As águas subterrâneas são responsáveis por sustentar diversos sistemas aquáticos, e estão intimamente ligadas a segurança hídrica do planeta, uma vez que 97% da água doce disponível se concentra no subsolo. O seu uso é ligado à diversas vantagens, tanto econômicas quanto de saúde, porém por estarem escondidas no subterrâneo, o gerenciamento, controle e consolidação de políticas públicas específicas são dificultados. Além disso, a desinformação a cerca de sua importância social, ambiental e econômica as deixam vulneráveis a contaminação e mau uso. Por isso, a fim de aumentar o conhecimento à cerca da qualidade desse recurso, diversos pesquisadores propõem metodologias que permitam avaliar o quão vulneráveis essas águas são à contaminação. Uma dessas metodologias possui propósito específico à realidade brasileira e é conhecida como metodologia GOD. Porém para que sua aplicação seja realizada em mapas representativos, é necessário que técnicas de estimativas sejam corretamente aplicadas. Neste contexto, objetivou-se avaliar, atavés da técnica de validação cruzada, o desempenho de diferentes modelos do índice GOD produzidos pelos interpoladores Krigagem Ordinária, Vizinho mais próximo, Inverso da distância ao quadrado e mínima curvatura. O estudo procedeu-se na Bacia Hidrográfica do Rio Pardo - RS, por meio da análise de 143 poços tubulares distribuídos pela área. E revelou que a classe de vulnerabilidade extrema não foi identificada em nenhum poço, que 16,1% deles são classificados como de vulnerabilidade insignificante; 21,7% como vulnerabilidade média; 30,8% vulnerabilidade baixa e 31,5% como vulnerabilidade alta. Para a interpolação dos dados, o estudo demonstrou que a Krigagem Ordinária foi o interpolador mais preciso e acurado. O modelo de distribuição espacial gerado, apontou que à vulnerabilidade a contaminação das águas subterrâneas da bacia é bem distribuída entre as regiões norte e sul. Sendo as classes insignificante e baixa concentradas na região norte, e as classes média e alta na região sul.

The importance of understanding spatial variability of soils is connected to crop management planning. This understanding makes it possible to treat soil not as a uniform, but a variable entity, and it enables site-specific management to increase production efficiency, which is the target of precision agriculture. Questions remain as the optimum soil sampling interval needed to make site-specific fertilizer recommendations in Brazil. The objectives of this study were: i) to evaluate the spatial variability of the main attributes that influence fertilization recommendations, using georeferenced soil samples arranged in grid patterns of different resolutions; ii) to compare the spatial maps generated with those obtained with the standard sampling of 1 sample ha-1, in order to verify the appropriateness of the spatial resolution. The attributes evaluated were phosphorus (P), potassium (K), organic matter (OM), base saturation (V%) and clay. Soil samples were collected in a 100 × 100 m georeferenced grid. Thinning was performed in order to create a grid with one sample every 2.07, 2.88, 3.75 and 7.20 ha. Geostatistical techniques, such as semivariogram and interpolation using kriging, were used to analyze the attributes at the different grid resolutions. This analysis was performed with the Vesper software package. The maps created by this method were compared using the kappa statistics. Additionally, correlation graphs were drawn by plotting the observed values against the estimated values using cross-validation. P, K and V%, a finer sampling resolution than the one using 1 sample ha-1 is required, while for OM and clay coarser resolutions of one sample every two and three hectares, respectively, may be acceptable.

