Development of a Minimalistic Data Collection Strategy for QUAL2Kw

Abstract

In-stream water-quality models provide guidance in watershed management decisions by linking pollutant loads to changes in water quality. These models are particularly useful for determining wasteload allocations, developing numeric nutrient criteria, and aiding in total maximum daily load (TMDL) analyses. Unfortunately, the routine data collected as part of the governmental monitoring efforts do not typically meet the data requirements for modeling. Consequently, this study presents a data collection methodology suited to meet basic in-stream water-quality modeling requirements for a commonly used model (QUAL2Kw). To set some model parameters directly, methods are provided for estimating maximum sediment oxygen demand and determining appropriate reaeration formulas based on observed oxygen time series. The quantity of data gathered within an example case study was minimized to reduce cost, which resulted in expected challenges (e.g., designation of appropriate loading values from highly variable point source information). Similar to other modeling studies, parameter estimates were also not readily identifiable. However, even simple methods to set key parameters and reduce the number requiring calibration proved beneficial. Although most situations will require additional calibration and data for model corroboration, this approach provides an initial framework to aid in the judicious use of resources to meet watershed management decision making needs within the context of wasteload allocation and/or numeric nutrient criteria development.