Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
BESS-STAIR: a framework to estimate daily, 30 m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
Center for Advanced Bioenergy and Bioproducts Innovation, University
of Illinois at Urbana Champaign, Urbana, Illinois, USA
Kaiyu Guan
CORRESPONDING AUTHOR
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
Center for Advanced Bioenergy and Bioproducts Innovation, University
of Illinois at Urbana Champaign, Urbana, Illinois, USA
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
Ming Pan
Department of Civil and Environmental Engineering, Princeton
University, New Jersey, USA
Youngryel Ryu
Department of Landscape Architecture and Rural Systems Engineering,
Seoul National University, Seoul, Republic of Korea
Bin Peng
College of Agricultural, Consumer and Environmental Sciences,
University of Illinois at Urbana Champaign, Urbana, Illinois, USA
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
Sibo Wang
National Center of Supercomputing Applications, University of Illinois
at Urbana Champaign, Urbana, Illinois, USA
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Cited
25 citations as recorded by crossref.
- The utility and applicability of vegetation index-based models for the spatial disaggregation of evapotranspiration S. Munusamy et al. 10.1007/s00271-024-00963-1
- Spatial and temporal forecasting of groundwater anomalies in complex aquifer undergoing climate and land use change A. Talib et al. 10.1016/j.jhydrol.2024.131525
- Challenges and opportunities in precision irrigation decision-support systems for center pivots J. Zhang et al. 10.1088/1748-9326/abe436
- A decadal (2008–2017) daily evapotranspiration data set of 1 km spatial resolution and spatial completeness across the North China Plain using TSEB and data fusion C. Zhang et al. 10.1016/j.rse.2021.112519
- A Global Implementation of Single‐ and Dual‐Source Surface Energy Balance Models for Estimating Actual Evapotranspiration at 30‐m Resolution Using Google Earth Engine H. Jaafar et al. 10.1029/2022WR032800
- A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest Q. Yang et al. 10.1016/j.rse.2023.113880
- Evaluation of average leaf inclination angle quantified by indirect optical instruments in crop fields K. Li et al. 10.1016/j.jag.2024.104206
- Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center‐Pivot Irrigation Water Use at High Spatio‐Temporal Resolution J. Zhang et al. 10.1029/2022WR032967
- Incorporating changes in land surface temperature improves BESS evapotranspiration estimates under water-deficit conditions: A case study for US Midwest and Great Plains grasslands X. Lu et al. 10.1016/j.jhydrol.2024.132201
- Soil and environmental issues in sandy soils J. Huang & A. Hartemink 10.1016/j.earscirev.2020.103295
- Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand J. Zhang et al. 10.1038/s41467-021-25254-7
- Connections between the hydrological cycle and crop yield in the rainfed U.S. Corn Belt W. Zhou et al. 10.1016/j.jhydrol.2020.125398
- CubeSats deliver new insights into agricultural water use at daily and 3 m resolutions B. Aragon et al. 10.1038/s41598-021-91646-w
- Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model G. Senay et al. 10.1016/j.rse.2022.113011
- Assessment of global gridded transpiration products using the extended instrumental variable technique (EIVD) C. Li et al. 10.1016/j.jhydrol.2023.129880
- Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa W. S. Ha et al. 10.3390/rs12142337
- CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data C. Li et al. 10.5194/essd-16-1811-2024
- Assessing Different Plant‐Centric Water Stress Metrics for Irrigation Efficacy Using Soil‐Plant‐Atmosphere‐Continuum Simulation J. Zhang et al. 10.1029/2021WR030211
- Tracking diurnal to seasonal variations of gross primary productivity using a geostationary satellite, GK-2A advanced meteorological imager S. Jeong et al. 10.1016/j.rse.2022.113365
- Estimation of crop evapotranspiration from MODIS data by combining random forest and trapezoidal models P. Hao et al. 10.1016/j.agwat.2021.107249
- A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States C. Jiang et al. 10.5194/essd-13-281-2021
- Enhancing the Application of Earth Observations for Improved Environmental Decision-Making Using the Early Warning eXplorer (EWX) S. Shukla et al. 10.3389/fclim.2020.583509
- Evaluation of four image fusion NDVI products against in-situ spectral-measurements over a heterogeneous rice paddy landscape J. Kong et al. 10.1016/j.agrformet.2020.108255
- Mapping crop evapotranspiration with high-resolution imagery and meteorological data: insights into sustainable agriculture in Prince Edward Island F. Imtiaz et al. 10.3389/frsen.2023.1274019
- ERTFM: An Effective Model to Fuse Chinese GF-1 and MODIS Reflectance Data for Terrestrial Latent Heat Flux Estimation L. Zhang et al. 10.3390/rs13183703
24 citations as recorded by crossref.
