ASTM D6312-1998(2012)e1 7500 Standard Guide for Developing Appropriate Statistical Approaches for Groundwater Detection Monitoring Programs《制定关于地下水监测监控程序的适当统计方法制定的标准指南》.pdf

《ASTM D6312-1998(2012)e1 7500 Standard Guide for Developing Appropriate Statistical Approaches for Groundwater Detection Monitoring Programs《制定关于地下水监测监控程序的适当统计方法制定的标准指南》.pdf》由会员分享，可在线阅读，更多相关《ASTM D6312-1998(2012)e1 7500 Standard Guide for Developing Appropriate Statistical Approaches for Groundwater Detection Monitoring Programs《制定关于地下水监测监控程序的适当统计方法制定的标准指南》.pdf（15页珍藏版）》请在麦多课文档分享上搜索。

1、Designation: D6312 98 (Reapproved 2012)1Standard Guide forDeveloping Appropriate Statistical Approaches forGroundwater Detection Monitoring Programs1This standard is issued under the fixed designation D6312; the number immediately following the designation indicates the year oforiginal adoption or,

2、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.1NOTEEditorial changes were made throughout in February 2012.1. Scope1.1 This guide covers th

3、e context of groundwater monitor-ing at waste disposal facilities. Regulations have requiredstatistical methods as the basis for investigating potentialenvironmental impact due to waste disposal facility operation.Owner/operators must perform a statistical analysis on aquarterly or semiannual basis.

4、Astatistical test is performed oneach of many constituents (for example, 10 to 50 or more) foreach of many wells (5 to 100 or more). The result is potentiallyhundreds, and in some cases, a thousand or more statisticalcomparisons performed on each monitoring event. Even if thefalse positive rate for

5、a single test is small (for example, 1 %),the possibility of failing at least one test on any monitoringevent is virtually guaranteed. This assumes you have done thecorrect statistic in the first place.1.2 This guide is intended to assist regulators and industryin developing statistically powerful g

6、roundwater monitoringprograms 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

7、not.1.3 When applied inappropriately, 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

8、that the facilityhas impacted 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

9、while false positive ratesapproach 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 det

10、ection monitoring for hazardous 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 ba

11、ckground levels indicatesthat 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 monitorin

12、g network that might arisedue 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

13、.Due to the absence of spatial 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 note

14、d that the statistical methodsdescribed 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 topi

15、c and the associated literature ispresented by Gibbons (1).21.10 The values stated in both inch-pound and SI units areto be regarded as the standard. The values given in parenthesesare for information only.1This guide is under the jurisdiction ofASTM Committee D18 on Soil and Rockand is the direct r

16、esponsibility of Subcommittee D18.21 on Groundwater andVadose Zone Investigations.Current edition approved Feb. 15, 2012. Published December 2012. Originallyapproved in 1998. Last previous edition approved in 2005 as D631298(2005).DOI: 10.1520/D6312-98R12E1.2The boldface numbers given in parentheses

17、 refer to a list of references at theend of the text.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States11.11 This standard does not purport to address all of thesafety concerns, if any, associated with its use. It is theresponsibility of

18、 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 specificcourse of action. This docum

19、ent 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 adequacy ofa given professional se

20、rvice 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 ASTM Standards:3D653 Terminolo

21、gy Relating to Soil, Rock, and ContainedFluids3. Terminology3.1 Definitions:3.1.1 For definitions of common technical terms in thisstandard, refer to Terminology D653.3.2 Definitions of Terms Specific to This Standard:3.2.1 assessment monitoring program, ngroundwatermonitoring that is intended to de

22、termine 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 chart, nastatistical method for intra-well comparisons that is sensitive toboth immediate and gradual releases.

