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 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 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 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.

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.

A Rainfall Erosivity database for Brazil from MSWEP rainfall dataset

2021 ◽  
Author(s):  
Ingrid Petry ◽  
Fernando Mainardi Fan
Keyword(s):  
Temporal Resolution ◽  
Soil Loss ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Regression Equations ◽  
R Factor ◽  
Thiessen Polygons ◽  
Erosivity Index ◽  
Factor Map

<p>In erosion studies the behavior of rainfall is primordial, since rain is responsible for the first stage of the erosion process: the detachment of soil particles. The erosive potential of rainfall, erosivity, is considered in the universal soil loss equations (R)USLE family through the parameter R, or R factor. This factor is calculated from the rainfall erosivity index, which is the product of kinetic energy of the rain by the maximum intensity of the rain of 30 minutes of duration. As sub-hour rainfall data is not always available, there are in the literature a series of equations obtained from regression, which use monthly and annual rainfall and present a good estimate of erosivity for your study site. In Brazil, in addition to limitations regarding the temporal resolution of rainfall data, there are also spatial limitations. Monitoring stations are concentrated mostly in urbanized areas, usually near the coast. The other regions, such as agricultural and forest areas, are poorly monitored, and these areas are of great interest for monitoring erosion, not only because they are periodically exposed soil areas, but also because of the high rainfall rates that humid forests like Amazon have. MSWEP is a rainfall database that combines observed, satellite and reanalysis data. It has global coverage, temporal resolution of 3 hours, spatial 0.1º and data from 1979 to 2016. Databases like this have great potential to be used in areas such as Brazil, due to its spatial and temporal resolution. In this context, considering the relevance that the soil loss equations still present today, this work developed a rainfall erosivity database entitled REDB-BR (Rainfall Erosivity Database for Brazil). It provides the R factor in a 0.1º resolution grid, developed with 37 years of rainfall data from the MSWEP dataset. The R factor was calculated trough 73 erosivity index regression equations, which mostly uses the Modified Fournier Index (MFI), a relation between monthly precipitation and annual precipitation. Thiessen polygons were used in order to spatialize and define the areas of each equation. Over the Brazilian territory, the R factor ranges from 1.200 to 20.000 MJ mm ha-1 h-1 year-1, with the higher values in the North region, and the lowest values in the Northeast. The spatial patterns of erosivity are very similar to the climatic zones of Brazil. The R factor map takes advantage of MSWEP dataset and presents a spatial resolution very detailed to a country with continental scale such as Brazil. The database includes the equations shapefile and table, Thiessen Polygons shapefile and the R factor map in raster format, which allows more possibilities of application. The database can be accessed at <https://zenodo.org/record/4428308#.X_hxsOhKiUk>. We identified sudden changes in behavior between the delimited areas, which suggests a need for more regression equations in order to better represent the behavior of the erosivity in the Brazilian territory.</p>

scholarly journals Determination of erosion rainfall criteria based on natural rainfall measurement and its impact on spatial distribution of rainfall erosivity in the Czech Republic

2019 ◽  
Vol 14 (No. 3) ◽  
pp. 153-162 ◽  
Author(s):  
Jiří Brychta ◽  
Miloslav Janeček
Keyword(s):  
Spatial Distribution ◽  
Temporal Resolution ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Control Measures ◽  
Rainfall Erosivity ◽  
Time Step ◽  
R Factor ◽  
Soil Losses ◽  
Runoff Plots

Rainfall erosivity is the main factor of the USLE or RUSLE equations. Its accuracy depends on recording precision and its temporal resolution, number of stations and their spatial distribution, length of recorded period, recorded period, erosion rainfall criteria, time step of rainfall intensity and interpolation method. This research focuses on erosion rainfall criteria. A network of 32 ombrographic stations, 1-min temporal resolution rainfall data, 35.6-year period and experimental runoff plots were used. We analysed 8951 rainfalls from ombrographic stations, 100 rainfalls and caused soil losses and runoffs from experimental runoff plots. Main parameter which influenced the number of erosion rainfalls was the precondition AND/OR which determines if conditions of rainfall total (H) have to be fulfilled simultaneously with rainfall intensity (I<sub>15</sub> or I<sub>30</sub>) or not. We proved that if parameters I<sub>15 </sub>&gt; 6.25 mm/15 min AND H &gt; 12.5 mm were fulfilled, then 84.2% of rainfalls caused soil loss &gt; 0.5 t/ha and 73.7% ≥ 1 t/ha. In the case of precondition OR only 44.6% of rainfalls caused soil loss &gt; 0.5 t/ha and 33.9% ≥ 1 t/ha. If the precondition AND was fulfilled, there were on average 75.5 rainfalls, average R factor for each rainfall was 21 MJ/ha·cm/h (without units below in the text, according international unit: 210 MJ/ha·mm/h) and average annual R factor was 45.4. In the case of precondition OR there were on average 279 rainfalls but average R factor for each rainfall was only 9.1 and average annual R factor was 67.4. Therefore if the precondition OR is used, R factor values are overestimated due to a high number of rainfalls with no or very low erosive potential. The resulting overestimated soil losses calculated using USLE/RUSLE subsequently cause an overestimation of financial expenses for erosion-control measures.  

