A decision support system for phosphorus management at a watershed scale.

Area of Science:

• Environmental Science
• Agricultural Science
• Water Resource Management

Background:

• Phosphorus (P) is a key nutrient driving algal blooms in aquatic ecosystems.
• Agricultural P management is crucial for mitigating aquatic pollution.
• Identifying and addressing P loss sources in agricultural watersheds is essential.

Purpose of the Study:

• To develop and apply a decision support system (DSS) for managing phosphorus losses from agricultural lands.
• To identify critical source areas (CSAs) of phosphorus loss within a Swedish agricultural watershed.
• To diagnose causes of P loss and prescribe effective best management practices (BMPs).

Main Methods:

• Development of a DSS integrating the Maryland Phosphorus Index (PI), diagnosis and prescription expert systems (ES), and the GLEAMS model.
• Application of the PI to identify CSAs within the agricultural watershed.
• Utilizing ES for diagnosing P loss causes and recommending BMPs.
• Employing GLEAMS simulations to evaluate the environmental impact of BMPs on P losses.

Main Results:

• The PI identified small watershed areas (5.2–10.4%) as CSAs with high potential P movement.
• Key P loss causes identified include high soil P, excessive fertilization, proximity to streams, and subsurface drainage.
• Recommended BMPs such as buffer strips and reduced P application significantly decreased runoff and sediment P losses.
• GLEAMS simulations showed a 55% reduction in runoff P and a 71% reduction in sediment P losses with BMP implementation.

Conclusions:

• The developed DSS is effective in pinpointing CSAs and guiding BMP selection for phosphorus management.
• Implementing recommended BMPs can substantially reduce phosphorus losses, benefiting water quality.
• The DSS provides a valuable tool for long-term strategic planning and evaluation of BMP effectiveness in agricultural watersheds.