WATER QUALITY CALIBRATION CRITERIA FOR BACTERIA TMDL DEVELOPMENT

ABSTRACT. The objective of this study was to report the development of statistics and associated criteria for assessing calibration endpoints of a watershed-scale model used to simulate in-stream bacteria concentrations. Development of these statistics grew out of the authors ’ experience modeling i...

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Bibliographic Details
Main Authors: S. M. Kim, B. L. Benham, K. M. Brannan, R. W. Zeckoski, G. R. Yagow
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.533.2070
http://www.tmdl.bse.vt.edu/uploads/File/pub_db_files/Kim_Water Quality Calibration criteria for bacteria TMDL development.pdf
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Summary:ABSTRACT. The objective of this study was to report the development of statistics and associated criteria for assessing calibration endpoints of a watershed-scale model used to simulate in-stream bacteria concentrations. Development of these statistics grew out of the authors ’ experience modeling in-stream bacteria for TMDLs addressing bacterial impairments. The calibration statistics include: geometric mean, daily violation rate of bacteria water quality criterion, and the minimum-maximum range associated with a “temporal window ” that spans a period of several days. Because in-stream bacteria concentrations are typically sampled infrequently (on a monthly basis, at best) and represent only an instant in time, it is not reasonable to expect any model to simulate a daily average concentration equal to an observed value on a particular day. For this reason, the authors developed the temporal-window statistic. The temporal-window statistic uses simulated hourly-concentrations over a period of several days (five days were used by the authors) to calculate the minimum-maximum range that is compared to observed in-stream bacteria concentrations. Each temporal window is centered on the day the observed data was collected. Thus, this measure of model calibration determines how frequently the observed data falls within the range of simulated data during a time period that extends several days before and after the observation. Criteria for assessing the sufficiency of a model calibration for simulating in-stream bacteria concentration were developed using the relative difference between the simulated and observed statistics. The reported calibration statistics and criteria can be used to guide the water quality model calibration process for simulation of in-stream bacteria concentration. This article illustrates the application of the calibration statistics to HSPF simulations for the Beaver Creek watershed in Virginia.