Testing the Visual Soil Assessment tool on Estonian farm fields

NASA Astrophysics Data System (ADS)

Reintam, Endla; Are, Mihkel; Selge, Are

2017-04-01

Soil quality estimation plays important role in decision making on farm as well on policy level. Sustaining the production ability and good health of the soil the chemical, physical and biological indicators should be taken into account. The system to use soil chemical parameters is usually quite well established in most European counties, including Estonia. However, measuring soil physical properties, such bulk density, porosity, penetration resistance, structural stability ect is time consuming, needs special tools and is highly weather dependent. In that reason these parameters are excluded from controllable quality parameters in policy in Estonia. Within the project "Interactive Soil Quality Assessment in Europe and China for Agricultural Productivity and Environmental Resilience" (iSQAPER) the visual soil assessment (VSA) tool was developed for easy detection of soil quality as well the different soil friendly agricultural management practices (AMP) were detected. The aim of current study was to test the VSA tool on Estonian farm fields under different management practices and compare the results with laboratory measurements. The main focus was set on soil physical parameters. Next to the VSA, the undisturbed soil samples were collected from the depth of 5-10 cm and 25-30 cm. The study revealed that results of a visually assessed soil physical parameters, such a soil structure, soil structural stability, soil porosity, presence of tillage pan, were confirmed by laboratory measurements in most cases. Soil water stable structure measurement on field (on 1 cm2 net in one 1 l box with 4-6 cm air dry clods for 5-10 min) underestimated very well structured soil on grassland and overestimated the structure aggregates stability of compacted soil. The slightly better soil quality was detected under no-tillage compared to ploughed soils. However, the ploughed soil got higher quality points compared with minimum tillage. The slurry application (organic manuring) had controversial impact - it increased the number of earthworms but decreased soil structural stability. Even the manuring with slurry increases organic matter amount in the soil, the compaction due to the use of heavy machinery during the application, especially on wet soil, reduces the positive effect of slurry.

Soil pH determines microbial diversity and composition in the park grass experiment.

PubMed

Zhalnina, Kateryna; Dias, Raquel; de Quadros, Patricia Dörr; Davis-Richardson, Austin; Camargo, Flavio A O; Clark, Ian M; McGrath, Steve P; Hirsch, Penny R; Triplett, Eric W

2015-02-01

The Park Grass experiment (PGE) in the UK has been ongoing since 1856. Its purpose is to study the response of biological communities to the long-term treatments and associated changes in soil parameters, particularly soil pH. In this study, soil samples were collected across pH gradient (pH 3.6-7) and a range of fertilizers (nitrogen as ammonium sulfate, nitrogen as sodium nitrate, phosphorous) to evaluate the effects nutrients have on soil parameters and microbial community structure. Illumina 16S ribosomal RNA (rRNA) amplicon sequencing was used to determine the relative abundances and diversity of bacterial and archaeal taxa. Relationships between treatments, measured soil parameters, and microbial communities were evaluated. Clostridium, Bacteroides, Bradyrhizobium, Mycobacterium, Ruminococcus, Paenibacillus, and Rhodoplanes were the most abundant genera found at the PGE. The main soil parameter that determined microbial composition, diversity, and biomass in the PGE soil was pH. The most probable mechanism of the pH impact on microbial community may include mediation of nutrient availability in the soil. Addition of nitrogen to the PGE plots as ammonium sulfate decreases soil pH through increased nitrification, which causes buildup of soil carbon, and hence increases C/N ratio. Plant species richness and plant productivity did not reveal significant relationships with microbial diversity; however, plant species richness was positively correlated with soil microbial biomass. Plants responded to the nitrogen treatments with an increase in productivity and a decrease in the species richness.

High resolution modelling of soil moisture patterns with TerrSysMP: A comparison with sensor network data

NASA Astrophysics Data System (ADS)

Gebler, S.; Hendricks Franssen, H.-J.; Kollet, S. J.; Qu, W.; Vereecken, H.

2017-04-01

The prediction of the spatial and temporal variability of land surface states and fluxes with land surface models at high spatial resolution is still a challenge. This study compares simulation results using TerrSysMP including a 3D variably saturated groundwater flow model (ParFlow) coupled to the Community Land Model (CLM) of a 38 ha managed grassland head-water catchment in the Eifel (Germany), with soil water content (SWC) measurements from a wireless sensor network, actual evapotranspiration recorded by lysimeters and eddy covariance stations and discharge observations. TerrSysMP was discretized with a 10 × 10 m lateral resolution, variable vertical resolution (0.025-0.575 m), and the following parameterization strategies of the subsurface soil hydraulic parameters: (i) completely homogeneous, (ii) homogeneous parameters for different soil horizons, (iii) different parameters for each soil unit and soil horizon and (iv) heterogeneous stochastic realizations. Hydraulic conductivity and Mualem-Van Genuchten parameters in these simulations were sampled from probability density functions, constructed from either (i) soil texture measurements and Rosetta pedotransfer functions (ROS), or (ii) estimated soil hydraulic parameters by 1D inverse modelling using shuffle complex evolution (SCE). The results indicate that the spatial variability of SWC at the scale of a small headwater catchment is dominated by topography and spatially heterogeneous soil hydraulic parameters. The spatial variability of the soil water content thereby increases as a function of heterogeneity of soil hydraulic parameters. For lower levels of complexity, spatial variability of the SWC was underrepresented in particular for the ROS-simulations. Whereas all model simulations were able to reproduce the seasonal evapotranspiration variability, the poor discharge simulations with high model bias are likely related to short-term ET dynamics and the lack of information about bedrock characteristics and an on-site drainage system in the uncalibrated model. In general, simulation performance was better for the SCE setups. The SCE-simulations had a higher inverse air entry parameter resulting in SWC dynamics in better correspondence with data than the ROS simulations during dry periods. This illustrates that small scale measurements of soil hydraulic parameters cannot be transferred to the larger scale and that interpolated 1D inverse parameter estimates result in an acceptable performance for the catchment.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Depth-resolved microbial community analyses in two contrasting soil cores contaminated by antimony and arsenic.

PubMed

Xiao, Enzong; Krumins, Valdis; Xiao, Tangfu; Dong, Yiran; Tang, Song; Ning, Zengping; Huang, Zhengyu; Sun, Weimin

2017-02-01

Investigation of microbial communities of soils contaminated by antimony (Sb) and arsenic (As) is necessary to obtain knowledge for their bioremediation. However, little is known about the depth profiles of microbial community composition and structure in Sb and As contaminated soils. Our previous studies have suggested that historical factors (i.e., soil and sediment) play important roles in governing microbial community structure and composition. Here, we selected two different types of soil (flooded paddy soil versus dry corn field soil) with co-contamination of Sb and As to study interactions between these metalloids, geochemical parameters and the soil microbiota as well as microbial metabolism in response to Sb and As contamination. Comprehensive geochemical analyses and 16S rRNA amplicon sequencing were used to shed light on the interactions of the microbial communities with their environments. A wide diversity of taxonomical groups was present in both soil cores, and many were significantly correlated with geochemical parameters. Canonical correspondence analysis (CCA) and co-occurrence networks further elucidated the impact of geochemical parameters (including Sb and As contamination fractions and sulfate, TOC, Eh, and pH) on vertical distribution of soil microbial communities. Metagenomes predicted from the 16S data using PICRUSt included arsenic metabolism genes such as arsenate reductase (ArsC), arsenite oxidase small subunit (AoxA and AoxB), and arsenite transporter (ArsA and ACR3). In addition, predicted abundances of arsenate reductase (ArsC) and arsenite oxidase (AoxA and AoxB) genes were significantly correlated with Sb contamination fractions, These results suggest potential As biogeochemical cycling in both soil cores and potentially dynamic Sb biogeochemical cycling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

SIMULATING RADIONUCLIDE FATE AND TRANSPORT IN THE UNSATURATED ZONE: EVALUATION AND SENSITIVITY ANALYSES OF SELECT COMPUTER MODELS

EPA Science Inventory

Numerical, mathematical models of water and chemical movement in soils are used as decision aids for determining soil screening levels (SSLs) of radionuclides in the unsaturated zone. Many models require extensive input parameters which include uncertainty due to soil variabil...

Handling the unknown soil hydraulic parameters in data assimilation for unsaturated flow problems

NASA Astrophysics Data System (ADS)

Lange, Natascha; Erdal, Daniel; Neuweiler, Insa

2017-04-01

Model predictions of flow in the unsaturated zone require the soil hydraulic parameters. However, these parameters cannot be determined easily in applications, in particular if observations are indirect and cover only a small range of possible states. Correlation of parameters or their correlation in the range of states that are observed is a problem, as different parameter combinations may reproduce approximately the same measured water content. In field campaigns this problem can be helped by adding more measurement devices. Often, observation networks are designed to feed models for long term prediction purposes (i.e. for weather forecasting). A popular way of making predictions with such kind of observations are data assimilation methods, like the ensemble Kalman filter (Evensen, 1994). These methods can be used for parameter estimation if the unknown parameters are included in the state vector and updated along with the model states. Given the difficulties related to estimation of the soil hydraulic parameters in general, it is questionable, though, whether these methods can really be used for parameter estimation under natural conditions. Therefore, we investigate the ability of the ensemble Kalman filter to estimate the soil hydraulic parameters. We use synthetic identical twin-experiments to guarantee full knowledge of the model and the true parameters. We use the van Genuchten model to describe the soil water retention and relative permeability functions. This model is unfortunately prone to the above mentioned pseudo-correlations of parameters. Therefore, we also test the simpler Russo Gardner model, which is less affected by that problem, in our experiments. The total number of unknown parameters is varied by considering different layers of soil. Besides, we study the influence of the parameter updates on the water content predictions. We test different iterative filter approaches and compare different observation strategies for parameter identification. Considering heterogeneous soils, we discuss the representativeness of different observation types to be used for the assimilation. G. Evensen. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99(C5):10143-10162, 1994

Misrepresentation of hydro-erosional processes in rainfall simulations using disturbed soil samples

NASA Astrophysics Data System (ADS)

Thomaz, Edivaldo L.; Pereira, Adalberto A.

2017-06-01

Interrill erosion is a primary soil erosion process which consists of soil detachment by raindrop impact and particle transport by shallow flow. Interill erosion affects other soil erosion sub-processes, e.g., water infiltration, sealing, crusting, and rill initiation. Interrill erosion has been widely studied in laboratories, and the use of a sieved soil, i.e., disturbed soil, has become a standard method in laboratory experiments. The aims of our study are to evaluate the hydro-erosional response of undisturbed and disturbed soils in a laboratory experiment, and to quantify the extent to which hydraulic variables change during a rainstorm. We used a splash pan of 0.3 m width, 0.45 m length, and 0.1 m depth. A rainfall simulation of 58 mm h- 1 lasting for 30 min was conducted on seven replicates of undisturbed and disturbed soils. During the experiment, several hydro-physical parameters were measured, including splashed sediment, mean particle size, runoff, water infiltration, and soil moisture. We conclude that use of disturbed soil samples results in overestimation of interrill processes. Of the nine assessed parameters, four displayed greater responses in the undisturbed soil: infiltration, topsoil shear strength, mean particle size of eroded particles, and soil moisture. In the disturbed soil, five assessed parameters displayed greater responses: wash sediment, final runoff coefficient, runoff, splash, and sediment yield. Therefore, contextual soil properties are most suitable for understanding soil erosion, as well as for defining soil erodibility.

Biological and biochemical soil quality indicators for agricultural management

NASA Astrophysics Data System (ADS)

Bongiorno, Giulia

2017-04-01

Soil quality is defined as the capacity of a soil to perform multiple functions. Agricultural soils can, in principle, sustain a wide range of functions. However, negative pressure exerted by natural and anthropogenic soil threats such as soil erosion, soil organic matter losses and soil compaction have the potential to permanently damage soil quality. Soil chemical, physical and biological parameters can be used as indicators of soil quality. The specific objective of this study is to assess the suitability of novel soil parameters as soil quality indicators. We focus on biological/biochemical parameters, due to the unique role of soil biota in soil functions and to their high sensitivity to disturbances. The novel indicators are assessed in ten European long-term field experiments (LTEs) with different agricultural land use (arable and permanent crops), management regimes and pedo-climatic characteristics. The contrasts in agricultural management are represented by conventional/reduced tillage, organic/mineral fertilization and organic matter addition/no organic matter addition. We measured two different pools of labile organic carbon (dissolved organic carbon (DOC), and permanganate oxidizable carbon (POXC)), and determined DOC quality through its fractionation in hydrophobic and hydrophilic compounds. In addition, total nematode abundance has been assessed with qPCR. These parameters will be related to soil functions which have been measured with a minimum data set of indicators for soil quality (including TOC, macronutrients, and soil respiration). As a preliminary analysis, the Sensitivity Index (SI) for a given LTE was calculated for DOC and POXC according to Bolinder et al., 1999 as the ratio of the soil attribute under modified practices (e.g. reduced tillage) compared to the conventional practices (e.g. conventional tillage). The overall effect of the sustainable management on the indicators has been derived by calculating an average SI for those LTEs which included the sustainable management taken into account. A parametric t-test was used to determine the comprehensive significance of the average SI for a given indicator. Reduced tillage increased DOC and POXC in the 0-10 cm of soil (SI=1.19 and 1.18 respectively) compared to conventional tillage. Organic fertilization increased DOC and POXC in the 0-10 cm compared to mineral fertilization (SI=1.43 and 1.41) and compared to no fertilizer applications (SI=1.27 and 1.17). DOC was slightly more sensitive than POXC, however, the t-test resulted to be significant only for POXC. Preliminary tests revealed a significant correlation between POXC and DOC (Spearman ρ=0.53, p<0.001). POXC was more strongly correlated with TOC (ρ=0.8, p<0.001), soil respiration (ρ=0.5, p<0.001) and total nematode number (ρ=0.25, p<0.001), than DOC (ρ=0.37, p<0.001; ρ=0.28, p<0.001; ρ=0.04, p=0.5, respectively). These preliminary results could indicate the better suitability of POXC as soil quality indicator compared to DOC. Further analyses will be implemented to elucidate these relations (including DOC quality parameters and hot water extractable carbon). In the coming months, nematode community composition and abundance of specific groups will be assessed with molecular techniques (sequencing and qPCR). Together, the results will permit to assess the feasibility of the implementation of novel indicators to monitor the effects of agricultural management on soil functions.

