Sources: Jie Niu, Bill Riley, Jacob Gimbel, Dan Hawkes
Storing water is one of the important hydrologic functions of a watershed. As a direct measure of watershed resilience, watershed storage is important for understanding climate-change impacts on water resources. Recently, Jie Niu, formerly of Michigan State University and now a postdoc climate scientist with LBNL, led a team of investigators in quantifying water-budget components and storage changes for two of the largest watersheds in Michigan—the Grand River and the Saginaw Bay watersheds—using remotely sensed data and a process-based hydrologic model (PAWS+CLM) that includes detailed representations of subsurface and land-surface processes. They used the model to compute annual-average fluxes due to evapotranspiration, surface runoff, recharge, and groundwater contribution to streams—as well as to analyze the impacts of land use/land cover (LULC) and soil types on annual hydrologic budgets, using correlation analysis.
This work provides new estimates of watershed-scale water budgets and storage changes. The results are expected to aid in the analysis and interpretation of the current trend of declining lake levels, in understanding projected future impacts of climate change, and in identifying appropriate climate adaptation strategies—particularly in keeping with ESD-Climate Sciences Department projects involving the National Oceanic and Atmospheric Administration (NOAA). Niu is currently applying the PAWS+CLM model in a DOE-funded project investigating Amazonian watershed hydrological and biogeochemical dynamics, and how these processes might change over the 21st century.
An article reporting on Niu’s Michigan work was recently published in Water Resources Research (September 2014, Volume 50), with a figure (Figure 1) from the article shown on the journal’s front cover.
To learn more, go to: http://onlinelibrary.wiley.com/enhanced/doi/10.1002/2014WR015589/
Citation: Niu, J., C. Shen, S.-G. Li, and M.S. Phankumar (2014), Quantifying storage changes in regional Great Lakes watersheds using a coupled subsurface-land surface process model and GRACE, MODIS products. Water Resources Research, 50 (9), 7259–7377; DOI: 10.1002/2014WR015589.
Funding Source: NOAA