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Data quality and uncertainty in reservoir water-quality modeling

Abstract - AWRA Annual Spring Speciality Conference on Water Quality Monitoring and Modeling
By Jerad D. Bales

Abstract

Water-quality models, whether mechanistic or stochastic, should be developed by using spatially and temporally detailed, synoptically collected data for calibration and testing. Often, however, models are developed with only limited data. Even when very detailed data sets are collected for modeling applications, uncertainty remains in model simulations because of uncertainty in data (errors and lack of complete temporal and spatial coverage) and in model formulations.

A laterally averaged hydrodynamic and chemical transport model was constructed for each of three Catawba River Basin reservoirs in North Carolina (table 1) by using the CE-QUAL-W2 modeling framework. The 12,400-km2 Catawba River Basin extends from the mountains of the Blue Ridge physiographic province in North Carolina to Lake Wateree, located in the low rolling terrain of the Piedmont Province of South Carolina. In North Carolina, the Catawba River Basin has the highest population density and one of the highest growth rates of all of the 17 major river basins in the State. The only extended free-flowing reach of the river in North Carolina is between Bridgewater Dam at Lake James, the upstream-most reservoir, and the headwaters of Lake Rhodhiss. Thirteen of the 14 reservoirs on the river were constructed before 1930.