TY - JOUR
T1 - Integrating hydrograph modeling with real-time flow monitoring to generate hydrograph-specific sampling schemes
AU - Gall, Heather E.
AU - Jafvert, Chad T.
AU - Jenkinson, Byron
N1 - Funding Information:
We would like to thank the EPA for funding this research under the Science to Achieve Results (STAR) Program grant number RD833417. We also would like to extend our gratitude to the application engineers at Campbell Scientific, Inc., especially Robert Hyatt and Blake Farnsworth, for their valuable help and advice regarding their company’s equipment; to Douglas Magers at Purdue University, who was instrumental in establishing an Internet connection at our base station; to Steven Smith and Jeffery Fields at Purdue’s Animal Science Research and Education Center for access to tile drain maps and the manure application database; and to Linda Lee at Purdue University. Additional thanks are extended to three anonymous reviewers, whose comments and suggestions greatly improved this manuscript.
PY - 2010/11/8
Y1 - 2010/11/8
N2 - 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.
AB - 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.
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U2 - 10.1016/j.jhydrol.2010.08.028
DO - 10.1016/j.jhydrol.2010.08.028
M3 - Article
AN - SCOPUS:77957871923
SN - 0022-1694
VL - 393
SP - 331
EP - 340
JO - Journal of Hydrology
JF - Journal of Hydrology
IS - 3-4
ER -