The use of simulation models is probably the most efficient means for predicting the behavior of pesticides in the soil-plant-water system. The CMLS (Chemical Movement in Layered Soils) simulation model for predicting the fate of pesticides was used for studying the behavior of tebuthiuron, a herbicide used in sugar cane crops, from a sampling grid with 111 sampling points 200 m apart from one another and encompassing three types of soil: Ustic Quartzipsamment, Rhodic Hapludox and Typic Hapludox, all with medium and clay textures. The 373 points assessed by the simulator, generated from samples coming from the original grid and through the geostatistical methods of variography and ordinary kriging, returned the depth values reached by the herbicide after six years of simulation (1989-1995). For the Ustic Quartzipsamment, tebuthiuron, in four simulated points, returned depth values above 43 m and a maximum 50 m, with a certain amount of the product still remaining in the soil that was close to 10% of the original 1.1 kg ha-1 applied. Results from the column assay used for validating the model showed that the model overestimated the depth reached by the herbicide in 6.6% as compared to the column value for the Ustic Quartzipsamment. The depth was underestimated in 4.5% and 20% for the Typic Hapludox and the Rhodic Hapludox, respectively. These data support the adequacy of the model for assessing the fate of tebuthiuron in both Ustic Quartzipsamment and Typic Hapludox.

Solos submetidos ao mesmo sistema de manejo em locais com pequena variação de relevo, manifestam variabilidade espacial diferenciada de seus atributos. Esta variabilidade é condicionada pela posição dos solos na paisagem ou no declive, mesmo que o relevo seja de pequena expressão. O estudo teve como objetivo avaliar a influência da forma do relevo na variabilidade espacial de atributos químicos em um latossolo cultivado com cana-de-açúcar em dois compartimentos da paisagem. Os solos foram amostrados nos pontos de cruzamento de uma malha, com intervalos regulares de 10 m, perfazendo um total de 100 pontos, nas profundidades de 0-0,2 m e 0,6-0,8 m. Foi avaliado a variabilidade espacial do pH, fósforo (P), potássio (K), cálcio (Ca), magnésio (Mg), acidez potencial (H+Al), capacidade de troca catiônica (CTC) e saturação por bases (V%). Pequenas variações nas formas do relevo condicionaram variabilidade diferenciada para os atributos químicos do solo. Os atributos químicos estudados apresentaram-se dependentes da pedoforma em ambas profundidades estudadas. Um maior número de amostras devem ser coletados em áreas com forma de relevo côncavo e convexo devido à maior variabilidade. O uso conjunto das formas do relevo e geoestatística possibilita definir áreas com diferentes variabilidades espaciais para atributos químicos do solo.

Spatial modelling of air temperature (maximum, mean and minimum) of the State of São Paulo (Brazil) was calculated by multiple regression analysis and ordinary kriging. Climatic data (mean values of five or more years) were obtained from 256 meteorological stations distributed uniformly over the State. The correlation between the climatic dependent variables, with latitude and altitude as independent variables was significant and could explain most of the spatial variability. The coefficients of determination (P < 0.05) varied in the range of 0.924 and 0.953, showing that multiple regression analysis is an accurate method for the modelling of air temperature for the State of São Paulo. Finally, these regression equations were used together with the kriged maps of the residual errors to build 15 digital maps of air temperature using a 0.5 km² Digital Elevation Model in a Geographic Information System.

Monthly averages of maximum and minimum temperature, mean relative humidity, sunshine duration and wind speed at 2 m height, relative to 148 Iranian weather stations and period 1991–2005 were utilized for interpolation and gridding the variables to 1◦ in latitude and longitude. The Ordinary kriging method was used coupled with a spherical isotropic variogram. Monthly precipitation of the APHRODITE dataset was regridded to the same mesh grid for computing the aridity index jointly with the gridded variables. The required elevation for estimation of ETo at each grid node was extracted from the digital elevation map of Iran. The adequacy of gridded variables was proved through a set of statistical indicators applied to the cross-validated interpolation errors. The Penman–Monteith (PM-ETo) reference evapotranspiration (ETo) was estimated using the gridded variables and statistically compared with those of observational datasets relative to some stations covering all climatic regions of Iran. Results indicated that the PM-ETo computed using gridded variables well fitted the PM-ETo computed using observed full weather variables at those selected stations. ETo was also estimated by the Hargreaves–Samani (HS) and FAO-PM temperature (PMT) methods using gridded variables of minimum and maximum temperature (Tmin and Tmax). To estimate ETo with HS and PMT methods, appropriate kRs, an empirical radiation adjustment coefficient, were considered for each station, whereas Tmin was adjusted for estimation of the dew point temperature (Tdew) used for PMT computation. It was found that the appropriate kRs for both HS and PMT methods are identical all over the country and they are smaller in dry-sub-humid to humid areas and higher in semiarid to hyper-arid climates. The result suggested that the HS and PMT methods appropriately predict ETo all over Iran if the appropriate kRs are utilized. The spatial patterns of ETo computed with HS and PMT methods found to be identical and resemble to that of PM-ETo, all showing a gradual increasing from north to south, with the lowest ETo values observed over northern humid and sub-humid climates of Iran and larger ETo for arid and hyper-arid climates in the southern and eastern country. Results indicated that the HS and PMT methods are appropriate alternatives for estimation of ETo for all climatic regions of Iran, either when using observation or gridded data

