The precipitation driven correlation based mapping method (PCM) for identifying the critical source areas of non-point source pollution

- TN and TP yields were highly correlated with the precipitations.
- Urban area has the highest correlation between participation and nutrient yields.
- PCM was proposed to identify the critical source areas (CSAs).
- PCM tackles the problem of limited monitoring data in CSAs identification.
- PCM provides better spatial coverage in identification of CSAs.

SummaryCritical source areas (CSAs) are the areas that are relatively more erosion-prone and contribute significantly more pollutants per unit area. They have been widely recognized as optimal locations for the control of non-point source (NPS) pollution. Modeling approach has been frequently used to identify the CSAs of NPS pollution on a basin scale. In previous studies, CSAs were identified based on the simulated average annual nutrient yields for the simulation period at the levels of sub-basin or hydrologic response unit (HRU). However, this method did not consider the impact of uneven spatial distribution of precipitation, which is considered to be the driven force of NPS pollution. In many cases, due to limited length of qualified monitoring data collected, the simulation period may not cover a full spectrum of the precipitation characteristics so that some potential CSAs may be missed. In the present study, the precipitation driven correlation based mapping method (PCM) was proposed, which can reduce the impact of uncertain spatial-temporal distribution of precipitation and identify the CSAs of NPS pollution with a better coverage. This method was applied to the Zhang River Basin, a watershed in North China that occupies an area of 18,072 km2. The SWAT (Soil and Water Assessment Tool) was used for simulation purposes. By using PCM, the maps of CSAs for controlling total nitrogen (TN) and total phosphorus (TP) were produced. This study has found that the monthly precipitation is highly correlated with the TN and TP yields. It was observed that TN yields have slightly higher correlation value with the precipitation than TP yields. Hence, the precipitation has more impacts on TN yields than TP yields. The impact is more substantial in urban areas than other areas.