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Watershed Planning within a Quantitative Scenario Analysis Framework
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Spatially explicit methodology for coordinated manure management in shared watersheds.

Mahmoud Sharara1, Apoorva Sampat2, Laura W Good3

  • 1Biological Systems Engineering, Univ. of Wisconsin-Madison, 460 Henry Mall, Madison, WI 53706, United States.

Journal of Environmental Management
|January 31, 2017
PubMed
Summary

This study optimizes livestock manure management to reduce phosphorus loss and transport costs. The methodology identifies ideal storage and transport strategies for better water quality and farm economics.

Keywords:
Community-based managementGISManure managementOptimizationPhosphorus runoff

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Area of Science:

  • Environmental Science
  • Agricultural Engineering
  • Water Resource Management

Background:

  • Consolidated livestock production can negatively impact water quality.
  • Agricultural phosphorus (P) loss from manure is a significant environmental concern.

Purpose of the Study:

  • To develop a methodology for optimizing manure management to minimize P loss during winter application.
  • To balance environmental goals (reducing P loss) with economic goals (minimizing transport costs).

Main Methods:

  • Compiled spatial and non-spatial data on livestock, crops, soil, terrain, and hydrography.
  • Classified fields by P-loss risk based on slope, soil type, and proximity to water.
  • Developed an optimization model to determine optimal manure storage location, size, and transport strategy.

Main Results:

  • The model identified optimal strategies for manure management considering environmental and economic factors.
  • Analyzed scenarios for storage capacity, capital investment, and future production increases.
  • Demonstrated the methodology in two Wisconsin HUC-10 subwatersheds.

Conclusions:

  • The proposed optimization model provides a framework for sustainable livestock manure management.
  • Informed decisions on manure storage and transportation can mitigate P loss and reduce costs.
  • The methodology is adaptable to various management and production scenarios.