Precipitation estimation is a challenging task, especially in regions where its spatial distribution is irregular and highly variable. This study evaluated the spatial distribution of annual rainfall in a semiarid Brazilian basin under different regimes and its impact on land use and land cover dynamics. Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) records and observed data from 40 weather stations over a time series of 55 years were used, in addition to the Standardized Precipitation Index. Spatiotemporal analysis was carried out based on geostatistics. Remote sensing images were also interpreted for different rainfall regimes using the Normalized Difference Vegetation Index and Modified Normalized Difference Water Index. The Gaussian semivariogram model best represented the rainfall spatial structure, showing strong spatial dependence. Results indicated that rainfall amount in the basin significantly increases with elevation, as expected. There is high variation in the dynamics of water storage that can threaten water security in the region. Our findings point out that the application of geostatistics for mapping both the annual precipitation and the Standardized Precipitation Index provides a powerful framework to support hydrological analysis, as well as land use and land cover management in semiarid regions.

A incorporação de cenários pluviométricos a estudos de aptidão agrícola é desejável, pois possibilita torná-los ajustados e adequados à variabilidade natural das precipitações e às expectativas pluviométricas dos modelos numéricos de previsão climatológica em uso no Brasil. Devido à importância de conhecer a distribuição das chuvas de uma determinada região, objetiva-se por este trabalho determinar cenários pluviométricos do Estado da Paraíba utilizando o modelo probabilístico distribuição Gama incompleta e o teste de Kolmogorov-Smirnov. Utilizaram-se os totais mensais de precipitações que possuem vinte ou mais anos de observações. Para cada posto pluviométrico, foi estabelecido o total de precipitação pluviométrica registrado nos três meses consecutivos mais chuvosos de cada ano hidrológico completo. Os conjuntos dos anos secos, regulares e chuvosos de cada posto foram utilizados para obter as correspondentes médias mensais dos totais pluviométricos, necessárias para caracterizar os cenários. Para a determinação dos níveis de 25, 50 e 75% de probabilidade de precipitação foi realizado com auxílio do modelo probabilístico de distribuição Gama incompleta e o ajuste das distribuições de foram avaliados pelo teste Kolmogorov-Smirnov a 95% de significância. Para o mapeamento foi utilizado a Krigeagem. Os resultados demonstraram que o uso do modelo probabilístico distribuição Gama incompleta e do teste de Kolmogorov-Smirnov responderam bem aos dados trabalhados apresentando boa coerência; com o uso do método geoestatístico de interpolação de dados pela Krigeagem foi possível mapear os resultados apresentando bons resultados na espacialização dos cenários pluviométricos; os cenários seco, regular e chuvoso apresentaram padrões de valores maiores de probabilidade de ocorrência de chuvas na região do Litoral, Agreste e Brejo, e menores valores na região do Cariri/Curimataú, voltando a aumentar na região do Sertão e Alto Sertão do Estado da Paraíba.

