With biocrusts playing a cardinal role in C and N fixation in arid zones, information regarding the factors that determine their limits of growth is of uttermost importance for the study of ecosystem structure and function. This is also the case in the western Negev dunefields, where although abundant on the sandy surfaces, biocrusts are scarce on finegrained (mainly loessial) sediments, termed playas. In the Nizzana research site (NRS), visibly distinct surfaces, with and without biocrusts were noted within a single playa. In an attempt to characterize these distinct surfaces, a set of random measurements were carried out, which included measurements of crack density, microrelief and chlorophyll content of the upper 0-1 cm. Following a cluster analysis, four distinct types of surfaces (hereafter habitats) were defined, one with substantial amount of chlorophyll content which can be regarded as biocrust (P4), and three non-crusted surfaces (P1- P3). Within each type, two 50 cm-deep pits were dug and the pH, electrical conductivity (EC) and fine (silt and clay) content (FC) of samples collected at 1-5, 5-10, 10-20, 20-30, 30-40 and 40-50 cm-depth were analyzed. In addition, periodical moisture measurements were carried out (in pairs) to a depth of 0-20 cm at each surface type during 2013/14. All non-crusted habitats (P1-P3) were characterized by loessial subsurface sediments. Conversely, P4 was either characterized by loessial subsurface sediments (and in this case it was characterized by a slightly concave surface) or having a sandy subsurface (at ~5-10 cm depth). While the non-crusted surfaces exhibited low moisture content, P4 exhibited deeper and higher moisture content explained either by the more sandy sediments or by lower water loss through runoff. The findings point to the close link between surface and subsurface properties and indicate that water availability may explain biocrust establishment and growth also at the loessial playa surfaces. Biocrusts may thus serve as bioindicators for habitats with high moisture content.
Rain gauges, weather radars, satellite sensors and modelled data from weather centres are used operationally for estimating the spatial-temporal variability of rainfall. However, the associated uncertainties can be very high, especially in poorly equipped regions of the world. Very recently, an innovative method, named SM2RAIN, that uses soil moisture observations to infer rainfall, has been proposed by Brocca et al. (2013) with very promising results when applied with in situ and satellite-derived data. However, a thorough analysis of the physical consistency of the SM2RAIN algorithm has not been carried out yet. In this study, synthetic soil moisture data generated from a physically-based soil water balance model are employed to check the reliability of the assumptions made in the SM2RAIN algorithm. Next, high quality and multiyear in situ soil moisture observations, at different depths (5-30 cm), and rainfall for ten sites across Europe are used for testing the performance of the algorithm, its limitations and applicability range. SM2RAIN shows very high accuracy in the synthetic experiments with a correlation coefficient, R, between synthetically generated and simulated data, at daily time step, higher than 0.940 and an average Bias lower than 4%. When real datasets are used, the agreement between observed and simulated daily rainfall is slightly lower with average R-values equal to 0.87 and 0.85 in the calibration and validation periods, respectively. Overall, the performance is found to be better in humid temperate climates and for sensors installed vertically. Interestingly, algorithms of different complexity in the reproduction of the underlying hydrological processes provide similar results. The average contribution of surface runoff and evapotranspiration components amounts to less than 4% of the total rainfall, while the soil moisture variations (63%) and subsurface drainage (30%) terms provide a much higher contribution. Overall, the SM2RAIN algorithm is found to perform well both in the synthetic and real data experiments, thus offering a new and independent source of data for improving rainfall estimation, and consequently enhancing hydrological, meteorological and climatic studies.
In the Baixo Vouga region of north-central Portugal, forests occupy half of the territory, of which two thirds are Eucalypts plantations. The hydrological implications of this large-scale introduction of eucalypt are unknown and the aim of this exploratory study, realized in the Caramulo Mountains, was to describe overland flow (OLF), subsurface flow (SSF) and stream flow (Q) in a catchment dominated by Eucalyptus plantations. The main conclusions are that annual OLF rate is low, spatially heterogeneous between 0.1% and 6% and concentrated during the wet season as saturation excess, particularly as return flow. Infiltration-excess OLF due to the strong soil water repellence (SWR) is dominant during dry season, but produces residual runoff amount. SSF is the principal mechanism of runoff formation. It originates from matrix flow and pipe flow at the soil-bedrock interface, principally during the wet season. Matrix flow is correlated with soil moisture (SM) content, with a threshold of 25 %. Pipe flow starts with saturation of soil bottom but without saturation of the entire soil profile, due to a large network of macropores. Stream flow response is highly correlated with matrix flow behaviour in timing and intensity. SWR induces a very patchy moistening of the soil, concentrates the fluxes and accelerates them almost 100 times greater than normal percolation of the water in the matrix.
