Employing a unique and rich data set of water quality attributes in conjunction with detailed household characteristics and trip information, we develop a mixed logit model of recreational lake usage and undertake thorough model specification and fitting procedures to identify the best set of explanatory variables, and their functional form for the estimated model. Our empirical analysis shows that individuals are responsive to the full set of water quality measures used by biologists to identify the impaired status of lakes. Thus, changes in these quality measures are not simply a scientific exercise, but they also translate into changes in the recreational usage patterns and well-being of individual households. Willingness-to-pay (WTP) estimates are reported based on improvements in these physical measures.