Abstract. The predictive skills of single-and two-equation (or K-e) models to compute profiles of mean velocity (U), turbulent kinetic energy (K), and Reynolds stresses ðu 0 w 0 Þ are compared against datasets collected in eight vegetation types and in a flume experiment. These datasets range in canopy height h from 0.12 to 23 m, and range in leaf area index (LAI) from 2 to 10 m 2 m À2 . We found that for all datasets and for both closure models, measured and modelled U, K, and u 0 w 0 agree well when the mixing length (l m ) is a priori specified. In fact, the root-mean squared error between measured and modelled U, K, and u 0 w 0 is no worse than published values for second-and third-order closure approaches. Within the context of onedimensional modelling, there is no clear advantage to including a turbulent kinetic dissipation rate (e) budget when l m can be specified instead. The broader implication is that the added complexity introduced by the e budget in K-e models need not translate into improved predictive skills of U, K, and u 0 w 0 profiles when compared to single-equation models.