that are used in this standard a
23、nd areprovided for the user.3.2.1 assessment monitoring program, ngroundwatermonitoring that is intended to determine the nature and extentof a potential site impact following a verified statisticallysignificant exceedance of the detection monitoring program.3.2.2 combined Shewhart (CUSUM) control c
24、hart, nastatistical method for intra-well comparisons that is sensitive toboth immediate and gradual releases.3.2.3 detection limit (DL), nthe true concentration atwhich there is a specified level of confidence (for example,99 % confidence) that the analyte is present in the sample (2).3.2.4 detecti
25、on monitoring program, ngroundwater moni-toring that is intended to detect a potential impact from afacility by testing for statistically significant changes in geo-chemistry in a downgradient monitoring well relative tobackground levels.3.2.5 intra-well comparisons, na comparison of one ormore new
26、monitoring measurements to statistics computedfrom a sample of historical measurements from that same well.3.2.6 inter-well comparisons, na comparison of a newmonitoring measurement to statistics computed from a sampleof background measurements (for example, upgradient versusdowngradient comparisons
27、).3.2.7 quantification limit (QL), nthe concentration atwhich quantitative determinations of an analytes concentra-tion in the sample can be reliably made during routinelaboratory operating conditions (3).3.3 Definitions of Terms Specific to This Standard:3.3.1 false negative rate, nin detection mon
28、itoring, therate at which the statistical procedure does not indicate possiblecontamination when contamination is present.3.3.2 false positive rate, nin detection monitoring, the rateat which the statistical procedure indicates possible contami-nation when none is present.3.3.3 nonparametric, adja t
29、erm referring to a statisticaltechnique in which the distribution of the constituent in thepopulation is unknown and is not restricted to be of a specifiedform.3.3.4 nonparametric prediction limit, nthe largest (orsecond largest) of n background samples. The confidence levelassociated with the nonpa
30、rametric prediction limit is a functionof n and k.3.3.5 parametric, adja term referring to a statistical tech-nique in which the distribution of the constituent in thepopulation is assumed to be known.3.3.6 prediction interval or limit, na statistical estimate ofthe minimum or maximum concentration,
31、 or both, that willcontain the next series of k measurements with a specified levelof confidence (for example, 99 % confidence) based on asample of n background measurements.3.3.7 verification resample, nin the event of an initialstatistical exceedance, one (or more) new independent sampleis collect
32、ed and analyzed for that well and constituent whichexceeded the original limit.3.4 Symbols:3.4.1 the false positive rate for an individual comparison(that is, one well and constituent).3.4.2 *the site-wide false positive rate covering all wellsand constituents.3.4.3 kthe number of future comparisons
33、 for a singlemonitoring event (for example, the number of downgradientmonitoring wells multiplied by the number of constituents tobe monitored) for which statistics are to be computed.3.4.4 nthe number of background measurements.3.4.5 2the true population variance of a constituent.3.4.6 sthe sample-
34、based standard deviation of a constitu-ent computed from n background measurements.3.4.7 s2the sample-based variance of a constituent com-puted from n background measurements.3.4.8 the true population mean of a constituent.3.4.9 xthe sample-based mean or average concentration ofa constituent compute
35、d from n background measurements.4. Summary of Guide4.1 This guide is summarized in Fig. 1, which provides aflowchart illustrating the steps in developing a statisticalmonitoring plan. The monitoring plan is based either onbackground versus monitoring well comparisons (for example,3For referenced AS
36、TM standards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.D6312 172FIG. 1 Development of a Statistical Detection Monitoring PlanD6312 173
37、FIG. 1 (continued)D6312 174upgradient versus downgradient comparisons or intra-wellcomparisons, or a combination of both). Fig. 1 illustrates thevarious decision points at which the general comparativestrategy is selected (that is, upgradient background versusintra-well background) and how the stati
38、stical methods are tobe selected based on site-specific considerations. The statisticalmethods include parametric and nonparametric predictionlimits for background versus monitoring well comparisons andcombined Shewhart-CUSUM control charts for intra-wellcomparisons. Note that the background databas
39、e is intended toexpand as new data become available during the course ofmonitoring.5. Significance and Use5.1 The principal use of this guide is in groundwaterdetection monitoring of hazardous and municipal solid wastedisposal facilities. There is considerable variability in the wayin which existing
40、 regulation and guidance are interpreted andFIG. 1 (continued)D6312 175FIG. 1 (continued)D6312 176FIG. 1 (continued)D6312 177practiced. Often, much of current practice leads to statisticaldecision rules that lead to excessive false positive or falsenegative rates, or both. The significance of this p
41、roposed guideis that it jointly minimizes false positive and false negativerates at nominal levels without sacrificing one error for another(while maintaining acceptable statistical power to detect actualimpacts to groundwater quality (4).5.2 Using this guide, an owner/operator or regulatoryagency s
42、hould be able to develop a statistical detectionmonitoring program that will not falsely detect contaminationwhen it is absent and will not fail to detect contamination whenit is present.6. ProcedureNOTE 1In the following, an overview of the general procedure isdescribed with specific technical deta
43、ils described in Section 6.6.1 Detection Monitoring:6.1.1 Upgradient Versus Downgradient Comparisons:6.1.1.1 Detection frequency 50 %.6.1.1.2 If the constituent is normally distributed, compute anormal prediction limit (5) selecting the false positive ratebased on number of wells, constituents, and
44、verificationresamples (6) adjusting estimates of sample mean and variancefor nondetects.6.1.1.3 If the constituent is lognormally distributed, com-pute a lognormal prediction limit (7).6.1.1.4 If the constituent is neither normally nor lognor-mally distributed, compute a nonparametric prediction lim
45、it (7)unless background is insufficient to achieve a 5 % site-widefalse positive rate. In this case, use a normal distribution untilsufficient background data are available (7).6.1.1.5 If the background detection frequency is greater thanzero but less than 50 %.6.1.1.6 Compute a nonparametric predic
46、tion limit and de-termine if the background sample size will provide adequateprotection from false positives.6.1.1.7 If insufficient data exist to provide a site-wide falsepositive rate of 5 %, more background data must be collected.6.1.1.8 As an alternative to 6.1.1.7 use a Poisson predictionlimit
47、which can be computed from any available set ofbackground measurements regardless of the detection fre-quency (see 3.3.4 of Ref (4) ).6.1.1.9 If the background detection frequency equals zero,use the laboratory-specific QL (recommended) or limits re-quired by applicable regulatory agency (8).46.1.1.
48、10 This only applies for those wells and constituentsthat have at least 13 background samples. Thirteen samplesprovide a 99 % confidence nonparametric prediction limit withone resample for a single well and constituent (see Table 1).6.1.1.11 If less than 13 samples are available, more back-ground da
49、ta must be collected to use the nonparametricprediction limit.6.1.1.12 An alternative would be to use a Poisson predictionlimit that can be computed from four or more backgroundmeasurements regardless of the detection frequency and canadjust for multiple wells and constituents.6.1.1.13 If downgradient wells fail, determine cause.6.1.1.14 If the downgradient wells fail because of natural oroff-site causes, select constituents for intra-well comparisons(9).6.1.1.15 If site impacts are found, a site plan for assessmentmonitoring may be necess
