scholarly journals Values of rainfall erosivity factor for the Czech Republic

2013 ◽  
Vol 61 (2) ◽  
pp. 97-102 ◽  
Author(s):  
Miloslav Janeček ◽  
Vít Květoň ◽  
Eliška Kubátová ◽  
Dominika Kobzová ◽  
Michaela Vošmerová ◽  
...  
Keyword(s):  
Czech Republic ◽  
Water Erosion ◽  
Rainfall Erosivity ◽  
The Czech Republic ◽  
Average Value ◽  
R Factor ◽  
The Usa ◽  
Time Division ◽  
R Factors

Abstract The processing of ombrographic data from 29 meteorological stations of the Czech Hydrometeorological Institute (CHMI), according to the terms of the Universal Soil Loss Equation for calculating long term loss of soil through water erosion, erosion hazard rains and their occurrence have been selected, with their relative amount and erosiveness - R-Factors determined for each month and years. By comparing the value of the time division of the R-Factor in the area of the Czech Republic and in selected areas of the USA it has been demonstrated that this division may be applied in the conditions of the Czech Republic. For the Czech Republic it is recommended to use the average value R = 40 based on the original evaluation.

scholarly journals Time variations of rainfall erosivity factor in the Czech Republic

2009 ◽  
Vol 4 (No. 4) ◽  
pp. 131-141 ◽  
Author(s):  
E. Kubátová ◽  
M. Janeček ◽  
D. Kobzová
Keyword(s):  
Czech Republic ◽  
Rainfall Erosivity ◽  
The Czech Republic ◽  
R Factor ◽  
The Usa ◽  
Time Variations ◽  
Time Division ◽  
R Factors ◽  
Meteorological Institute

The ombrographic data have been selected from 24 meteorological stations of the Czech Hydro Meteorological Institute (CHMI), according to the terms of the Universal Soil Loss Equation for calculating the long term loss of soil through water erosion, erosion hazard rains and their occurrence, with their relative amounts and erosiveness, R-factors determined for each month. By comparing the value of the time division of the R-factor in the area of the Czech Republic and in the selected areas of the USA, it has been demonstrated that this division may be applied in the conditions of the Czech Republic.

scholarly journals Differentiation and regionalization of rainfall erosivity factor values in the Czech Republic

2012 ◽  
Vol 7 (No. 1) ◽  
pp. 1-9 ◽  
Author(s):  
M. Janeček ◽  
V. Květoň ◽  
E. Kubátová ◽  
D. Kobzová
Keyword(s):  
Czech Republic ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
The Czech Republic ◽  
Average Value ◽  
R Factor ◽  
Soil Loss Equation

The rain erosivity R-factor is one of the main parameters in the Universal Soil Loss Equation (USLE). This paper describes the procedure used to update, differentiate and regionalize the rainfall erosivity R-factor. For the Czech Republic it is recommended to use the average value R = 40.

scholarly journals Revised Determination of the Rainfall-runoff Erosivity Factor R for Application of USLE in the Czech Republic

2013 ◽  
Vol 1 (No. 2) ◽  
pp. 65-71 ◽  
Author(s):  
Janeček Miloslav ◽  
Tippl Eliška Kubátová and Martin
Keyword(s):  
Czech Republic ◽  
Rainfall Intensity ◽  
Rainfall Runoff ◽  
Rainfall Events ◽  
The Czech Republic ◽  
Average Value ◽  
R Factor ◽  
Erosive Rainfall

The evaluation of a series (1961–2000) of ombrographic records from 13 selected stations of Czech Hydrometeorological Institute provided long-term annual summation values and annual peaks of the rainfallrunoff erosivity factor R in the USLE. The evaluation indicated that by defining an erosive rainfall event as (a) rainfall ≥ 12.5 mm or (b) rainfall intensity > 6 mm per 15 minutes, there were on average 8 erosive rainfall events per station, varying from 1 to 25. The long-term summation values of R factor were in the range of 42 to 106 (average 66) and annual peaks ranged from 19 to 38 (average 29). If the criteria (a) and (b) were to be fulfilled simultaneously, there were on average more than 2 erosive rainfall events per year per station, the number varying from 0 to 12. The long-term summation values of R factor ranged from 25 to 67 (average 45), with annual peaks from 17 to 36 (average 27.5). The long-term investigations of soil losses by erosion on experimental runoff plots, near Třebsín (Prague-West district), caused by storms, reveal that these losses were mostly caused by rainfall events satisfying both criteria (a) and (b) at the same time. The results of this investigation suggest that the average value of the erosivity factor R = 20 recommended for the Czech Republic until now should be increased to R = 45 and/or 66, which in practical terms would necessitate more stringent conservation measures.

