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Identifying critical source areas using multiple methods for effective diffuse pollution mitigation.

S M Reaney1, E B Mackay2, P M Haygarth3

  • 1Department of Geography, Durham University, Durham, DH1 3LE, UK.

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|September 9, 2019
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Summary
This summary is machine-generated.

Identifying critical source areas (CSAs) for diffuse pollution is key for effective mitigation. This study compares smartphone apps, GIS-based SCIMAP, and drone data for CSA identification, recommending a multi-evidence approach.

Keywords:
Critical source areaDiffuse pollutionDronesMappingPhone appWalkover survey

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Area of Science:

  • Environmental Science
  • Water Resource Management
  • Agricultural Science

Background:

  • Diffuse pollution from agriculture significantly degrades freshwater quality and ecosystems.
  • Critical Source Areas (CSAs) are key locations for implementing diffuse pollution mitigation strategies.
  • Accurate identification of CSAs across various spatial scales within catchments remains a challenge.

Purpose of the Study:

  • To evaluate and compare different methods for identifying CSAs.
  • To highlight the benefits and drawbacks of each approach for diffuse pollution management.
  • To inform the development of integrated strategies for mitigating agricultural pollution.

Main Methods:

  • Comparison of traditional walkover surveys with a smartphone app, a GIS-based SCIMAP model, and drone-enhanced SCIMAP.
  • Assessment of spatial and temporal resolution differences in CSA identification.
  • Evaluation of the cost-effectiveness and scalability of each method.

Main Results:

  • All methods identified CSAs, but with variations in feature prioritization due to differences in spatial and temporal resolution.
  • Smartphone apps and GIS/drone-enhanced SCIMAP offer distinct advantages in capturing small-scale features and data resolution.
  • Walkover surveys provide valuable local knowledge, complementing modeling approaches.

Conclusions:

  • A multi-evidence-based approach, integrating local knowledge with varied data resolutions from methods like SCIMAP, is recommended for effective diffuse pollution management.
  • The choice of method should consider the specific catchment scale and management objectives.
  • Optimizing CSA identification is crucial for targeted and efficient water quality improvement efforts.