Multiscale Bayesian neural networks for soil water content estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.; Springer, Everett P.

2008-08-01

Artificial neural networks (ANN) have been used for some time now to estimate soil hydraulic parameters from other available or more easily measurable soil properties. However, most such uses of ANNs as pedotransfer functions (PTFs) have been at matching spatial scales (1:1) of inputs and outputs. This approach assumes that the outputs are only required at the same scale as the input data. Unfortunately, this is rarely true. Different hydrologic, hydroclimatic, and contaminant transport models require soil hydraulic parameter data at different spatial scales, depending upon their grid sizes. While conventional (deterministic) ANNs have been traditionally used in these studies, the use of Bayesian training of ANNs is a more recent development. In this paper, we develop a Bayesian framework to derive soil water retention function including its uncertainty at the point or local scale using PTFs trained with coarser-scale Soil Survey Geographic (SSURGO)-based soil data. The approach includes an ANN trained with Bayesian techniques as a PTF tool with training and validation data collected across spatial extents (scales) in two different regions in the United States. The two study areas include the Las Cruces Trench site in the Rio Grande basin of New Mexico, and the Southern Great Plains 1997 (SGP97) hydrology experimental region in Oklahoma. Each region-specific Bayesian ANN is trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000), and predictions of the soil water contents at different pressure heads with point scale data (1:1) inputs are made. The resulting outputs are corrected for bias using both linear and nonlinear correction techniques. The results show good agreement between the soil water content values measured at the point scale and those predicted by the Bayesian ANN-based PTFs for both the study sites. Overall, Bayesian ANNs coupled with nonlinear bias correction are found to be very suitable tools for deriving soil hydraulic parameters at the local/fine scale from soil physical properties at coarser-scale and across different spatial extents. This approach could potentially be used for soil hydraulic properties estimation and downscaling.

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Soil Water Characteristics of Cores from Low- and High-Centered Polygons, Barrow, Alaska, 2012

DOE Data Explorer

Graham, David; Moon, Ji-Won

2016-08-22

This dataset includes soil water characteristic curves for soil and permafrost in two representative frozen cores collected from a high-center polygon (HCP) and a low-center polygon (LCP) from the Barrow Environmental Observatory. Data include soil water content and soil water potential measured using the simple evaporation method for hydrological and biogeochemical simulations and experimental data analysis. Data can be used to generate a soil moisture characteristic curve, which can be fit to a variety of hydrological functions to infer critical parameters for soil physics. Considering the measured the soil water properties, the van Genuchten model predicted well the HCP, in contrast, the Kosugi model well fitted LCP which had more saturated condition.

Soil fertility and plant diversity enhance microbial performance in metal-polluted soils.

PubMed

Stefanowicz, Anna M; Kapusta, Paweł; Szarek-Łukaszewska, Grażyna; Grodzińska, Krystyna; Niklińska, Maria; Vogt, Rolf D

2012-11-15

This study examined the effects of soil physicochemical properties (including heavy metal pollution) and vegetation parameters on soil basal respiration, microbial biomass, and the activity and functional richness of culturable soil bacteria and fungi. In a zinc and lead mining area (S Poland), 49 sites were selected to represent all common plant communities and comprise the area's diverse soil types. Numerous variables describing habitat properties were reduced by PCA to 7 independent factors, mainly representing subsoil type (metal-rich mining waste vs. sand), soil fertility (exchangeable Ca, Mg and K, total C and N, organic C), plant species richness, phosphorus content, water-soluble heavy metals (Zn, Cd and Pb), clay content and plant functional diversity (based on graminoids, legumes and non-leguminous forbs). Multiple regression analysis including these factors explained much of the variation in most microbial parameters; in the case of microbial respiration and biomass, it was 86% and 71%, respectively. The activity of soil microbes was positively affected mainly by soil fertility and, apparently, by the presence of mining waste in the subsoil. The mining waste contained vast amounts of trace metals (total Zn, Cd and Pb), but it promoted microbial performance due to its inherently high content of macronutrients (total Ca, Mg, K and C). Plant species richness had a relatively strong positive effect on all microbial parameters, except for the fungal component. In contrast, plant functional diversity was practically negligible in its effect on microbes. Other explanatory variables had only a minor positive effect (clay content) or no significant influence (phosphorus content) on microbial communities. The main conclusion from this study is that high nutrient availability and plant species richness positively affected the soil microbes and that this apparently counteracted the toxic effects of metal contamination. Copyright © 2012 Elsevier B.V. All rights reserved.

Verification and completion of a soil data base for process based erosion model applications in Mato Grosso/Brazil

NASA Astrophysics Data System (ADS)

Schindewolf, Marcus; Schultze, Nico; Schönke, Daniela; Amorim, Ricardo S. S.; Schmidt, Jürgen

2014-05-01

The study area of central Mato Grosso is subjected to severe soil erosion. Continuous erosion leads to massive losses of top soil and related organic carbon. Consequently agricultural soil soils suffer a drop in soil fertility which only can be balanced by mineral fertilization. In order to control soil degradation and organic carbon losses of Mato Grosso cropland soils a process based soil loss and deposition model is used. Applying the model it will be possible to: - identify the main areas affected by soil erosion or deposition in different scales under present and future climate and socio-economic conditions - estimate the related nutrient and organic carbon losses/yields - figure out site-related causes of soil mobilization/deposition - locate sediment and sediment related nutrient and organic matter pass over points into surface water bodies - estimate the impacts of climate and land use changes on the losses of top soil, sediment bound nutrients and organic carbon. Model input parameters include digital elevation data, precipitation characteristics and standard soil properties as particle size distribution, total organic carbon (TOC) and bulk density. The effects of different types of land use and agricultural management practices are accounted for by varying site-specific parameters predominantly related to soil surface properties such as erosional resistance, hydraulic roughness and percentage ground cover. In this context the existing EROSION 3D soil parameter data base deducted from large scale rainfall simulations in Germany is verified for application in the study area, using small scale disc type rainfall simulator with an additional runoff reflux approach. Thus it's possible to enlarge virtual plot length up to at least 10 m. Experimental plots are located in Cuiabá region of central Mato Grosso in order to cover the most relevant land use variants and tillage practices in the region. Results show that derived model parameters are highly influenced by soil management. This indicates a high importance of tillage impact on resistance to erosion, mulch cover and TOC. The measured parameter ranges can generally be confirmed by the existing data base, which only need to be completed due to changed phenological stages in Mato Grosso compared to German conditions.

Gap assessment in current soil monitoring networks across Europe for measuring soil functions

NASA Astrophysics Data System (ADS)

van Leeuwen, J. P.; Saby, N. P. A.; Jones, A.; Louwagie, G.; Micheli, E.; Rutgers, M.; Schulte, R. P. O.; Spiegel, H.; Toth, G.; Creamer, R. E.

2017-12-01

Soil is the most important natural resource for life on Earth after water. Given its fundamental role in sustaining the human population, both the availability and quality of soil must be managed sustainably and protected. To ensure sustainable management we need to understand the intrinsic functional capacity of different soils across Europe and how it changes over time. Soil monitoring is needed to support evidence-based policies to incentivise sustainable soil management. To this aim, we assessed which soil attributes can be used as potential indicators of five soil functions; (1) primary production, (2) water purification and regulation, (3) carbon sequestration and climate regulation, (4) soil biodiversity and habitat provisioning and (5) recycling of nutrients. We compared this list of attributes to existing national (regional) and EU-wide soil monitoring networks. The overall picture highlighted a clearly unbalanced dataset, in which predominantly chemical soil parameters were included, and soil biological and physical attributes were severely under represented. Methods applied across countries for indicators also varied. At a European scale, the LUCAS-soil survey was evaluated and again confirmed a lack of important soil biological parameters, such as C mineralisation rate, microbial biomass and earthworm community, and soil physical measures such as bulk density. In summary, no current national or European monitoring system exists which has the capacity to quantify the five soil functions and therefore evaluate multi-functional capacity of a soil and in many countries no data exists at all. This paper calls for the addition of soil biological and some physical parameters within the LUCAS-soil survey at European scale and for further development of national soil monitoring schemes.

New best estimates for radionuclide solid-liquid distribution coefficients in soils. Part 2: naturally occurring radionuclides.

PubMed

Vandenhove, H; Gil-García, C; Rigol, A; Vidal, M

2009-09-01

Predicting the transfer of radionuclides in the environment for normal release, accidental, disposal or remediation scenarios in order to assess exposure requires the availability of an important number of generic parameter values. One of the key parameters in environmental assessment is the solid liquid distribution coefficient, K(d), which is used to predict radionuclide-soil interaction and subsequent radionuclide transport in the soil column. This article presents a review of K(d) values for uranium, radium, lead, polonium and thorium based on an extensive literature survey, including recent publications. The K(d) estimates were presented per soil groups defined by their texture and organic matter content (Sand, Loam, Clay and Organic), although the texture class seemed not to significantly affect K(d). Where relevant, other K(d) classification systems are proposed and correlations with soil parameters are highlighted. The K(d) values obtained in this compilation are compared with earlier review data.

Experimental datasets on engineering properties of expansive soil treated with common salt.

PubMed

Durotoye, Taiwo O; Akinmusuru, Joseph O; Ogundipe, Kunle E

2018-06-01

Construction of highway pavements or high rise structures over the expansive soils are always problematic due to failures of volume change or swelling characteristic experienced in the water permeability of the soil. The data in this article represented summary of (Durotoye et al., 2016; Durotoye, 2016) [1], [2]. The data explored different percentages of sodium chloride as additive in stabilizing the engineering properties of expansive soil compared with other available stabilizer previously worked on. Experimental procedures carried out on expansive soil include: (Liquid limit, Plastic limit, Plasticity index, Shrinkage limit, Specific gravity Free swell index and Optimum water content) to determine the swelling parameters and (maximum dry density, California bearing ratio and unconfined compressive strength) to determine the strength parameters. The results of the experiment were presented in pie charts.

Hydrologic and micrometeorologic data from an unsaturated zone study at a low-level radioactive waste burial site near Barnwell, South Carolina

USGS Publications Warehouse

Dennehy, K.F.; McMahon, P.B.

1985-01-01

Two years of selected hydrologic and micrometeorologic data collected at a low-level radioactive waste burial site near Barnwell, South Carolina are available on magnetic tape in card-image format. Hydrologic data include daily measurements of soil-moisture tension, soil-moisture specific conductance, and soil temperature at four monitoring site locations. Micrometeorlogic data include hourly measurements for the following parameters: dry- and wet-bulb temperatures, soil temperatures, soil heat flux, wind speeds and direction, incoming and reflected short-wave solar radiation, incoming and emitted long-wave radiation, net radiation and precipitation. (USGS)

Effects and risk assessment of linear alkylbenzene sulfonates in agricultural soil. 1. Short-term effects on soil microbiology.

PubMed

Elsgaard, L; Petersen, S O; Debosz, K

2001-08-01

Linear alkylbenzene sulfonates (LAS) may occur in sewage sludge that is applied to agricultural soil, in which LAS can be inhibitory to biological activity. As a part of a broader risk assessment of LAS in the terrestrial environment, we tested the short-term effects of aqueous LAS on microbial parameters in a sandy agricultural soil that was incubated for up to 11 d. The assays included 10 microbial soil parameters; ethylene degradation; potential ammonium oxidation; potential dehydrogenase activity; beta-glucosidase activity; iron reduction; the populations of cellulolytic bacteria, fungi and actinomycetes; the basal soil respiration; and the phospholipid fatty acid (PLFA) content. Except for beta-glucosidase activity, basal respiration, and total PLFA content, all soil parameters were sensitive to LAS, with EC10 values in the range of less than 8 to 22 mg/kg dry weight. This probably reflected a similar mode of LAS toxicity, ascribed to cell membrane interactions, and showed that sensitivity to LAS was common for various soil microorganisms. The extracellular beta-glucosidase activity was rather insensitive to LAS (ECI10, 47 mg/kg dry wt), whereas the basal soil respiration was not inhibited even at 793 mg/kg dry weight. This was interpreted as a combined response of inhibited and stimulated compartments of the microbial community. The PLFA content, surprisingly, showed no decrease even at 488 mg/kg. In conclusion, LAS inhibited specific microbial activities, although this could not be deduced from the basal respiration or the total PLFA content. The lowest EC10 values for microbial soil parameters were slightly higher than the predicted no-effect concentrations recently derived for plants and soil fauna (approximately 5 mg/kg dry wt).

