Uncertainty Analysis of Hydrological Parameters of the APEXgraze Model for Grazing Activities

Authors: MASKEY, MAHESH - Oak Ridge Institute For Science And Education (ORISE); Nelson, Amanda; Moriasi, Daniel; Northup, Brian

Submitted to: Ecological Modelling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/16/2024
Publication Date: 11/6/2024
Citation: Maskey, M.L., Nelson, A.M., Moriasi, D.N., Northup, B.K. 2024. Uncertainty Analysis of Hydrological Parameters of the APEXgraze Model for Grazing Activities. Ecological Modelling. 499. https://doi.org/10.1016/j.ecolmodel.2024.110917.
DOI: https://doi.org/10.1016/j.ecolmodel.2024.110917

Interpretive Summary: Agro-hydrological models used for studying water quantity and quality from small-scale watersheds may result in uncertainty in parameters and response variables. The levels of uncertainty can be difficult to determine, particularly in models assessing surface runoff. Models simulating surface runoff can result in multiple parameter combinations that meet the conditions being simulated, and therefore inconsistent uncertainty levels. We devised a generalized method for uncertainty analysis that statistically accounts for more than one acceptable solution from calibrated agro-hydrological models. We tested our approach in such a model for uncertainty analysis of runoff and sediment-related parameters made for two small-scale watershed with a) native prairie and b) cereals (winter wheat and one season of oats) in a semi-arid region of Oklahoma, United States, where grazing operations are common. This work demonstrated that a simple approach to uncertainty analysis was effective in representing the internal dynamics of hydrological processes. The proposed approach successfully produced a narrow range of water balance values within the range of parameters set for uncertainty analysis, thereby quantifying and reducing uncertainty of the model results. This approach can be applied to any hydrologic modeling and will allow users to calculate and present the uncertainty of model results with reduced computational time and increased confidence.

Technical Abstract: Scientists have often employed agro-hydrological models to investigate water quality and quantity in small-scale watersheds. However, these models have a degree of uncertainty in their parameters and response variables. Little research has been done on the uncertain range of runoff-related parameters for watershed models that assess the impact of grazing operations on watershed processes. To address these issues, we proposed a generalized framework for uncertainty analysis. This framework takes accounts for multiple acceptable solutions from calibrated agro-hydrological models. We considered a calibrated Agricultural Policy Extender (APEX) model with the grazing module APEXgraze to test our protocol. In this regard, we adopted two calibrated APEXgraze models for two fields in a semi-arid region of Oklahoma, United States, where grazing operations are common. While one field was managed with native prairie and frequent grazing activities, the other one with cereals (winter wheat and one season of oats) but light grazing. The results from this study were statistically significant and reasonable. Our method effectively produced a narrow range of water balance within the range of parameters considered for uncertainty analysis parameters. Further, this notion can detect redundant parameters from relevant sensitivity and uncertainty analyses. This study proves the effectiveness of our approach and its importance in the field of hydrological sciences.