Spatiotemporal characteristics of nonpoint source nutrient loads and their impact on river water quality in Yancheng city, China, simulated by an improved export coefficient model coupled with grid-based runoff calculations

Abstract

Accurately quantifying the spatiotemporal nutrient loads from nonpoint sources (NPSs) is still difficult due to the high spatial heterogeneity and temporal variability in rainfall-runoff processes. The export coefficient model (ECM) is a widely used tool to estimate the NPS nutrient load on an annual time scale, but it hardly considers the spatiotemporal distribution of the export coefficient. To address this issue, the ECM is improved by incorporating a grid-based rainfall-runoff module together with land-use data and analysing the spatiotemporal characteristics of the NPS nutrient loads in Yancheng city located in eastern China. Moreover, the effect of NPS nutrient loads on river water quality is assessed using a conceptual model. The results indicate that the improved ECM can simulate reasonable spatiotemporal variation in NPS nutrient loads, and the relative error in the total phosphorus (TP) load is less than 17.14 %. Precipitation has a considerable influence on both the total nitrogen (TN) and TP loads, which varied greatly from 1990 to 2018, with average annual values of 30.57 × 103 tons and 2.44 × 103 tons, respectively. The spatial distributions of the TN and TP loads were greatly affected by land-use patterns, and bodies of water and rural land had relatively high load intensities. Both TN and TP concentrations in the river exceeded the national standard, but TP was significantly reduced in the past 10 years, while TN was still at high level. This study provides a reference for reducing the river pollution in Yancheng city, especially by identifying pollution sources requiring priority control.