Question: What would happen if a data set did not contain data for an analytical method with criteria in DQM?

Answer: DQM only evaluates the data for the analytical methods contained in the dataset for which the analytical methods are also configured in the selected DQM QAPP.

Question: What does ND_QUALIFIERS mean?

Answer: The ND in ND_QUALIFIERS stands for "Non-Detect". If an exception is encountered for one of the rules for one of the DQM checks for a not-detected result, then the ND_QUALIFIER contained in RT_DQM_RULE will be populated in the DQM_QUALIFER and the APPLY_QUALIFIER columns in the DQM Event Review after creating a DQM Event.

Click the down arrow in the QUALIFIER or ND_QUALIFIER column to display all of the qualifiers with STATUS_FLAG = ‘A’ in RT_DQM_QUALIFIER.

Question: How do I change the ‘remark’ for a qualifier?

Answer: The REMARK column in the RT_DQM_RULE is the remark that is placed in the APPLY_REMARK column after an Event is created (if an exception to the rule is encountered); this remark can be edited for each DQM QAPP. When the Event is completed, this remark is written into the DQM_REMARK column of DT_RESULT to document the specific reason for the application of a qualifier. (The REMARK column in RT_DQM_QUALIFIER is not used by DQM).

Question: Why is the ‘J’ qualifier used for many different situations?

Examples: Holding time exceedances, five different RPD failures, and spike recoveries.

Answer: The US EPA National Functional Guidelines include a list of data validation qualifiers, including the “J” qualifier. The “J” qualifier is defined in this document as “The result is an estimated quantity”. There are many reasons that the “J” validation qualifier is prescribed to be used by the data validation guidelines, and therefore there are many DQM rules that the “J” qualifier could be applied if a rule exception is encountered. If your project requirements differ, simply change the qualifiers in your DQM QAPP to match the requirements of your project.

Question: How do I assign a rank for qualifiers?

Example: Depending on which exception DQM finds first, either UJ or JU is returned (within the same dataset) – is there a way to force DQM to always output UJ and never JU?

Answer: Qualifiers can be ranked in RT_DQM_QUALIFIER by populating QUALIFIER_RANK. The lower the number, the higher the ranking. Additionally, there are several parameter values that require consideration and population in RT_DQM_CHECK_PARAM for the global parameters check in the DQM QAPP EDD. For additional details, see Ranking Qualifiers and Reason Codes and DQM Settings > Qualifiers Tab.

We have a feature request with our development team to add greater control on the merger of qualifiers to a future build of DQM. Currently, order of the qualifiers when merging can be forced when the combination itself exists in RT_DQM_QUALIFIER. For example, if there is J, U, and UJ in the RT_DQM_QUALIFIER table, the merge of J and R will be UJ, not JU. If there are common combinations wanted in a certain order (such as UJ), please add those combinations to the RT_DQM_QUALIFIER table.

Question: How do I set up a hierarchy of data qualification to avoid multiple, possibly conflicting data qualifiers for a given result?

Answer: DQM functionality includes several configuration options for ranking qualifiers and reason codes to allow you to define the data qualification hierarchy appropriate for your project needs. Details on ranking qualifiers and reason codes can be found here.

Question: How do I change a DQM_RULE?

Answer: For the existing DQM functionality to work as designed, none of the DQM Rules can be changed. Only the QUALIFIER, ND_QUALIFIER, and REMARK columns can be changed in a new DQM QAPP EDD by uploading the EDD into EQuIS or by reconfiguring these fields directly in the DQM Settings Form.

DQM FAQs: Qualifiers