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  • Soils
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  • 1
    Language: English
    In: Journal of Hydrology, October 2015, Vol.529, pp.1754-1767
    Description: Soil moisture plays a key role in the water and energy balance in soil, vegetation and atmosphere systems. According to Wood et al. (2011) there is a grand need to increase global-scale hyper-resolution water–energy–biogeochemistry land surface modelling capabilities. These modelling capabilities should also recognize epistemic uncertainties, as well as the nonlinearity and hysteresis in its dynamics. Unfortunately, it is not clear how to parameterize hydrological processes as a function of scale, and how to test deterministic models with regard to epistemic uncertainties. In this study, high resolution long-term simulations were conducted in the highly instrumented TERENO hydrological observatory of the Wüstebach catchment. Soil hydraulic parameters were derived using inverse modelling with the Hydrus-1D model using the global optimization scheme SCE-UA and soil moisture data from a wireless soil moisture sensor network. The estimated parameters were then used for 3D simulations of water transport using the integrated parallel simulation platform ParFlow-CLM. The simulated soil moisture dynamics, as well as evapotranspiration (ET) and runoff, were compared with long-term field observations to illustrate how well the model was able to reproduce the water budget dynamics. We investigated different anisotropies of hydraulic conductivity to analyze how fast lateral flow processes above the underlying bedrock affect the simulation results. For a detail investigation of the model results we applied the empirical orthogonal function (EOF) and wavelet coherence methods. The EOF analysis of temporal–spatial patterns of simulated and observed soil moisture revealed that introduction of heterogeneity in the soil porosity effectively improves estimates of soil moisture patterns. Our wavelet coherence analysis indicates that wet and dry seasons have significant effect on temporal correlation between observed and simulated soil moisture and ET. Our study demonstrates the usefulness of the EOF and wavelet coherence methods for a more in-depth validation of spatially highly resolved hydrological 3D models.
    Keywords: 3d Hydrological Simulation ; Soil Moisture ; Eof Analysis ; Wavelet Coherence Analysis ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 2
    Language: English
    In: Journal of Hydrology, October 2015, Vol.529, pp.872-889
    Description: Many attempts have been made to characterize particle size distribution (PSD) curves using different mathematical models, which are primarily used as a basis for estimating soil hydraulic properties. The principle step in using soil PSD to predict soil hydraulic properties is determining an accurate and continuous curve for PSD. So far, the characteristics of the PSD models, their fitting accuracy, and the effects of their parameters on the shape and position of PSD curves have not been investigated. In this study all developed PSD models, their characteristics, behavior of their parameters, and their fitting capability to the UNSODA database soil samples were investigated. Results showed that beerkan estimation of soil transfer (BEST), two and three parameter Weibull, Rosin and Rammler (1 and 2), unimodal and bimodal Fredlund, and van Genuchten models were flexible over the entire range of soil PSD. Correspondingly, the BEST, two and three parameter Weibull, Rosin and Rammler (1 and 2), hyperbolic and offset renormalized log-normal models possessed a high fitting capability over the entire range of PSD. The few parameters of the BEST, Rosin and Rammler (1 and 2), and two parameter Weibull models provides ease of use in soil physics and mechanics research. Thus, they are seemingly fit with acceptable accuracy in predicting the PSD curve. Although the fractal models have physical and mathematical basis, they do not have the adequate flexibility to contribute a description of the PSD curve. Different aspects of the PSD models should be considered in selecting a model to describe a soil PSD.
    Keywords: Fitting ; Mathematical Psd Models ; Models Parameters ; Particle Size Distribution ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 3
    Language: English
    In: Chemosphere, Jan, 2014, Vol.95, p.470(8)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.chemosphere.2013.09.100 Byline: Stephan Sittig, Roy Kasteel, Joost Groeneweg, Diana Hofmann, Bjorn Thiele, Stephan Koppchen, Harry Vereecken Abstract: acents We show transformation and sequestration of the antibiotic sulfadiazine in two soils. acents Transformation products were found in liquid phase and extracts from the sorbed phase. acents We used a compartment model including all species and did global optimization. acents Sorption and transformation are concentration dependent. Article History: Received 12 December 2012; Revised 21 September 2013; Accepted 29 September 2013
    Keywords: Soils ; Sulfadiazine
    ISSN: 0045-6535
    Source: Cengage Learning, Inc.
