A simulation based approach to quantify the difference between event-based and routine water quality monitoring schemes

• Monitoring schemes must use appropriate sampling schemes to quantify exports.
• Historical water quality datasets usually contain sparse and limited observations.
• Comparisons of sampling schemes can be made using linear mixed model based simulations.
• Combining event and routine sampling improved the accuracy of estimates by up to 16.1 tonnes year−1.

Study regionSouth eastern Australia.Study focusThis region is characterised with rainfall events that are associated with large exports of nutrients and sediments. Many water quality monitoring schemes use a form of event-based sampling to quantify these exports. Previous water quality studies that have evaluated different sampling schemes often rely on continuously monitored water quality data. However, many catchment authorities only have access to limited historical data which consists of event-based and monthly routine samples. Therefore there is a need to develop a method that assesses the importance of sampling events using information from limited historical data. This work presents a simulation based approach using unconditional simulation based on historical stream discharge. Such an approach offers site-specific information on optimal sampling schemes. A linear mixed model is used to model the relationship between total phosphorus and stream discharge and the auto-correlation of total phosphorus.New hydrological insights for the regionThe inclusion of event-based sampling improved annual load estimates of all sites with a maximum RMSE difference of 16.11 tonnes between event-based and routine sampling. Based on the accuracy of annual loads, event-based sampling was found to be more important in catchments with a large relief and high annual rainfall in this region. Using this approach, different sampling schemes can be compared based on limited historical data.