Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized...

Area of Science:

• Environmental Science
• Hydrology
• Ecology

Background:

• Effective watershed management demands models understanding pollutant sources and transport across diverse landscapes.
• Limited research exists on how landscape spatial configuration influences pollutant transport processes.

Purpose of the Study:

• To investigate nutrient (TN and TP) source composition and transport processes in the Beiyun River Watershed.
• To reveal the influence of landscape patterns on nutrient transport using integrated models.
• To identify pollution hotspots and inform nutrient control strategies.

Main Methods:

• Constructed SPARROW_TN and SPARROW_TP models by integrating direct pollution source data and landscape pattern data.
• Utilized landscape metrics to enhance model accuracy and analyze spatial variations in nutrient loads.
• Performed source apportionment for total nitrogen (TN) and total phosphorus (TP).

Main Results:

• Model simulations showed significant improvement with landscape metrics (R² increased to 0.93 for TN and 0.91 for TP).
• Identified spatial variations in TN and TP loads, yields, and source compositions, effectively pinpointing pollution hotspots.
• TN sources: atmospheric deposition (35.25%), untreated sewage (28.23%), agriculture (22.60%), treated sewage (13.92%). TP sources: untreated sewage (44.94%), agriculture (40.22%), treated sewage (11.51%).
• Specific landscape metrics (grassland patch index, buildup land shape index, forest interspersion index) showed correlations with nutrient transport.

Conclusions:

• Landscape patterns play a crucial role in nutrient transport processes within watersheds.
• Integrated modeling approaches enhance the understanding of nutrient dynamics and source contributions.
• Findings provide critical insights for developing spatially explicit nutrient management and control measures.