48 citations as recorded by crossref.

1. Remote sensing-based energy balance for lettuce in an arid environment: influence of management scenarios on irrigation and evapotranspiration modeling R. Dhungel et al. https://doi.org/10.1007/s00271-023-00848-9
2. Which crop has the highest bioethanol yield in the United States? T. Lin et al. https://doi.org/10.3389/fenrg.2023.1070186
3. Predicting spatial patterns of within-field crop yield variability B. Maestrini & B. Basso https://doi.org/10.1016/j.fcr.2018.01.028
4. Crop models capture the impacts of climate variability on corn yield D. Niyogi et al. https://doi.org/10.1002/2015GL063841
5. Incorporating dynamic crop growth processes and management practices into a terrestrial biosphere model for simulating crop production in the United States: Toward a unified modeling framework Y. You et al. https://doi.org/10.1016/j.agrformet.2022.109144
6. Carbon fluxes in spring wheat agroecosystem in India K. Reddy et al. https://doi.org/10.5194/esd-14-915-2023
7. Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site‐Level Observations in the Central Midwestern United States Y. Cheng et al. https://doi.org/10.1029/2019MS001719
8. Impacts of climate change and mitigation strategies for the safe climatic space of global staple crops C. Li et al. https://doi.org/10.1360/CSB-2025-0553
9. Investigating Terrestrial Carbon Uptake Over India Using Multimodel Simulations of Gross Primary Productivity and Satellite‐Based Biophysical Product G. Uchale et al. https://doi.org/10.1029/2023JG007468
10. The observed and model-simulated response of southern African vegetation to drought S. Lawal et al. https://doi.org/10.1016/j.agrformet.2019.107698
11. Carbon dynamics in the Amazonian Basin: Integration of eddy covariance and ecophysiological data with a land surface model B. El-Masri et al. https://doi.org/10.1016/j.agrformet.2013.03.011
12. The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0) J. Elliott et al. https://doi.org/10.5194/gmd-8-261-2015
13. Comparing crop growth and carbon budgets simulated across AmeriFlux agricultural sites using the Community Land Model (CLM) M. Chen et al. https://doi.org/10.1016/j.agrformet.2018.03.012
14. Influence of Soil Properties in Different Management Systems: Estimating Soybean Water Changes in the Agro-IBIS Model V. Moreira et al. https://doi.org/10.1175/EI-D-16-0033.1
15. Night-time decline in plant respiration is consistent with substrate depletion S. Jones et al. https://doi.org/10.1038/s43247-024-01312-y
16. Temporally variable parameters simulate asymmetrical interannual variation of aboveground and belowground carbon pools in an alpine meadow Q. Xu et al. https://doi.org/10.1016/j.agrformet.2021.108480
17. Evaluation of Hydroclimatic Variability and Prospective Irrigation Strategies in the U.S. Corn Belt M. Orduña Alegría et al. https://doi.org/10.3390/w11122447
18. Effects of Multiple Planting Densities on Lignin Metabolism and Lodging Resistance of the Strip Intercropped Soybean Stem B. Cheng et al. https://doi.org/10.3390/agronomy10081177
19. Climate-driven uncertainties in modeling terrestrial energy and water fluxes: a site-level to global-scale analysis R. Barman et al. https://doi.org/10.1111/gcb.12473
20. Investigating Wetland and Nonwetland Soil Methane Emissions and Sinks Across the Contiguous United States Using a Land Surface Model S. Shu et al. https://doi.org/10.1029/2019GB006251
21. Evaluation of JULES-crop performance against site observations of irrigated maize from Mead, Nebraska K. Williams et al. https://doi.org/10.5194/gmd-10-1291-2017
22. Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2) E. Sinha et al. https://doi.org/10.1029/2022MS003171
23. Worldwide Maize and Soybean Yield Response to Environmental and Management Factors Over the 20th and 21st Centuries T. Lin et al. https://doi.org/10.1029/2021JG006304
24. Impact of environmental changes and land management practices on wheat production in India S. Gahlot et al. https://doi.org/10.5194/esd-11-641-2020