- The utility and applicability of vegetation index-based models for the spatial disaggregation of evapotranspiration S. Munusamy et al. 10.1007/s00271-024-00963-1
- Spatial and temporal forecasting of groundwater anomalies in complex aquifer undergoing climate and land use change A. Talib et al. 10.1016/j.jhydrol.2024.131525
- Challenges and opportunities in precision irrigation decision-support systems for center pivots J. Zhang et al. 10.1088/1748-9326/abe436
- A decadal (2008–2017) daily evapotranspiration data set of 1 km spatial resolution and spatial completeness across the North China Plain using TSEB and data fusion C. Zhang et al. 10.1016/j.rse.2021.112519
- A Global Implementation of Single‐ and Dual‐Source Surface Energy Balance Models for Estimating Actual Evapotranspiration at 30‐m Resolution Using Google Earth Engine H. Jaafar et al. 10.1029/2022WR032800
- A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest Q. Yang et al. 10.1016/j.rse.2023.113880
- Evaluation of average leaf inclination angle quantified by indirect optical instruments in crop fields K. Li et al. 10.1016/j.jag.2024.104206
- Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center‐Pivot Irrigation Water Use at High Spatio‐Temporal Resolution J. Zhang et al. 10.1029/2022WR032967
- Incorporating changes in land surface temperature improves BESS evapotranspiration estimates under water-deficit conditions: A case study for US Midwest and Great Plains grasslands X. Lu et al. 10.1016/j.jhydrol.2024.132201
- Soil and environmental issues in sandy soils J. Huang & A. Hartemink 10.1016/j.earscirev.2020.103295
- Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand J. Zhang et al. 10.1038/s41467-021-25254-7
- Connections between the hydrological cycle and crop yield in the rainfed U.S. Corn Belt W. Zhou et al. 10.1016/j.jhydrol.2020.125398
- CubeSats deliver new insights into agricultural water use at daily and 3 m resolutions B. Aragon et al. 10.1038/s41598-021-91646-w
- Mapping actual evapotranspiration using Landsat for the conterminous United States: Google Earth Engine implementation and assessment of the SSEBop model G. Senay et al. 10.1016/j.rse.2022.113011
- Assessment of global gridded transpiration products using the extended instrumental variable technique (EIVD) C. Li et al. 10.1016/j.jhydrol.2023.129880
- Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa W. S. Ha et al. 10.3390/rs12142337
- CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data C. Li et al. 10.5194/essd-16-1811-2024
- Assessing Different Plant‐Centric Water Stress Metrics for Irrigation Efficacy Using Soil‐Plant‐Atmosphere‐Continuum Simulation J. Zhang et al. 10.1029/2021WR030211
- Tracking diurnal to seasonal variations of gross primary productivity using a geostationary satellite, GK-2A advanced meteorological imager S. Jeong et al. 10.1016/j.rse.2022.113365
- Estimation of crop evapotranspiration from MODIS data by combining random forest and trapezoidal models P. Hao et al. 10.1016/j.agwat.2021.107249
- A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States C. Jiang et al. 10.5194/essd-13-281-2021
- Enhancing the Application of Earth Observations for Improved Environmental Decision-Making Using the Early Warning eXplorer (EWX) S. Shukla et al. 10.3389/fclim.2020.583509
- Evaluation of four image fusion NDVI products against in-situ spectral-measurements over a heterogeneous rice paddy landscape J. Kong et al. 10.1016/j.agrformet.2020.108255
- Mapping crop evapotranspiration with high-resolution imagery and meteorological data: insights into sustainable agriculture in Prince Edward Island F. Imtiaz et al. 10.3389/frsen.2023.1274019
Latest update: 23 Nov 2024
Short summary
Quantifying crop water use at each field every day is challenging because of the complexity of the evapotranspiration (ET) process and the unavailability of data at high spatiotemporal resolutions. We fuse multi-satellite data and employ a sophisticated model to estimate ET at 30 m resolution and a daily interval. With validation against 86 site years of ground truth in the US Corn Belt, we are confident that our ET estimation is accurate and a reliable tool for water resource management.
Quantifying crop water use at each field every day is challenging because of the complexity of...