Joyce Aguiar Dias

A variabilidade climática impõe riscos severos aos sistemas de segunda safra no Cerrado. Este estudo avaliou a variabilidade temporal das secas e os riscos climáticos associados à produção de algodão em Campo Verde, Mato Grosso, no período de 1970 a 2024. Foram utilizados dados da reanálise ERA5-Land para o cálculo do Índice Padronizado de Precipitação (SPI) nas escalas de 1, 3 e 6 meses. As tendências foram avaliadas pelos testes de Mann-Kendall e de Sen, evidenciando elevada variabilidade interanual da precipitação, com média de 1684,0 mm, além de aumento na ocorrência de eventos de seca moderada a severa a partir de 2020. Observou-se tendência negativa significativa da disponibilidade hídrica entre maio e outubro, indicando maior persistência do período seco e irregularidade no estabelecimento das chuvas. O SPI-6 também revelou anomalias persistentes, com implicações potenciais para a recarga hídrica do solo. Para o algodão, esse cenário amplia os riscos durante o estabelecimento, a floração e o enchimento das maçãs, podendo comprometer produtividade e qualidade da fibra. Conclui-se que o SPI constitui uma ferramenta relevante para subsidiar o planejamento agrícola, o ZARC, o ajuste das épocas de semeadura e as práticas conservacionistas. Palavras-chave: variabilidade climática; índice padronizado de precipitação; déficit hídrico; cerrado brasileiro; sistemas agrícolas. Temporal variability of droughts (SPI) and climate risk for cotton in Campo Verde, Mato Grosso Climate variability imposes severe risks on second-crop systems in the Cerrado. This study evaluated the temporal variability of droughts and the climate risks associated with cotton production in Campo Verde, Mato Grosso, from 1970 to 2024. ERA5-Land reanalysis data were used to calculate the Standardized Precipitation Index (SPI) at 1-, 3-, and 6-month time scales. Trends were evaluated using the Mann-Kendall test and Sen's slope estimator, revealing high interannual precipitation variability, with a mean of 1,684.0 mm, as well as an increase in the occurrence of moderate to severe drought events from 2020 onward. A significant negative trend in water availability was observed between May and October, indicating greater persistence of the dry season and irregularity in the onset of rainfall. The SPI-6 also revealed persistent anomalies, with potential implications for soil water recharge. For cotton, this scenario amplifies the risks during crop establishment, flowering, and boll filling, potentially compromising yield and fiber quality. In conclusion, the SPI constitutes a relevant tool to support agricultural planning, Agricultural Climate Risk Zoning (ZARC), the adjustment of sowing dates, and conservation practices. Keywords: climate variability; standardized precipitation index; water deficit; Brazilian Cerrado; agricultural systems.

The objective of this study was to assess the variability of annual and monthly precipitation under current and future climate conditions, and to characterize its effects on soybean grain yield in the municipality of Tangará da Serra, Mato Grosso state, Brazil, using future climate projections from General Circulation Models (GCMs) and the Decision Support System for Agrotechnology Transfer (DSSAT), employing the CROPGRO-Soybean module. Model calibration was based on climate, soil, and management data, as well as genetic coefficients and field observations from the 2015/2016 growing season, considering cultivars with different maturity groups. Simulations were performed for six different sowing dates. Results indicated both positive and negative monthly fluctuations in precipitation under the current scenario. Among these, significant reductions were observed in September, October, and December, along with a general decreasing trend in annual precipitation for the region. Future scenarios (RCPs 4.5 and 8.5) showed both positive and negative variations, though not statistically significant. Earlyand intermediate-maturing cultivars exhibited lower yields and greater variability, whereas the late-maturing cultivar showed superior yield across all scenarios and sowing dates. Early sowings (September 20 to October 20) resulted in the lowest yields, while late sowings (November 1 and 10) were more favorable. Annual average precipitation was 1711 mm (current), 1494 mm (RCP 4.5), and 1515 mm (RCP 8.5). It is concluded that climate variability significantly affects soybean grain yield, with late-maturing cultivars and delayed sowings being recommended to enhance adaptation under future climate conditions.