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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #376853
Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Uncertainty assessment of multi-parameter, multi-GCM, and multi-RCP simulations for streamflow and non-floodplain wetland (NFW) water storage

Author
item LEE, S. - University Of Maryland
item QI, J. - University Of Maryland
item McCarty, Gregory
item YEO, I.Y. - University Of Newcastle
item ZHANG, X. - Global Change Research Institute
item Moglen, Glenn
item DU, L. - US Department Of Agriculture (USDA)

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/9/2021
Publication Date: 6/11/2021
Citation: Lee, S., Qi, J., McCarty, G.W., Yeo, I., Zhang, X., Moglen, G.E., Du, L. 2021. Uncertainty assessment of multi-parameter, multi-GCM, and multi-RCP simulations for streamflow and non-floodplain wetland (NFW) water storage. Journal of Hydrology. 600:126564. https://doi.org/10.1016/j.jhydrol.2021.126564.
DOI: https://doi.org/10.1016/j.jhydrol.2021.126564

Interpretive Summary: Increased awareness of the hydrological, ecological, and biogeochemical benefits of wetlands in agricultural landscapes has led to research on mapping wetland extent, monitoring wetland dynamics and quantifying wetland ecosystem functions. Watershed models such as SWAT (Soil and Water Assessment Tool) are often used in these assessments, but the uncertainty associated with model output is often not quantified. This study measured uncertainties of SWAT model parameters and climate change data used in simulating streamflow and wetland hydrology for a wetland-dominant watershed. Uncertainty associated with climate change data was the greatest single contributor accounting for 46% and 49% of the total streamflow and wetland water storage projection uncertainties. This work indicates that uncertainty analyses are needed for robust assessment of non-floodplain wetland hydrology and ecosystem function in the face of climate change.

Technical Abstract: In this study, we assessed the impacts of uncertainty from hydrologic model parameters and climate change data on streamflow and catchment-level non-floodplain wetland (NFW) water storage within the Coastal Plain of the Chesapeake Bay watershed. The hydrologic model used in this study is Soil and Water Assessment Tool (SWAT) coupled with improved wetland modules. Model uncertainty was represented by using 12 parameter sets (PARs) with acceptable model performances. Eight Global Circulation Models (GCMs), each under three Representative Concentration Pathways (RCP 2.6, 4.5, and 8.5) were used to drive SWAT to represent climate change uncertainty. The contribution of individual sources to the total uncertainty was quantified using an analysis of variance (ANOVA). The results showed that the selection of PARs, GCMs, and RCPs did not make substantial differences to monthly streamflow projections, while projected NFW water storage significantly varied. However, the changes of projected hydrologic values relative to historical conditions greatly differed by PARs, GCMs, and RCPs, leading to high uncertainty in the assessment of climate change impacts. Variability of GCM projections was the greatest single contributor accounting for 46% and 49% of the total streamflow and NFW water storage projection uncertainties, respectively, followed by PARs and RCPs. Our work suggests that model parameter and climate change uncertainties should be thoroughly considered for robust assessment of projected NFW hydrology and associated functions under climate change.