An application of different mulch materials may lead to changes in soil properties. Our previous study, focused on the impact of various mulches during the 4-year period, showed that the change in some properties can be very rapid (e.g., soil pH), but in other cases such as hydraulic properties, the changes can be gradual. To find out, whether the extension of the mulching period will further affect the studied soil properties, the experiment continued for another 2 years. Differences between values of organic carbon content (Cox), soil physical quality (Sinf), gravitational water (GW) and readily available water (RAW) of soils not covered by any mulch and under various mulches (bark chips; wood chips; wheat straw; Agrotex EKO+ decomposable matting; polypropylene fabric covered bark chips; crushed stone) were much larger than those observed in our previous study. On the other hand, the opposite trend was observed for the water stable aggregates (WSA) index or soil pH. Differences between additionally measured hydraulic conductivities at the pressure head of −2 cm and repellency index (RI) were mostly insignificant. Results indicated that organic mulches can either positively (e.g., increase WSA index and Cox, and decrease GW) or negatively (e.g., decrease Sinf and RAW, and increase RI) affect soil properties.
Knowledge of the distribution of plant roots in a soil profile (i.e. root density) is needed when simulating root water uptake from soil. Therefore, this study focused on evaluating barley and wheat root densities in a sand-vermiculite substrate. Barley and wheat were planted in a flat laboratory box under greenhouse conditions. The box was always divided into two parts, where a single plant row and rows cross section (respectively) was simulated. Roots were excavated at the end of the experiment and root densities were assessed using root zone image processing and by weighing. For this purpose, the entire area (width of 40 and height of 50 cm) of each scenario was divided into 80 segments (area of 5x5 cm). Root density in each segment was expressed as a root percentage of the entire root cluster. Vertical root distributions (i.e. root density with respect to depth) were also calculated as a sum of root densities in each 5 cm layer. Resulting vertical root densities, measured evaporation from the water table (used as the potential root water uptake), and the Feddes stress response function model were used for simulating substrate water regime and actual root water uptake for all scenarios using HYDRUS-1D. All scenarios were also simulated using HYDRUS-2D. One scenario (areal root density of barley sown in a single row, obtained using image analysis) is presented in this paper (because most scenarios showed root water uptakes similar to results of 1D scenarios). The application of two root detecting techniques resulted in noticeably different root density distributions. Differences were mainly attributed to the fact that fine roots of high density (located mostly at the deeper part of the box) had lower weights in comparison to the weight of few large roots (at the box top). Thus, at the deeper part, higher root density (with respect to the entire root zone) was obtained using the image analysis in comparison to that from the gravimetric analysis. Conversely, lower root density was obtained using the image analysis at the upper part in comparison to that from the gravimetric analysis. On the other hand, fine roots overlapped each other and therefore were not visible in the image, which resulted in lower root density values from image analysis. Root water uptakes simulated with HYDRUS-1D using diverse root densities obtained for each cereal declined differently from the potential root water uptake values depending on water scarcity at depths of higher root density. and Usually, an earlier downtrend associated with gradual root water uptake decreases and vice versa. Similar root water uptakes were simulated for the presented scenario using the HYDRUS1D and HYDRUS-2D models. The impact of the horizontal root density distribution on root water uptake was, in this case, less important than the impact of the vertical root distribution resulting from different techniques and sowing scenarios.
The aim of this study was to assess the impact of different vegetation on the distribution of rainfall (due to throughfall and stemflow), water regime, and Al and SO4 2- leaching from forest soils. The water flow and Al and SO4 2- transport were modeled using HYDRUS-1D. The study was performed at two elevation transects on the Paličník and Smědava Mountain in Jizera mountains. Podzols and Cambisols were prevailing soil units in this area. It was shown that the effect of the precipitation redistribution on water regime was considerable in the beech forest, while it was almost negligible in the spruce forest. Redistribution of precipitation under trees caused runoff (in one case), increased water discharge through the soil profile bottom, reduction of water storage in the soil, and thus reduction of root water uptake. Simulated Al leaching from the soil profile was determined mainly by the initial Al content in the soil profile bottom. Leaching of SO4 2- was mainly determined by its initial content in the soil and to a lesser extent by redistributed precipitation and SO4 2- deposition.
The goal of this study was to evaluate the effect of products from a municipal wastewater treatment plant on the H2O and CO2 effluxes from two soils. The net H2O and CO2 effluxes were measured at the surface of nine beds with two different soils (Cambisol and Arenosol) and two crops (maize or vegetables). Soils in some beds were amended with stabilized sewage sludge (bed with Cambisol and maize) or composted sewage sludge (two beds with Cambisol and both crops) or were irrigated with treated wastewater (two beds with Cambisol and both crops, and one bed with Arenosol and vegetable). Remaining beds were irrigated with tap water (two beds with Cambisol and both crops, and one bed with Arenosol and vegetable). While stabilized and composted sewage sludge positively affected the CO2 emission, the effect of treated wastewater was not confirmed. Different treatments had negligible effect on the water efflux, which was mainly affected by the plant canopy that influence the temperature of the soil surface. Statistical analyses showed that trends of the CO2 efflux with respect to various scenarios measured on different days changed during the season. No significant correlations were found between the average H2O and CO2 effluxes and measured soil properties.
Treated water from wastewater treatment plants that is increasingly used for irrigation may contain pharmaceuticals and, thus, contaminate soils. Therefore, this study focused on the impact of soil conditions on the root uptake of selected pharmaceuticals and their transformation in a chosen soil–plant system. Green pea plants were planted in 3 soils. Plants were initially irrigated with tap water. Next, they were irrigated for 20 days with a solution of either atenolol (ATE), sulfamethoxazole (SUL), carbamazepine (CAR), or all of these three compounds. The concentrations of pharmaceuticals and their metabolites [atenolol acid (AAC), N1-acetyl sulfamethoxazole (N1AS), N4-acetyl sulfamethoxazole (N4AS), carbamazepine 10,11-epoxide (EPC), 10,11-dihydrocarbamazepine (DHC), trans-10,11- dihydro-10,11-dihydroxy carbamazepine (RTC), and oxcarbazepine (OXC)] in soils and plant tissues were evaluated after harvest. The study confirmed high (CAR), moderate (ATE, AAC, SUL), and minor (N4AC) root uptake of the studied compounds by the green pea plants, nonrestricted transfer of the CAR species into the different plant tissues, and a very high efficiency in metabolizing CAR in the stems and leaves. The results showed neither a synergic nor competitive influence of the application of all compounds in the solution on their uptake by plants. The statistical analysis proved the negative relationships between the CAR sorption coefficients and the concentrations of CAR, EPC, and OXC in the roots (R = –0.916, –0.932, and –0.925, respectively) and stems (R = –0.837, –0.844, and –0.847, respectively).