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Rose VJ, Forney WM, Norton RA, Harrison JA. 2018. Catchment characteristics, water quality, and cyanobacterial blooms in Washington and Oregon Lakes. Lake Reserve Manage. 35:51-63 A cyanobacterial bloom (CB) model specifically developed as a screening tool for at-risk and affected lakes would benefit natural resource managers and scientists seeking cost-effective monitoring and mitigation measures to prevent blooms. We tested whether water quality, land use/land cover (LULC), and lake morphometry data could explain CB occurrence in a dataset containing 60 lakes and reservoirs in the Pacific Northwest United States using univariate and multiple logistic regressions. Of the explanatory variables evaluated by univariate regression, chlorophyll a concentration was most strongly associated with CB occurrence (pseudo-r(2) = 0.39). Other factors significantly related to CB occurrence included modeled dissolved inorganic phosphorus (DIP) yield, total phosphorus concentration (TP), "mixed forest," "developed - open space," and "developed - low intensity" (positive correlations), and water clarity, "evergreen forest," and "barren land" (negative correlations). The best multiple regression model evaluated included the following independent variables: TP, "drainage area," and "developed - open space" (AIC = 47.67, modified R-2 = 0.53). We selected the best performing univariate model to test for lakes at risk of developing CBs to highlight how simple models based on water quality and LULC factors may be valuable tools for conducting preliminary screenings as part of a monitoring program. Consistent with other studies, our findings suggest an important role for phosphorus in controlling CBs in the Pacific Northwest. Our study indicates that, in addition to more traditionally used water quality data, LULC variables and modeled DIP yield are strongly associated with CBs and may be valuable in the development of predictive models.