Krigagem Ordinária Aplicada À Precipitação Pluviométrica Nos Estados Do Rio Grande Do Sul E Santa Catarina  Ordinary Kriging Applied to the Rainfall in the States of Rio Grande Do Sul and Santa Catarina

Pires, Carlos Alberto da Fonseca; Reis, Janete Teresinha; Dullius, Ângela Isabel dos Santos; Priesnitz, Mariane Camargo; Pereira, Maria João Veloso da Costa Ramos

doi:10.5902/2179460x22140

Cited by 2 publications

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“…Spatial analyzes involving climatic events are rare and require simulation studies [20]. In studies of this type, it is desirable that the random variables have a symmetrical distribution in order to satisfy the first-and second-order stationarities.…”

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confidence: 99%

The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

et al. 2021

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An accurate analysis of spatial rainfall distribution is of great importance for managing watershed water resources, in addition to giving support to meteorological studies and agricultural planning. This work compares the performance of two interpolation methods: Inverse distance weighted (IDW) and Kriging, in the analysis of annual rainfall spatial distribution. We use annual rainfall data for the state of Rio Grande do Sul (Brazil) from 1961 to 2017. To determine which proportion of the sample results in more accurate rainfall distribution maps, we use a certain amount of points close to the estimated point. We use mean squared error (MSE), coefficient of determination (R2), root mean squared error (RMSE) and modified Willmott's concordance index (md). We conduct random fields simulations study, and the performance of the geostatistics and classic methods for the exposed case was evaluated in terms of precision and accuracy obtained by Monte Carlo simulation to support the results. The results indicate that the co-ordinary Kriging interpolator showed better goodness of fit, assuming altitude as a covariate. We concluded that the geostatistical method of Kriging using nine closer points (50% of nearest neighbors) was the one that better represented annual rainfall spatial distribution in the state of Rio Grande do Sul.

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Section: Introductionmentioning

confidence: 99%

The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

et al. 2021

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A spatial approach to rainfall in Sertão do Pajeú – Pernambuco

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Changes in precipitation have implications for the hydrological cycle and water resources. Climate change is expected to alter average temperature and precipitation values, increasing the variability of these events, which could cause more intense and frequent floods and droughts. The objective of this study was to characterize the rainfall in the microregion of Pajeú, in Pernambuco, as well as to provide subsidies for public policies aimed at water scarcity. For this, rainfall data were used at stations belonging to the micro-region and its surroundings, for the period from January 1980 to December 2019. In addition, to mitigate the influences caused by temporal heterogeneity, stations with large discontinuity of information. The Inverse Weighted Distance was used to perform the interpolation of data and preparation of maps with isolines of rainfall. The results show the places with the highest annual rainfall during the study period were Serra Talhada and Triunfo, and the lowest rainfall occurred in the vicinity of Ingazeira and Tabira.

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Krigagem Ordinária Aplicada À Precipitação Pluviométrica Nos Estados Do Rio Grande Do Sul E Santa Catarina Ordinary Kriging Applied to the Rainfall in the States of Rio Grande Do Sul and Santa Catarina

Abstract: Resumo Os estados do Sul, segundo ROSSETI, (2000)

Cited by 2 publications

References 1 publication

The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

The assessment of annual rainfall field by applying different interpolation methods in the state of Rio Grande do Sul, Brazil

A spatial approach to rainfall in Sertão do Pajeú – Pernambuco

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