scholarly journals The rainfall erosivity factor in the Czech Republic and its uncertainty

2016 ◽  
Vol 20 (10) ◽  
pp. 4307-4322 ◽  
Author(s):  
Martin Hanel ◽  
Petr Máca ◽  
Petr Bašta ◽  
Radek Vlnas ◽  
Pavel Pech
Keyword(s):  
Czech Republic ◽  
Spatial Interpolation ◽  
Rainfall Erosivity ◽  
Monthly Precipitation ◽  
The Czech Republic ◽  
Interpolation Methods ◽  
R Factor ◽  
Record Length ◽  
Spatial Coverage ◽  
Spatial Interpolation Methods

Abstract. In the present paper, the rainfall erosivity factor (R factor) for the area of the Czech Republic is assessed. Based on 10 min data for 96 stations and corresponding R factor estimates, a number of spatial interpolation methods are applied and cross-validated. These methods include inverse distance weighting, standard, ordinary, and regression kriging with parameters estimated by the method of moments and restricted maximum likelihood, and a generalized least-squares (GLS) model. For the regression-based methods, various statistics of monthly precipitation as well as geographical indices are considered as covariates. In addition to the uncertainty originating from spatial interpolation, the uncertainty due to estimation of the rainfall kinetic energy (needed for calculation of the R factor) as well as the effect of record length and spatial coverage are also addressed. Finally, the contribution of each source of uncertainty is quantified. The average R factor for the area of the Czech Republic is 640 MJ ha−1 mm h−1, with values for the individual stations ranging between 320 and 1520 MJ ha−1 mm h−1. Among various spatial interpolation methods, the GLS model relating the R factor to the altitude, longitude, mean precipitation, and mean fraction of precipitation above the 95th percentile of monthly precipitation performed best. Application of the GLS model also reduced the uncertainty due to the record length, which is substantial when the R factor is estimated for individual sites. Our results revealed that reasonable estimates of the R factor can be obtained even from relatively short records (15–20 years), provided sufficient spatial coverage and covariates are available.

scholarly journals Evaluation of discrepancies in spatial distribution of rainfall erosivity in the Czech Republic caused by different approaches using GIS and geostatistical tools

2017 ◽  
Vol 12 (No. 2) ◽  
pp. 117-127 ◽  
Author(s):  
J. Brychta ◽  
M. Janeček
Keyword(s):  
Spatial Distribution ◽  
Czech Republic ◽  
Temporal Resolution ◽  
Agricultural Land ◽  
Interpolation Method ◽  
Rainfall Data ◽  
Rainfall Erosivity ◽  
Yearly Variation ◽  
The Czech Republic ◽  
R Factor

The study presents all approaches of rainfall erosivity factor (R) computation and estimation used in the Czech Republic (CR). A lot of distortions stem from the difference in erosive rainfall criteria, time period, tipping rain gauges errors, low temporal resolution of rainfall data, the type of interpolation method, and inappropriate covariates. Differences in resulting R values and their spatial distribution caused by the described approaches were analyzed using the geostatistical method of Empirical Bayesian Kriging and the tools of the geographic information system (GIS). Similarity with the highest temporal resolution approach using 1-min rainfall data was analyzed. Different types of covariates were tested for incorporation to the cokriging method. Only longitude exhibits high correlation with R and can be recommended for the CR conditions. By incorporating covariates such as elevation, with no or weak correlation with R, the results can be distorted even by 81%. Because of significant yearly variation of R factor values and not clearly confirmed methodology of R values calculation and their estimation at unmeasured places we recommend the R factor for agricultural land in the Czech Republic R = 40 MJ/ha·cm/h +/– 10% depends on geographic location.

scholarly journals Rainfall erosivity factor in the Czech Republic and its Uncertainty

2016 ◽  
Author(s):  
Martin Hanel ◽  
Petr Máca ◽  
Petr Bašta ◽  
Radek Vlnas ◽  
Pavel Pech
Keyword(s):  
Czech Republic ◽  
Spatial Interpolation ◽  
Rainfall Erosivity ◽  
Monthly Precipitation ◽  
The Czech Republic ◽  
Interpolation Methods ◽  
R Factor ◽  
Record Length ◽  
Spatial Coverage ◽  
Spatial Interpolation Methods