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 The development of regional differentiation of office construction in the Czech Republic: 1990–2010

2015 ◽  
Vol 23 (1) ◽  
pp. 21-33
Author(s):  
Pavel Domalewski ◽  
Jan Baxa
Keyword(s):  
Spatial Distribution ◽  
Czech Republic ◽  
Questionnaire Survey ◽  
Large Scale ◽  
Capital City ◽  
Office Building ◽  
Regional Differentiation ◽  
Key Factors ◽  
The Czech Republic ◽  
Dominant Position

Abstract The factors that were crucial for the construction of administrative buildings in the regional capitals of the Czech Republic are subject to examination in this article. One primary question is whether the development of office construction reflects the qualitative importance of the cities, or whether there are some other regularities in the spatial distribution of construction. To identify the key factors, controlled interviews with experts professionally involved in the construction of administrative buildings were carried out, and these data were then extended as part of a large-scale questionnaire survey with other experts on the issue. The results have confirmed the dominant position of the capital city of Prague in terms of its qualitative importance, as the remaining regional capitals have less than one-tenth of the volume of modern office building areas. The greatest differences in the construction of administrative buildings have been noted in Brno and Ostrava, despite the fact that they exhibit similar characteristics when considered in the light of respondent-determined factors.

Visible marking of wader nests to avoid damage by farmers does not increase nest predation

2017 ◽  
Vol 28 (2) ◽  
pp. 293-301 ◽  
Author(s):  
VÁCLAV ZÁMEČNÍK ◽  
VOJTĚCH KUBELKA ◽  
MIROSLAV ŠÁLEK
Keyword(s):  
Czech Republic ◽  
Nest Predation ◽  
Agricultural Land ◽  
Positive Experience ◽  
The Czech Republic ◽  
Trade Off ◽  
Nest Protection ◽  
Vanellus Vanellus ◽  
The Impact ◽  
Ground Nesting

SummaryOnly a few studies have assessed the predation risk on artificially marked nests, or have examined ways of marking nests to avoid destruction by machinery. Until now, however, neither type of study has directly addressed this apparent trade-off experimentally. The impact of marking the nests of Northern Lapwing Vanellus vanellus with thin 2 m-long conspicuous bamboo poles with the top end highlighted with reflective red or orange spray has been tested for three years in two breeding areas of waders in the Czech Republic. A total of 52 pairs of nests on agricultural land, with each pair consisting of one marked nest and one unmarked reference counterpart nest, were monitored for 2004 nest-days until hatching, agricultural operations or failure. The results proved that marking itself does not result in increased nest predation. The nests found in the early incubation stage were under higher threat of depredation, irrespective of the presence of marking. Our results show that it is possible to find a finely-tuned trade-off in nest marking of ground-nesting birds between risk of damage by agricultural machinery and risk of increased nest predation. Our positive experience with Northern Lapwing, and episodically with three other wader species in the Czech Republic, suggests that this direct nest protection could be used effectively for a wider variety of ground-nesting birds.

Pre-industrial landscape of the Jeseníky region as a natural and cultural heritage

2020 ◽  
Author(s):  
Jaromír Kolejka ◽  
Eva Nováková
Keyword(s):  
Czech Republic ◽  
Industrial Revolution ◽  
Agricultural Land ◽  
Local Administration ◽  
Economic Pressure ◽  
Forest Land ◽  
The Czech Republic ◽  
Industrial Landscape ◽  
The Subject ◽  
State Protection

Small parcels of agricultural land are rare in the present landscape of Czech Republic and become the subject of interests of the state protection of the nature, the landscape and the environment. At the same time, such areas represent interesting subjects for the local administration as attractive tourist object. In the historical territory of Moravia (the eastern 1/3 of the Czech Republic), a regional inventory of areas with preserved ancient land use structure was carried out on all individual cadastral territories (focused not only on small parcels, but also on large aristocratic estates on agricultural and forest land originated before the main wave of industrial revolution Moravia, before 1850. The sites are still subjects to topic economic pressure on land consolidation. Their existence in the future is under threat and is decreasing every year both in number and size. The inventory results are presented on example of the Jeseníky region.

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