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  • 4
    Language: English
    In: Journal of Hydrology, 2011, Vol.399(3), pp.410-421
    Description: ► Top soil moisture observations for estimation of hydraulic parameters. ► Simultaneous update of model states (soil moisture) and hydraulic parameters. ► SIR-PF for propagation of non-Gaussian distributions through a nonlinear model. ► Estimation of hydr. parameters driven by non linearity between SM and pressure head. In a synthetic study we explore the potential of using surface soil moisture measurements obtained from different satellite platforms to retrieve soil moisture profiles and soil hydraulic properties using a sequential data assimilation procedure and a 1D mechanistic soil water model. Four different homogeneous soil types were investigated including loamy sand, loam, silt, and clayey soils. The forcing data including precipitation and potential evapotranspiration were taken from the meteorological station of Aachen (Germany). With the aid of the forward model run, a synthetic data set was designed and observations were generated. The virtual top soil moisture observations were then assimilated to update the states and hydraulic parameters of the model by means of a particle filtering data assimilation method. Our analyses include the effect of assimilation strategy, measurement frequency, accuracy in surface soil moisture measurements, and soils differing in textural and hydraulic properties. With this approach we were able to assess the value of periodic spaceborne observations of top soil moisture for soil moisture profile estimation and identify the adequate conditions (e.g. temporal resolution and measurement accuracy) for remotely sensed soil moisture data assimilation. Updating of both hydraulic parameters and state variables allowed better predictions of top soil moisture contents as compared with updating of states only. An important conclusion is that the assimilation of remotely-sensed top soil moisture for soil hydraulic parameter estimation generates a bias depending on the soil type. Results indicate that the ability of a data assimilation system to correct the soil moisture state and estimate hydraulic parameters is driven by the non linearity between soil moisture and pressure head.
    Keywords: Soil Moisture ; Data Assimilation ; Particle Filter ; Sequential Importance Resampling ; Hydrus-1d ; Smos ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 5
    In: Global Change Biology, March 2017, Vol.23(3), pp.1338-1352
    Description: Salinity intrusion caused by land subsidence resulting from increasing groundwater abstraction, decreasing river sediment loads and increasing sea level because of climate change has caused widespread soil salinization in coastal ecosystems. Soil salinization may greatly alter nitrogen (N) cycling in coastal ecosystems. However, a comprehensive understanding of the effects of soil salinization on ecosystem N pools, cycling processes and fluxes is not available for coastal ecosystems. Therefore, we compiled data from 551 observations from 21 peer‐reviewed papers and conducted a meta‐analysis of experimental soil salinization effects on 19 variables related to N pools, cycling processes and fluxes in coastal ecosystems. Our results showed that the effects of soil salinization varied across different ecosystem types and salinity levels. Soil salinization increased plant N content (18%), soil (12%) and soil total N (210%), although it decreased soil (2%) and soil microbial biomass N (74%). Increasing soil salinity stimulated soil NO fluxes as well as hydrological and fluxes more than threefold, although it decreased the hydrological dissolved organic nitrogen () flux (59%). Soil salinization also increased the net N mineralization by 70%, although salinization effects were not observed on the net nitrification, denitrification and dissimilatory nitrate reduction to ammonium in this meta‐analysis. Overall, this meta‐analysis improves our understanding of the responses of ecosystem N cycling to soil salinization, identifies knowledge gaps and highlights the urgent need for studies on the effects of soil salinization on coastal agro‐ecosystem and microbial N immobilization. Additional increases in knowledge are critical for designing sustainable adaptation measures to the predicted intrusion of salinity intrusion so that the productivity of coastal agro‐ecosystems can be maintained or improved and the N losses and pollution of the natural environment can be minimized.
    Keywords: Costal Ecosystem ; Denitrification ; Dissimilatory Nitrate Reduction To Ammonium Dnra ; Nitrogen Cycle ; Salinity Intrusion ; Sea‐Level Rise ; Soil Salinization
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 6
    Language: English
    In: Journal of Hydrology, May 2016, Vol.536, pp.365-375
    Description: In distributed hydrological modelling one often faces the problem that input data need to be aggregated to match the model resolution. However, aggregated data may be too coarse for the parametrization of the processes represented. This dilemma can be circumvented by the adjustment of certain model parameters. For instance, the reduction of local hydraulic gradients due to spatial aggregation can be partially compensated by increasing soil hydraulic conductivity. In this study, we employed the information entropy concept for the scale dependent parameterization of soil hydraulic conductivity. The loss of information content of terrain curvature as consequence of spatial aggregation was used to determine an amplification factor for soil hydraulic conductivity to compensate the resulting retardation of water flow. To test the usefulness of this approach, continuous 3D hydrological simulations were conducted with different spatial resolutions in the highly instrumented Wüstebach catchment, Germany. Our results indicated that the introduction of an amplification factor can effectively improve model performances both in terms of soil moisture and runoff simulation. However, comparing simulated soil moisture pattern with observation indicated that uniform application of an amplification factor can lead to local overcorrection of soil hydraulic conductivity. This problem could be circumvented by applying the amplification factor only to model grid cells that suffer from high information loss. To this end, we tested two schemes to define appropriate location-specific correction factors. Both schemes led to improved model performance both in terms of soil water content and runoff simulation. Thus, we anticipate that our proposed scaling approach is useful for the application of next-generation hyper-resolution global land surface models.
