Too ill to cure? - An uncertainty-based probabilistic model assessment on one of China's most eutrophic lakes

Eutrophication is a global challenge, which is exemplified by the tremendous efforts but little results in restoring the sixth largest and also one of the most eutrophic freshwater lakes in China, Lake Dianchi. Considering large parametric uncertainties in water quality modeling, the traditionally used deterministic water quality model is expanded to a probabilistic model to explore the Lake Dianchi's potential responses to different levels of pollutant load reductions. The results show that, given the long pollution history and severe pollution state in Lake Dianchi, a minimum pollution load reduction by half (base year 2003) is required to maintain the water quality state as it is now in 40 years. At least a 60% nutrient load reduction is required to generate any likelihood of water quality improvement, however, the system stabilizes quickly after about 10 years, which may explain why tremendous investments have generated little results. 80% of nutrient load reduction for 40 years has 95% probability of meeting the TN target but only a below 50% (45%) probability in meeting the TP target, and even less to meet water quality target for Chla. The feasibility of ever reaching the Chinese drinking water standards for total phosphorous and total nitrogen is questionable.

Automated summary

Eutrophication is a global challenge, and Lake Dianchi in China is an example of the difficulty in restoring a highly eutrophic freshwater lake. By using a probabilistic water quality model, it is found that a minimum 50% reduction in pollution load is required to maintain the current water quality state in Lake Dianchi. To improve water quality, at least a 60% reduction in nutrient load is needed. However, the system stabilizes quickly after about 10 years, which may explain the limited results from previous restoration efforts.