TY - JOUR
T1 - An application of GRACE mission datasets for streamflow and baseflow estimation in the Conterminous United States basins
AU - Mohanasundaram, S.
AU - Mekonnen, Mesfin M.
AU - Haacker, Erin
AU - Ray, Chittaranjan
AU - Lim, Sokneth
AU - Shrestha, Sangam
N1 - Funding Information:
We would like to acknowledge and thank the Nebraska Environmental Trust for providing a grant to Nebraska Water Center, part of Daugherty Water for Food Global Institute at the University of Nebraska that supported part of the time for the corresponding author of this research article while working at the University of Nebraska as a postdoctoral research fellow. Data access, computational facility, and other support were provided by the Nebraska Water Center. We also would like to thank the Water Engineering and Management program at the Asian Institute of Technology for providing computational facility and other support to the corresponding author and Ms. Sokneth Lim.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/10
Y1 - 2021/10
N2 - Runoff and baseflow estimates provide critical information on surface and groundwater flow dynamics, water resource availability, and water usage patterns for effective water resource planning and management. Developing a physical-based model at large spatial scales such as continental/global scales require extensive datasets, complex parameterization, and higher computational capacity. Recent advances in satellite datasets related to water cycle process modeling, on the other hand, involve less parameterization and more effective computation over larger spatial and finer temporal scales. Evapotranspiration (ET) is a critical flux in the water cycle that can be estimated with reasonable accuracy from satellite-based information by using complementary relationship (CR) concepts. Similarly, the Gravity Recovery and Climate Experiment (GRACE) mission satellite datasets provide useful estimates of total water storage change over large spatial extents. GRACE datasets have been extensively used in groundwater storage change and groundwater depletion studies. However, the application of GRACE data products for estimating runoff and baseflow is limited. Therefore, in this study, we used a CR approach to estimate ET and a water balance method for estimating runoff and baseflow over the Conterminous United States (CONUS). We evaluated the CR-based water balance model (CR-GRACE) with United States Geological Survey (USGS) runoff datasets based on hydrologic unit code level-2 (HUC-2) basin boundaries. The CR-GRACE model estimated annual runoff values agreed with USGS runoff values with root mean square error (RMSE) and correlation coefficient values of 14.7 mm/month and 0.81, respectively. We also evaluated the CR-GRACE model with two well-known Land Surface Models (LSM), Noah-LSM and Variable Infiltration Capacity LSM (VIC-LSM), from the Global Land Data Assimilation System (GLDAS) database. The comparison results for baseflow estimates from the CR-GRACE model have improved over Noah-LSM and VIC-LSM model estimates with RMSE values of 62.16, 101.00, and 207.32 mm/year, respectively. Furthermore, this study demonstrates the feasibility of using the CR-GRACE model to estimate runoff and baseflows with limited parameterization and datasets.
AB - Runoff and baseflow estimates provide critical information on surface and groundwater flow dynamics, water resource availability, and water usage patterns for effective water resource planning and management. Developing a physical-based model at large spatial scales such as continental/global scales require extensive datasets, complex parameterization, and higher computational capacity. Recent advances in satellite datasets related to water cycle process modeling, on the other hand, involve less parameterization and more effective computation over larger spatial and finer temporal scales. Evapotranspiration (ET) is a critical flux in the water cycle that can be estimated with reasonable accuracy from satellite-based information by using complementary relationship (CR) concepts. Similarly, the Gravity Recovery and Climate Experiment (GRACE) mission satellite datasets provide useful estimates of total water storage change over large spatial extents. GRACE datasets have been extensively used in groundwater storage change and groundwater depletion studies. However, the application of GRACE data products for estimating runoff and baseflow is limited. Therefore, in this study, we used a CR approach to estimate ET and a water balance method for estimating runoff and baseflow over the Conterminous United States (CONUS). We evaluated the CR-based water balance model (CR-GRACE) with United States Geological Survey (USGS) runoff datasets based on hydrologic unit code level-2 (HUC-2) basin boundaries. The CR-GRACE model estimated annual runoff values agreed with USGS runoff values with root mean square error (RMSE) and correlation coefficient values of 14.7 mm/month and 0.81, respectively. We also evaluated the CR-GRACE model with two well-known Land Surface Models (LSM), Noah-LSM and Variable Infiltration Capacity LSM (VIC-LSM), from the Global Land Data Assimilation System (GLDAS) database. The comparison results for baseflow estimates from the CR-GRACE model have improved over Noah-LSM and VIC-LSM model estimates with RMSE values of 62.16, 101.00, and 207.32 mm/year, respectively. Furthermore, this study demonstrates the feasibility of using the CR-GRACE model to estimate runoff and baseflows with limited parameterization and datasets.
KW - Baseflow
KW - Complementary relationship
KW - Evapotranspiration
KW - GRACE
KW - Runoff
KW - Water balance equation
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U2 - 10.1016/j.jhydrol.2021.126622
DO - 10.1016/j.jhydrol.2021.126622
M3 - Article
AN - SCOPUS:85110068278
VL - 601
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
M1 - 126622
ER -