A framework to develop joint nutrient criteria for lake eutrophication management in eutrophic lakes

Abstract

Nutrient criteria provide the numeric basis for lake eutrophication management. However, there are two obstacles that can hinder the effective application of nutrient criteria, including 1) although total phosphorus (TP) and total nitrogen (TN) might co-limit phytoplankton biomass in eutrophic lakes, their criteria are often developed independently; and 2) the linkage between nutrient criteria and the percentile-based compliance assessment method of chlorophyll a (CHL; as a measure of phytoplankton biomass) has not been well established. To resolve these obstacles, we propose a novel analytical framework of nutrient criteria development, by which joint nutrient criteria are developed using quantile regression (QR). We demonstrated the steps necessary to utilize this novel approach using TP, TN, and CHL data from Lake Dianchi, a hypereutrophic lake located in southwestern China. First, we built candidate QR models to quantify the nutrient-CHL relationship at six regression quantiles. Next, we conducted the sequential Wald test to select the “best” model for each regression quantile. Finally, we visualized the joint nutrient criteria surface using a contour map. The contour map effectively illustrated the joint nutrient criteria by showing the linkage of TP and TN criterion. In addition, based on the QR, it was easy to deduce nutrient criteria which met the requirement of percentile-based compliance assessment. We further found that joint nutrient criteria could help the selection of an efficient load reduction strategy in the watershed. The proposed method can be generalized to other systems and may facilitate site-specific lake eutrophication management.