A framework for priority non-point source area identification and load estimation integrated with APPI and PLOAD model in Fujiang Watershed, China

The non-point source (NPS) pollution is difficult to manage and control due to its complicated generation and formation. In large scale watersheds, the priority sources areas (PSAs) identification is an important and necessary process for efficient aquatic environmental management. Here, a framework for the PSAs identification and pollution load estimation in PSAs screened for Best Management Practices (BMPs) is proposed. Fujiang Watershed, a branch of Jialingjiang, the upper reach of Yangtze River, was chosen for evaluation of the method proposed here. The entire Fujiang Watershed was divided into 21 subbasins, after which the Agricultural Pollution Potential Index (APPI) was used to identify the PSAs, and a modified runoff coefficient was introduced to mitigate the impact of the rainfall heterogeneity in the process. Next, the identified PSAs were further divided into 34 subbasins, after which quantification of the pollution load was conducted using the Pollution Load (PLOAD) model. The results indicated that there are five subbasins have much higher NPS pollution load intensities, with an average value of 6.05 t/km2/year for TN and 0.31 t/km2/year for TP. According to the cluster analysis on land use structure, these five subbasins were featured by higher proportion of agricultural land, suggesting a need for better fertilizer application management. The method developed here provided a helpful framework for conducting NPS pollution management in a large watershed.

Research highlights
► A framework for PSAs identification and pollution load estimation is proposed.
► APPI and PLOAD model can provide satisfied simulating results in Fujiang Watershed.
► The cluster analysis on land use structure calls for better fertilizer application.
► We proposed a modified runoff coefficient to mitigate the effect of uneven rainfall.