AGROCLIMATIC CONTROLS ON ROBUSTA COFFEE YIELD UNDER FUTURE CLIMATE SCENARIOS IN THE SREPOK RIVER BASIN

Authors

DOI:

https://doi.org/10.36253/ijam-4112

Keywords:

Robusta coffee, Climate change, Yield prediction, LASSO regression, Mechine Learning

Abstract

Climate change poses significant challenges to coffee production in the Central Highlands of Vietnam, the country's primary coffee-growing region. This study assesses the impacts of climate change on Robusta coffee yield in the Srepok River Basin using meteorological and yield data from the 2001–2020 period at five study sites: Buon Ho, Dak Mil, M'Drak, Buon Ma Thuot, and Lak. The Least Absolute Shrinkage and Selection Operator (LASSO) variable selection method was employed to identify key climatic factors from 72 variables aggregated at monthly, growing season, and annual scales. Results indicate that water balance variables (potential evapotranspiration (PET), water surplus (SUR)) and extreme temperature indices play a dominant role in determining yield, while seasonal and monthly variables account for 68% of selected predictors, reflecting the existence of "sensitive climate windows" throughout the coffee phenological cycle. Four machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Regression, and eXtreme Gradient Boosting) were trained for yield simulation, with SVR and XGBoost demonstrating superior performance (Nash–Sutcliffe Efficiency > 0.75; R² > 0.84). Future climate scenarios (2026–2100) were generated by downscaling three CMIP6 General Circulation Models (GCMs: CanESM5, MPI-ESM1-2-HR, and NorESM2-MM) under four Shared Socioeconomic Pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, and SSP5-8.5). Simulation results exhibit marked spatial heterogeneity in climate change impacts: Dak Mil emerges as the most vulnerable area, with potential yield reductions reaching 58.10% by the end of the century, while M'Drak, which has the highest baseline water surplus, shows the smallest fluctuations. This research provides a scientific basis for production planning and the formulation of adaptive strategies to ensure the sustainable development of the coffee sector under a changing climate.

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Published

2026-07-08

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Pham, L., Pham, N., & Nguyen, B. (2026). AGROCLIMATIC CONTROLS ON ROBUSTA COFFEE YIELD UNDER FUTURE CLIMATE SCENARIOS IN THE SREPOK RIVER BASIN. Italian Journal of Agrometeorology. https://doi.org/10.36253/ijam-4112

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