The main aim of the study was to find out whether cultural tourism could be a driver of rural development in the selected area and in general. In case yes, to what extent and under what conditions. Three districts in the South-Moravian Region, Znojmo, Břeclav, and Hodonín, situated in the rural borderland with Austria and Slovakia represented the study area. Both geographical and sociological methods were used to gather evidence for cultural tourism in that study. Firstly, attractiveness analysis of the area defined for cultural tourism took place. Next, factors influencing the potential for cultural tourism affecting rural development in South Moravia were evaluated. Finally, synergistic relations were discussed. In the territory, many forms of tourism intersect. Based on the results, it can be stated that cultural tourism can hardly be the main driver of rural development after the decline of agriculture because the region’s economy has branched out in several directions. However, it can be an important complementary activity that yields both economic and non-economic benefits.

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.

No abstract

The effect of the morphology is key aspect of erosion modelling. In Universal Soil Loss Equation (USLE) type methods, this effect is expressed by the topographic factor (LS). The LS calculation in GIS is performed by a unit contributing area (UCA) method and can mainly be influenced by the pixel resolution, by the flow direction algorithm and by the inclusion of a hydrologically closed unit (HCU) principle, the cutoff slope angle (CSA) principle and the ephemeral gullies extraction (EG) principle. This research presents a new LS-RUSLE tool created with the inclusion of these principles in the automatic user-friendly GIS tool. The HCU principle using a specific surface runoff interruption algorithm, based on pixels with NoData values at the interruption points (pixels), appears to be key. With this procedure, the occurrence of overestimation results by flow conversion was rapidly reduced. Additionally, the reduction of extreme L and LS values calculated in the GIS environment was reached by the application of the CSA and EG principles. The results of the LS-RUSLE model show the prospective use of this tool in practice.

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 (I₁₅ or I₃₀) or not. We proved that if parameters I₁₅> 6.25 mm/15 min AND H > 12.5 mm were fulfilled, then 84.2% of rainfalls caused soil loss > 0.5 t/ha and 73.7% ≥ 1 t/ha. In the case of precondition OR only 44.6% of rainfalls caused soil loss > 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.