Time-series modeling of reservoir effects on river nitrate concentrations

Abstract

Saylorville Reservoir is a 24.1 km 2 impoundment of the Des Moines River located approximately 10 km north of the City of Des Moines, Iowa, USA. Surface water from the Des Moines River used for drinking water supply is impaired for nitrate–nitrogen. Monthly mean nitrate concentration data collected upstream and downstream of the reservoir for a 30-year period (1977–2006) were selected for time-series analysis. Our objectives were to (1) develop a model describing nitrate concentrations downstream of the reservoir as a function of the concentrations entering the reservoir and (2) use the model to provide a 1-month ahead forecast for downstream water quality. Results indicated that downstream nitrate can be effectively modeled using a transfer function approach that utilized inflow concentrations during the current and previous month as input variables. Inflow concentrations were modeled using an AR(20) model, with the higher order model consistent with temporal correlation noted by others. The transfer function model suggested that the reservoir is reducing nitrate concentrations by 22 ± 6%, a reduction that greatly exceeds previous estimates. Monthly nitrate forecasted with the model were nearly all within a 95% prediction interval of their actual measured values and did not appear greatly affected by flow variations.