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Enhanced Model Better Assesses Impact Of Climate Variability

Date:
June 25, 2001
Source:
University Of Illinois At Urbana-Champaign
Summary:
By adding topographic features to their hydrologic model, researchers at the University of Illinois can better assess the impact of climate variability and global warming on terrestrial systems such as stream ecology, water quality and water resources management.

CHAMPAIGN, Ill. — By adding topographic features to their hydrologic model, researchers at the University of Illinois can better assess the impact of climate variability and global warming on terrestrial systems such as stream ecology, water quality and water resources management. "Hydrologic models provide an essential link between the physical climate and terrestrial systems," said Praveen Kumar, a UI professor of civil and environmental engineering. "Modeling the terrestrial hydrologic dynamics properly is crucial to predicting the atmospheric dynamics as well as predicting the climate’s impact on terrestrial systems."

The natural unit for the representation of hydrologic processes is a river basin, Kumar said. "By using a large-area, basin-scale model, we can better characterize the variation of moisture distribution between land surface and atmosphere, so we can more effectively study key feedback mechanisms." For their study, Kumar and graduate student Ji Chen combined digital elevation data from the United States Geological Survey along with hydrologic characteristics such as river basin boundaries and drainage networks. Then they added topographic parameters – water table fluctuations and vertical and horizontal ground water transport – to the model. To compare results, they ran the model both with and without these topographic enhancements.

Simulations for the entire North American continent were performed using the International Satellite Land Surface Climatology Project datasets for the years 1987 and 1988. The researchers validated their model by comparing model predictions against streamflow data collected by the USGS on rivers such as the Mississippi, Missouri and Ohio.

"When run with the enhancements, the model captured both the seasonal and the inter-annual variability quite realistically," Kumar said. "For example, seasonal patterns of streamflow in the tributaries of the Mississippi River basin were consistent with the actual measurements. The model also correctly predicted the winter-spring runoff from the Appalachian mountain range."

Because a severe drought occurred in the Midwest during the summer of 1988, the two-year simulation also provided an opportunity to assess the model’s performance for a dry year as well as for a typical year. The model properly portrayed the impact of the drought through decreased streamflow and increased water table depths within the affected region.

"By incorporating topographic influences into the model, predictions of terrestrial water balance and streamflow were improved significantly," Kumar said. "This provides a much better mechanism for assessing the impact of climate fluctuations on terrestrial hydrology, and for studying the potential consequences of environmental problems."

The researchers described their model in the May 1 issue of the Journal of Climate. The National Aeronautics and Space Administration and the National Science Foundation supported this work.


Story Source:

The above story is based on materials provided by University Of Illinois At Urbana-Champaign. Note: Materials may be edited for content and length.


Cite This Page:

University Of Illinois At Urbana-Champaign. "Enhanced Model Better Assesses Impact Of Climate Variability." ScienceDaily. ScienceDaily, 25 June 2001. <www.sciencedaily.com/releases/2001/06/010605075448.htm>.
University Of Illinois At Urbana-Champaign. (2001, June 25). Enhanced Model Better Assesses Impact Of Climate Variability. ScienceDaily. Retrieved August 27, 2014 from www.sciencedaily.com/releases/2001/06/010605075448.htm
University Of Illinois At Urbana-Champaign. "Enhanced Model Better Assesses Impact Of Climate Variability." ScienceDaily. www.sciencedaily.com/releases/2001/06/010605075448.htm (accessed August 27, 2014).

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