Off-the-shelf data collection platforms include software or programming instructions that allow
them to be configured to communicate with a variety of instruments. Additionally, personal
computer communications packages can communicate with water quality equipment and store
and transmit data; however, design flexibility is generally less. BASIC software programs
(Microsoft Corporation) can be developed as an alternative to off-the-shelf communications
packages and afford the user control over communication protocol and data storage format
(Vorwerk, Moore, and Carroll 1996). The data storage format is an important design
consideration because it facilitates integration of the final monitor data set with other pertinent
data sets (for example, hydroproject operation data) and allows real-time data presentation to
better fit project requirements.
Postdeployment data validation is a crucial final step in the monitor installation process, as
this evaluates the representativeness of the monitor location. Although postvalidation may seem
unnecessary if care was taken during preinstallation sampling, the installation itself may have a
measurable impact on how the water quality is represented by the equipment. A dam release
monitor could be installed in the tailrace of a project, with water pumped to it from an area
determined to reflect the area of management concern during generation periods. Subsequent
calibration visits may confirm that the sensors are operating well within the manufacturer's
specifications. From this, it may be assumed that the monitor is accurately representing the
parameters of concern. If, however, the water were being warmed as it passed from the tailrace
through the pipe to the monitor, it would actually reflect the water within the sample chamber
and not the tailwater. Likewise, changes in the physical structure of a site or introduction of
water quality improvement measures may alter the representativeness of an established monitor.
These concerns must be addressed via postdeployment verification studies.
After the monitor is in place and recording representative water quality data, the next concern
is how the data should be used. Raw monitor data are of little use if they are not presented in a
manner that facilitates interpretation. Off-the-shelf spreadsheet and database programs such as
Excel (Microsoft Corporation), SAS (SAS Institute, Inc.), and SPSS (SPSS, Inc.) expedite data
analysis and reporting by facilitating the linkage of monitor data with other project data. Data
must undergo vigorous error-detection and filtering processes prior to analysis. Raw monitor data
must be edited to remove machine characters, usually artifacts of the data collection software,
before they can be properly imported into analysis software packages.
Water quality sensors typically exhibit some degree of response drift as a result of the
sensors' chemical reactions (for example, oxidation of DO probes). Sensor drift can also result
from biological activity. For example, algal growth on DO probes may decrease the reported DO
may reduce the degree of sensor drift; however, postdeployment corrections for sensor drift can
further improve data accuracy.
Water Quality Technical Note AM-02 (January 1998)