Sugarcane decision-making support using Eta Model precipitation forecasts

• Autor(a) principal: Moreto, Victor B.
• Data de Publicação: 2021
• Outros Autores: Rolim, Glauco de S., Esteves, João T., Vanuytrecht, Eline, Chou, Sin Chan
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s00703-020-00738-1; http://hdl.handle.net/11449/221470

Agricultural activity is largely influenced by climatic conditions. Rainfall is essential for crop production, and precipitation events also interfere with soil preparation, planting, application of pesticides and harvesting. Weather forecast models are tools to facilitate decision making for agricultural activities, hence high accuracy is desired. Farmers often criticize the accuracy of weather forecasts, which sometimes fail to predict precipitation events, leading to yield loss and environmental harm. In this study, precipitation forecasts of the Eta Model were evaluated for 28 of Brazil’s most productive sugarcane areas, considering a grid of 15 × 15 km. Using a combination of different indicators of forecast success, observed and forecasted daily precipitation data were compared for consecutive days of all 10-day periods in a course of 6 years (2005–2010). Skill scores and performance diagrams based on the indicators were used to evaluate the goodness and robustness of the model forecasts. The Eta Model forecasts showed overall accuracies ranging between 55 and 71% for the Atlantic forest biomes (located North-West and South-East of São Paulo) and the Cerrado biomes (located in the Goiás State and in the Center-North São Paulo State), respectively. The forecasts were most reliable for up to 4 days, showing an accuracy of 60%. Forecasts for periods of more than 4 days had an average accuracy of 40–50%. The probability of detecting rainfall correctly was the strongest characteristic of Eta Model, with more than 70% hits.