Next Article in Journal
An Optimization Model for Water Management Based on Water Resources and Environmental Carrying Capacities: A Case Study of the Yinma River Basin, Northeast China
Next Article in Special Issue
Hydrological Modeling in Data-Scarce Catchments: The Kilombero Floodplain in Tanzania
Previous Article in Journal
Spatio-Temporal Variations of the Stable H-O Isotopes and Characterization of Mixing Processes between the Mainstream and Tributary of the Three Gorges Reservoir
Previous Article in Special Issue
Assessment of Suitable Areas for Home Gardens for Irrigation Potential, Water Availability, and Water-Lifting Technologies
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Water 2018, 10(5), 564; https://doi.org/10.3390/w10050564

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

1
Department of Bioengineering, University of Missouri, Columbia, MO 65201, USA
2
Industrial & Manufacturing Systems Engineering, University of Missouri, Columbia, MO 65201, USA
3
USDA–ARS, Cropping Systems and Water Quality Research Unit, Columbia, MO 65211, USA
4
Salt River Project, Surface Water Resources, Tempe, AZ 85072, USA
*
Author to whom correspondence should be addressed.
Received: 19 March 2018 / Revised: 19 April 2018 / Accepted: 24 April 2018 / Published: 26 April 2018
Full-Text   |   PDF [12262 KB, uploaded 3 May 2018]   |  

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. View Full-Text
Keywords: climate change; impact; hydrology; SWAT climate change; impact; hydrology; SWAT
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Gautam, S.; Costello, C.; Baffaut, C.; Thompson, A.; Svoma, B.M.; Phung, Q.A.; Sadler, E.J. 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. Water 2018, 10, 564.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Water EISSN 2073-4441 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top