Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-5489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatial heterogeneity effects on land surface modeling of water and energy partitioning
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
Gautam Bisht
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
L. Ruby Leung
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA
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14 citations as recorded by crossref.
- Intercomparison of Runoff and River Discharge Reanalysis Datasets at the Upper Jinsha River, an Alpine River on the Eastern Edge of the Tibetan Plateau S. Chen et al. 10.3390/w17060871
- Impact of Updating Vegetation Information on Land Surface Model Performance M. Ruiz‐Vásquez et al. 10.1029/2023JD039076
- Quantifying uncertainty in forecasts of when and where invasions happen A. Saffer et al. 10.1007/s10530-025-03573-w
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- Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration S. Sun et al. 10.1016/j.agrformet.2024.110256
- Contrasting sensitivity and resilience to soil moisture and vapor pressure deficit between natural and planted forests under afforestation projects F. Huang et al. 10.1016/j.jenvman.2025.127798
- Global 1 km land surface parameters for kilometer-scale Earth system modeling L. Li et al. 10.5194/essd-16-2007-2024
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- High-resolution land surface modelling over Africa: the role of uncertain soil properties in combination with forcing temporal resolution B. Oloruntoba et al. 10.5194/hess-29-1659-2025
- A Multi–Task 3D–ResNet–BiLSTM transfer learning approach for winter wheat yield prediction using multi–source remote sensing data: Evaluating the impact of source crop selection (corn and soybean) in transfer learning M. Fathi et al. 10.1016/j.rsase.2025.101766
- Integrating NDVI-Based Within-Wetland Vegetation Classification in a Land Surface Model Improves Methane Emission Estimations T. Yazbeck et al. 10.3390/rs16060946
1 citations as recorded by crossref.
Latest update: 03 Nov 2025
Short summary
Land surface heterogeneity plays a critical role in the terrestrial water, energy, and biogeochemical cycles. Our study systematically quantified the effects of four dominant heterogeneity sources on water and energy partitioning via Sobol' indices. We found that atmospheric forcing and land use land cover are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning. Our findings can help prioritize the future development of land surface models.
Land surface heterogeneity plays a critical role in the terrestrial water, energy, and...