Hydrologic characterization of desert soils with varying degrees of pedogenesis: 2. Inverse modeling for eff ective properties

USGS Publications Warehouse

Mirus, B.B.; Perkins, K.S.; Nimmo, J.R.; Singha, K.

2009-01-01

To understand their relation to pedogenic development, soil hydraulic properties in the Mojave Desert were investi- gated for three deposit types: (i) recently deposited sediments in an active wash, (ii) a soil of early Holocene age, and (iii) a highly developed soil of late Pleistocene age. Eff ective parameter values were estimated for a simplifi ed model based on Richards' equation using a fl ow simulator (VS2D), an inverse algorithm (UCODE-2005), and matric pressure and water content data from three ponded infi ltration experiments. The inverse problem framework was designed to account for the eff ects of subsurface lateral spreading of infi ltrated water. Although none of the inverse problems converged on a unique, best-fi t parameter set, a minimum standard error of regression was reached for each deposit type. Parameter sets from the numerous inversions that reached the minimum error were used to develop probability distribu tions for each parameter and deposit type. Electrical resistance imaging obtained for two of the three infi ltration experiments was used to independently test fl ow model performance. Simulations for the active wash and Holocene soil successfully depicted the lateral and vertical fl uxes. Simulations of the more pedogenically developed Pleistocene soil did not adequately replicate the observed fl ow processes, which would require a more complex conceptual model to include smaller scale heterogeneities. The inverse-modeling results, however, indicate that with increasing age, the steep slope of the soil water retention curve shitis toward more negative matric pressures. Assigning eff ective soil hydraulic properties based on soil age provides a promising framework for future development of regional-scale models of soil moisture dynamics in arid environments for land-management applications. ?? Soil Science Society of America.

Synergistic Utilization of Microwave Satellite Data and GRACE-Total Water Storage Anomaly for Improving Available Water Capacity Prediction in Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Gupta, M.; Bolten, J. D.; Lakshmi, V.

2015-12-01

The Mekong River is the longest river in Southeast Asia and the world's eighth largest in discharge with draining an area of 795,000 km² from the eastern watershed of the Tibetan Plateau to the Mekong Delta including three provinces of China, Myanmar, Lao PDR, Thailand, Cambodia and Viet Nam. This makes the life of people highly vulnerable to availability of the water resources as soil moisture is one of the major fundamental variables in global hydrological cycles. The day-to-day variability in soil moisture on field to global scales is an important quantity for early warning systems for events like flooding and drought. In addition to the extreme situations the accurate soil moisture retrieval are important for agricultural irrigation scheduling and water resource management. The present study proposes a method to determine the effective soil hydraulic parameters directly from information available for the soil moisture state from the recently launched SMAP (L-band) microwave remote sensing observations. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the physically based land surface model. This work addresses the improvement of available water capacity as the soil hydraulic parameters are optimized through the utilization of satellite-retrieved near surface soil moisture. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on FAO. The optimization process is divided into two steps: the state variable are optimized and the optimal parameter values are then transferred for retrieving soil moisture and streamflow. A homogeneous soil system is considered as the soil moisture from sensors such as AMSR-E/SMAP can only be retrieved for the top few centimeters of soil. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Improved Scheme of Modified Gaussian Deconvolution for Reflectance Spectra of Lunar Soils

NASA Technical Reports Server (NTRS)

Hiroi, T.; Pieters, C. M.; Noble, S. K.

2000-01-01

In our continuing effort for deconvolving reflectance spectra of lunar soils using the modified Gaussian model, a new scheme has been developed, including a new form of continuum. All the parameters are optimized with certain constraints.

Bioremediation of oil-contaminated soils by composting

NASA Astrophysics Data System (ADS)

Golodyaev, G. P.; Kostenkov, N. M.; Oznobikhin, V. I.

2009-08-01

Composting oil-contaminated soils under field conditions with the simultaneous optimization of their physicochemical and agrochemical parameters revealed the high efficiency of the soil purification, including that from benz[a]pyrene. The application of fertilizers and lime favored the intense development of indigenous microcenoses and the effective destruction of the oil. During the 95-day experimental period, the average daily rate of the oil decomposition was 157 mg/kg of soil. After the completion of the process, the soil became ecologically pure.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.

Microbial models with data-driven parameters predict stronger soil carbon responses to climate change.

PubMed

Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi

2015-06-01

Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.

Evaluating the environmental parameters that determine aerobic biodegradation half-lives of pesticides in soil with a multivariable approach.

PubMed

Wang, Yuxin; Lai, Adelene; Latino, Diogo; Fenner, Kathrin; Helbling, Damian E

2018-06-14

Aerobic biodegradation half-lives (half-lives) are key parameters used to evaluate pesticide persistence in soil. However, half-life estimates for individual pesticides often span several orders of magnitude, reflecting the impact that various environmental or experimental parameters have on half-lives in soil. In this work, we collected literature-reported half-lives for eleven pesticides along with associated metadata describing the environmental or experimental conditions under which they were derived. We then developed a multivariable framework to discover relationships between the half-lives and associated metadata. We first compared data for the herbicide atrazine collected from 95 laboratory and 65 field studies. We discovered that atrazine application history and soil texture were the parameters that have the largest influence on the observed half-lives in both types of studies. We then extended the analysis to include ten additional pesticides with data collected exclusively from laboratory studies. We found that, when data were available, pesticide application history and biomass concentrations were always positively associated with half-lives. The relevance of other parameters varied among the pesticides, but in some cases the variability could be explained by the physicochemical properties of the pesticides. For example, we found that the relative significance of the organic carbon content of soil for determining half-lives depends on the relative solubility of the pesticide. Altogether, our analyses highlight the reciprocal influence of both environmental parameters and intrinsic physicochemical properties for determining half-lives in soil. Copyright © 2018 Elsevier Ltd. All rights reserved.

Integration of Satellite, Global Reanalysis Data and Macroscale Hydrological Model for Drought Assessment in Sub-Tropical Region of India

NASA Astrophysics Data System (ADS)

Pandey, V.; Srivastava, P. K.

2018-04-01

Change in soil moisture regime is highly relevant for agricultural drought, which can be best analyzed in terms of Soil Moisture Deficit Index (SMDI). A macroscale hydrological model Variable Infiltration Capacity (VIC) was used to simulate the hydro-climatological fluxes including evapotranspiration, runoff, and soil moisture storage to reconstruct the severity and duration of agricultural drought over semi-arid region of India. The simulations in VIC were performed at 0.25° spatial resolution by using a set of meteorological forcing data, soil parameters and Land Use Land Cover (LULC) and vegetation parameters. For calibration and validation, soil parameters obtained from National Bureau of Soil Survey and Land Use Planning (NBSSLUP) and ESA's Climate Change Initiative soil moisture (CCI-SM) data respectively. The analysis of results demonstrates that most of the study regions (> 80 %) especially for central northern part are affected by drought condition. The year 2001, 2002, 2007, 2008 and 2009 was highly affected by agricultural drought. Due to high average and maximum temperature, we observed higher soil evaporation that reduces the surface soil moisture significantly as well as the high topographic variations; coarse soil texture and moderate to high wind speed enhanced the drying upper soil moisture layer that incorporate higher negative SMDI over the study area. These findings can also facilitate the archetype in terms of daily time step data, lengths of the simulation period, various hydro-climatological outputs and use of reasonable hydrological model.

Microbial effects on two tropical soils amended with different types of biochar

NASA Astrophysics Data System (ADS)

Paz, Jorge; Méndez, Ana; Fun, Shenglei; Gascó, Gabriel

2013-04-01

There is an increasing interest in using biochar as soil amendment due to its potential to reduce greenhouse gas emissions from soils and to mitigate heavy metal pollution. In addition, sometimes biochar has been found to increase soil productivity due to its favourable effect on soil aggregation and water holding capacity. However, results obtained can differ greatly depending on the type of biochar utilised. On the other hand, the response of the microbial community to biochar addition is not so well understood. In our experiment we have sampled two soils, differing in their fertility status. A greenhouse pot experiment was established to see the effect of adding four different biochars, differing on their feedstock (Miscanthus, sewage sludge, paper mill waste and pinewood). Additionally, half of the samples excluded soil earthworms, while the other half had 3 individuals of the earthworm Pontoscolex corethrurus. Pots, containing 400 g of soil, were planted with proso millet. Assessed parameters included millet height, soil microbial biomass and soil enzymatic activity related to different biogeochemical cycles (invertase, B-glucosaminidase, B-glucosidase, urease, phosphomonoesterase, arylsulphatase) The effects of biochar on soil biological properties depended on the type of feedstock used for biochar production and pre-existent soil parameters such as soil fertility status. Earthworm presence generally had a positive effect on soil microbial properties.

Short-term effects of irrigation with treated domestic wastewater on microbiological activity of a Vertic xerofluvent soil under Mediterranean conditions.

PubMed

Kayikcioglu, Huseyin Husnu

2012-07-15

Approximately 70% of the world water use, including all the water diverted from rivers and pumped from underground, is used for agricultural irrigation, so the reuse of treated domestic wastewater (TWW) for purposes such as agricultural and landscape irrigation reduces the amount of water that needs to be extracted from natural water sources as well as reducing discharge of wastewater to the environment. Thus, TWW is a valuable water source for recycling and reusing in arid and semi-arid regions which are frequently confronting water shortages. In this regard, this study was planned to reveal the short-term effects of advanced-TWW irrigation on microbial parameters of Vertic xerofluvent soil. For this purpose, certain parameters were measured in the study, including soil total organic carbon (C(org)), N-mineralization (N(min)), microbial biomass carbon (C(mic)), soil microbial quotient (C(mic)/C(org)) and the activities of the enzymes dehydrogenase (DHG), urease (UA), alkaline phosphatase (ALKPA), β-glucosidase (GLU) and aryl sulphatase (ArSA) in soils irrigated with TWW and fresh water (FW). All of the microbial parameters were negatively affected by TWW irrigation. Microbial parameters decreased by 10.1%-54.1% in comparison with the FW plots. This decrease especially in enzymatic activities of soil irrigated with TWW, presumably due to some heavy metals inhibited their activity associated with the soil types and the concentrations of heavy metals in wastewater. In contrast, C(mic)/C(org) was found higher in the plots irrigated with TWW at the end of the experiment. The addition of organic matter to soil by irrigation with TWW is cause for the increase in this ratio. The dose of irrigation should be modified to reduce the quantity and to increase the frequency of application to avoid the loss of aggregation and salt accumulation. TWW irrigation is a strategy with many benefits to agricultural land management; however, long-term studies should be implemented to investigate the microbiological characteristics of soil and to assess the feasibility of wastewater reuse for irrigation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamic Response of Reinforced Soil Systems. Volume 1. Report

DTIC Science & Technology

1993-03-01

include Security Clas~sification) DYNAMIC RWSPC!SE OF REIFý1Cý SOIL SYSTEM~, VCTJI4E I OF II: PREPO~r 󈧐. PERSONAL AUTHOR($) BMW3U, R.C.; FRAWASZY...protected by a burster slab. These protection measures are costly, time consuming to construct, and sensitive to multiple strikes. Soil has been used to...characterize the static load-deflection behavior of the reinforced soil. Dynamic pullout tests were then performed using the same parameters as the static

Informing soil models using pedotransfer functions: challenges and perspectives

NASA Astrophysics Data System (ADS)

Pachepsky, Yakov; Romano, Nunzio

2015-04-01

Pedotransfer functions (PTFs) are empirical relationships between parameters of soil models and more easily obtainable data on soil properties. PTFs have become an indispensable tool in modeling soil processes. As alternative methods to direct measurements, they bridge the data we have and data we need by using soil survey and monitoring data to enable modeling for real-world applications. Pedotransfer is extensively used in soil models addressing the most pressing environmental issues. The following is an attempt to provoke a discussion by listing current issues that are faced by PTF development. 1. As more intricate biogeochemical processes are being modeled, development of PTFs for parameters of those processes becomes essential. 2. Since the equations to express PTF relationships are essentially unknown, there has been a trend to employ highly nonlinear equations, e.g. neural networks, which in theory are flexible enough to simulate any dependence. This, however, comes with the penalty of large number of coefficients that are difficult to estimate reliably. A preliminary classification applied to PTF inputs and PTF development for each of the resulting groups may provide simple, transparent, and more reliable pedotransfer equations. 3. The multiplicity of models, i.e. presence of several models producing the same output variables, is commonly found in soil modeling, and is a typical feature in the PTF research field. However, PTF intercomparisons are lagging behind PTF development. This is aggravated by the fact that coefficients of PTF based on machine-learning methods are usually not reported. 4. The existence of PTFs is the result of some soil processes. Using models of those processes to generate PTFs, and more general, developing physics-based PTFs remains to be explored. 5. Estimating the variability of soil model parameters becomes increasingly important, as the newer modeling technologies such as data assimilation, ensemble modeling, and model abstraction, become progressively more popular. The variability PTFs rely on the spatio-temporal dynamics of soil variables, and that opens new sources of PTF inputs stemming from technology advances such as monitoring networks, remote and proximal sensing, and omics. 6. Burgeoning PTF development has not so far affected several persisting regional knowledge gaps. Remarkably little effort was put so far into PTF development for saline soils, calcareous and gypsiferous soils, peat soils, paddy soils, soils with well expressed shrink-swell behavior, and soils affected by freeze-thaw cycles. 7. Soils from tropical regions are quite often considered as a pseudo-entity for which a single PTF can be applied. This assumption will not be needed as more regional data will be accumulated and analyzed. 8. Other advances in regional PTFs will be possible due to presence of large databases on region-specific useful PTF inputs such as moisture equivalent, laser diffractometry data, or soil specific surface. 9. Most of flux models in soils, be it water, solutes, gas, or heat, involve parameters that are scale-dependent. Including scale dependencies in PTFs will be critical to improve PTF usability. 10. Another scale-related matter is pedotransfer for coarse-scale soil modeling, for example, in weather or climate models. Soil hydraulic parameters in these models cannot be measured and the efficiency of the pedotransfer can be evaluated only in terms of its utility. There is a pressing need to determine combinations of pedotransfer and upscaling procedures that can lead to the derivation of suitable coarse-scale soil model parameters. 11. The spatial coarse scale often assumes a coarse temporal support, and that may lead to including in PTFs other environmental variables such as topographic, weather, and management attributes. 12. Some PTF inputs are time- or space-dependent, and yet little is known whether the spatial or temporal structure of PTF outputs is properly predicted from such inputs 13. Further exploration is needed to use PTF as a source of hypotheses on and insights into relationships between soil processes and soil composition as well as between soil structure and soil functioning. PTFs are empirical relationships and their accuracy outside the database used for the PTF development is essentially unknown. Therefore they should never be considered as an ultimate source of parameters in soil modeling. Rather they strive to provide a balance between accuracy and availability. The primary role of PTF is to assist in modeling for screening and comparative purposes, establishing ranges and/or probability distributions of model parameters, and creating realistic synthetic soil datasets and scenarios. Developing and improving PTFs will remain the mainstream way of packaging data and knowledge for applications of soil modeling.