In a previous study, the topsoil and root zone ASCAT satellite soil moisture data were implemented into three multi-objective calibration approaches of the TUW hydrological model in 209 Austrian catchments. This paper examines the model parametrization in those catchments, which in the validation of the dual-layer conceptual semi-distributed model showed improvement in the runoff simulation efficiency compared to the single objective runoff calibration. The runoff simulation efficiency of the three multi-objective approaches was separately considered. Inferences about the specific location and the physiographic properties of the catchments where the inclusion of ASCAT data proved beneficial were made. Improvements were primarily observed in the watersheds with lower slopes (median of the catchment slope less than 15 per cent) and a higher proportion of farming land use (median of the proportion of agricultural land above 20 per cent), as well as in catchments where the runoff is not significantly influenced by snowmelt and glacier runoff. Changes in the mean and variability of the field capacity parameter FC of the soil moisture regime were analysed. The values of FC decreased by 20 per cent on average. Consequently, the catchments’ water balance closure generally improved by the increase in catchment evapotranspiration during the validation period. Improvements in model efficiency could be attributed to better runoff simulation in the spring and autumn month. The findings refine recommendations regarding when hydrological modelling could consider satellite soil moisture data added to runoff signatures in calibration useful.
We examine the feasibility and added value of upscaling point data of soil moisture from a small- to a mesoscale catchment for the purpose of single-event flood prediction. We test the hypothesis that in a given catchment, the present soil moisture status is a key factor governing peak discharge, flow volume and flood duration. Multiple regression analyses of rainfall, pre-event discharge, single point soil moisture profiles from representative locations and peak discharge, discharge duration, discharge volume are discussed. The soil moisture profiles are selected along a convergent slope connected to the groundwater in flood plain within the small-scale catchment Husten (2.6 km²), which is a headwater catchment of the larger Hüppcherhammer catchment (47.2 km², Germany). Results show that the number of explanatory variables in the regression models is higher in summer (up to 8 variables) than in winter (up to 3 variables) and higher in the meso-scale catchment than in the small-scale catchment (up to 2 variables). Soil moisture data from selected key locations in the small catchment improves the quality of regression models established for the meso-scale catchment. For the different target variables peak discharge, discharge duration and discharge volume the adding of the soil moisture from the flood plain and the lower slope as explanatory variable improves the quality of the regression model by 15%, 20% and 10%, respectively, especially during the summer season. In the winter season the improvement is smaller (up to 6%) and the regression models mainly include rainfall characteristics as explanatory variables. The appearance of the soil moisture variables in the stepwise regression indicates their varying importance, depending on which characteristics of the discharge are focused on. Thus, we conclude that point data for soil moisture in functional landscape elements describe the catchments’ initial conditions very well and may yield valuable information for flood prediction and warning systems.
To reveal and evaluate the mechanism of transforming rainfall into runoff in the region, where the subsurface flow plays a dominant role in the runoff formation, a continuous hydrological and climatic data monitoring has been set-up in the experimental catchment Uhlířská (the Jizera Mountains, CR). The soil profile (Dystric Cambisol), formed on the weathered granite bedrock, is shallow and highly heterogeneous. Beside a standard catchment data observation a hillslope transect was instrumented to control the flow dynamics in the soil profile. From three soil horizons, the subsurface outflow is recorded in the subsurface trench. Adjacent to the trench the soil water suction is scanned by triplets of automatic tensiometers. Within the soil profile the unsaturated regime prevails, nevertheless the soil keeps almost saturated. Nearly simultaneous reaction of suction on a rainfall in all soil horizons implies a rapid vertical flow. Local preferential flow paths are conducting infiltrating water at significantly variable rates when saturation is reached. Groundwater table, soil moisture and subsurface runoff measured at the hillslope transect and the total outflow from the catchment, are correlated. The outflow from the catchment is dominantly controlled by soil moisture however the mechanism of its generation is not yet fully understood. and V oblasti s dominantním podpovrchovým odtokem bylo započato s kontinuálním hydrologickým a klimatickým monitoringem s cílem popsat a vyhodnotit transformaci srážky na odtok. Experimentální povodí Uhlířská se nachází v severní části České republiky v Jizerských horách. Půdní profil, klasifikovaný jako dystrická kambizem na zvětralém žulovém podloží, je mělký a velmi heterogenní. Svahový transekt byl vystrojen pro sledování dynamiky podpovrchového odtoku. Ve třech půdních horizontech je monitorován odtok a půdní sací tlak. V půdním profilu převládá nenasycený stav, ačkoliv je půdní vlhkost dlouhodobě blízko nasycení. Rychlé vertikální proudění je indikováno téměř současnou odezvou půdního sacího tlaku na srážku ve všech půdních horizontech. Po dosažení nasycení infiltrující voda protéká preferenčními cestami s výrazně odlišnými lokálními rychlostmi. Závislost hladiny podzemní vody, půdní vlhkosti, podpovrchového odtoku ve svahovém transektu na odtoku z povodí je významná. Odtok vody z povodí, které leží na zvětralém žulovém podloží, je dominantně určován půdní vlhkostí. Přes tato zjištění není mechanismus tvorby odtoku zatím jednoznačně popsatelný.
