An approach for probabilistic forecasting of seasonal turbidity threshold exceedance

To this end, a generalized approach is developed that uses seasonal forecasts to predict the likelihood of exceeding a prescribed water quality limit. Because many water quality standards are based on thresholds, this study utilizes a logistic regression technique, which employs nonparametric or "local" estimation that can capture nonlinear features in the data.

The approach is applied to a drinking water source in the Pacific Northwest United States that has experienced elevated turbidity values that are correlated with streamflow. The main steps of the approach are to (1) obtain a seasonal probabilistic precipitation forecast, (2) generate streamflow scenarios conditional on the precipitation forecast, (3) use a local logistic regression to compute the turbidity threshold exceedance probabilities, and (4) quantify the likelihood of turbidity exceedance corresponding to the seasonal climate forecast.