Abstract. In the present paper, the rainfall erosivity factor (R-factor) for the area of the Czech Republic is assessed. Based on 10-minute data for 96 stations and corresponding R-factor estimates, a number of spatial interpolation methods are applied and cross-validated. These methods include inverse distance weighting, standard, ordinary and regression kriging with parameters estimated by the method of moments and restricted maximum likelihood and a generalized least-squares (GLS) model. For the regression-based methods, various statistics of monthly precipitation as well as geographical indices are considered as covariates. In addition to the uncertainty originating from spatial interpolation, also the uncertainty due to estimation of the rainfall kinetic energy (needed for calculation of the R-factor) as well as the effect of record length and spatial coverage are addressed. Finally, the contribution of each source of uncertainty is quantified. The average R-factor for the area of the Czech Republic is 64 MJ ha−1 cm h−1, with values for the individual stations ranging between 32 and 152 MJ ha−1 cm h−1. Among various spatial interpolation methods, the GLS model relating R-factor to the mean altitude, longitude, mean precipitation and mean excess above the 95th percentile of monthly precipitation performed best. Application of the GLS model also reduced the uncertainty due to the record length, which is substantial when the R-factor is estimated for individual sites. Our results revealed that reasonable estimates of the R-factor can be obtained even from relativelly short records (15–20 years), provided sufficient spatial coverage and covariates are available.

A cross-cultural comparison of dietary intakes and physical activity between American and Czech school-aged children

2009 ◽  
Vol 12 (7) ◽  
pp. 986-990 ◽  
Author(s):  
Lenka Humenikova Shriver ◽  
Gail Gates
Keyword(s):  
Physical Activity ◽  
Czech Republic ◽  
Public Schools ◽  
Pilot Study ◽  
Fast Food ◽  
Dietary Intakes ◽  
Cross Sectional ◽  
The Czech Republic ◽  
The Usa ◽  
American Children

AbstractObjectiveThe prevalence of child overweight in the Czech Republic is substantially lower than that in the USA. The objective of the present pilot study was to explore dietary intakes, frequency of dining in fast-food establishments, and the amount and intensity of physical activity between a sample of American and Czech children.DesignA cross-sectional correlational pilot study.SettingFour public schools in the USA and four public schools in the Czech Republic.SubjectsNinety-five Czech and forty-four American 4–6th graders from urban public schools participated in the study. Dietary intake and number of fast-food visits were evaluated using two multiple-pass 24 h recalls. Physical activity was measured using the modified Self-Administered Physical Activity Checklist.ResultsAmerican children (mean age 10·8 (se 0·2) years) consumed more energy and fat, less fruits and vegetables, more soft drinks, and visited fast-food establishments more often than Czech children (mean age 11·0 (se 0·1) years). Although no differences were found in vigorous activity by nationality, Czech children spent significantly more time in moderate physical activities than American children.ConclusionsDespite the influx of some negative Western dietary trends into the country, Czech children had a healthier diet and were more physically active than American children. Further research is warranted to determine whether the same differences in dietary intakes, physical activity and fast-food visits exist between nationally representative samples of American and Czech children.

New Arch Footbridges

2021 ◽  
Author(s):  
Jiří Stráský ◽  
Tomas Romportl ◽  
Pavel Kaláb ◽  
Leonard Šopík
Keyword(s):  
Czech Republic ◽  
Dynamic Analysis ◽  
Dynamic Behaviour ◽  
Human Dimensions ◽  
Span Length ◽  
Structural Members ◽  
The Czech Republic ◽  
The Usa ◽  
Structural Solution

<p>Four arch pedestrian and cyclist bridges built in the USA, Slovakia and in the Czech Republic are described in terms of their architectural and structural solution, static and dynamic behaviour, and technology of their construction. The bridges with span length up to 104 m have slender decks which are suspended on arches of a butterfly arrangement. The dynamic analysis proved that all structures are comfortable to users. The footbridges are structurally efficient, they are light and transparent, correspond to the scale of the landscape and all structural members have human dimensions.</p>

Long-term changes in body weight, BMI, and adiposity rebound among children and adolescents in the Czech republic

2007 ◽  
Vol 5 (3) ◽  
pp. 409-425 ◽  
Author(s):  
J. Vignerová ◽  
L. Humeníkova ◽  
M. Brabec ◽  
J. Riedlová ◽  
P. Bláha
Keyword(s):  
Body Weight ◽  
Czech Republic ◽  
Children And Adolescents ◽  
The Czech Republic ◽  
Adiposity Rebound ◽  
Long Term Changes

The Czech Republic: No Promised Land for Carers and Persons Dependent on Long-Term Care

2018 ◽  
pp. 57-92
Author(s):  
Kristina Koldinská ◽  
Martin Štefko
Keyword(s):  
Czech Republic ◽  
Long Term Care ◽  
Term Care ◽  
The Czech Republic ◽  
Promised Land
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