Knowledge on soil moisture is indispensable for a range of hydrological models, since it exerts a considerable influence on runoff conditions. Proper tools are nowadays applied in order to gain in-sight into soil moisture status, especially of uppermost soil layers, which are prone to weather changes and land use practices. In order to establish relationships between meteorological conditions and topsoil moisture, a simple model would be required, characterized by low computational effort, simple structure and low number of identified and calibrated parameters. We demonstrated, that existing model for shallow soils, considering mass exchange between two layers ( the upper and the lower), as well as with the atmosphere and subsoil, worked well for sandy loam with deep ground water table in Warsaw conurbation. GLUE (Generalized Likelihood Uncertainty Estimation) linked with GSA (Global Sensitivity Analysis) provided for final determination of parameter values and model confidence ranges. Including the uncertainty in a model structure, caused that the median soil moisture solution of the GLUE was shifted from the one optimal in deterministic sense. From the point of view of practical model application, the main shortcoming were the underestimated water exchange rates between the lower soil layer (ranging from the depth of 0.1 to 0.2 m below ground level) and subsoil. General model quality was found to be satisfactory and promising for its utilization for establishing measures to regain retention in urbanized conditions.
The need for a better understanding of factors controlling the variability of soil water content (θ) in space and time to adequately predict the movement of water in the soil and in the interphase soil-atmosphere is widely recognised. In this paper, we analyse how soil properties, surface cover and topography influence soil moisture (θ) over karstic lithology in a sub-humid Mediterranean mountain environment. For this analysis we have used 17 months of θ measurements with a high temporal resolution from different positions on a hillslope at the main recharge area of the Campo de Dalías aquifer, in Sierra de Gádor (Almería, SE Spain). Soil properties and surface cover vary depending on the position at the hillslope, and this variability has an important effect on θ. The higher clay content towards the lower position of the hillslope explains the increase of θ downslope at the subsurface horizon throughout the entire period studied. In the surface horizon (0-0.1 m), θ patterns coincide with those found at the subsurface horizon (0.1-0.35 m) during dry periods when the main control is also exerted by the higher percentage of clay that increases downslope and limits water depletion through evaporation. However, in wet periods, the wettest regime is found in the surface horizon at the upper position of the hillslope where plant cover, soil organic matter content, available water, unsaturated hydraulic conductivity (Kunsat) and infiltration rates are higher than in the lower positions. The presence of rock outcrops upslope the θ sampling area, acts as runoff sources, and subsurface flow generation between surface and subsurface horizons also may increase the differences between the upper and the lower positions of the hillslope during wet periods. Both rock and soil cracks and fissures act disconnecting surface water fluxes and reducing run-on to the lower position of the hillslope and thus they affect θ pattern as well as groundwater recharge. Understanding how terrain attributes, ground cover and soil factors interact for controlling θ pattern on karst hillslope is crucial to understand water fluxes in the vadose zone and dominant percolation mechanisms which also contribute to estimate groundwater recharge rates. Therefore, understanding of soil moisture dynamics provides very valuable information for designing rational strategies for the use and management of water resources, which is especially urgent in regions where groundwater supports human consume or key economic activities.