23、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 detection monitoring program, ngroundwater moni-toring that is intended to detect a potential impact from afacility b

24、y 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 monitoring measurements to statistics computedfrom a sample of historical measurements from that same well.3.2

25、.6 inter-well comparisons, na comparison of a newmonitoring measurement to statistics computed from a sampleof background measurements (for example, upgradient versusdowngradient comparisons).3.2.7 prediction interval or limit, na statistical estimate ofthe minimum or maximum concentration, or both,

26、 that willcontain the next series of k measurements with a specified levelof confidence (for example, 99 % confidence) based on asample of n background measurements.3.2.8 quantification limit (QL), nthe concentration atwhich quantitative determinations of an analytes concentra-tion in the sample can

27、 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 monitoring, therate at which the statistical procedure does not indicate possiblecontamination when contamination is present.3.3.2 false pos

28、itive rate, nin detection monitoring, the rateat which the statistical procedure indicates possible contami-nation when none is present.3.3.3 nonparametric, adja term referring to a statisticaltechnique in which the distribution of the constituent in thepopulation is unknown and is not restricted to

29、 be of a specifiedform.3.3.4 nonparametric prediction limit, nthe largest (orsecond largest) of n background samples. The confidence levelassociated with the nonparametric prediction limit is a functionof n and k .3.3.5 parametric, adja term referring to a statistical tech-nique in which the distrib

30、ution of the constituent in thepopulation is assumed to be known.3.3.6 verification resample, nin the event of an initialstatistical exceedance, one (or more) new independent sampleis collected and analyzed for that well and constituent whichexceeded the original limit.3.4 Symbols:3.4.1 the false po

31、sitive 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 for a singlemonitoring event (for example, the number of downgradientmonitoring wells multiplied by the numb

32、er 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-based standard deviation of a constitu-ent computed from n background measurements.3.4.7 s2the sample-based v

33、ariance 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 computed from n background measurements.4. Summary of Guide4.1 This guide is summarized in Fig. 1, which provides af

34、lowchart illustrating the steps in developing a statisticalmonitoring plan. The monitoring plan is based either onbackground versus monitoring well comparisons (for example,upgradient versus downgradient comparisons or intra-wellcomparisons, or a combination of both). Fig. 1 illustrates the3For refe

35、renced ASTM 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 98 (2012)12FIG. 1 Development of a Statistical Detection Monitor

36、ing PlanD6312 98 (2012)13FIG. 1 (continued)D6312 98 (2012)14FIG. 1 (continued)D6312 98 (2012)15FIG. 1 (continued)D6312 98 (2012)16FIG. 1 (continued)D6312 98 (2012)17various decision points at which the general comparativestrategy is selected (that is, upgradient background versusintra-well backgroun

37、d) and how the statistical 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 th

38、e background database 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

39、wayin which existing Guide USEPA regulation and guidance areinterpreted and practiced. Often, much of current practice leadsto statistical decision rules that lead to excessive false positiveor false negative rates, or both. The significance of thisproposed guide is that it jointly minimizes false p

40、ositive andfalse negative rates at nominal levels without sacrificing oneerror for another (while maintaining acceptable statisticalpower to detect actual impacts to groundwater quality (4).5.2 Using this guide, an owner/operator or regulatoryagency should be able to develop a statistical detectionm

41、onitoring 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 details described in Section 6.6.1 Detection Monitori

42、ng: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 verificationresamples (6) adjusting estimates of

43、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 limit (7)unless background is insufficient to achiev

44、e 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 prediction limit and de-termine if the background sampl

45、e 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 which can be computed from any available set ofba

46、ckground 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).46.1.1.10 This only applies for those wells and constitu

47、entsthat 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 data must be collected to use the nonparametricpred

48、iction 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 do

49、wngradient 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 necessary (10).6.1.2 Intra-well Comparisons:6.1.2.1 For those facilities that either have no definablehydraulic gradient, have no existing contamination, have toofew background wells to meaningfully characterize spatialvariability (for example, a site with one upgradient well or afacility in which upgradient water quality is either inaccessibleor