Assessing soil biodiversity potentials in Europe.

PubMed

Aksoy, Ece; Louwagie, Geertrui; Gardi, Ciro; Gregor, Mirko; Schröder, Christoph; Löhnertz, Manuel

2017-07-01

Soil is important as a critical component for the functioning of terrestrial ecosystems. The largest part of the terrestrial biodiversity relies, directly or indirectly, on soil. Furthermore, soil itself is habitat to a great diversity of organisms. The suitability of soil to host such a diversity is strongly related to its physico-chemical features and environmental properties. However, due to the complexity of both soil and biodiversity, it is difficult to identify a clear and unambiguous relationship between environmental parameters and soil biota. Nevertheless, the increasing diffusion of a more integrated view of ecosystems, and in particular the development of the concept of ecosystem services, highlights the need for a better comprehension of the role played by soils in offering these services, including the habitat provision. An assessment of the capability of soils to host biodiversity would contribute to evaluate the quality of soils in order to help policy makers with the development of appropriate and sustainable management actions. However, so far, the heterogeneity of soils has been a barrier to the production of a large-scale framework that directly links soil features to organisms living within it. The current knowledge on the effects of soil physico-chemical properties on biota and the available data at continental scale open the way towards such an evaluation. In this study, the soil habitat potential for biodiversity was assessed and mapped for the first time throughout Europe by combining several soil features (pH, soil texture and soil organic matter) with environmental parameters (potential evapotranspiration, average temperature, soil biomass productivity and land use type). Considering the increasingly recognized importance of soils and their biodiversity in providing ecosystem services, the proposed approach appears to be a promising tool that may contribute to open a forum on the need to include soils in future environmental policy making decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

Modelling the water balance of irrigated fields in tropical floodplain soils using Hydrus-1D

NASA Astrophysics Data System (ADS)

Beyene, Abebech; Frankl, Amaury; Verhoest, Niko E. C.; Tilahun, Seifu; Alamirew, Tena; Adgo, Enyew; Nyssen, Jan

2017-04-01

Accurate estimation of evaporation, transpiration and deep percolation is crucial in irrigated agriculture and the sustainable management of water resources. Here, the Hydrus-1D process-based numerical model was used to estimate the actual transpiration, soil evaporation and deep percolation from irrigated fields of floodplain soils. Field experiments were conducted from Dec 2015 to May 2016 in a small irrigation scheme (50 ha) called 'Shina' located in the Lake Tana floodplains of Ethiopia. Six experimental plots (three for onion and three for maize) were selected along a topographic transect to account for soil and groundwater variability. Irrigation amount (400 to 550 mm during the growing period) was measured using V-notches installed at each plot boundary and daily groundwater levels were measured manually from piezometers. There was no surface runoff observed in the growing period and rainfall was measured using a manual rain gauge. All daily weather data required for the evapotranspiration calculation using Pen Man Monteith equation were collected from a nearby metrological station. The soil profiles were described for each field to include the vertical soil heterogeneity in the soil water balance simulations. The soil texture, organic matter, bulk density, field capacity, wilting point and saturated moisture content were measured for all the soil horizons. Soil moisture monitoring at 30 and 60 cm depths was performed. The soil hydraulic parameters for each horizon was estimated using KNN pedotransfer functions for tropical soils and were effectively fitted using the RETC program (R2= 0.98±0.011) for initial prediction. A local sensitivity analysis was performed to select and optimize the most important hydraulic parameters for soil water flow in the unsaturated zone. The most sensitive parameters were saturated hydraulic conductivity (Ks), saturated moisture content (θs) and pore size distribution (n). Inverse modelling using Hydrus-1D further optimized these parameters (R2 =0.74±0.13). Using the optimized hydraulic parameters, the soil water dynamics were simulated using Hydrus-1D. The atmospheric boundary conditions with surface runoff was used as upper boundary condition with measured rainfall and irrigation input data. The variable pressure head was selected as lower boundary conditions with daily records of groundwater level as time-variable input data. The Hydrus-1D model was successfully applied and calibrated in the study area. The average seasonal actual transpiration values are 310±13 mm for onion and 429±24.7 mm for maize fields. The seasonal average soil evaporation ranges from 12±2.05 mm for maize fields to 38±2.85 mm for onion fields. The seasonal deep percolation from irrigation appeared to be 12 to 40% of applied irrigation. The Hydrus-1D model was able to simulate the temporal and the spatial variations of soil water dynamics in the unsaturated zone of tropical floodplain soils. Key words: floodplains, hydraulic parameters, parameter optimization, small-scale irrigation

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jędrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jedrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Evaluation of Two Soil Water Redistribution Models (Finite Difference and Hourly Cascade Approach) Through The Comparison of Continuous field Sensor-Based Measurements

NASA Astrophysics Data System (ADS)

Ferreyra, R.; Stockle, C. O.; Huggins, D. R.

2014-12-01

Soil water storage and dynamics are of critical importance for a variety of processes in terrestrial ecosystems, including agriculture. Many of those systems are under significant pressure in terms of water availability and use. Therefore, assessing alternative scenarios through hydrological models is an increasingly valuable exercise. Soil water holding capacity is defined by the concepts of soil field capacity and plant available water, which are directly related to soil physical properties. Both concepts define the energy status of water in the root system and closely interact with plant physiological processes. Furthermore, these concepts play a key role in the environmental transport of nutrients and pollutants. Soil physical parameters (e.g. saturated hydraulic conductivity, total porosity and water release curve) are required as input for field-scale soil water redistribution models. These parameters are normally not easy to measure or monitor, and estimation through pedotransfer functions is often inadequate. Our objectives are to improve field-scale hydrological modeling by: (1) assessing new undisturbed methodologies for determining important soil physical parameters necessary for model inputs; and (2) evaluating model outputs, making a detailed specification of soil parameters and the particular boundary condition that are driving water movement under two contrasting environments. Soil physical properties (saturated hydraulic conductivity and determination of water release curves) were quantified using undisturbed laboratory methodologies for two different soil textural classes (silt loam and sandy loam) and used to evaluate two soil water redistribution models (finite difference solution and hourly cascade approach). We will report on model corroboration results performed using in situ, continuous, field measurements with soil water content capacitance probes and digital tensiometers. Here, natural drainage and water redistribution were monitored following a controlled water application where the study areas were isolated from other water inputs and outputs. We will also report on the assessment of two soil water sensors (Decagon Devices 5TM capacitance probe and UMS T4 tensiometers) for the two soil textural classes in terms of consistency and replicability.

A factorial assessment of the sensitivity of the BATS land-surface parameterization scheme. [BATS (Biosphere-Atmosphere Transfer Scheme)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henderson-Sellers, A.

Land-surface schemes developed for incorporation into global climate models include parameterizations that are not yet fully validated and depend upon the specification of a large (20-50) number of ecological and soil parameters, the values of which are not yet well known. There are two methods of investigating the sensitivity of a land-surface scheme to prescribed values: simple one-at-a-time changes or factorial experiments. Factorial experiments offer information about interactions between parameters and are thus a more powerful tool. Here the results of a suite of factorial experiments are reported. These are designed (i) to illustrate the usefulness of this methodology andmore » (ii) to identify factors important to the performance of complex land-surface schemes. The Biosphere-Atmosphere Transfer Scheme (BATS) is used and its sensitivity is considered (a) to prescribed ecological and soil parameters and (b) to atmospheric forcing used in the off-line tests undertaken. Results indicate that the most important atmospheric forcings are mean monthly temperature and the interaction between mean monthly temperature and total monthly precipitation, although fractional cloudiness and other parameters are also important. The most important ecological parameters are vegetation roughness length, soil porosity, and a factor describing the sensitivity of the stomatal resistance of vegetation to the amount of photosynthetically active solar radiation and, to a lesser extent, soil and vegetation albedos. Two-factor interactions including vegetation roughness length are more important than many of the 23 specified single factors. The results of factorial sensitivity experiments such as these could form the basis for intercomparison of land-surface parameterization schemes and for field experiments and satellite-based observation programs aimed at improving evaluation of important parameters.« less

Effects of long-term continuous cropping on soil nematode community and soil condition associated with replant problem in strawberry habitat.

PubMed

Li, Xingyue; Lewis, Edwin E; Liu, Qizhi; Li, Heqin; Bai, Chunqi; Wang, Yuzhu

2016-08-10

Continuous cropping changes soil physiochemical parameters, enzymes and microorganism communities, causing "replant problem" in strawberry cultivation. We hypothesized that soil nematode community would reflect the changes in soil conditions caused by long-term continuous cropping, in ways that are consistent and predictable. To test this hypothesis, we studied the soil nematode communities and several soil parameters, including the concentration of soil phenolic acids, organic matter and nitrogen levels, in strawberry greenhouse under continuous-cropping for five different durations. Soil pH significantly decreased, and four phenolic acids, i.e., p-hydroxybenzoic acid, ferulic acid, cinnamic acid and p-coumaric acid, accumulated with time under continuous cropping. The four phenolic acids were highly toxic to Acrobeloides spp., the eudominant genus in non-continuous cropping, causing it to reduce to a resident genus after seven-years of continuous cropping. Decreased nematode diversity indicated loss of ecosystem stability and sustainability because of continuous-cropping practice. Moreover, the dominant decomposition pathway was altered from bacterial to fungal under continuous cropping. Our results suggest that along with the continuous-cropping time in strawberry habitat, the soil food web is disturbed, and the available plant nutrition as well as the general health of the soil deteriorates; these changes can be indicated by soil nematode community.

Effects of long-term continuous cropping on soil nematode community and soil condition associated with replant problem in strawberry habitat

NASA Astrophysics Data System (ADS)

Li, Xingyue; Lewis, Edwin E.; Liu, Qizhi; Li, Heqin; Bai, Chunqi; Wang, Yuzhu

2016-08-01

Continuous cropping changes soil physiochemical parameters, enzymes and microorganism communities, causing “replant problem” in strawberry cultivation. We hypothesized that soil nematode community would reflect the changes in soil conditions caused by long-term continuous cropping, in ways that are consistent and predictable. To test this hypothesis, we studied the soil nematode communities and several soil parameters, including the concentration of soil phenolic acids, organic matter and nitrogen levels, in strawberry greenhouse under continuous-cropping for five different durations. Soil pH significantly decreased, and four phenolic acids, i.e., p-hydroxybenzoic acid, ferulic acid, cinnamic acid and p-coumaric acid, accumulated with time under continuous cropping. The four phenolic acids were highly toxic to Acrobeloides spp., the eudominant genus in non-continuous cropping, causing it to reduce to a resident genus after seven-years of continuous cropping. Decreased nematode diversity indicated loss of ecosystem stability and sustainability because of continuous-cropping practice. Moreover, the dominant decomposition pathway was altered from bacterial to fungal under continuous cropping. Our results suggest that along with the continuous-cropping time in strawberry habitat, the soil food web is disturbed, and the available plant nutrition as well as the general health of the soil deteriorates; these changes can be indicated by soil nematode community.

Urban Soil Hydrology: bridging the data gap with a nationwide field study

NASA Astrophysics Data System (ADS)

Schifman, L. A.; Shuster, W.

