This paper evaluates a recently created Soil and Water Assessment Tool (SWAT) calibration tool built using the Windows Azure Cloud environment and a parallel version of the Dynamically Dimensioned Search (DDS) calibration method modified to run in Azure. The calibration tool was tested for six model scenarios constructed for three watersheds of increasing size each for a 2 year and 10 year simulation duration. Results show significant speedup in calibration time and, for up to 64 cores, minimal losses in speedup for all watershed sizes and simulation durations. An empirical relationship is presented for estimating the time needed to calibration a SWAT model using the cloud calibration tool as a function of the number of Hydrologic Response Units (HRUs), time steps, and cores used for the calibration. A cloud-based, parallel SWAT calibration algorithm is evaluated.1000 runs are sufficient for flow calibration using up to 256 cores in parallel.Speedup of the parallel SWAT calibration tool is linear for up to 64 cores.Cost to calibrate a SWAT model can be estimated from HRU and time step counts.