With developments in recent years, methods for bathymetric surveys using acoustic sensors (echo sounders) and signals transmitted by satellite navigation receivers, it becomes possible to describe the submerged same level of detail which is embossed with the surface relief describes terrestrial. A graphical representation of the underwater relief occurs from Digital Elevation Models (DEMs) generated by interpolating seeking, from measurements, predict the depth at unsampled locations. The geometrical information taken from bathymetric surveys, the volume of liquid water or mud present, for example in a reservoir, is the most relevant. This study sought to determine the products generated by single beam bathymetric survey, as well as the methods of kriging interpolation and Topo to Raster. The study areas were a box of decanting of the water treatment plant and a dam lake of Furnas, where surveys were conducted, with total station and bathymetric surveys, with a single beam echo sounder which operates at frequencies 33 kHz and 210 kHz . In the settling box, first bathymetric survey was conducted (Lbat 1). Then be emptied and cleaned the box and before filling it again, surveying, (Ltop) was performed with total station. Immediately after filling, without water and mud decanted, another bathymetric survey (Lbat 2) was performed. To survey the dam lake of Furnas, held automated bathymetric survey, ie, using the GNSS technology for positioning. First, the data from the survey, we evaluated the methods of kriging interpolation and Topo to Raster in the DEM generation of the settling box. The conclusion was that the interpolator Top to Raster conditioning showed remarkable deformations at the edges and in the center of the study area and should be discarded. The next stage of this work was to evaluate the accuracy of DEMs generated by applying kriging on data from single beam bathymetric survey, Lbat 2, using the frequencies of 33 kHz and 210 kHz. Possession of DEMs were calculated discrepancies between information from them and points of surveying. The results showed an accuracy of about 5 cm in mean depths of 3.21 m, and that as the surveys were conducted after cleaning the box, with clean water, there was no significant difference in the accuracy of DEMs generated with depths raised to the frequencies 33 kHz and 210 kHz. Then the DEMs were generated by kriging for the first bathymetric survey, Lbat 1, when solid waste resulting from the settling process still existed. Volumes were calculated and compared to evaluate the frequency of 33 kHz echo sounder to determine the volume of mud in the box. After analyzing the results, it was found that using only the first bathymetric survey, with the frequencies 33 kHz and 210 kHz, there was detected 186 m3 of sludge, in a total volume of 799 m3 of water and mud which, with the clean water the volume is determined by accurate bathymetry, showing discrepancy of 0.63% for the frequency of 210 kHz and 0.12% for the frequency of 33 kHz. To survey the lake of Furnas DEMs were generated by kriging interpolation method and the Top to Raster, varying the spacing between the regular survey lines using horizontal scan lines to the regular survey lines. Through statistical analysis of the discrepancies between estimated by interpolating depths and depths observed in the scan lines of the bathymetric survey, the kriging showed better results for spacings of 40 and 80 meters. Considering the isobatimétricas between different DEMs created, it is observed that for larger spacings the interpolator to Top Raster presented smoother features when compared to the DEMs generated by kriging.

Mapping rainfall erosivity is a practical and indispensable tool for land use planning at regional scale, like large river basins. The objective of this study was to evaluate the spatial distribution of the annual erosive potential of rainfall for the Upper Paraguai Basin (BAP) in Brazil. For this, 125 pluviometric stations located in BAP and its surroundings were analyzed. The rainfall erosivity was estimated for each station using the Modified Fournier Index. For the spatial distribution of the erosive potential, the values for erosivity in each station were interpolated using the kriging method. Annual erosivity at BAP ranged from 5,105 to 9,169, with an average of 6,800 MJ mm ha-1 h-1. Erosivity was classified as moderate to strong in 69% of BAP and in 31% of the basin the erosive potential of rainfall was classified as strong. An increase in erosivity going from southwest to northeast was also observed. Areas with high values of rainfall erosivity in BAP, associated with upland areas and with soils that are more susceptible to erosion show the greatest vulnerability to natural rainfall erosion. These lands should be carefully managed to minimize soil erosion and its impacts on the Pantanal.