Mapping average annual precipitation in Serbia (1961–1990) by using regression kriging

Bajat, Branislav; Pejović, Milutin; Luković, Jelena; Manojlovic, Predrag; Ducic, Vladan; Mustafic, Sanja

doi:10.1007/s00704-012-0702-2

Cited by 48 publications

(28 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A moderate continental climate occurs in the largest part of the territory (central, western, eastern, and southern parts of the country), while the south and southwestern regions of the country are subjected to Mediterranean influences with a modified Mediterranean climate [38,39]. The average annual amount of precipitation for the entire country is 739 mm [40]. Most of the terrain is exposed to the penetration of moist air masses from the west.…”

Section: Study Area and Datamentioning

confidence: 99%

Extreme Precipitation Events in Serbia: Defining the Threshold Criteria for Emergency Preparedness

et al. 2018

View full text Add to dashboard Cite

Abstract:Considering recent weather events in Serbia (especially the floods in 2014), a need has arisen for research that would help in identifying extreme weather phenomena. Therefore, the aim of this paper is to determine the thresholds above which intense precipitation can be considered as extreme precipitation events in Serbia. In this study, we determined the frequency of precipitation occurring at an intensity above the threshold of an extreme phenomenon , as well as the frequency of precipitation occurring at or above the absolute daily maximum in the reference period . The study sample included daily rainfall observations from 28 stations from the national meteorological network in Serbia. Applying a decile method, all the stations recording precipitation above the threshold of dangerous phenomena on the same day are classified into the corresponding decile. The threshold value was determined as the average value of the extreme annual precipitation in the analyzed period. The cases that are due to the high prevalence listed in the last decile are considered extreme. The results showed that the critical number of observation points above which an event is considered extreme precipitation event is 6.21, and a warning of the danger could be ensured only in the case of neighboring stations in the network. The threshold of extreme precipitation events for the individual stations ranges up to 130 mm. The obtained results might be used to mitigate the effects of extreme precipitation events in Serbia in the future.

show abstract

Section: Study Area and Datamentioning

confidence: 99%

Extreme Precipitation Events in Serbia: Defining the Threshold Criteria for Emergency Preparedness

et al. 2018

View full text Add to dashboard Cite

show abstract

“…A significant prediction error in interpolation appears at the boundary of the study area, known as "edge effects." These effects could be mitigated by taking into account the precipitation data of stations just outside the border [15]. In this study, the precipitation data of meteorological stations located at the 100 km peripheral buffer of Loess Plateau was added in order to improve the prediction results of the study area boundary.…”

Section: Discussionmentioning

confidence: 99%

“…In order to evaluate the interpolation by MLRK and GWRK, adjusted determination coefficients (adjusted R 2 ) were calculated for the deterministic part by MLR and GWR, and five-fold cross-validation was implemented for interpolated residuals by OK [15]. The whole prediction error of back-transformed precipitation corresponding to MLRK and GWRK was evaluated by comparing estimated values with actual observations at validation points.…”

Section: Validation Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

Jin

Zhang

Shi

et al. 2016

Water

View full text Add to dashboard Cite

Abstract:Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK) and geographically weighted regression Kriging (GWRK) methods were employed using precipitation data from the period 1980-2010 from 435 meteorological stations. The predictors in regression Kriging were selected by stepwise regression analysis from many auxiliary environmental factors, such as elevation (DEM), normalized difference vegetation index (NDVI), solar radiation, slope, and aspect. All predictor distribution maps had a 500 m spatial resolution. Validation precipitation data from 130 hydrometeorological stations were used to assess the prediction accuracies of the MLRK and GWRK approaches. Results showed that both prediction maps with a 500 m spatial resolution interpolated by MLRK and GWRK had a high accuracy and captured detailed spatial distribution data; however, MLRK produced a lower prediction error and a higher variance explanation than GWRK, although the differences were small, in contrast to conclusions from similar studies.

show abstract

“…Regression-Kriging has been applied widely in various fields such as climatology (Bajat et al, 2013;Tadić, 2010), soil science (Hengl et al, 2004;Omuto and Vargas, 2015;Zhu and Lin, 2010), and species distribution modelling (Meng, 2006;Hengl et al, 2009). …”

Section: Introductionmentioning

confidence: 99%

Improving the understanding of rainfall distribution and characterisation in the Cathedral Peak catchments using a geo-statistical technique

Morris

Toucher

Clulow

et al. 2016

WSA

View full text Add to dashboard Cite

The characterisation of rainfall variability, spatially and temporally, is essential for hydrological and ecological analyses. Inherently, this variability is distinctly more obvious in mountainous areas compared to lowlands. The objective of this study was to ascertain if the use of the regression-Kriging technique would provide improved estimates and understanding of the rainfall distribution across the Cathedral Peak catchments in the Drakensberg escarpment region, South Africa. Findings showed longitude and altitude to be the overall best predictors of the distribution of rainfall for the annual period, wet season and dry season, with longitude explaining 72% and altitude explaining 26% of the rainfall variability for mean annual precipitation, 73% and 26% for the wet season and 50% and 22% for the dry season, respectively. The combination of both longitude and altitude showed a larger coefficient of determination, of 0.73, 0.74 and 0.51, for the annual, wet season and dry season, respectively. Long-term mean annual rainfall patterns showed an overall strong directional distribution from west to east with a distinct pattern observed during the dry season. It was concluded that regression-Kriging is a useful alternative method for characterising rainfall distribution as well as prediction errors for mountainous areas.

show abstract

Mapping average annual precipitation in Serbia (1961–1990) by using regression kriging

Cited by 48 publications

References 28 publications

Extreme Precipitation Events in Serbia: Defining the Threshold Criteria for Emergency Preparedness

Extreme Precipitation Events in Serbia: Defining the Threshold Criteria for Emergency Preparedness

Estimating Loess Plateau Average Annual Precipitation with Multiple Linear Regression Kriging and Geographically Weighted Regression Kriging

Improving the understanding of rainfall distribution and characterisation in the Cathedral Peak catchments using a geo-statistical technique

Contact Info

Product

Resources

About