Spatially-explicit methodology for manure management at the watershed level

Abstract. Consolidation and clustering of livestock operations without adequate manure management have been linked to adverse impacts on water quality in host watersheds. This clustering trend could be leveraged to facilitate a coordinated, sustainable manure management strategy in these watersheds. This study presents a methodology to optimize manure management within a hydrologic region to minimize agricultural phosphorus (P) loss. Geospatial data representing crop, soil, terrain, livestock production, and hydrography in the target study area were compiled. A data processing model was developed to determine manure P production rates, crop P uptake, existing manure storage capabilities, and transportation distances. Additionally, for each field, the slope, hydrologic soil group (HSG), and proximity to waterbodies were used to classify crop fields according to their runoff risk for winter applied manure. Manure storages design was accomplished using mixed integer programming (MIP) model that can (1) minimize total manure handling cost, (2) minimize daily (weekly) manure application to sensitive fields, or (3) minimize daily haul while minimizing total cost. The optimization criteria was informed by the spatial distribution of livestock farms and receiving fields, crop rotations on fields, and road network within the study area. A case study encompassing two contiguous 10-digit hydrologic unit subwatersheds (HUC-10) in South Central Wisconsin, USA was used demonstrate the proposed methodology. Advanced manure processing strategies, such as pelletization, and precipitation could be integrated into the community storage design methodology to assess cost and potential for manure export.