TY - JOUR
T1 - High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product
AU - Yang, Yi
AU - Guan, Kaiyu
AU - Peng, Bin
AU - Pan, Ming
AU - Jiang, Chongya
AU - Franz, Trenton E.
N1 - Funding Information:
We acknowledge the support from NSF CAREER award (Award Abstract #1847334) managed through the NSF Environmental Sustainability Program and USDA/NSF Cyber-Physical-System Program. We also acknowledge the support from the annual small research grant for graduate students from USGS Illinois Water Resources Center. We thank Murugesu Sivapalan for helpful comments on this study. We acknowledge the following AmeriFlux sites for their data records: US-Ne1, US-Ne1, US-Ne3, US- Bo1, US-IB1, US-Br1, and US-Ro1, US-Br3. In addition, funding for AmeriFlux data resources and core site data was provided by the U.S. Department of Energy's Office of Science.
Funding Information:
We acknowledge the support from NSF CAREER award (Award Abstract #1847334) managed through the NSF Environmental Sustainability Program and USDA/NSF Cyber-Physical-System Program. We also acknowledge the support from the annual small research grant for graduate students from USGS Illinois Water Resources Center. We thank Murugesu Sivapalan for helpful comments on this study. We acknowledge the following AmeriFlux sites for their data records: US-Ne1, US-Ne1, US-Ne3, US- Bo1, US-IB1, US-Br1, and US-Ro1, US-Br3. In addition, funding for AmeriFlux data resources and core site data was provided by the U.S. Department of Energy’s Office of Science.
Publisher Copyright:
© 2020
PY - 2021/5
Y1 - 2021/5
N2 - High-resolution simulation of water budgets across the agricultural landscape is critically important to a variety of applications, such as precision agriculture, water resources management, and environmental quality assessment. Model-data integration has been shown to be an effective approach to reduce model uncertainties and there is a growing opportunity to improve land surface modeling through spatially explicit calibration with satellite data in recent decades. Recently, a satellite-based daily 30-m resolution evapotranspiration (ET) product BESS-STAIR has been developed, achieving a high performance and well capturing the spatial and temporal dynamics of ET across the U.S. Corn Belt. To explore the potential of high-resolution spatially explicit calibration for advancing land surface modeling at fine scales, we carried out calibration experiments for the Noah-MP land surface model (LSM) over cropland using this newly developed BESS-STAIR ET. We first used Sobol sensitivity analysis to identify the most sensitive parameters for the Noah-MP's ET simulation. The most sensitive vegetation (minimum stomatal resistance) and soil parameters (saturated hydraulic conductivity, saturated matric potential, and a soil pore size distribution parameter) were calibrated using BESS-STAIR ET to improve model simulation of surface water balance. We conducted calibration experiments at 8 eddy covariance flux tower sites that grew maize and soybean across the U.S. Corn Belt, as well as a regional calibration study on the Spoon River watershed in Champaign, Illinois. When benchmarked with flux tower measurements, the BESS-STAIR ET–calibrated model (driven by flux tower forcing) on average reduced the RMSE of hourly ET from 61 W/m2 to 47 W/m2 for maize, and from 66 W/m2 to 53 W/m2 for soybean, and matched the performance of directly calibrating using flux tower measured ET. The regional study found that calibration using BESS-STAIR ET also improved the simulation of long-term regional water budgets and achieved better performance of ET than traditionally lumped calibration using streamflow. Further analysis revealed that the high-resolution calibration can resolve the spatial variations of ET to a certain extent, and the accuracy of the calibration can be largely attributed to the low bias and excellent long-term correlation of the BESS-STAIR ET data itself. Our study thus demonstrates the effectiveness of high-resolution model calibration and provides important implications in field-scale hydrological modeling and precision agricultural applications.
AB - High-resolution simulation of water budgets across the agricultural landscape is critically important to a variety of applications, such as precision agriculture, water resources management, and environmental quality assessment. Model-data integration has been shown to be an effective approach to reduce model uncertainties and there is a growing opportunity to improve land surface modeling through spatially explicit calibration with satellite data in recent decades. Recently, a satellite-based daily 30-m resolution evapotranspiration (ET) product BESS-STAIR has been developed, achieving a high performance and well capturing the spatial and temporal dynamics of ET across the U.S. Corn Belt. To explore the potential of high-resolution spatially explicit calibration for advancing land surface modeling at fine scales, we carried out calibration experiments for the Noah-MP land surface model (LSM) over cropland using this newly developed BESS-STAIR ET. We first used Sobol sensitivity analysis to identify the most sensitive parameters for the Noah-MP's ET simulation. The most sensitive vegetation (minimum stomatal resistance) and soil parameters (saturated hydraulic conductivity, saturated matric potential, and a soil pore size distribution parameter) were calibrated using BESS-STAIR ET to improve model simulation of surface water balance. We conducted calibration experiments at 8 eddy covariance flux tower sites that grew maize and soybean across the U.S. Corn Belt, as well as a regional calibration study on the Spoon River watershed in Champaign, Illinois. When benchmarked with flux tower measurements, the BESS-STAIR ET–calibrated model (driven by flux tower forcing) on average reduced the RMSE of hourly ET from 61 W/m2 to 47 W/m2 for maize, and from 66 W/m2 to 53 W/m2 for soybean, and matched the performance of directly calibrating using flux tower measured ET. The regional study found that calibration using BESS-STAIR ET also improved the simulation of long-term regional water budgets and achieved better performance of ET than traditionally lumped calibration using streamflow. Further analysis revealed that the high-resolution calibration can resolve the spatial variations of ET to a certain extent, and the accuracy of the calibration can be largely attributed to the low bias and excellent long-term correlation of the BESS-STAIR ET data itself. Our study thus demonstrates the effectiveness of high-resolution model calibration and provides important implications in field-scale hydrological modeling and precision agricultural applications.
KW - BESS
KW - Evapotranspiration
KW - High-resolution modeling
KW - Land surface model
KW - Parameter estimation
KW - STAIR
UR - http://www.scopus.com/inward/record.url?scp=85095993357&partnerID=8YFLogxK
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U2 - 10.1016/j.jhydrol.2020.125730
DO - 10.1016/j.jhydrol.2020.125730
M3 - Article
AN - SCOPUS:85095993357
SN - 0022-1694
VL - 596
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 125730
ER -