Although the effects of spatial and temporal variability of precipitation on hydrologic modeling results have been well established, there has been very little attention given to sampling impacts on model calibration. To examine the effects of temporal sampling of rainfall, a combination of numerical simulations and calibration experiments have been carried out. A “true” runoff scenario, which is used for calibration of models using longer sampling periods, is established using very high resolution precipitation data and parameters derived from the physical properties of the soils. Three point infiltration models were chosen to isolate the effects of temporal sampling. A simple empirical model, a more complex empirical model, and a physics-based model were tested and compared. Numerical simulations using parameters based directly on soil properties demonstrated an undersimulation of runoff as the precipitation signal is smoothed at lower sampling frequencies. Calibration of selected parameters may compensate for this undersimulation effect. This impact becomes more pronounced for higher infiltration capacities, as calibration is required to compensate for greater underestimation of runoff. The adjustments that are necessary to compensate for the sampling effect illustrate how some of the physical meaning of the parameters is lost in the calibration process. Since the calibrated model parameters correspond to physical properties of the system, these results demonstrate that it may not be possible to make a priori parameter estimates based solely on physical properties of the system or to use parameters calibrated using data with different temporal or spatial sampling.
If you can't find a tool you're looking for, please click the link at the top of the page to "Go to old article view". Alternatively, view our Knowledge Base articles for additional help. Your feedback is important to us, so please let us know if you have comments or ideas for improvement.