|KIM, KEEWOOK - Us Environmental Protection Agency (EPA)
|WHELAN, GENE - Us Environmental Protection Agency (EPA)
|PURUCKER, THOMAS - Us Environmental Protection Agency (EPA)
|BOHRMANN, THOMAS - Us Environmental Protection Agency (EPA)
|05CYTERSKY, THOMAS - Us Environmental Protection Agency (EPA)
|MOLINA, MARIROSA - Us Environmental Protection Agency (EPA)
|GU, YIN - Us Environmental Protection Agency (EPA)
|GUBER, ANDREY - Michigan State University
Submitted to: Hydrological Processes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/6/2013
Publication Date: 10/1/2014
Citation: Kim, K., Whelan, G., Purucker, T., Bohrmann, T., Cytersky, T., Molina, M., Gu, Y., Pachepsky, Y.A., Guber, A., Franklin, D.H. 2014. Rainfall-runoff model parameter estimation and uncertainty evaluation on small plots. Hydrological Processes. 28:5220-5235.
Interpretive Summary: Most studies on overland flow and contaminant transport have been conducted on small runoff plots. Field scale, rather than plot scale, studies are important for management and policy decisions. It has been established that flow and transport parameters obtained from plot experiments differ from parameters obtained at the field scale. Our hypothesis was that field-scale parameters of overland flow and transport could be estimated from the uncertainty in plot-scale parameters. Using data from multiple rainfall experiments, the USDA-ARS model kineros2/stwir was used to conduct simulations and parameter estimation to determine both plot scale and field scale parameters. We found that uncertainty in plot-scale parameters could indeed be used to estimate filed-scale parameters. Results of this work represent a considerable advance in surface hydrology, as they substantially increase the value of relatively easily conducted plot-scale experiments. This finding can be applied in environmental engineering to obtain data needed for management planning, design, and implementation of overland water flow and contaminant transport.
Technical Abstract: Four seasonal rainfall simulations in 2009 and 2010 were applied to a field containing 36 plots (0.75 × 2 m each), resulting in 144 runoff events. In all simulations, a constant rate of rainfall was applied, then halted 60 minutes after initiation of runoff, with plot-scale monitoring of runoff every five minutes during that period. Runoff was simulated with the KINEROS2/STWIR field-scale model, whose hydrodynamics are based on the kinematic wave equation. Due to the non-linear nature of the model and a highly parameterized model with respect to the available data, several approaches were investigated to upscale nine runoff-related parameters from a series of small monitored plots to the field scale. Inverse modeling was performed using the PEST algorithm to individually calibrate the nine KINEROS2/STWIR parameters on 36 plots. The parameters were averaged, and bootstrapping was used to assess uncertainty of the parameters via estimation of confidence intervals (CI). A Monte Carlo simulation using the bootstrap results showed reasonable field-scale representation of flow rates. Median values of calibrated parameters were within the 95% confidence interval obtained with bootstrapping. The simulated results for the median values associated with the 90% CI flow rates produced similar trends as those exhibited with the observed data, suggesting that median values from the PEST inverse modeling could be used to represent the unmonitored field-scale parameters.