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Nutrient loading from non-point sources is the single largest remaining source of water quality impairments in the State of Kansas. Water Quality Trading (WQT) can be used to reduce nutrient loads, allow point sources to meet the required water quality criteria, and then achieve both economic and environmental benefits. Even though WQT has been promoted for decades, the existing programs have had unexpectedly low trading volumes. Recent studies have shown that the most likely impediment to trades might be the failure to address environmental uncertainties inherent to using a single, fixed, empirical trading ratio. The goals for this study are to analyze and quantify nutrient load reduction with combined watershed modeling and GIS techniques, and then to estimate site-specific load reduction rates and trading ratios for every potential scenario. The nutrient loading changes among 36 land management practice scenarios have been modeled at Lower Kansas Subbasin in northeastern Kansas. We evaluated three crop types, two fertilizer-application methods, two edge of field BMP conditions, and four tillage-practice scenarios. The trading ratios were estimated through statistical analyses which estimate load uncertainties with designated confidence levels for every potential scenario. The modeled pollutant load reductions show significant spatiotemporal differences among the subwatersheds. The annual and monthly site-specific average load reductions, reduction rates, uncertain ratios and trading ratios were determined to address the impacts of changes in land management, climate, soil type, and landscape variants within the watershed.