Modeling the non-point source pollution risks by combing pollutant sources, precipitation, and landscape structure.

Area of Science:

• Environmental Science
• Water Resource Management
• Ecology

Background:

• Traditional nutrient simulation models often overlook landscape structure's role in pollution.
• Non-point source (NPS) pollution, particularly total nitrogen (TN) export, is a significant environmental challenge in large river basins.
• Effective management requires models that integrate multiple contributing factors.

Purpose of the Study:

• To develop and validate a novel Source-Precipitation-Landscape Model (SPLM) for predicting NPS total nitrogen (TN) pollution.
• To quantify TN exports and identify key drivers within the Haihe River Basin (HRB), China.
• To provide a tool for policymakers to mitigate NPS pollution in rapidly urbanizing regions.

Main Methods:

• Developed the Source-Precipitation-Landscape Model (SPLM) integrating pollutant sources, precipitation, and landscape structure.
• Applied the SPLM to simulate NPS TN exports across 1578 catchments in the Haihe River Basin.
• Validated the model's accuracy using TN concentration data from 35 sampling catchments in 2013.

Main Results:

• The SPLM demonstrated high accuracy in simulating NPS TN export and intensity, particularly TN intensity.
• Mean TN export in the HRB was 441.97 tons, with an average intensity of 2.08 t/km².
• TN export intensity varied significantly, with plain sub-basins exhibiting higher intensities than mountainous ones. Land use, livestock, and rural population were the primary contributors to TN exports.

Conclusions:

• The SPLM is a reliable tool for assessing and managing NPS TN pollution.
• Understanding the spatial variation and key drivers of TN export is crucial for targeted pollution control.
• The model's adaptability offers potential for application in other regions facing similar environmental pressures.