2016-12-01

Urban communities generally rely on hydrologic models or tools for assessing suitable sites for green infrastructure. These rainfall-runoff models, e.g. National Stormwater Calculator (NSWC), query soil hydrologic information from national databases, e.g. Soil Survey Geographic Database (SSURGO), or are estimated via pedotransfer-based algorithms like USDA Rosetta. As part of urban soil hydrologic assessments we have collected soil textural and hydrologic data in 12 cities throughout the United States and compared these measurements to NSWC and SSURGO queried infiltration rates (Kunsat) and Rosetta-estimated drainage rates (Ksat and Kunsat). We found that soil hydrologic parameters obtained through pedotransfer functions and queries to soil databases are not representative of field-measured values (RMSE range from 6.2 to 15.2 for infiltration and from 13.2 to 16.3 for drainage). Although the NSWC queries SSURGO, we found that SSURGO overestimates infiltration and NSWC underestimates with MEs of 4.9, and -1.4, respectively. In Rosetta, we found that pedotransfer functions overestimated drainage rates (MEs 1.8 to 3.8). In an attempt to improve drainage estimates using Rosetta the soil texture was adjusted in soils with an apparent portion of finer sands. Here, sand included: very coarse, coarse, and medium sand, whereas silt included fine, and very fine sand and silt, with the justification that fine sands behave similarly to silt. These adjusted estimates resulted in generally underestimating drainage and still not suitable for use in planning for stormwater detention (e.g., infiltrative green infrastructure). With this work we highlight the importance of obtaining field measured values when assessing sites for green infrastructure planning instead of relying on estimates, as the discrepancies in sensitive parameters such as Kunsat and Ksat, implications for parameter selection in error propagation through rainfall-runoff models, and consequences for over- or under-design of stormwater control measures for detention.

Soil eco-physiological indicators from a coal mining area in El Bierzo District (Spain).

NASA Astrophysics Data System (ADS)

Díaz Puente, Fco. Javier; Mejuto Mendieta, Marcos; Cardona García, Ana Isabel; Rodríguez Gallego, Vergelina; García Álvarez, Avelino

2010-05-01

CIEMAT. Avda. Complutense, 22. 28040 Madrid. Spain. The El Bierzo carboniferous basin (León, N.W. of Spain) is placed in a tenth of the surface of this district, in the area called "Bierzo Alto". Coal has been mined in El Bierzo from the late XVIII century, having been intensely exploited during the XX century. The mining activity has left a heritage of withdrawed mining structures. Nowadays some mining activity remains in the area, and new exploitations based on open pit processes, cause the burial of natural soil with overlaying mine tailings. Characterization and study of the edaphic landscapes in the area is a necessary activity within the framework of its overall restoration planning, also providing fundamental information for the design and monitoring of waste coal recovery activities. For this work eight zones were chosen, representing the spatial variability within the upper basin of the Rodrigatos river, into the Bierzo Alto, including reference areas not affected by mining activities. In addition three mine tailings outside the area are included in this work to cover the variability of restoration processes. After a first study, based on physical, physico-chemical and chemical characteristics of soils, we have continued the study including some eco-physiological parameters. The objective of this work is to identify potential soil disruption, its extent and causes. Soil microbial activity is influenced by a wide set of soil characteristics. Eco-physiological parameters analysed in this work are: • Microbial Biomass carbon • Basal Respirometry • Maximum respiratory rate Microbial biomass carbon was analysed according the Substrate Induced Respirometry (SIR) method. Relational parameters such as metabolic quotient (CO2-C/Cmic) and the Cmic/Corg ratio have been obtained from these variables. Our results shown that soil microbial biomass carbon is strongly influenced by the water holding capacity (WHC) of the samples (R=0,895) as well as by organic matter (O.M.) content (R=0,801), in addition, WHC and O.M. are also strongly related (R=0,794), so O.M. seems to be the key variable in the soils studied. Recovery stage of the studied plots may be stablished with each of the mentioned parameters. All the correlations mentioned were significant at P<0.001 level. Maximum respiratory rate as well as Metabolic quotient data also allow to identify most stressed soils, corresponding with coal mine tailings in the Rodrigatos river basin. Results obtained for Cmic/Corg ratio show difficulties to be interpreted in the case of mine tailings. The practice of burying soils with coal mining debris has provided this new surface with relatively high inputs of organic carbon, in excess of this provided from fresh organic matter. In our study eco-physiological parameters are usefull tools in order to clasify the restoration level of mine tailings, specially those parameters having a high correlation with the organic matter content, Nevertheless some of those parameters then present some added difficulties to be interpreted that will be discussed in this work. Acknowledgement: We appreciate technical support in the field from Mr. Luis del Riego Celada, as well as the financial support from the Fundación Ciudad de la Energía.

Sensitivity Analysis of the Land Surface Model NOAH-MP for Different Model Fluxes

NASA Astrophysics Data System (ADS)

Mai, Juliane; Thober, Stephan; Samaniego, Luis; Branch, Oliver; Wulfmeyer, Volker; Clark, Martyn; Attinger, Sabine; Kumar, Rohini; Cuntz, Matthias

2015-04-01

Land Surface Models (LSMs) use a plenitude of process descriptions to represent the carbon, energy and water cycles. They are highly complex and computationally expensive. Practitioners, however, are often only interested in specific outputs of the model such as latent heat or surface runoff. In model applications like parameter estimation, the most important parameters are then chosen by experience or expert knowledge. Hydrologists interested in surface runoff therefore chose mostly soil parameters while biogeochemists interested in carbon fluxes focus on vegetation parameters. However, this might lead to the omission of parameters that are important, for example, through strong interactions with the parameters chosen. It also happens during model development that some process descriptions contain fixed values, which are supposedly unimportant parameters. However, these hidden parameters remain normally undetected although they might be highly relevant during model calibration. Sensitivity analyses are used to identify informative model parameters for a specific model output. Standard methods for sensitivity analysis such as Sobol indexes require large amounts of model evaluations, specifically in case of many model parameters. We hence propose to first use a recently developed inexpensive sequential screening method based on Elementary Effects that has proven to identify the relevant informative parameters. This reduces the number parameters and therefore model evaluations for subsequent analyses such as sensitivity analysis or model calibration. In this study, we quantify parametric sensitivities of the land surface model NOAH-MP that is a state-of-the-art LSM and used at regional scale as the land surface scheme of the atmospheric Weather Research and Forecasting Model (WRF). NOAH-MP contains multiple process parameterizations yielding a considerable amount of parameters (˜ 100). Sensitivities for the three model outputs (a) surface runoff, (b) soil drainage and (c) latent heat are calculated on twelve Model Parameter Estimation Experiment (MOPEX) catchments ranging in size from 1020 to 4421 km2. This allows investigation of parametric sensitivities for distinct hydro-climatic characteristics, emphasizing different land-surface processes. The sequential screening identifies the most informative parameters of NOAH-MP for different model output variables. The number of parameters is reduced substantially for all of the three model outputs to approximately 25. The subsequent Sobol method quantifies the sensitivities of these informative parameters. The study demonstrates the existence of sensitive, important parameters in almost all parts of the model irrespective of the considered output. Soil parameters, e.g., are informative for all three output variables whereas plant parameters are not only informative for latent heat but also for soil drainage because soil drainage is strongly coupled to transpiration through the soil water balance. These results contrast to the choice of only soil parameters in hydrological studies and only plant parameters in biogeochemical ones. The sequential screening identified several important hidden parameters that carry large sensitivities and have hence to be included during model calibration.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Soil properties affect the toxicities of 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) to the enchytraeid worm Enchytraeus crypticus.

PubMed

Kuperman, Roman G; Checkai, Ronald T; Simini, Michael; Phillips, Carlton T; Kolakowski, Jan E; Lanno, Roman

2013-11-01

The authors investigated individual toxicities of 2,4,6-trinitrotoluene (TNT) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) to the potworm Enchytraeus crypticus using the enchytraeid reproduction test. Studies were designed to generate ecotoxicological benchmarks that can be used for developing ecological soil-screening levels for ecological risk assessments of contaminated soils and to identify and characterize the predominant soil physicochemical parameters that can affect the toxicities of TNT and RDX to E. crypticus. Soils, which had a wide range of physicochemical parameters, included Teller sandy loam, Sassafras sandy loam, Richfield clay loam, Kirkland clay loam, and Webster clay loam. Analyses of quantitative relationships between the toxicological benchmarks for TNT and soil property measurements identified soil organic matter content as the dominant property mitigating TNT toxicity for juvenile production by E. crypticus in freshly amended soil. Both the clay and organic matter contents of the soil modulated reproduction toxicity of TNT that was weathered and aged in soil for 3 mo. Toxicity of RDX for E. crypticus was greater in the coarse-textured sandy loam soils compared with the fine-textured clay loam soils. The present studies revealed alterations in toxicity to E. crypticus after weathering and aging TNT in soil, and these alterations were soil- and endpoint-specific. © 2013 SETAC.

Thermal properties of degraded lowland peat-moorsh soils

NASA Astrophysics Data System (ADS)

Gnatowski, Tomasz

2016-04-01

Soil thermal properties, i.e.: specific heat capacity (c), thermal conductivity (K), volumetric heat capacity (C) govern the thermal environment and heat transport through the soil. Hence the precise knowledge and accurate predictions of these properties for peaty soils with high amount of organic matter are especially important for the proper forecasting of soil temperature and thus it may lead to a better assessment of the greenhouse gas emissions created by microbiological activity of the peatlands. The objective of the study was to develop the predictive models of the selected thermal parameters of peat-moorsh soils in terms of their potential applicability for forecasting changes of soil temperature in degraded ecosystems of the Middle Biebrza River Valley area. Evaluation of the soil thermal properties was conducted for the parameters: specific heat capacity (c), volumetric heat capacities of the dry and saturated soil (Cdry, Csat) and thermal conductivities of the dry and saturated soil (Kdry, Ksat). The thermal parameters were measured using the dual-needle probe (KD2-Pro) on soil samples collected from seven peaty soils, representing total 24 horizons. The surface layers were characterized by different degrees of advancement of soil degradation dependent on intensiveness of the cultivation practises (peaty and humic moorsh). The underlying soil layers contain peat deposits of different botanical composition (peat-moss, sedge-reed, reed and alder) and varying degrees of decomposition of the organic matter, from H1 to H7 (von Post scale). Based on the research results it has been shown that the specific heat capacity of the soils differs depending on the type of soil (type of moorsh and type of peat). The range of changes varied from 1276 J.kg-1.K-1 in the humic moorsh soil to 1944 J.kg-1.K-1 in the low decomposed sedge-moss peat. It has also been stated that in degraded peat soils with the increasing of the ash content in the soil the value of specific heat has decreased in a non-linear manner. Thermal parameters of the dry mass of the studied soils (Kdry, Cdry) were characterised by the mean value of approximately 0.11±0.028 W.m-1.K-1 and 0.781±0.220 MJ.m-3.K-1. The application of the correlation analysis showed that the most significant predictor of these properties of soils is the soil bulk density which, respectively explains: 54.6% and 67.1% of their variation. The increase of the accuracy in determining Kdry and Cdry was obtained by developing regression models, which apart from the bulk density also include the chemical properties of the peat soils. In the fully saturated soil the Ksat value ranged from 0.47 to 0.63 W.m-1.K-1, and the Csat varied from 3.200 to 3.995 MJ.m-3.K-1. The variation coefficients of these soil thermal features are at the level of approx. 5%. The obtained results allowed to conclude that the significant diversity of studied soils doesn't cause the significant differences in thermal soil parameters in fully saturated soils. The developed statistical relationships indicate that parameters Ksat and Csat were poorly correlated with saturated moisture content.

Constraining ecosystem model with adaptive Metropolis algorithm using boreal forest site eddy covariance measurements

NASA Astrophysics Data System (ADS)

Mäkelä, Jarmo; Susiluoto, Jouni; Markkanen, Tiina; Aurela, Mika; Järvinen, Heikki; Mammarella, Ivan; Hagemann, Stefan; Aalto, Tuula

2016-12-01

We examined parameter optimisation in the JSBACH (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013) ecosystem model, applied to two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon-exchange-related formulations, and optimised them using the adaptive Metropolis (AM) algorithm for Hyytiälä with a 5-year calibration period (2000-2004) followed by a 4-year validation period (2005-2008). Sodankylä acted as an independent validation site, where optimisations were not made. The tuning provided estimates for full distribution of possible parameters, along with information about correlation, sensitivity and identifiability. Some parameters were correlated with each other due to a phenomenological connection between carbon uptake and water stress or other connections due to the set-up of the model formulations. The latter holds especially for vegetation phenology parameters. The least identifiable parameters include phenology parameters, parameters connecting relative humidity and soil dryness, and the field capacity of the skin reservoir. These soil parameters were masked by the large contribution from vegetation transpiration. In addition to leaf area index and the maximum carboxylation rate, the most effective parameters adjusting the gross primary production (GPP) and evapotranspiration (ET) fluxes in seasonal tuning were related to soil wilting point, drainage and moisture stress imposed on vegetation. For daily and half-hourly tunings the most important parameters were the ratio of leaf internal CO2 concentration to external CO2 and the parameter connecting relative humidity and soil dryness. Effectively the seasonal tuning transferred water from soil moisture into ET, and daily and half-hourly tunings reversed this process. The seasonal tuning improved the month-to-month development of GPP and ET, and produced the most stable estimates of water use efficiency. When compared to the seasonal tuning, the daily tuning is worse on the seasonal scale. However, daily parametrisation reproduced the observations for average diurnal cycle best, except for the GPP for Sodankylä validation period, where half-hourly tuned parameters were better. In general, the daily tuning provided the largest reduction in model-data mismatch. The models response to drought was unaffected by our parametrisations and further studies are needed into enhancing the dry response in JSBACH.

