Abstract
The identification of the probability distribution function for the representation of the monthly rainfall is relevant in agricultural planning, mainly regard to the establishment of crops. The aim of this work was to verify the probability distribution (exponential, gamma or normal) which best fits to data monthly rainfall of 14 sites in the state of Mato Grosso do Sul. Rainfall data of 14 stations (sites) of the State of Mato Grosso do Sul it were obtained from the National Water Agency (ANA) database, collected in the period 1975 - 2013. At each of the 168 time series of monthly rainfall was applied the Kolmogorov-Smirnov test to assess the fit to probability distributions exponential, gamma and normal. The normal probability distribution presented the best fit to monthly rainfall series of Mato Grosso do Sul and it can be used for the estimation the monthly rainfall, especially in the rainy season months (October to March). The exponential probability distribution can be used for the estimation of monthly rainfall in the driest months of the year (May to September). Thus, we recommend that these distributions be used in future research, aimed to estimate the probable rainfall for the Mato Grosso do Sul State.
Highlights
The State of Mato Grosso do Sul (MS) covers an area of approximately 350,000 km2, of which 13,000 km2 are explored in agriculture, being the crops of higher expression soybean, maize, cotton, sugarcane and irrigated rice (CONAB, 2014)
Rainfall daily database of 14 stations of Mato Grosso do Sul, from 1975 to 2013, it were obtained of the Database of the Agência Nacional de Águas (ANA, 2014)
The statistic value of D maximum of the Kolmogorov-Smirnov adhesion test (KS) test informs the maximum distance between the theoretical and empirical probabilities obtained under the probability distribution function under test (ASSIS et al, 1996)
Summary
The State of Mato Grosso do Sul (MS) covers an area of approximately 350,000 km, of which 13,000 km are explored in agriculture, being the crops of higher expression soybean, maize, cotton, sugarcane and irrigated rice (CONAB, 2014). Agriculture has the rainfall as its main source of water, which may compromise the crop production due to its uneven behavior, sometimes with long periods of drought, sometimes with high intensity rains that exceed the water retention capacity of the soil, triggering floods (SILVA et al, 2007; SOCCOL et al, 2010; VIEIRA et al, 2010; CORRÊA et al, 2014). Besides the influence in agriculture, very long periods of droughts affect the water level of water sources and reservoirs of hydroelectric plants, bringing problems to the urban water supply and electric power generation (RODRIGUES et al, 2013; TEODORO et al, 2015a; TEODORO et al, 2016). The northern region is is affected by Upper Tropospheric Cyclonic Vortex, Front Systems and South Atlantic Convergence Zone. The southern region is influenced by Upper Tropospheric Cyclonic Vortex and Front Systems
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