25. Improving a Biogeochemical Model to Simulate Surface Energy, Greenhouse Gas Fluxes, and Radiative Forcing for Different Land Use Types in Northeastern United States J. Deng et al. https://doi.org/10.1029/2019GB006520
26. The Purdue Agro-climatic (PAC) dataset for the U.S. Corn Belt: Development and initial results X. Liu et al. https://doi.org/10.1016/j.crm.2016.10.005
27. Land-use emissions play a critical role in land-based mitigation for Paris climate targets A. Harper et al. https://doi.org/10.1038/s41467-018-05340-z
28. A fully coupled crop-water-energy balance model based on satellite data for maize and tomato crops yield estimates: The FEST-EWB-SAFY model C. Corbari et al. https://doi.org/10.1016/j.agwat.2022.107850
29. Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration C. Bieri et al. https://doi.org/10.5194/gmd-18-3755-2025
30. Projected changes in Malawi’s growing season E. Vizy et al. https://doi.org/10.1007/s00382-014-2424-x
31. Estimating Trends and Variation of Net Biome Productivity in India for 1980–2012 Using a Land Surface Model S. Gahlot et al. https://doi.org/10.1002/2017GL075777
32. Improving maize growth processes in the community land model: Implementation and evaluation B. Peng et al. https://doi.org/10.1016/j.agrformet.2017.11.012
33. Differential roles of perennial and annual grasses in semi-arid grassland response to precipitation repackaging: Insights from experiment-informed Community Land Model (CLM5.0) parameterization T. Hu et al. https://doi.org/10.1016/j.agrformet.2026.111079
34. Estimates of Biomass Yield for Perennial Bioenergy Grasses in the USA Y. Song et al. https://doi.org/10.1007/s12155-014-9546-1
35. Calibration and validation of SiBcrop Model for simulating LAI and surface heat fluxes of winter wheat in the North China Plain Y. CHEN et al. https://doi.org/10.1016/S2095-3119(20)63178-1
36. Decadal-Scale Changes in the Seasonal Surface Water Balance of the Central United States from 1984 to 2007 B. Dong et al. https://doi.org/10.1175/JHM-D-19-0050.1
37. Divergent climate feedbacks on winter wheat growing and dormancy periods as affected by sowing date in the North China Plain F. Liu et al. https://doi.org/10.5194/bg-18-2275-2021
38. Challenging terrestrial biosphere models with data from the long‐term multifactor Prairie Heating and CO2 Enrichment experiment M. De Kauwe et al. https://doi.org/10.1111/gcb.13643
39. Simulating the ecosystem-atmosphere carbon, water and energy fluxes at a subtropical Indian forest using an ecosystem model P. Deb Burman et al. https://doi.org/10.1016/j.ecolmodel.2024.110637
40. Implementing Dynamic Rooting Depth for Improved Simulation of Soil Moisture and Land Surface Feedbacks in Noah‐MP‐Crop X. Liu et al. https://doi.org/10.1029/2019MS001786
41. Biotic responses buffer warming‐induced soil organic carbon loss in Arctic tundra J. Liang et al. https://doi.org/10.1111/gcb.14325
42. Improvement of modeling plant responses to low soil moisture in JULESvn4.9 and evaluation against flux tower measurements A. Harper et al. https://doi.org/10.5194/gmd-14-3269-2021
43. Vegetation Growth Models Improve Surface Layer Flux Simulations of a Temperate Grassland C. Klein et al. https://doi.org/10.2136/vzj2017.03.0052
44. The C-FEWS framework: Supporting studies of climate-induced extremes on food, energy, and water systems at the regional scale C. Vörösmarty et al. https://doi.org/10.3389/fenvs.2023.1069613
45. The Interplay Between Bioenergy Grass Production and Water Resources in the United States of America Y. Song et al. https://doi.org/10.1021/acs.est.5b05239
46. Improving a Process-Based Model to Simulate Forest Carbon Allocation under Varied Stand Density W. Jiao et al. https://doi.org/10.3390/f13081212
47. Comprehensive assessments of carbon dynamics in an intermittently-irrigated rice paddy Y. Hwang et al. https://doi.org/10.1016/j.agrformet.2020.107933
48. Estimation of Permafrost SOC Stock and Turnover Time Using a Land Surface Model With Vertical Heterogeneity of Permafrost Soils S. Shu et al. https://doi.org/10.1029/2020GB006585