Field observations and consecutive modelling of soil erosion events proved to be essential for understanding and predicting erosion and sediment transport. An experimental approach often utilizes a large variety of rainfall simulators. In this technical note a complex methodology is introduced, using a mobile rainfall simulator developed at the Czech Technical University in Prague. An experimental setup with two watered plots (16 + 1 m2) was established, which enables simultaneous measurements in two scales and monitoring of surface runoff, flow velocity, infiltration, sediment subsurface flow, vegetation cover effect suspended solids and phosphorus transport, surface roughness and surface evolution under rainfall and other variables. The simulator is built on a trailer transportable by car with folding arm carrying four FullJet WSQ nozzles operating independently. The configuration and water pressure 0.7 bar leads to the total watered area 2.4 x 9.6 m. Average drop size (d50) reaches 1.75 mm for 0.7 bar pressure. Christiansen uniformity index CU reaches 85%. A selection of experimental results highlights both the advantages and the weaknesses of the presented experimental setup.

The Czech landscape has undergone various changes over the last 100 years and has been mainly adapted agriculturally for economic purposes. This has resulted, among other things, in reservoirs being clogged with sediment. The Vrchlice Reservoir was built in 1970 to supply drinking water for around 50,000 inhabitants, and increased sedimentation has been detected in the reservoir in recent years. Water erosion and sediment transport were modeled with WaTEM/SEDEM. Sediment volumes were measured in eight ponds across the watershed for calibration purposes. Modeled results from ponds in watersheds covered mostly with arable lands generally corresponded with the measured values. Although in forested watersheds, the measured sediment volumes greatly exceeded modeled sediment yields, indicating high uncertainty in using USLE-based models in non-agricultural watersheds. The modeled scenarios represented pre-Communist, Communist, and post-Communist eras. For these periods WaTEM/SEDEM was used to evaluate three isolated effects: the effects of various crops on arable lands, the effects of farmland fragmentation, and finally the effects of changes in land use. The change in crops proved to be an important factor causing high siltation rate (potential 23% reduction in sediment yield for historical periods), and land fragmentation played the second important role (potential 15% reduction in sediment yield can be reached by land fragmentation). Across all scenarios, the lowest sediment yield and reservoirs siltation rates were obtained from the pre-Communist and Communist crop share under current land use conditions, and current land use with farmland fragmentation implemented, as it was re-constructed for the pre-Communist era. This supports the idea that the introduction of green areas within arable lands are beneficial to the landscape and can help reduce soil erosion and reservoir siltation.

Non-point sources of water pollution caused by agricultural crop production are a serious problem in Czechia, at present. This paper describes a new approach for the mutual delineation and assessment of different pollution sources where the critical points method is used to identify the origin of contamination and the source areas. The critical points, i.e., sites presenting the entry of quick surface and drainage runoff into waters, are classified into three (for surface pollution sources using a WaTEM/SEDEM model) or four (subsurface = drainage sources via the catchment-measures need index) categories, respectively. This enabled us to prioritize the most endangered areas at different scales, ranging from the third-order catchments to very small subcatchments, and to design the appropriate combination of control measures to mitigate surface and drainage water runoff, with these being the main drivers of associated pollution. This methodology was applied to a study conducted in the Czech Republic within the entire Vltava River basin, with a total area of 27,578 km², and utilized in depth to assess a 543 km² catchment of the Vlašimská Blanice River. When the effect of the designed surface runoff control measures system had been assessed for sediment transport through outlet profiles of the fourth-order catchments, the average reduction reached 43%. The total reduction in the subsurface transport of nitrogen within the fourth-order catchments was 24%. The approach and results are planned to be projected into river basin management plans for the Vltava River basin. Nevertheless, a thorough reassessment of current legislations and strategies is needed to enable the broader adoption of mitigation measures and sustainable management patterns within agricultural landscapes.

Accelerated soil erosion by water has many offsite impacts on the municipal infrastructure. This paper discusses how to easily detect potential risk points around municipalities by simple spatial analysis using GIS. In the Czech Republic, the WaTEM/SEDEM model is verified and used in large scale studies to assess sediment transports. Instead of computing actual sediment transports in river systems, WaTEM/SEDEM has been innovatively used in high spatial detail to define indices of sediment flux from small contributing areas. Such an approach has allowed for the modeling of sediment fluxes in contributing areas with above 127,484 risk points, covering the entire Czech Republic territory. Risk points are defined as outlets of contributing areas larger than 1 ha, wherein the surface runoff goes into residential areas or vulnerable bodies of water. Sediment flux indices were calibrated by conducting terrain surveys in 4 large watersheds and splitting the risk points into 5 groups defined by the intensity of sediment transport threat. The best sediment flux index resulted from the correlation between the modeled total sediment input in a 100 m buffer zone of the risk point and the field survey data (R² from 0.57 to 0.91 for the calibration watersheds). Correlation analysis and principal component analysis (PCA) of the modeled indices and their relation to 11 lumped characteristics of the contributing areas were computed (average K-factor; average R-factor; average slope; area of arable land; area of forest; area of grassland; total watershed area; average planar curvature; average profile curvature; specific width; stream power index). The comparison showed that for risk definition the most important is a combination of morphometric characteristics (specific width and stream power index), followed by watershed area, proportion of grassland, soil erodibility, and rain erosivity (described by PC2).