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

Janeček, M.; Květoň, Vít; Kubátová, E.; Kobzova, Dominika

doi:10.17221/2/2011-swr

Cited by 13 publications

(20 citation statements)

References 2 publications

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“…The following linear function based on low temporal resolution data was newly derived for the R map creation: R = 0.065P S + 18.025 (7) This map exhibits 70% similarity with the methodology of Janeček et al (2012bJaneček et al ( , 2013 for a tolerance limit of 5 MJ/ha·cm/h (Figure 3) and 21% for 1 MJ/ ha·cm/h. Goovarts (2000) found high correlation with elevation data for the Portugal conditions with r 2 = 0.75.…”

Section: Resultsmentioning

confidence: 99%

“…Best fitting gave the K-Bessel function. These results were compared with the R map according to Janeček et al (2012bJaneček et al ( , 2013 based on the highest temporal resolution (1-min) rainfall data for the same time period interpolated using the EBK method ( Figure 5). The R according to Janeček et al (2012bJaneček et al ( , 2013 was calculated using equations (4), (5), (6):…”

Section: Methodsmentioning

confidence: 99%

“…That is why the mentioned criteria set by Wischmeier and Smith (1978) do not correspond to R = 0 but approximately R = 4. Janeček et al (2012bJaneček et al ( , 2013 created the R map using 31 OS for the period 1971-2000 and precondition AND (Figure 1d). According to this map average R = 40 was recommended for agricultural areas (without mountainous border areas).…”

mentioning

confidence: 99%

“…Among erosive rainfall criteria, preconditions (OR/AND) and R calculation approach is the Figure 1. Overview of all rainfall erosivity factor (R) maps created for the Czech Republic (a) Janeček et al (1992) (b) Krása (2004) (c) Dostál et al (2006) (d) Janeček et al (2012bJaneček et al ( , 2013 (e) Hanel (2013) in Krása et al (2014) (f ) Rožnovský et al (2013) in Krása et al (2014) (g) Panagos et al (2015) (a)…”

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confidence: 99%

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

Brychta¹,

Janeček²

2017

Soil & Water Res.

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Brychta J., Janeček M. (2017): Evaluation of discrepancies in spatial distribution of rainfall erosivity in the Czech Republic caused by different approaches using GIS and geostatistical tools. Soil & Water Res., 12: 117−127.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.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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

Brychta¹,

Janeček²

2017

Soil & Water Res.

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“…This does not correspond to the temporal distribution of storm events that is assumed by soil erosion prediction methods (USLEWischmeier, 1976), modified for conditions in the Czech Republic (Janeček et al, 2012), where the most frequent occurrence of storm events is expected in June-July. During the period of May-July are the soil properties most susceptible to surface runoff, because the bulk density is high and the topsoil porosity is low (Fig.…”

Section: Resultsmentioning

confidence: 91%

Identification of prevailing storm runoff generation mechanisms in an intensively cultivated catchment

Zumr

Dostál

Devátý

2015

Journal of Hydrology and Hydromechanics

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Abstract:The fact that flash floods initiated in arable catchments are often accompanied by massive sediment and nutrient loads often leads to the assumption that surface runoff is the principle pathway by which runoff reaches watercourses. On the basis of an evaluation of several rainfall-runoff events in a representative agricultural catchment, we show that runoff from cultivated land may be generated in a way similar to that seen on forested slopes, where shallow subsurface runoff is the predominant pathway by which runoff makes its way to watercourses in most runoff events. To identify the predominant runoff pathway, we employed a combination of turbidity measurements and stream discharge data. Suspended sediment flux, a newly introduced index representing the ratio between precipitation duration and total sediment yield, and direction of the discharge-turbidity hysteresis loops were proposed as reflective indicators of the frequency of runoff via different pathways.In our study, most of the events initiated by rainstorms of various intensities and durations resulted in rapid increases in stream discharge. Although we observed temporal variability of topsoil properties attributable to seasonal weather changes and agricultural activities, e.g. bulk density and porosity, runoff generation was mainly driven by precipitation characteristics and the initial catchment saturation.

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Spatial variability and interdependence of rain event characteristics in the Czech Republic

Hanel

Máca

2013

Hydrol. Process.

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Rain event characteristics are assessed in a 10‐year (1991–2000) record for 122 stations in the Czech Republic. Individual rain events are identified using the minimum interevent time (mit) concept. For each station, the optimal mit value is estimated by examining the distribution of interevent times. In addition, various mit values are considered to account for the effect of mit on rain event characteristics and their interrelationships. The interdependence between rain event characteristics and altitude, average rainfall depth, and geographic location are explored using simple linear models. Most rain event characteristics can be to some extent explained by average total rainfall or altitude, although models including the former significantly outperformed models using the latter. Significant correlation was found among several pairs of monthly mean characteristics often including event rain rate (with event duration, depth, maximum intensity, and fraction of intraevent rainless periods). Moreover, strong correlation was revealed between number of events, interevent time, event depth, and duration. In general, correlation decreases in absolute value with mit. Strong spatial correlation was found for the mean monthly interevent time and number of events. Spatial correlation was considerably smaller for other characteristics. In general, spatial dependence was smaller for larger mit values. Copyright © 2013 John Wiley & Sons, Ltd.

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

Cited by 13 publications

References 2 publications

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

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

Identification of prevailing storm runoff generation mechanisms in an intensively cultivated catchment

Spatial variability and interdependence of rain event characteristics in the Czech Republic

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