A Bayesian-based multilevel factorial analysis method for analyzing parameter uncertainty of hydrological model

NASA Astrophysics Data System (ADS)

Liu, Y. R.; Li, Y. P.; Huang, G. H.; Zhang, J. L.; Fan, Y. R.

2017-10-01

In this study, a Bayesian-based multilevel factorial analysis (BMFA) method is developed to assess parameter uncertainties and their effects on hydrological model responses. In BMFA, Differential Evolution Adaptive Metropolis (DREAM) algorithm is employed to approximate the posterior distributions of model parameters with Bayesian inference; factorial analysis (FA) technique is used for measuring the specific variations of hydrological responses in terms of posterior distributions to investigate the individual and interactive effects of parameters on model outputs. BMFA is then applied to a case study of the Jinghe River watershed in the Loess Plateau of China to display its validity and applicability. The uncertainties of four sensitive parameters, including soil conservation service runoff curve number to moisture condition II (CN2), soil hydraulic conductivity (SOL_K), plant available water capacity (SOL_AWC), and soil depth (SOL_Z), are investigated. Results reveal that (i) CN2 has positive effect on peak flow, implying that the concentrated rainfall during rainy season can cause infiltration-excess surface flow, which is an considerable contributor to peak flow in this watershed; (ii) SOL_K has positive effect on average flow, implying that the widely distributed cambisols can lead to medium percolation capacity; (iii) the interaction between SOL_AWC and SOL_Z has noticeable effect on the peak flow and their effects are dependent upon each other, which discloses that soil depth can significant influence the processes of plant uptake of soil water in this watershed. Based on the above findings, the significant parameters and the relationship among uncertain parameters can be specified, such that hydrological model's capability for simulating/predicting water resources of the Jinghe River watershed can be improved.

Soil water content and evaporation determined by thermal parameters obtained from ground-based and remote measurements

NASA Technical Reports Server (NTRS)

Reginato, R. J.; Idso, S. B.; Jackson, R. D.; Vedder, J. F.; Blanchard, M. B.; Goettelman, R.

1976-01-01

Soil water contents from both smooth and rough bare soil were estimated from remotely sensed surface soil and air temperatures. An inverse relationship between two thermal parameters and gravimetric soil water content was found for Avondale loam when its water content was between air-dry and field capacity. These parameters, daily maximum minus minimum surface soil temperature and daily maximum soil minus air temperature, appear to describe the relationship reasonably well. These two parameters also describe relative soil water evaporation (actual/potential). Surface soil temperatures showed good agreement among three measurement techniques: in situ thermocouples, a ground-based infrared radiation thermometer, and the thermal infrared band of an airborne multispectral scanner.

Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Carbon Content in an Arctic Tundra

NASA Astrophysics Data System (ADS)

Tran, A. P.; Dafflon, B.; Hubbard, S.

2017-12-01

Soil organic carbon (SOC) is crucial for predicting carbon climate feedbacks in the vulnerable organic-rich Arctic region. However, it is challenging to achieve this property due to the general limitations of conventional core sampling and analysis methods. In this study, we develop an inversion scheme that uses single or multiple datasets, including soil liquid water content, temperature and ERT data, to estimate the vertical profile of SOC content. Our approach relies on the fact that SOC content strongly influences soil hydrological-thermal parameters, and therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. The scheme includes several advantages. First, this is the first time SOC content is estimated by using a coupled hydrogeophysical inversion. Second, by using the Community Land Model, we can account for the land surface dynamics (evapotranspiration, snow accumulation and melting) and ice/liquid phase transition. Third, we combine a deterministic and an adaptive Markov chain Monte Carlo optimization algorithm to better estimate the posterior distributions of desired model parameters. Finally, the simulated subsurface variables are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using synthetic experiments. The results show that compared to inversion of single dataset, joint inversion of these datasets significantly reduces parameter uncertainty. The joint inversion approach is able to estimate SOC content within the shallow active layer with high reliability. Next, we apply the scheme to estimate OC content along an intensive ERT transect in Barrow, Alaska using multiple datasets acquired in the 2013-2015 period. The preliminary results show a good agreement between modeled and measured soil temperature, thaw layer thickness and electrical resistivity. The accuracy of estimated SOC content will be evaluated by comparison with measurements from soil samples along the transect. Our study presents a new surface-subsurface, deterministic-stochastic hydrogeophysical inversion approach, as well as the benefit of including multiple types of data to estimate SOC and associated hydrological-thermal dynamics.

Biochemical changes in black oat (avena strigosa schreb) cultivated in vineyard soils contaminated with copper.

PubMed

Girotto, Eduardo; Ceretta, Carlos A; Rossato, Liana V; Farias, Julia G; Brunetto, Gustavo; Miotto, Alcione; Tiecher, Tadeu L; de Conti, Lessandro; Lourenzi, Cledimar R; Schmatz, Roberta; Giachini, Admir; Nicoloso, Fernando T

2016-06-01

Soils used for the cultivation of grapes generally have a long history of copper (Cu) based fungicide applications. As a result, these soils can accumulate Cu at levels that are capable of causing toxicity in plants that co-inhabit the vineyards. The aim of the present study was to evaluate growth parameters and oxidative stress in black oat plants grown in vineyard soils contaminated with high levels of Cu. Soil samples were collected from the Serra Gaúcha and Campanha Gaúcha regions, which are the main wine producing regions in the state of Rio Grande do Sul, in southern Brazil. Experiments were conducted in a greenhouse in 2009, with soils containing Cu concentrations from 2.2 to 328.7 mg kg(-1). Evaluated parameters included plant root and shoot dry matter, Cu concentration in the plant's tissues, and enzymatic and non-enzymatic biochemical parameters related to oxidative stress in the shoots of plants harvested 15 and 40 days after emergence. The Cu absorbed by plants predominantly accumulated in the roots, with little to no translocation to the shoots. Even so, oat plants showed symptoms of toxicity when grown in soils containing high Cu concentrations. The enzymatic and non-enzymatic antioxidant systems of oat plants were unable to reverse the imposed oxidative stress conditions. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Assessment of derelict soil quality: Abiotic, biotic and functional approaches.

PubMed

Vincent, Quentin; Auclerc, Apolline; Beguiristain, Thierry; Leyval, Corinne

2018-02-01

The intensification and subsequent closing down of industrial activities during the last century has left behind large surfaces of derelict lands. Derelict soils have low fertility, can be contaminated, and many of them remain unused. However, with the increasing demand of soil surfaces, they might be considered as a resource, for example for non-food biomass production. The study of their physico-chemical properties and of their biodiversity and biological activity may provide indications for their potential re-use. The objective of our study was to investigate the quality of six derelict soils, considering abiotic, biotic, and functional parameters. We studied (i) the soil bacteria, fungi, meso- and macro-fauna and plant communities of six different derelict soils (two from coking plants, one from a settling pond, two constructed ones made from different substrates and remediated soil, and an inert waste storage one), and (ii) their decomposition function based on the decomposer trophic network, enzyme activities, mineralization activity, and organic pollutant degradation. Biodiversity levels in these soils were high, but all biotic parameters, except the mycorrhizal colonization level, discriminated them. Multivariate analysis showed that biotic parameters co-varied more with fertility proxies than with soil contamination parameters. Similarly, functional parameters significantly co-varied with abiotic parameters. Among functional parameters, macro-decomposer proportion, enzyme activity, average mineralization capacity, and microbial polycyclic aromatic hydrocarbon degraders were useful to discriminate the soils. We assessed their quality by combining abiotic, biotic, and functional parameters: the compost-amended constructed soil displayed the highest quality, while the settling pond soil and the contaminated constructed soil displayed the lowest. Although differences among the soils were highlighted, this study shows that derelict soils may provide a biodiversity ecosystem service and are functional for decomposition. Copyright © 2017 Elsevier B.V. All rights reserved.

Poplar response to cadmium and lead soil contamination.

PubMed

Radojčić Redovniković, Ivana; De Marco, Alessandra; Proietti, Chiara; Hanousek, Karla; Sedak, Marija; Bilandžić, Nina; Jakovljević, Tamara

2017-10-01

An outdoor pot experiment was designed to study the potential of poplar (Populus nigra 'Italica') in phytoremediation of cadmium (Cd) and lead (Pb). Poplar was treated with a combination of different concentrations of Cd (w = 10, 25, 50mgkg -1 soil) and Pb (400, 800, 1200mgkg -1 soil) and several physiological and biochemical parameters were monitored including the accumulation and distribution of metals in different plant parts (leaf, stem, root). Simultaneously, the changes in the antioxidant system in roots and leaves were monitored to be able to follow synergistic effects of both heavy metals. Moreover, a statistical analysis based on the Random Forests Analysis (RFA) was performed in order to determine the most important predictors affecting growth and antioxidative machinery activities of poplar under heavy metal stress. The study demonstrated that tested poplar could be a good candidate for phytoextraction processes of Cd in moderately contaminated soils, while in heavily contaminated soil it could be only considered as a phytostabilisator. For Pb remediation only phytostabilisation process could be considered. By using RFA we pointed out that it is important to conduct the experiments in an outdoor space and include environmental conditions in order to study more realistic changes of growth parameters and accumulation and distribution of heavy metals. Also, to be able to better understand the interactions among previously mentioned parameters, it is important to conduct the experiments during prolonged time exposure., This is especially important for the long life cycle woody species. Copyright © 2017. Published by Elsevier Inc.

The estimation of soil water fluxes using lysimeter data

NASA Astrophysics Data System (ADS)

Wegehenkel, M.

2009-04-01

The validation of soil water balance models regarding soil water fluxes in the field is still a problem. This requires time series of measured model outputs. In our study, a soil water balance model was validated using lysimeter time series of measured model outputs. The soil water balance model used in our study was the Hydrus-1D-model. This model was tested by a comparison of simulated with measured daily rates of actual evapotranspiration, soil water storage, groundwater recharge and capillary rise. These rates were obtained from twelve weighable lysimeters with three different soils and two different lower boundary conditions for the time period from January 1, 1996 to December 31, 1998. In that period, grass vegetation was grown on all lysimeters. These lysimeters are located in Berlin, Germany. One potential source of error in lysimeter experiments is preferential flow caused by an artificial channeling of water due to the occurrence of air space between the soil monolith and the inside wall of the lysimeters. To analyse such sources of errors, Hydrus-1D was applied with different modelling procedures. The first procedure consists of a general uncalibrated appli-cation of Hydrus-1D. The second one includes a calibration of soil hydraulic parameters via inverse modelling of different percolation events with Hydrus-1D. In the third procedure, the model DUALP_1D was applied with the optimized hydraulic parameter set to test the hy-pothesis of the existence of preferential flow paths in the lysimeters. The results of the different modelling procedures indicated that, in addition to a precise determination of the soil water retention functions, vegetation parameters such as rooting depth should also be taken into account. Without such information, the rooting depth is a calibration parameter. However, in some cases, the uncalibrated application of both models also led to an acceptable fit between measured and simulated model outputs.

Estimation of soil saturated hydraulic conductivity by artificial neural networks ensemble in smectitic soils

NASA Astrophysics Data System (ADS)

Sedaghat, A.; Bayat, H.; Safari Sinegani, A. A.

2016-03-01

The saturated hydraulic conductivity ( K s ) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K s by using available soil data and fractal parameters. There were found significant correlations between K s and fractal parameters of particles and microaggregates. Estimation of K s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K s . Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K s .

Moisture can be the dominant environmental parameter governing cadaver decomposition in soil.

PubMed

Carter, David O; Yellowlees, David; Tibbett, Mark

2010-07-15

Forensic taphonomy involves the use of decomposition to estimate postmortem interval (PMI) or locate clandestine graves. Yet, cadaver decomposition remains poorly understood, particularly following burial in soil. Presently, we do not know how most edaphic and environmental parameters, including soil moisture, influence the breakdown of cadavers following burial and alter the processes that are used to estimate PMI and locate clandestine graves. To address this, we buried juvenile rat (Rattus rattus) cadavers (approximately 18 g wet weight) in three contrasting soils from tropical savanna ecosystems located in Pallarenda (sand), Wambiana (medium clay), or Yabulu (loamy sand), Queensland, Australia. These soils were sieved (2mm), weighed (500 g dry weight), calibrated to a matric potential of -0.01 megapascals (MPa), -0.05 MPa, or -0.3 MPa (wettest to driest) and incubated at 22 degrees C. Measurements of cadaver decomposition included cadaver mass loss, carbon dioxide-carbon (CO(2)-C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, ninhydrin-reactive nitrogen (NRN) and soil pH. Cadaver burial resulted in a significant increase in CO(2)-C evolution, MBC, enzyme activities, NRN and soil pH. Cadaver decomposition in loamy sand and sandy soil was greater at lower matric potentials (wetter soil). However, optimal matric potential for cadaver decomposition in medium clay was exceeded, which resulted in a slower rate of cadaver decomposition in the wettest soil. Slower cadaver decomposition was also observed at high matric potential (-0.3 MPa). Furthermore, wet sandy soil was associated with greater cadaver decomposition than wet fine-textured soil. We conclude that gravesoil moisture content can modify the relationship between temperature and cadaver decomposition and that soil microorganisms can play a significant role in cadaver breakdown. We also conclude that soil NRN is a more reliable indicator of gravesoil than soil pH. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

NASA Technical Reports Server (NTRS)

Gulden, L. E.; Rosero, E.; Yang, Z.-L.; Rodell, Matthew; Jackson, C. S.; Niu, G.-Y.; Yeh, P. J.-F.; Famiglietti, J. S.

