Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for...

Area of Science:

• Environmental Science
• Water Quality Management
• Agricultural Hydrology

Background:

• Microbial pollution from agriculture threatens surface water quality.
• Farm management practices significantly influence fecal pollution levels.
• Costly catchment interventions exist but require efficient spatial targeting.

Purpose of the Study:

• To evaluate the SCIMAP model's effectiveness in predicting microbial water pollution.
• To assess SCIMAP's suitability for targeting fecal indicator organism (FIO) pollution management.
• To determine optimal land cover risk weightings for FIO risk mapping.

Main Methods:

• Applied the SCIMAP risk-based model to two UK river catchments.
• Utilized land cover risk weightings and hydrological connectivity.
• Employed Monte-Carlo sampling for model performance assessment and weighting derivation.
• Compared model outputs for E. coli against observed water quality data.

Main Results:

• SCIMAP performance in predicting FIO risk was variable between catchments.
• Better prediction accuracy was observed in the Yealm catchment (r _s=0.88) compared to the Wyre (r _s=-0.36).
• Significant uncertainty was linked to assigning risk weightings to different land use classes.

Conclusions:

• SCIMAP demonstrates potential for spatially targeting diffuse fecal indicator organism pollution management.
• Further enhancements are necessary to develop SCIMAP into a reliable FIO risk-mapping tool.
• The model's utility is currently limited by variability and uncertainty in risk assessments.