Hydrophobicity is a property of soils that reduces their affinity for water, which may help impeding the pressure build-up within aggregates, and reducing aggregate disruption. The purpose of this study was to examine the relation of soil hydrophobicity and drying temperature to water stability of aggregates while preventing the floating of dry aggregates using unhydrophobized and hydrophobized surface Andisol. Soil was hydrophobized using stearic acid into different hydrophobicities. Hydrophobicity was determined using sessile drop contact angle and water drop penetration time (WDPT). Water stability of aggregates (%WSA) was determined using artificially prepared model aggregates. The %WSA increased as the contact angle and WDPT increased. Contact angle and WDPT, which provided maximum %WSA showing less than 1 s of floating, was around 100° and 5 s, respectively. Although the %WSA gradually increased with increasing contact angle and WDPT above this level, high levels of hydrophobicity initiated aggregate floating, which would cause undesirable effects of water repellency. Heating at 50°C for 5 h d-1 significantly affected %WSA and hydrophobicity in hydrophobized samples, but did not in unhydrophobized samples. The results indicate that the contact angle and wetting rate (WDPT) are closely related with the water stability of aggregates. The results further confirm that high levels of hydrophobicities induce aggregate floating, and the drying temperature has differential effects on hydrophobicity and aggregate stability depending on the hydrophobic materials present in the soil.
Weighing lysimeters can be used for studying the soil water balance and to analyse evapotranspiration (ET). However, not clear was the impact of the bottom boundary condition on lysimeter results and soil water movement. The objective was to analyse bottom boundary effects on the soil water balance. This analysis was carried out for lysimeters filled with fine- and coarse-textured soil monoliths by comparing simulated and measured data for lysimeters with a higher and a lower water table. The eight weighable lysimeters had a 1 m2 grass-covered surface and a depth of 1.5 m. The lysimeters contained four intact monoliths extracted from a sandy soil and four from a soil with a silty-clay texture. For two lysimeters of each soil, constant water tables were imposed at 135 cm and 210 cm depths. Evapotranspiration, change in soil water storage, and groundwater recharge were simulated for a 3-year period (1996 to 1998) using the Hydrus-1D software. Input data consisted of measured weather data and crop model-based simulated evaporation and transpiration. Snow cover and heat transport were simulated based on measured soil temperatures. Soil hydraulic parameter sets were estimated (i) from soil core data and (ii) based on texture data using ROSETTA pedotransfer approach. Simulated and measured outflow rates from the sandy soil matched for both parameter sets. For the sand lysimeters with the higher water table, only fast peak flow events observed on May 4, 1996 were not simulated adequately mainly because of differences between simulated and measured soil water storage caused by ET-induced soil water storage depletion. For the silty-clay soil, the simulations using the soil hydraulic parameters from retention data (i) were matching the lysimeter data except for the observed peak flows on May, 4, 1996, which here probably resulted from preferential flow. The higher water table at the lysimeter bottom resulted in higher drainage in comparison with the lysimeters with the lower water table. This increase was smaller for the finer-textured soil as compared to the coarser soil.
Soil sorptivity is considered a key parameter describing early stages of water (rain) infiltration into a relatively dry soil and it is related to build-up complexity of the capillary system and soil wettability (contact angles of soil pore walls). During the last decade an increasing water repellency of sandy soils under pine forest and grassland vegetation has been frequently observed at Mlaky II location in SW Slovakia. The dry seasons result in uneven wetting of soil and up to hundredfold decrease in soil sorptivity in these vegetated soil as compared to reference sandy material, which was out of the reach of ambient vegetation and therefore readily wettable. As far as water binding to low moisture soils is governed by adsorption processes, we hypothesized that soil water repellency detected by water drop penetration test and by index of water repellency should also influence the water vapour adsorption parameters (monolayer water content, Wm, specific surface area, A, maximum adsorption water, Wa, maximum hygroscopic water MH, fractal dimension, DS and adsorption energies, Ea) derived from BET model of adsorption isotherms. We found however, that the connection of these parameters to water repellency level is difficult to interpret; nevertheless the centres with higher adsorption energy prevailed evidently in wettable materials. The water repellent forest and grassland soils reached less than 80% of the adsorption energy measured on wettable reference material. To get more conclusive results, which would not be influenced by small but still present variability of field materials, commercially available homogeneous siliceous sand was artificially hydrophobized and studied in the same way, as were the field materials. This extremely water repellent material had two-times lower surface area, very low fractal dimension (close to 2) and substantially lower adsorption energy as compared to the same siliceous sand when not hydrophobized.
Mosses are often overlooked; however, they are important for soil-atmosphere interfaces with regard to water exchange. This study investigated the influence of moss structural traits on maximum water storage capacities (WSCmax) and evaporation rates, and species-specific effects on water absorption and evaporation patterns in moss layers, mosssoil- interfaces and soil substrates using biocrust wetness probes. Five moss species typical for Central European temperate forests were selected: field-collected Brachythecium rutabulum, Eurhynchium striatum, Oxyrrhynchium hians and Plagiomnium undulatum; and laboratory-cultivated Amblystegium serpens and Oxyrrhynchium hians. WSCmax ranged from 14.10 g g–1 for Amblystegium serpens (Lab) to 7.31 g g–1 for Plagiomnium undulatum when immersed in water, and 11.04 g g–1 for Oxyrrhynchium hians (Lab) to 7.90 g g–1 for Oxyrrhynchium hians when sprayed, due to different morphologies depending on the growing location. Structural traits such as high leaf frequencies and small leaf areas increased WSCmax. In terms of evaporation, leaf frequency displayed a positive correlation with evaporation, while leaf area index showed a negative correlation. Moisture alterations during watering and desiccation were largely controlled by species/substrate-specific patterns. Generally, moss cover prevented desiccation of soil surfaces and was not a barrier to infiltration. To understand water’s path from moss to soil, this study made a first contribution.
Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting. In this paper, the forecasting performance of a new model combining a long range dependent autoregressive fractionally integrated moving average (ARFIMA) model with a wavelet transform used as a method of deseasonalization is examined. It is analysed, whether applying wavelets in order to model the seasonal component in a hydrological time series, is an alternative to moving average deseasonalization in combination with an ARFIMA model. The one-to-ten-steps-ahead forecasting performance of this model is compared with two other models, an ARFIMA model with moving average deseasonalization, and a multiresolution wavelet based model. All models are applied to a time series of mean daily discharge exhibiting long range dependence. For one and two day forecasting horizons, the combined wavelet - ARFIMA approach shows a similar performance as the other models tested. However, for longer forecasting horizons, the wavelet deseasonalization - ARFIMA combination outperforms the other two models. The results show that the wavelets provide an attractive alternative to the moving average deseasonalization.
During the last decades several studies in cognitive psychology have shown that many of our actions do not depend on the reasons that we adduce afterwards, when we have to account for them. Our decisions seem to be often influenced by normatively or explanatorily irrelevant features of the environment of which we are not aware, and the reasons we offer for those decisions are a posteriori rationalisations. But exactly what reasons has the psychological research uncovered? In philosophy, a distinction has been commonly made between normative and motivating reasons: normative reasons make an action right, whereas motivating reasons explain our behaviour. Recently, Maria Alvarez has argued that, apart from normative (or justifying) reasons, we should further distinguish between motivating and explanatory reasons. We have, then, three kinds of reasons, and it is not clear which of them have been revealed as the real reasons for our actions by the psychological research. The answer we give to this question will have important implications both for the validity of our classifications of reasons and for our understanding of human action.