Real‐Time Sampling Strategies for Estimating Nutrient Loadings

Abstract

An investigation of water‐quality sampling strategies, applicable to real‐time sampling programs, is presented. The sampling strategies are designed to be a component of the data‐collection process for the determination of the annual mass load of pollutants, or nutrients, in a river. As such, the sampling schemes are intended for use in situations where stream‐flow data are collected regularly, but concentration data are collected during only a limited number of time periods. The sampling strategies are evaluated through the use of a Monte Carlo experiment that created synthetic stream‐flow and associated nutrient concentration data. The performance of each sampling strategy is evaluated and compared in terms of an accuracy measure and a precision measure to establish the relative merits of the proposed schemes. A sampling scheme incorporating stratified sampling with realtime updating of the sampling characteristics is found to give the best estimate of the annual mass load.