| Title: | Assessing long-term hydrological impact of climate change using an ensemble approach and comparison with global gridded model-A case study on Goodwater Creek experimental watershed |
| Authors: | Guatam, S., C. Costello, C. Baffaut, A. Thomspon, B.M. Svoma, Q.A. Phung and E.J. Sadler |
| Year: | 2018 |
| Journal: | Water |
| Volume (Issue): | 10 |
| Pages: | |
| Article ID: | 564 |
| DOI: | 10.3390/w10050564 |
| URL (non-DOI journals): | |
| Model: | SWAT |
| Broad Application Category: | hydrologic only |
| Primary Application Category: | model and/or data comparison |
| Secondary Application Category: | climate change |
| Watershed Description: | 73 km^2 Goodwater Creek, a tributary of the Salt River which drains portions of Boone and Audrain counties in northeast Missouri, U.S. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | Potential impacts of climate change on the hydrological components of the Goodwater
Creek Experimental Watershed were assessed using climate datasets from the Coupled Model
Intercomparison Project Phase 5 and Soil and Water Assessment Tool (SWAT). Historical and future
ensembles of downscaled precipitation and temperature, and modeled water yield, surface runoff,
and evapotranspiration, were compared. Ensemble SWAT results indicate increased springtime
precipitation, water yield, surface runoff and a shift in evapotranspiration peak one month earlier
in the future. To evaluate the performance of model spatial resolution, gridded surface runoff
estimated by Lund–Potsdam–Jena managed Land (LPJmL) and Jena Diversity-Dynamic Global
Vegetation model (JeDi-DGVM) were compared to SWAT. Long-term comparison shows a 6–8%
higher average annual runoff prediction for LPJmL, and a 5–30% lower prediction for JeDi-DGVM,
compared to SWAT. Although annual runoff showed little change for LPJmL, monthly runoff
projection under-predicted peak runoff and over-predicted low runoff for LPJmL compared to
SWAT. The reasons for these differences include differences in spatial resolution of model inputs and
mathematical representation of the physical processes. Results indicate benefits of impact assessments
at local scales with heterogeneous sets of parameters to adequately represent extreme conditions that
are muted in global gridded model studies by spatial averaging over large study domains. |
| Language: | English |
| Keywords: | climate change; impact; hydrology; SWAT |