Mapeamento da precipitação mínima provável para o sul de Minas Gerais

Adjustment of multiple linear regression equations has allowed estimating the value of a certain climatological variable according to geographical coordinates with acceptable degree of accuracy. The aim of this study was to verify if the average monthly rainfall could be estimated according to the altitude, latitude and longitude in Mato Grosso do Sul State (MS). Rainfall data of 32 stations of MS were collected from 1954 to 2013. It were formed 384 time series (12 months × 32 sites), with different numbers of years of observations in each series. On each of the 384 monthly rainfall time series it was calculated the average (a), at least 30 years of observation, forming 12 matrices 32 x 4 (32 sites x 4 variables: altitude, latitude, longitude and monthly rainfall). It was estimated for each matrix the Pearson's linear correlation coefficient among the variables, performing the multicollinearity diagnosis for each matrix. Correlations were unfolded by path analysis in direct and indirect effects and in each month it was used the multiple linear regression model. The altitude and latitude have greater effect on the spatial distribution of rainfall in MS. The multiple linear regression equations generated in this study will subsidize researches of crop zoning, indication for sowing times, irrigation, determination of yield potential, climate risks zoning and credit and agricultural insurance.

Section: Resultssupporting

confidence: 85%

Altitude and geographic coordinates to estimate monthly rainfall in the state of Mato Grosso do Sul

Teodoro

Cunha²,

Corrêa³

et al. 2016

“…This behavior shows that despite the tropical features present in Mato Grosso do Sul, the altitude is among the physiographic factors, followed by the latitude, the most factor influential in the monthly rainfall during dry, transitional, and rainy seasons, regardless of the period of the year, resembling the results obtained in studies performed in other Brazilian States (BAÚ et al, 2006;ÁVILA et al, 2009;ULIANA et al, 2013).…”

Section: Resultssupporting

confidence: 80%

Probable monthly rainfall associated with distinct biomes of Mato Grosso do Sul state

Teodoro¹,

Silva²,

Oliveira‐Júnior³

et al. 2017

ABSTRACT:The aim of this study was to determine the probable monthly rainfall for the state of Mato Grosso do Sul, considering the level of 75% probability, and study the spatial distribution associated with its different biomes. The rainfall data of 32 stations (sites) in the state of Mato Grosso do Sul were collected in the period 1954-2013. In each of the 384 series, the average monthly rainfall was calculated, for at least 30 years of observation. The Kolmogorov-Smirnov adhesion test was applied to the rainfall time series to check the fit of the data to a normal distribution. The likely fallout was estimated at 75% probability, using the normal probability distribution and, subsequently, it was adopted the method of Ordinary Kriging interpolation mathematics to spatial data. Based on the likely monthly precipitation estimated, the State of Mato Grosso do Sul possess three distinct periods, with the precipitation associated with different biomes: the rainy season (between the months November to March, where increased precipitation occurred in the Savanna biome), dry season (between the months from

“…It is important to mention that the groups identified as homogeneous by AA followed a NorthSouth alignment. This behavior shows that despite the tropical features present in the Tocantins State, the latitude is, among the physiographic factors, the one that has the most influence in the monthly rainfall during the dry, transitional and rainy seasons, resembling the results obtained in studies performed in other Brazilian States (BAÚ et al 2006, ÁVILA et al 2009ULIANA et al 2013;TEODORO et al, 2015a,b).…”

Section: Resultssupporting

confidence: 76%

Cluster analysis identified rainfall homogeneous regions in Tocantins state, Brazil

Oliveira‐Júnior¹,

Xavier²,

Teodoro³

et al. 2017

ABSTRACT:Identifying homogeneous regions regarding the monthly rainfall is relevant in agricultural planning, especially in relation to the installation of crops. Thus, the aim of this study was to apply the cluster analysis using Ward's algorithm to identify homogeneous regions in Tocantins State. Rainfall database of 34 stations (sites) of Tocantins, from 1976 to 2012, it were obtained of the Database of the Agência Nacional de Águas, Instituto Nacional de Meteorologia and Serviço Meteorológico do Brasil. Thus, were formed 408 time series (12 months × 34 sites) wherein AA technique was applied in conjunction with Ward's algorithm. Three homogeneous regions in relation to monthly rainfall were identified. Group 1, located in the extreme north of the state, has intermediate average values (135.58 mm) to the other groups. Group 2 showed the greatest variance (13,543.68 mm²) and higher average (162.19 mm) for the studied period. On the other hand, group 3 has the lowest average rainfall (117.93 mm) among the homogeneous groups. Separating the groups followed a north-south alignment which suggests that latitude is the physiographic factor that most influences the occurrence of monthly rainfall in the State of Tocantins.