How monitoring crops and drought, combined with climate projections, enhances food security: Insights from the Northwestern regions of Bangladesh

Abstract

Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as they provide future adaptation scenarios for agriculture. This study aims to project climatic scenarios for northern Bangladesh, assess agricultural and meteorological drought, and estimate crop yield using remote sensing and field data. Our simulated data from 21 CMIP6 models (ensemble mean) under SSP2-4.5 scenarios reveal that maximum temperatures will rise in northwestern regions such as Nawabganj, Rajshahi, Naogaon, Dinajpur, and Joypurhat. By 2050 and 2060, the areas affected by rising mean temperatures are expected to expand into other districts. Additionally, projected rainfall is expected to increase in northern districts, particularly after 2040. Drought assessments using the TOTRAM model reveal a water deficit in many areas in 2022, with milder conditions in 2023. Applying SPEI (Hargreaves-Zamani method) from 1984 to 2024, Sirajganj faced moderately dry conditions (14.38%), while Dinajpur had near-normal conditions (63.33%). Our crop yield model, incorporating Leaf Area Index (LAI), NDVI, SAVI, and field data, demonstrates successful yield estimation, with a significant correlation between predicted and observed yields. The multiple linear regression model achieved a 0.82 goodness-of-fit value, indicating effective yield estimation. We emphasize that timely, accurate information dissemination and monitoring are often more effective in preventing agricultural losses than structural developments. This study encourages decision-makers to integrate geospatial technologies and share critical information with farmers to strengthen food security.