The occurrence of rainfall extreme events leads to several environmental, social, cultural, and economic consequences, heavily impacting agriculture. The analysis of climate extreme indices at the municipal level is of the uttermost importance to the overall study of climate variability and regional food security. Corn, bean, and cassava are among the most cultivated temporary subsistence crops. Thus, the objective of this study was to analyze the relationship between subsistence agriculture productivity and the behavior of rainfall extreme indices in the Rio Grande do Norte state in the period from 1980 to 2013. We used the dataset provided by Xavier (2016) and the climate extreme indices obtained through the Expert Team on Climate Change Detection and Indices. Crop productivity data were retrieved from the Municipal Agriculture Survey from the Brazilian Institute of Geography and Statistics system. The methodology evaluated the behavior and the relationship between agricultural productivity time series and extreme precipitation indicators. We applied the following statistical techniques: descriptive analysis, time series trend analysis by the Mann-Kendall test, cluster analysis, and analysis of variance to check for equal means between identified groups. Cluster analysis was considered an adequate tool for the comprehension of data spatial distribution, allowing the identification of five homogenous subregions with different precipitation patterns. Rainfall extreme indices allowed the analysis of regional conditions regarding consecutive dry days, annual precipitation in wet days, and heavy rainfall. Trends were identified in these indices and they were significantly correlated with dryland crops productivity, indicating a direct relationship between water availability and regional agroclimatic stress.
The identification and delimitation of regions based on their agricultural aptitude is essential in order to assure the effective development and adaptation of climate vulnerable regions, such as the Northeast Brazil (NEB). The objective of this study was to analyze the influence of the water balance on subsistence corn, bean and cassava yields during the period from 1990 to 2019. Thus, we characterized the NEB used meteorological variables (precipitation, temperature, relative humidity and radiation) and water balance elements (potential evapotranspiration, water stored in the soil, water deficit and surplus) in order to determine the best sowing periods for the aforementioned crops. Data was assessed by using different statistical analysis tools such as Mann-Kendall’s test for trend identification, analysis of variance and correlation heatmaps. Results showed an increasing trend for radiation, temperature and potential evapotranspiration in the wetter regions of the NEB. An increase in water deficit conditions was also identified during September-October-November, and therefore a reduction in water stored in the soil during the following months in all regions of the NEB. In the wetter regions, potential evapotranspiration and temperature were positively correlated with bean and corn yields. In the drier regions, on the other hand, water stored in the soil and water surplus were more positively associated with crop yields. For the other climatic types, the following best sowing windows were identified based on the water balance: January through April (semiarid), March through June (dry subhumid), April through July (moist subhumid), March through July (humid B1) and January through June (humid B2).
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