2007-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set.

Effects of long-term continuous cropping on soil nematode community and soil condition associated with replant problem in strawberry habitat

PubMed Central

Li, Xingyue; Lewis, Edwin E.; Liu, Qizhi; Li, Heqin; Bai, Chunqi; Wang, Yuzhu

2016-01-01

Continuous cropping changes soil physiochemical parameters, enzymes and microorganism communities, causing “replant problem” in strawberry cultivation. We hypothesized that soil nematode community would reflect the changes in soil conditions caused by long-term continuous cropping, in ways that are consistent and predictable. To test this hypothesis, we studied the soil nematode communities and several soil parameters, including the concentration of soil phenolic acids, organic matter and nitrogen levels, in strawberry greenhouse under continuous-cropping for five different durations. Soil pH significantly decreased, and four phenolic acids, i.e., p-hydroxybenzoic acid, ferulic acid, cinnamic acid and p-coumaric acid, accumulated with time under continuous cropping. The four phenolic acids were highly toxic to Acrobeloides spp., the eudominant genus in non-continuous cropping, causing it to reduce to a resident genus after seven-years of continuous cropping. Decreased nematode diversity indicated loss of ecosystem stability and sustainability because of continuous-cropping practice. Moreover, the dominant decomposition pathway was altered from bacterial to fungal under continuous cropping. Our results suggest that along with the continuous-cropping time in strawberry habitat, the soil food web is disturbed, and the available plant nutrition as well as the general health of the soil deteriorates; these changes can be indicated by soil nematode community. PMID:27506379

Quadrant III RFI draft report: Appendix B-I, Volume 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-12-01

In order to determine the nature and extent of contamination at a RCRA site it is often necessary to investigate and characterize the chemical composition of the medium in question that represents background conditions. Background is defined as current conditions present at a site which are unaffected by past treatment, storage, or disposal of hazardous waste (OEPA, 1991). The background composition of soils at the Portsmouth Gaseous Diffusion Plant (PORTS) site was characterized for the purpose of comparing investigative soil data to a background standard for each metal on the Target Compound List/Target Analyte List and each radiological parameter ofmore » concern in this RFI. Characterization of background compositions with respect to organic parameters was not performed because the organic parameters in the TCL/TAL are not naturally occurring at the site and because the site is not located in a highly industrialized area nor downgradient from another unrelated hazardous waste site. Characterization of the background soil composition with respect to metals and radiological parameters was performed by collecting and analyzing soil boring and hand-auger samples in areas deemed unaffected by past treatment, storage, or disposal of hazardous waste. Criteria used in determining whether a soil sample location would be representative of the true background condition included: environmental history of the location, relation to Solid Waste Management Units (SWMU`s), prevailing wind direction, surface runoff direction, and ground-water flow direction.« less

Quadrant III RFI draft report: Appendix B-I, Volume 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-12-01

In order to determine the nature and extent of contamination at a RCRA site it is often necessary to investigate and characterize the chemical composition of the medium in question that represents background conditions. Background is defined as current conditions present at a site which are unaffected by past treatment, storage, or disposal of hazardous waste (OEPA, 1991). The background composition of soils at the Portsmouth Gaseous Diffusion Plant (PORTS) site was characterized for the purpose of comparing investigative soil data to a background standard for each metal on the Target Compound List/Target Analyte List and each radiological parameter ofmore » concern in this RFI. Characterization of background compositions with respect to organic parameters was not performed because the organic parameters in the TCL/TAL are not naturally occurring at the site and because the site is not located in a highly industrialized area nor downgradient from another unrelated hazardous waste site. Characterization of the background soil composition with respect to metals and radiological parameters was performed by collecting and analyzing soil boring and hand-auger samples in areas deemed unaffected by past treatment, storage, or disposal of hazardous waste. Criteria used in determining whether a soil sample location would be representative of the true background condition included: environmental history of the location, relation to Solid Waste Management Units (SWMU's), prevailing wind direction, surface runoff direction, and ground-water flow direction.« less

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Investigating the relationship between a soils classification and the spatial parameters of a conceptual catchment-scale hydrological model

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Lilly, A.

2001-10-01

There are now many examples of hydrological models that utilise the capabilities of Geographic Information Systems to generate spatially distributed predictions of behaviour. However, the spatial variability of hydrological parameters relating to distributions of soils and vegetation can be hard to establish. In this paper, the relationship between a soil hydrological classification Hydrology of Soil Types (HOST) and the spatial parameters of a conceptual catchment-scale model is investigated. A procedure involving inverse modelling using Monte-Carlo simulations on two catchments is developed to identify relative values for soil related parameters of the DIY model. The relative values determine the internal variability of hydrological processes as a function of the soil type. For three out of the four soil parameters studied, the variability between HOST classes was found to be consistent across two catchments when tested independently. Problems in identifying values for the fourth 'fast response distance' parameter have highlighted a potential limitation with the present structure of the model. The present assumption that this parameter can be related simply to soil type rather than topography appears to be inadequate. With the exclusion of this parameter, calibrated parameter sets from one catchment can be converted into equivalent parameter sets for the alternate catchment on the basis of their HOST distributions, to give a reasonable simulation of flow. Following further testing on different catchments, and modifications to the definition of the fast response distance parameter, the technique provides a methodology whereby it is possible to directly derive spatial soil parameters for new catchments.

Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.

2018-06-01

Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

A system for comparison of boring parameters of mini-HDD machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunsaulis, F.R.

A system has been developed to accurately evaluate changes in performance of a mini-horizontal directional drilling (HDD) system in the backreaming/pullback portion of a bore as the parameters influencing the backream are changed. Parameters incorporated in the study include spindle rotation rate, rate of pull, fluid flow rate, and backreamer design. The boring system is able to run at variable, operator-determined rates of spindle rotation and pullback speed utilizing electronic feedback controls for regulation. Spindle torque and pullback force are continuously measured and recorded giving an indication of the performance of the unit. A method has also been developed tomore » measure the pull load on the installed service line to determine the effect of the boring parameters on the service line. Variability of soil along the bore path is measured and quantified using a soil sampling system developed for the study. Sample results obtained with the system are included in the report. 2 refs., 5 figs., 2 tabs.« less

Evaluation of the Migration Capacity of Zn in the Soil–Plant System

NASA Astrophysics Data System (ADS)

Anisimov, V. S.; Anisimova, L. N.; Frigidova, L. M.; Dikarev, D. V.; Frigidov, R. A.; Korneev, Yu. N.; Sanzharov, A. I.; Arysheva, S. P.

2018-04-01

The mobility and migration capacity of Zn in the soil-plant system were studied in a series of pot experiments with barley as a test plant. The parameters of Zn accumulation depending on the metal concentrations in soils and soil solutions were estimated by soil and water culture methods. Experiments with barley in water culture were performed on a nutrient (soil) solution extracted from soddy-podzolic soil (Albic Retisol (Loamic, Ochric)) to which Zn2+ was added to reach working concentrations increasing from 0.07 to 430 μM. Different responses of barley plants to changes in the concentration of Zn in the studied soil were identified. Ranges of the corresponding concentrations in the soil and aboveground barley biomass were determined. Parameters of Zn accumulation by test plants were determined depending on the metal content in soddypodzolic soil and the soil solution. A new method was proposed for evaluating the buffer capacity of soils with respect to a heavy metal (Zn) using test plants (BCS(P)Zn). The method was used to evaluate the buffering capacity of loamy sandy soddy-podzolic soil. The considered methodological approach offers opportunities for using data obtained during the agroecological monitoring of agricultural lands with heavy metals (HMs), including the contents of exchangeable HMs and macroelements (C and Mg) in soils and concentrations of HMs and (Ca + Mg) in plants, in the calculation of the buffering capacity of the surveyed soils for HMs.

Application of municipal biosolids to dry-land wheat fields - A monitoring program near Deer Trail, Colorado (USA). A presentation for an international conference: "The Future of Agriculture: Science, Stewardship, and Sustainability", August 7-9, 2006, Sacramento, CA

USGS Publications Warehouse

Crock, James G.; Smith, David B.; Yager, Tracy J.B.

2006-01-01

Since late 1993, Metro Wastewater Reclamation District of Denver (Metro District), a large wastewater treatment plant in Denver, Colorado, has applied Grade I, Class B biosolids to about 52,000 acres of non-irrigated farmland and rangeland near Deer Trail, Colorado. In cooperation with the Metro District in 1993, the U.S. Geological Survey (USGS) began monitoring ground water at part of this site. In 1999, the USGS began a more comprehensive study of the entire site to address stakeholder concerns about the chemical effects of biosolids applications. This more comprehensive monitoring program has recently been extended through 2010. Monitoring components of the more comprehensive study included biosolids collected at the wastewater treatment plant, soil, crops, dust, alluvial and bedrock ground water, and stream bed sediment. Streams at the site are dry most of the year, so samples of stream bed sediment deposited after rain were used to indicate surface-water effects. This presentation will only address biosolids, soil, and crops. More information about these and the other monitoring components are presented in the literature (e.g., Yager and others, 2004a, b, c, d) and at the USGS Web site for the Deer Trail area studies at http://co.water.usgs.gov/projects/CO406/CO406.html. Priority parameters identified by the stakeholders for all monitoring components, included the total concentrations of nine trace elements (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc), plutonium isotopes, and gross alpha and beta activity, regulated by Colorado for biosolids to be used as an agricultural soil amendment. Nitrogen and chromium also were priority parameters for ground water and sediment components. In general, the objective of each component of the study was to determine whether concentrations of priority parameters (1) were higher than regulatory limits, (2) were increasing with time, or (3) were significantly higher in biosolids-applied areas than in a similar farmed area where biosolids were not applied. Where sufficient samples could be collected, statistical methods were used to evaluate effects. Rigorous quality assurance was included in all aspects of the study. The roles of hydrology and geology also were considered in the design, data collection, and interpretation phases of the study. Study results indicate that the chemistry of the biosolids from the Denver plant was consistent during 1999-2005, and total concentrations of regulated trace elements were consistently lower than the regulatory limits. Plutonium isotopes were not detected in the biosolids. Leach tests using deionized water to simulate natural precipitation indicate arsenic, molybdenum, and nickel were the most soluble priority parameters in the biosolids. Study results show no significant difference in concentrations of priority parameters between biosolids-applied soils and unamended soils where no biosolids were applied. However, biosolids were applied only twice during 1999-2003. The next soil sampling is not scheduled until 2010. To date concentrations of most of the priority parameters were not much greater in the biosolids than in natural soil from the sites. Therefore, many more biosolids applications would need to occur before biosolids effects on the soil priority constituents can be quantified. Leach tests using deionized water to simulate precipitation indicate that molybdenum and selenium were the priority parameters that were most soluble in both biosolids-applied soil and natural or unamended soil. Study results do not indicate significant differences in concentrations of priority parameters between crops grown in biosolids-applied areas and crops grown where no biosolids were applied. However, crops were grown only twice during 1999-2003, so only two crop samples could be collected. The wheat-grain elemental data collected during 1999-2003 for both biosolids-applied areas and unamended areas are similar

Feasibility study of bioremediation of a drilling-waste-polluted soil: stimulation of microbial activities and hydrocarbon removal.

PubMed

Rojas-Avelizapa, Norma; Olvera-Barrera, Erika; Fernández-Linares, Luis

2005-01-01

The objective of this study was to determine the feasibility of bioremediation as a treatment option for an aged and chronically polluted drilling waste soil located at the Southeast of Mexico. The polluted drilling-waste site with a mean total petroleum hydrocarbon concentration (TPHs) of 39,397 +/- 858 mg/kg was treated with one dose of a nutrient-surfactant commercial product at 40 mg/kg soil and two doses of H2O2 (50 and 100 mg H2O2/kg soil). In this study, the parameters that were monitored include soil respiration, heterotrophic and hydrocarbon-degrading bacteria as biological indicators, catalase and dehydrogenase activities, and TPHs degradation as decontamination parameters. The results demonstrated that the microbial activities can be stimulated in a polluted drilling-waste site by the addition of H2O2 and commercial product, thereby resulting in increasing TPHs degradation. These aspects must be taken into account when biodegradation studies involve the application of a commercial product.

Can we predict uranium bioavailability based on soil parameters? Part 1: effect of soil parameters on soil solution uranium concentration.

PubMed

Vandenhove, H; Van Hees, M; Wouters, K; Wannijn, J

2007-01-01

Present study aims to quantify the influence of soil parameters on soil solution uranium concentration for (238)U spiked soils. Eighteen soils collected under pasture were selected such that they covered a wide range for those parameters hypothesised as being potentially important in determining U sorption. Maximum soil solution uranium concentrations were observed at alkaline pH, high inorganic carbon content and low cation exchange capacity, organic matter content, clay content, amorphous Fe and phosphate levels. Except for the significant correlation between the solid-liquid distribution coefficients (K(d), L kg(-1)) and the organic matter content (R(2)=0.70) and amorphous Fe content (R(2)=0.63), there was no single soil parameter significantly explaining the soil solution uranium concentration (which varied 100-fold). Above pH=6, log(K(d)) was linearly related with pH [log(K(d))=-1.18 pH+10.8, R(2)=0.65]. Multiple linear regression analysis did result in improved predictions of the soil solution uranium concentration but the model was complex.

Evaluating soil carbon in global climate models: benchmarking, future projections, and model drivers

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Randerson, J. T.; Post, W. M.; Allison, S. D.

