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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Adaptive Cropping Systems Laboratory » Research » Publications at this Location » Publication #406301

Research Project: Developing Practices for Nutrient and Byproducts to Mitigate Climate Change, Improve Nutrient Utilization, and Reduce Effects on Environment (BRIDGE PROJECT)

Location: Adaptive Cropping Systems Laboratory

Title: Agronomic monsoon onset definitions to support planting decisions for rainfed rice in Bangladesh

Author
item Han, Eunjin
item MONTES, CARLO - International Maize & Wheat Improvement Center (CIMMYT)
item HUSSAIN, SK. GHULAM - International Maize & Wheat Improvement Center (CIMMYT)
item KRUPNIK, TIMOTHY - Columbia University

Submitted to: Climatic Change
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/25/2024
Publication Date: 5/13/2024
Citation: Han, E., Montes, C., Hussain, S., Krupnik, T.J. 2024. Agronomic monsoon onset definitions to support planting decisions for rainfed rice in Bangladesh. Climatic Change. 177. Article e77. https://doi.org/10.1007/s10584-024-03736-z.
DOI: https://doi.org/10.1007/s10584-024-03736-z

Interpretive Summary: Information on the timing of the monsoon onset is crucial for the livelihoods of people in Bangladesh, driving the decision-making of diverse stakeholders. The scientific community has made long-standing efforts to understand better the physical mechanisms of monsoon development and progression, and eventually to provide accurate predictions of monsoon timing in Bangladesh. However, there have been persistent ‘usability gaps’ between the knowledge producers (i.e., National Meteorological Services) and the actual users (i.e., extension workers or farmers in the case of agriculture) from the perspective of climate services. Ingesting end-users' perceptions in developing climate services is crucial to generate usable information beyond useful scientific knowledge. In the present study, we aim to develop agronomic monsoon onset definitions and evaluate them against traditional practices and local farming communities' perceptions in terms of rainfed aman rice yield. We designed a set of crop modeling experiments to evaluate different onset definitions derived from long-term rainfall analysis. Our results suggest that considering the inherent interannual variability and seasonality in the onset of the rainy season, in this case using agronomic and a fixed rainfall threshold as dynamical criteria to determine the monsoon onset, represents an advantage to the traditionally-used static dates in terms of aman rice yields, over relatively drier regions. The simulation results prove that the rainfall-based locally defined onset dates could help farmers reduce yield vulnerability (i.e., bringing down chances of getting lower yields) in the drier areas rather than wetter areas, mainly because of their higher year-to-year variability in monsoon onset and vulnerability to its early withdrawal than over the wetter areas.

Technical Abstract: The usability gaps between climate information producers and users have always been an issue in climate services. This study aims to tackle the gap for rice farmers in Bangladesh by exploring the potential value of tailored agronomic monsoon onset definitions. Summer aman rice is primarily cultivated under rainfed conditions, and farmers rely largely on monsoon rainfall and its onset for crop establishment. However, farmers’ perception of the arrival of sufficient rains does not necessarily coincide with meteorological definitions of monsoon onset. Therefore, localized agronomic definitions of monsoon onset need to be developed and evaluated to advance in the targeted actionable climate forecast. We analyzed historical daily rainfall from four locations across a north-south gradient in Bangladesh and defined dynamic definitions of monsoon onset based on a set of local parameters. The agronomic onset definition was evaluated in terms of attainable yields simulated by a rice simulation model compared to results obtained using conventional meteorological onset parameters defined by the amount of rainfall received and static onset dates. Our results show that average simulated yields increase up to 7 – 9% and probabilities of getting lower yields are reduced when the year-to-year varying dynamic onset is used over the two drier locations under fully rainfed conditions. It is mainly due to earlier transplanting dates, avoiding the impact of drought experienced with early monsoon demise. However, no yield increases are observed over the two wetter locations. This study shows the potential benefits of generating “localized and translated” climate predictions.