A simple stochastic model of point source solute transport in rivers based on gauging station data with implications for sampling requirements

A simple point-source water quality model was constructed to explore hypothetical scenarios of linear alkylbenzene sulphonate (LAS) load variability, chemical degradation kinetics, river discharge and river velocities within the context of planned water quality monitoring in the river Lambro, northern Italy. LAS is an anionic surfactant and a commonly used ingredient of household detergents. Input loads were derived from flow and concentration measurements at sewage treatment works (STW). River travel times are approximated using hydraulic geometry concepts based on existing records of stage, discharge and velocity measurements. The model proved to be especially useful in predicting the impact of overflows from an undersized STW near the top of the catchment on diurnal variations in water quality downstream. Probability density functions (pdf's) of LAS concentrations for a number of points on the river were approximated by running the model stochastically (using a Monte Carlo procedure) over independent frequency distributions of discharge, temperature and input load. The predicted concentration pdf's were then used to estimate the number of random grab and 24h composite samples, which would be required in order to estimate mean concentrations with confidence. This is especially important in situations where the analysis is expensive and the sample budget is limited. The model results showed that grab sampling was not a viable strategy in the Lambro largely due to the very strong diurnal variability in concentrations induced by the STW overflow. This conclusion was corroborated by field data. Copyright (C) 1999 Elsevier Science Ltd.