A simulation-based method to develop strategies for nitrogen pollution control in a creek watershed with sparse data.

Well-defined targets for nitrogen (N) release into the local environment are essential for water management in creeks, but difficulties often arise from working with data that are too sparse to achieve reliable evaluations. Here, a simulation-optimization approach based on the QUAL2K model was developed to put forward strategies for nitrogen pollution control in a creek with sparse data in Shixi Creek, southeast China. The model showed good agreement with field observations from 22 sampling sites sampled over the period from March 2017 to February 2019, with normalized objective function (NOF) less than 0.360. Based on this model, the water pollutant sources in the creek were distinguished and analyzed. Rural sewage discharge in Shixi Creek was the major factor threatening water quality in the stream. Seasonal variations may influence the transformation of riverine N. To make more than 80% of the area in Shixi Creek meet the water quality standard of grade III, an optimized approach is to reduce more than 55% of the N pollution from point source pollution and 10% from nonpoint source pollution. This study proposed an approach that can effectively evaluate strategies for water management in a creek watershed with sparse data.