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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 #398330

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: Evaluating agronomic onset definitions in Senegal through crop simulation modeling

item Han, Eunjin
item FAYE, ADAMA - Institut Senegalais De Recherches Agricoles
item DIOP, MBAYE - Institut Senegalais De Recherches Agricoles
item SINGH, BOHAR - Columbia University - New York
item GANYO, KOMLA KYKY - Togolese Institute Of Agronomic Research
item BAETHGEN, WALTER - Columbia University - New York

Submitted to: Atmosphere
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/15/2022
Publication Date: 12/17/2022
Citation: Han, E., Faye, A., Diop, M., Singh, B., Ganyo, K., Baethgen, W. 2022. Evaluating agronomic onset definitions in Senegal through crop simulation modeling. Atmosphere. 13(12):2122.

Interpretive Summary: In Senegal, weather-related risk, including the delayed onset or early cessation of the rainy season, is the most predominant factor threatening agricultural production. For climate services in agriculture, the National Meteorological Agency (ANACIM) of Senegal has defined an onset of rainy season based on the rainfall. In the field, however, farmers' planting decisions are made not necessarily relevant to the ANACIM's onset definition. To close the gap between the parallel efforts by a climate information producer (i.e., ANACIM) and its actual users in agriculture (e.g., farmers), it is desirable to understand how the currently available onset definitions are linked to the yield of specific crops. In this study, we evaluated multiple onset definitions, including rainfall-based and soil moisture-based ones, in terms of their utility in sorghum production using a crop simulation model. The results show that the rainfall-based definitions are highly variable year-to-year, and their delayed onset estimation could cause missing opportunities for higher yields with early planting. Overall, soil moisture-based onset dates determined by a crop simulation model are closer to the semi-optimal planting dates than the other definitions. The results emphasize that skillful onset forecasting is critical to improving managing risks of rainfed crop production in Senegal and in the U.S.

Technical Abstract: In accordance with the increasing improvement of climate services in Senegal, we evaluated the values of diverse onset definitions, from meteorological (rainfall-based) to agronomic (soil moisture-based) approaches, in terms of sorghum yield production. Data from four agricultural research experimental fields in Senegal and a well-calibrated sorghum crop model were used for the analysis. The meteorological onset definitions provide highly inter-annual variability of onset/planting dates due to their intrinsic weaknesses (i.e., being sensitive to certain threshold amounts/durations of rainfall/dry spells). The problems of highly variable onsets by the meteorological definitions were found detrimental when the onsets were delayed. Especially in drier regions, delayed planting caused severe water stress before and during a critical growth stage, anthesis, and thus significant yield decrease. Soil moisture-based onset definitions are more robust and closer to the semi-optimal planting dates than the meteorological ones. We found more benefits in planting early than procrastinating through the ex-ante crop modeling experiments. In the fields, the possibility of false onset (i.e., prolonged dry spell after onset) impedes farmers’ active response to the onset. This study emphasizes the importance of skillful and reliable forecasts of agronomic onset in the agricultural sector.