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Revised Method and Outcomes for Estimating Soil Phosphorus Losses from Agricultural Land in the Chesapeake Bay Watershed Model

Alisha Spears Mulkey, Frank J. Coale, Peter A. Vadas, Gary W. Shenk, Gopal X. Bhatt
Journal of environmental quality 2017 v.46 no.6 pp. 1388-1394
acreage, agricultural land, calibration, estimation, hydrologic models, monitoring, nutrient management, nutrients, phosphorus, pollution load, sediment transport, sediments, soil properties, water quality, watersheds, Chesapeake Bay
Current restoration efforts for the Chesapeake Bay watershed mandate a timeline for reducing the load of nutrients and sediment into receiving waters. The Chesapeake Bay watershed model (WSM) has been used for two decades to simulate hydrology and nutrient and sediment transport; however, spatial limitations of the WSM preclude edge‐of‐field scale representation of phosphorus (P) losses. Rather, the WSM relies on literature‐derived, county‐scale rates of P loss (targets) for simulated land uses. An independent field‐scale modeling tool, Annual Phosphorus Loss Estimator (APLE), was used as an alternative to the current WSM approach. Identical assumptions of county‐level acreage, soil properties, nutrient management practices, and transport factors from the WSM were used as inputs to APLE. Incorporation of APLE P‐loss estimates resulted in greater estimated total P loss and a revised spatial pattern of P loss compared with the WSM's original targets. Subsequently, APLE's revised estimates for P loss were substituted into the WSM and resulted in improved WSM calibration performance at up to 79% of tributary monitoring stations. The incorporation of APLE into the WSM will improve its ability to assess P loss and the impact of field management on Chesapeake Bay water quality. CORE IDEAS: APLE estimated P losses were compared with the Chesapeake Bay Watershed Model's (WSM) losses. Substituting the APLE estimated P loss into the WSM improved calibration performance. Findings suggest the importance of well‐estimated transport factors in modeling P losses.