
Avaliação da Técnica de Krigagem Ordinária Utilizando o Modelo Geoestatístico Estável no Preenchimento de Falhas de Séries de Precipitação Pluviométrica nas Sub-bacias Hidrográficas Localizadas em Regiões de Classificação Climática Distintas no Estado do Paraná
Author(s) -
Juliane Macedo Magerski,
Jorim Sousa das Virgens Filho
Publication year - 2021
Publication title -
revista brasileira de geografia física
Language(s) - English
Resource type - Journals
ISSN - 1984-2295
DOI - 10.26848/rbgf.v14.4.p2149-2171
Subject(s) - humanities , physics , philosophy
Hydroclimatological monitoring is of great relevance in problems involving socioeconomic and environmental issues. In this context, rainfall is an impacting factor in the interrelationship between climate and hydrography, and it is important to evaluate its characteristics and spatiotemporal distribution that help in urban territorial planning. This research aimed to assess the ordinary kriging technique, using the stable geostatistical model in filling gaps in monthly rainfall series, as well to analyze its spatialization in seasonal and annual periods in the hydrographic sub-basins of the Upper Tibagi River and the Lower Ivaí River, located in climatically distinct regions in the State of Parana. Monthly data of rainfall stations belonging to the Instituto Aguas Parana, INMET and IAPAR from 1974 to 2018 were used. ArcGis software was used for interpolation and generation of georeferenced maps, and a statistical analysis to verify the efficiency of the modeling, was conducted using the Wilcoxon test at 5% and EMA, REQM, r, d (Willmott), NS (Nash-Sutcliffe) statistics. In general, the rainfall classes were similarly represented in the maps generated with observed data and filled by the stable model. The statistical analysis showed a good efficiency of the modeling in the seasonal and annual periods, presenting relatively minimum values of EMA and REQM, as well as expressive values of the indexes r, d and NS, mainly, in the sub-basin of the Upper Tibagi River. Although the sub-basins are located in different climatic regions, anomalies due to local factors were not found in the data modeling and spatialization process.