Article ID Journal Published Year Pages File Type
5117026 Journal of Environmental Management 2017 9 Pages PDF
Abstract

•Manure management is a challenge in livestock-intensive watersheds.•This paper presents an optimization model to coordinate shared manure management.•Cost and phosphorus runoff risk were minimized simultaneously.•Case study was developed to demonstrate methodology capabilities.•Multiple scenarios were assessed to quantify impacts of various management decisions.

Increased clustering and consolidation of livestock production systems has been linked to adverse impacts on water quality. This study presents a methodology to optimize manure management within a hydrologic region to minimize agricultural phosphorus (P) loss associated with winter manure application. Spatial and non-spatial data representing livestock, crop, soil, terrain and hydrography were compiled to determine manure P production rates, crop P uptake, existing manure storage capabilities, and transportation distances. Field slope, hydrologic soil group (HSG), and proximity to waterbodies were used to classify crop fields according to their runoff risk for winter-applied manure. We use these data to construct a comprehensive optimization model that identifies optimal location, size, and transportation strategy to achieve environmental and economic goals. The environmental goal was the minimization of daily hauling of manure to environmentally sensitive crop fields, i.e., those classified as high P-loss fields, whereas the economic goal was the minimization of the transportation costs across the entire study area. A case study encompassing two contiguous 10-digit hydrologic unit subwatersheds (HUC-10) in South Central Wisconsin, USA was developed to demonstrate the proposed methodology. Additionally, scenarios representing different management decisions (storage facility maximum volume, and project capital) and production conditions (increased milk production and 20-year future projection) were analyzed to determine their impact on optimal decisions.

Related Topics
Physical Sciences and Engineering Energy Renewable Energy, Sustainability and the Environment
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