    Keywords: Scale Dependent Parameterization ; 3d Hydrological Modelling ; Topographical Information Content ; Soil Hydraulic Conductivity ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 7
    Language: English
    In: Journal of Hydrology, 04 August 2014, Vol.516, pp.154-160
    Description: Knowledge of spatial mean soil moisture and its variability over time is needed in many environmental applications. We analyzed dependencies of soil moisture variability on average soil moisture contents in soils with and without root water uptake using ensembles of non-stationary water flow simulations by varying soil hydraulic properties under different climatic conditions. We focused on the dry end of the soil moisture range and found that the magnitude of soil moisture variability was controlled by the interplay of soil hydraulic properties and climate. The average moisture at which the maximum variability occurred depended on soil hydraulic properties and vegetation. A positive linear relationship was observed between mean soil moisture and its standard deviation and was controlled by the parameter defining the shape of soil water retention curves and the spatial variability of saturated hydraulic conductivity. The influence of other controls, such as variable weather patterns, topography or lateral flow processes needs to be studied further to see if such relationship persists and could be used for the inference of soil hydraulic properties from the spatiotemporal variation in soil moisture.
    Keywords: Soil Moisture ; Variability ; Soil Hydraulic Properties ; Climate ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
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  • 8
    Language: English
    In: Environmental Pollution, Sept, 2013, Vol.180, p.152(7)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.envpol.2013.05.031 Byline: Daniela Kasel, Scott A. Bradford, JiAi A imA[macron]nek, Thomas Putz, Harry Vereecken, Erwin Klumpp Abstract: Column experiments were conducted in undisturbed and in repacked soil columns at water contents close to saturation (85-96%) to investigate the transport and retention of functionalized.sup.14C-labeled multi-walled carbon nanotubes (MWCNT) in two natural soils. Additionally, a field lysimeter experiment was performed to provide long-term information at a larger scale. In all experiments, no breakthrough of MWCNTs was detectable and more than 85% of the applied radioactivity was recovered in the soil profiles. The retention profiles exhibited a hyper-exponential shape with greater retention near the column or lysimeter inlet and were successfully simulated using a numerical model that accounted for depth-dependent retention. In conclusion, results indicated that the soils acted as a strong sink for MWCNTs. Little transport of MWCNTs is therefore likely to occur in the vadose zone, and this implies limited potential for groundwater contamination in the investigated soils. Author Affiliation: (a) Agrosphere Institute (IBG-3), Forschungszentrum Julich GmbH, 52425 Julich, Germany (b) US Salinity Laboratory, Agricultural Research Service, United States Department of Agriculture, Riverside, CA 92507, USA (c) Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA Article History: Received 8 February 2013; Revised 8 May 2013; Accepted 16 May 2013
    Keywords: Groundwater -- Analysis ; Soils -- Analysis ; Recharge Zones -- Analysis ; Vadose Zone -- Analysis ; Nanotubes -- Analysis ; Soil Carbon -- Analysis
    ISSN: 0269-7491
    Source: Cengage Learning, Inc.
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  • 9
    Language: English
    In: Journal of Hydrology, December 2017, Vol.555, pp.31-40
    Description: Forest canopy interception alters the isotopic tracer signal of precipitation leading to significant isotopic differences between open precipitation (δOP) and throughfall (δTF). This has important consequences for the tracer-based modeling of streamwater transit times. Some studies have suggested using a simple static correction to δOP by uniformly increasing it because δTF is rarely available for hydrological modeling. Here, we used data from a 38.5 ha spruce forested headwater catchment where three years of δOP and δTF were available to develop a data driven method that accounts for canopy effects on δOP. Changes in isotopic composition, defined as the difference δTF-δOP, varied seasonally with higher values during winter and lower values during summer. We used this pattern to derive a corrected δOP time series and analyzed the impact of using (1) δOP, (2) reference throughfall data (δTF ) and (3) the corrected δOP time series (δOP ) in estimating the fraction of young water ( ), i.e., the percentage of streamflow younger than two to three months. We found that derived from δOP came closer to δTF in comparison to δOP. Thus, a seasonally-varying correction for δOP can be successfully used to infer δTF where it is not available and is superior to the method of using a fixed correction factor. Seasonal isotopic enrichment patterns should be accounted for when estimating and more generally in catchment hydrology studies using other tracer methods to reduce uncertainty.
    Keywords: Isotope Hydrology ; Throughfall ; Fraction of Young Water ; Catchment Hydrology ; Geography
    ISSN: 0022-1694
    E-ISSN: 1879-2707
    Source: ScienceDirect Journals (Elsevier)
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  • 10
    Language: English
    In: Science of the Total Environment, 01 February 2016, Vol.543, pp.889-905
    Description: We used observed climate data, an ensemble of four GCM–RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM–RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived.
    Keywords: Groundwater Recharge ; Climate Change ; Synthetic Aperture Radar ; Mediterranean ; Mgrowa ; Environmental Sciences ; Biology ; Public Health
    ISSN: 0048-9697
    E-ISSN: 1879-1026
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