This study proposes a new workflow for crop growth evaluation and yield calibration in the Soil and Water Assessment Tool Plus (SWAT+) model and evaluates its impact on simulated hydrological and biogeochemical processes. The workflow was applied for ten small agricultural catchments in Europe. A detailed demonstration is provided for the German catchment, Schwarzer Schops. The workflow proved effective across all catchments, improving yield calibration from an initial R2 of 0.5-0.84. The results show that evapotranspiration and soil moisture were only moderately affected by crop calibration in three catchments (Belgium, Czech Republic and Norway) and negligibly changed in the remaining ones. Sediment and nutrient balance were affected more strongly: sediment, nitrogen and phosphorus loss change reached 82 % (Norway), 16 % and 20 % (Czech Republic), respectively. The proposed workflow is a valuable tool for improving the accuracy of SWAT + simulations and can be used to support decision-making in environmental management.
Maize biomass production and quality are influenced by numerous factors, including fertilization, soil characteristics, and climatic conditions. The aim of our study was to evaluate how different fertilization treatments ((1) Control, (2) farmyard manure (FYM), (3) FYM with added mineral nitrogen (FYM + N), and (4) FYM with added NPK mineral fertilizers (FYM + NPK)) affect the biomass yield and quality parameters (crude protein (CP), fiber content (FC), neutral detergent fiber (NDF), starch content (STR), organic matter digestibility (OMD), and neutral detergent fiber digestibility (DNDF)) of silage maize under various soil and climatic conditions in the Czech Republic (Caslav—degraded Chernozem, Ivanovice na Hané–Chernozem, Lukavec–Cambisol). The experiment was conducted from 2020 to 2023. Additionally, the study analyzed the effects of fertilization on soil chemical properties (pH, P, K, Ca, Mg, C, N). The highest average biomass yields were recorded in Ivanovice (23.8 t ha−1, A), followed by Lukavec (19.7 t ha−1, B) and Caslav (18.1 t ha−1, B). Comparing fertilizer treatments, no significant differences were observed among FYM, FYM + N, and FYM + NPK; however, all three treatments significantly outperformed the Control at all sites. Conversely, fertilization did not affect the quality parameters. For silage maize, FYM represents the optimal fertilization strategy, providing yields and quality comparable to the combined application of mineral N, P, and K, which are more costly (in terms of purchase and application) and, under certain conditions, may negatively impact the environment. Nevertheless, the application of mineral fertilizers increased soil nutrient content, thereby improving conditions for subsequent crops.
On 2nd June 2010, heavy rainfall triggered a significant debris flow on the southern slope of Leme & scaron;n & aacute; Mountain in the Javorn & iacute;ky Range (Outer Western Carpathians), Czech Republic. Multidisciplinary research was carried out there, including geomorphological survey, electrical resistivity tomography, laser scanning, soil and rainfall analysis. The debris flow occurred after the prolonged convective and intense rainfall. The antecedent precipitation index calculated for the previous 30 days reached 134.1 mm and the daily rainfall 37.4 mm, 13 times higher than the long-term average daily rainfall. The debris flow occurred in unconsolidated flysch sediments and caused minor damages. The locality was affected by slope movements in the past, as evidenced by two debris flow deposit cones in the valley. Electrical resistivity tomography revealed a sliding surface at a depth of 5 m and another at 15-20 m. However, according to local residents and the forest manager, no mass movement has been recorded in there in the last 40 years. Human intervention, particularly artificial drainage and deforestation, could also have contributed to the debris-flow triggering. The aim of this work was a complex analysis of the triggering conditions of the debris flow and a risk assessment of new events in this area.
The acceleration of soil erosion in undulating landscapes due to human activities has led to a larger area of land being affected by intensive soil redistribution. Colluvisols, sedimentary soils formed on concave slope positions, are considered to be important indicators of soil-landscape processes and soil organic carbon pools. In this study, we investigated the effectiveness of hyperspectral imaging in visible and near-infrared range to assess the detailed variability (both vertical and within each colluvial layer and in-situ soil horizon) of soil organic carbon (SOC) and CaCO3 concentrations in three deep Colluvisols developed on loess and located at different slope positions in southeast Czechia, and evaluate whether this in-detail mapped microvariability can be used as a proxy to assess the dynamics and history of colluvial sedimentation. A variety of nonlinear machine learning techniques such as cubist regression tree (Cubist), random forest (RF), support vector machine regression (SVMR) and one linear technique partial least square regression (PLSR) were compared to determine the most suitable model for the prediction of SOC and CaCO3 content in each profile. The results showed that RF provided the best performance for both SOC (R2 = 0.75) and CaCO3 (R2 = 0.76) contents. The maps depict significant differences in the vertical variability of the predicted properties in the profiles depending on the different intensity, form and period of sedimentation resulting from the slope position. The within-horizon/layer variability of SOC proves to be a suitable indicator of the character of deposition. High variability has been shown mainly in the medieval layers, where it reflects high-energy material redeposition, while low variability in the oldest and youngest parts of the profiles is probably associated with the type of deposited material and frequent pedoturbation, respectively. The within-horizon/layer variability of CaCO3, on the other hand, is independent of the dynamics of deposition. The study showed that imaging spectroscopy is a suitable tool to capture the detailed pattern of the colluvial matrix and, with appropriate sampling and processing, is applicable even in very deep soil profiles.
