Modeling the impact of climatic variables on cereal crop production in the Terai region of Nepal

Information from the abstract

Agricultural production in Nepal’s Terai plain is increasingly affected by climatic fluctuations, yet how multiple climate variables influence major cereals remain insufficiently understood. This study applies a Bayesian Vector Autoregressive (BVAR) model with Minnesota priors to examine the conditional associations and predictive relationships between climate variability and paddy, wheat, and maize yields using 36 years of annual data (1989–2024). Impulse response functions and forecast error variance decomposition were used to quantify the dynamic effects, evaluate the magnitude and persistence of climate shocks, and determine the contribution of individual climate variables. Paddy yield was negatively associated with Earth skin temperature (-0.456), air temperature (-0.401), and humidity (-0.356), while maximum temperature (0.441) and pressure (0.418) showed positive associations. Wheat exhibited the strongest response to wind variables, with minimum wind speed (0.392) positively associated and maximum wind speed (-0.361) negatively associated. Maize responded negatively to wind variability (-0.386) and humidity (-0.348); maximum temperature (0.341) and pressure (0.328) showed positive associations. Forecast validation showed BVAR outperforming classical VAR (13–16% RMSE improvement), ARIMA (9–13%), and persistence models (20–28%). Under the high-emissions SSP5-8.5 scenario, yields are projected to decline 12–18% by 2050. The study suggests the following adaptation strategies: (i) promote wind-resistant wheat varieties and shelter belts, (ii) improve drainage and moisture management for paddy, and (iii) develop drought-tolerant maize hybrids and optimize planting dates. These results indicate distinct, crop-specific associations between climate variability and cereal productivity, providing quantitative evidence for targeted adaptation planning for climate-resilient agriculture in the Terai region.

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Related topics: Climate change impacts on agriculture · Climate variability and models · Agricultural risk and resilience