Automated sample collection for water quality research and evaluation generally is performed by simple time-paced or flow-weighted sampling protocols. However, samples collected on strict time-paced or flow-weighted schemes may not adequately capture all elements of storm event hydrographs (i.e., rise, peak, and recession). This can result in inadequate information for calculating chemical mass flux over storm events. In this research, an algorithm was developed to guide automated sampling of hydrographs based on storm-specific information. A key element of the new " hydrograph-specific sampling scheme" is the use of a hydrograph recession model for predicting the hydrograph recession curve, during which flow-paced intervals are calculated for scheduling the remaining samples. The algorithm was tested at a tile drained Midwest agricultural site where real-time flow data were processed by a programmable datalogger that in turn activated an automated sampler at the appropriate sampling times to collect a total of twenty samples during each storm event independent of the number of sequential hydrographs generated. The utility of the algorithm was successfully tested with hydrograph data collected at both a tile drain and agricultural ditch, suggesting the potential for general applicability of the method. This sampling methodology is flexible in that the logic can be adapted for use with any hydrograph recession model; however, in this case a power law equation proved to be the most practical model.
All Science Journal Classification (ASJC) codes
- Water Science and Technology