2012-12-01

The carbon cycle plays a critical role in how the climate responds to anthropogenic carbon dioxide. To evaluate how well Earth system models (ESMs) from the Climate Model Intercomparison Project (CMIP5) represent the carbon cycle, we examined predictions of current soil carbon stocks from the historical simulation. We compared the soil and litter carbon pools from 17 ESMs with data on soil carbon stocks from the Harmonized World Soil Database (HWSD). We also examined soil carbon predictions for 2100 from 16 ESMs from the rcp85 (highest radiative forcing) simulation to investigate the effects of climate change on soil carbon stocks. In both analyses, we used a reduced complexity model to separate the effects of variation in model drivers from the effects of model parameters on soil carbon predictions. Drivers included NPP, soil temperature, and soil moisture, and the reduced complexity model represented one pool of soil carbon as a function of these drivers. The ESMs predicted global soil carbon totals of 500 to 2980 Pg-C, compared to 1260 Pg-C in the HWSD. This 5-fold variation in predicted soil stocks was a consequence of a 3.4-fold variation in NPP inputs and 3.8-fold variability in mean global turnover times. None of the ESMs correlated well with the global distribution of soil carbon in the HWSD (Pearson's correlation <0.40, RMSE 9-22 kg m-2). On a biome level there was a broad range of agreement between the ESMs and the HWSD. Some models predicted HWSD biome totals well (R2=0.91) while others did not (R2=0.23). All of the ESM terrestrial decomposition models are structurally similar with outputs that were well described by a reduced complexity model that included NPP and soil temperature (R2 of 0.73-0.93). However, MPI-ESM-LR outputs showed only a moderate fit to this model (R2=0.51), and CanESM2 outputs were better described by a reduced model that included soil moisture (R2=0.74), We also found a broad range in soil carbon responses to climate change predicted by the ESMs, with changes of -480 to 230 Pg-C from 2005-2100. All models that reported NPP and heterotrophic respiration showed increases in both of these processes over the simulated period. In two of the models, soils switched from a global sink for carbon to a net source. Of the remaining models, half predicted that soils were a sink for carbon throughout the time period and the other half predicted that soils were a carbon source.. Heterotrophic respiration in most of the models from 2005-2100 was well explained by a reduced complexity model dependent on soil carbon, soil temperature, and soil moisture (R2 values >0.74). However, MPI-ESM (R2=0.45) showed only moderate fit to this model. Our analysis shows that soil carbon predictions from ESMs are highly variable, with much of this variability due to model parameterization and variations in driving variables. Furthermore, our reduced complexity models show that most variation in ESM outputs can be explained by a simple one-pool model with a small number of drivers and parameters. Therefore, agreement between soil carbon predictions across models could improve substantially by reconciling differences in driving variables and the parameters that link soil carbon with environmental drivers. However it is unclear if this model agreement would reflect what is truly happening in the Earth system.

ECOUL: an interactive computer tool to study hydraulic behavior of swelling and rigid soils

NASA Astrophysics Data System (ADS)

Perrier, Edith; Garnier, Patricia; Leclerc, Christian

2002-11-01

ECOUL is an interactive, didactic software package which simulates vertical water flow in unsaturated soils. End-users are given an easily-used tool to predict the evolution of the soil water profile, with a large range of possible boundary conditions, through a classical numerical solution scheme for the Richards equation. Soils must be characterized by water retention curves and hydraulic conductivity curves, the form of which can be chosen among different analytical expressions from the literature. When the parameters are unknown, an inverse method is provided to estimate them from available experimental flow data. A significant original feature of the software is to include recent algorithms extending the water flow model to deal with deforming porous media: widespread swelling soils, the volume of which varies as a function of water content, must be described by a third hydraulic characteristic property, the deformation curve. Again, estimation of the parameters by means of inverse procedures and visualization facilities enable exploration, understanding and then prediction of soil hydraulic behavior under various experimental conditions.

Impact of Uncertainties in Meteorological Forcing Data and Land Surface Parameters on Global Estimates of Terrestrial Water Balance Components

NASA Astrophysics Data System (ADS)

Nasonova, O. N.; Gusev, Ye. M.; Kovalev, Ye. E.

2009-04-01

Global estimates of the components of terrestrial water balance depend on a technique of estimation and on the global observational data sets used for this purpose. Land surface modelling is an up-to-date and powerful tool for such estimates. However, the results of modelling are affected by the quality of both a model and input information (including meteorological forcing data and model parameters). The latter is based on available global data sets containing meteorological data, land-use information, and soil and vegetation characteristics. Now there are a lot of global data sets, which differ in spatial and temporal resolution, as well as in accuracy and reliability. Evidently, uncertainties in global data sets will influence the results of model simulations, but to which extent? The present work is an attempt to investigate this issue. The work is based on the land surface model SWAP (Soil Water - Atmosphere - Plants) and global 1-degree data sets on meteorological forcing data and the land surface parameters, provided within the framework of the Second Global Soil Wetness Project (GSWP-2). The 3-hourly near-surface meteorological data (for the period from 1 July 1982 to 31 December 1995) are based on reanalyses and gridded observational data used in the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II. Following the GSWP-2 strategy, we used a number of alternative global forcing data sets to perform different sensitivity experiments (with six alternative versions of precipitation, four versions of radiation, two pure reanalysis products and two fully hybridized products of meteorological data). To reveal the influence of model parameters on simulations, in addition to GSWP-2 parameter data sets, we produced two alternative global data sets with soil parameters on the basis of their relationships with the content of clay and sand in a soil. After this the sensitivity experiments with three different sets of parameters were performed. As a result, 16 variants of global annual estimates of water balance components were obtained. Application of alternative data sets on radiation, precipitation, and soil parameters allowed us to reveal the influence of uncertainties in input data on global estimates of water balance components.

Comparative treatment effectiveness of conventional trench and seepage pit systems.

PubMed

Field, J P; Farrell-Poe, K L; Walworth, J L

2007-03-01

On-site wastewater treatment systems can be a potential source of groundwater contamination in regions throughout the United States and other parts of the world. Here, we evaluate four conventional trench systems and four seepage pit systems to determine the relative effectiveness of these systems for the treatment of septic tank effluent in medium- to coarse-textured arid and semiarid soils. Soil borings were advanced up to twice the depth of the trenches (4 m) and seepage pits (15 m) at two horizontal distances (30 cm and 1.5 m) from the sidewalls of the systems. Soil samples were analyzed for various biological and chemical parameters, including Escherichia coli, total coliform, pH, total organic carbon, total dissolved solids, total nitrogen, ammonium-nitrogen, and nitrate-nitrogen. Most soil parameters investigated approached background levels more rapidly near the trenches than the seepage pits, as sampling distance increased both vertically and horizontally from the sidewalls of the systems.

An efficient soil water balance model based on hybrid numerical and statistical methods

NASA Astrophysics Data System (ADS)

Mao, Wei; Yang, Jinzhong; Zhu, Yan; Ye, Ming; Liu, Zhao; Wu, Jingwei

2018-04-01

Most soil water balance models only consider downward soil water movement driven by gravitational potential, and thus cannot simulate upward soil water movement driven by evapotranspiration especially in agricultural areas. In addition, the models cannot be used for simulating soil water movement in heterogeneous soils, and usually require many empirical parameters. To resolve these problems, this study derives a new one-dimensional water balance model for simulating both downward and upward soil water movement in heterogeneous unsaturated zones. The new model is based on a hybrid of numerical and statistical methods, and only requires four physical parameters. The model uses three governing equations to consider three terms that impact soil water movement, including the advective term driven by gravitational potential, the source/sink term driven by external forces (e.g., evapotranspiration), and the diffusive term driven by matric potential. The three governing equations are solved separately by using the hybrid numerical and statistical methods (e.g., linear regression method) that consider soil heterogeneity. The four soil hydraulic parameters required by the new models are as follows: saturated hydraulic conductivity, saturated water content, field capacity, and residual water content. The strength and weakness of the new model are evaluated by using two published studies, three hypothetical examples and a real-world application. The evaluation is performed by comparing the simulation results of the new model with corresponding results presented in the published studies, obtained using HYDRUS-1D and observation data. The evaluation indicates that the new model is accurate and efficient for simulating upward soil water flow in heterogeneous soils with complex boundary conditions. The new model is used for evaluating different drainage functions, and the square drainage function and the power drainage function are recommended. Computational efficiency of the new model makes it particularly suitable for large-scale simulation of soil water movement, because the new model can be used with coarse discretization in space and time.

Improvement of shallow landslide prediction accuracy using soil parameterisation for a granite area in South Korea

NASA Astrophysics Data System (ADS)

Kim, M. S.; Onda, Y.; Kim, J. K.

2015-01-01

SHALSTAB model applied to shallow landslides induced by rainfall to evaluate soil properties related with the effect of soil depth for a granite area in Jinbu region, Republic of Korea. Soil depth measured by a knocking pole test and two soil parameters from direct shear test (a and b) as well as one soil parameters from a triaxial compression test (c) were collected to determine the input parameters for the model. Experimental soil data were used for the first simulation (Case I) and, soil data represented the effect of measured soil depth and average soil depth from soil data of Case I were used in the second (Case II) and third simulations (Case III), respectively. All simulations were analysed using receiver operating characteristic (ROC) analysis to determine the accuracy of prediction. ROC analysis results for first simulation showed the low ROC values under 0.75 may be due to the internal friction angle and particularly the cohesion value. Soil parameters calculated from a stochastic hydro-geomorphological model were applied to the SHALSTAB model. The accuracy of Case II and Case III using ROC analysis showed higher accuracy values rather than first simulation. Our results clearly demonstrate that the accuracy of shallow landslide prediction can be improved when soil parameters represented the effect of soil thickness.

Root zone water quality model (RZWQM2): Model use, calibration and validation

USGS Publications Warehouse

Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

2012-01-01

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

Modeling Soil Water in the Caatinga Tropical Dry Forest of Northeastern Brazil

NASA Astrophysics Data System (ADS)

Wright, C.; Wilcox, B.; Souza, E.; Lima, J. R. D. S.; West, J. B.

2015-12-01

The Caatinga is a tropical dry forest unique to northeastern Brazil. It has a relatively high degree of endism and supports a population of about 20 million subsistence farmers. However, it is poorly understood, under-researched and often over-looked in regards to other Brazilian ecosystems. It is a highly perturbed system that suffers from deforestation, land use change, and may be threatened by climate change. How these perturbations affect hydrology is unknown, but may have implications for biodiversity and ecosystem services and resiliency. Therefore, understanding key hydrological processes is critical, particularly as related to deforestation. In this study, Hydrus 1D, which is based on van Genuchten parameters to describe the soil water curve and Richard's Equation to describe flow in the vadose zone, was used to model soil moisture in the Caatinga ecosystem. The aim was 1) to compare hydraulic characterization between a forested Caatinga site and a deforested pasture site, 2) to analyze inter-annual variability, and 3) to compare with observed soil moisture data. Hydraulic characterization included hydraulic conductivity, infiltration, water content and pressure head trends. Van Genuchten parameters were derived using the Beerkan method, which is based on soil texture, particle distribution, as well as in-situ small-scale infiltration experiments. Observational data included soil moisture and precipitation logged every half-hour from September 2013 to April 2014 to include the dry season and rainy season. It is expected that the forested Caatinga site will have a higher hydraulic conductivity as well as retain higher soil moisture values. These differences may be amplified during the dry season, as water resources become scarce. Deviations between modeled data and observed data will allow for further hypothesis to be proposed, especially those related to soil water repellency. Hence, these results may indicate difference in soil water dynamics between a forested and non-forested site which will have implications for land use and management strategies that promote water resource conservation and availability.

Magnetic and geochemical characterization of Andosols developed on basalts in the Massif Central, France

NASA Astrophysics Data System (ADS)

Grison, Hana; Petrovsky, Eduard; Stejskalova, Sarka; Kapicka, Ales

2015-05-01

Identification of Andosols is primarily based upon the content of their colloidal constituents—clay and metal-humus complexes—and on the determining of andic properties. This needs time and cost-consuming geochemical analyses. Our primary aim of this study is to describe the magnetic and geochemical properties of soils rich in iron oxides derived from strongly magnetic volcanic basement (in this case Andosols). Secondary aim is to explore links between magnetic and chemical parameters of andic soils with respect to genesis factors: parent material age, precipitation, and thickness of the soil profile. Six pedons of andic properties, developed on basaltic lavas, were analyzed down to parent rock by a set of magnetic and geochemical methods. Magnetic data of soil and rock samples reflect the type, concentration, and particle-size distribution of ferrimagnetic minerals. Geochemical data include soil reaction (pH in H2O), cation exchange capacity, organic carbon, and different forms of extractable iron and aluminum content. Our results suggest the following: (1) magnetic measurements of low-field mass-specific magnetic susceptibility can be a reliable indicator for estimating andic properties, and in combination with thermomagnetic curves may be suitable for discriminating between alu-andic and sil-andic subtypes. (2) In the studied Andosols, strong relationships were found between (a) magnetic grain-size parameters, precipitation, and exchangeable bases; (b) concentration of ferrimagnetic particles and degree of crystallization of free iron; and (c) parameters reflecting changes in magneto-mineralogy and soil genesis (parent material age + soil depth).

The desorptivity model of bulk soil-water evaporation

NASA Technical Reports Server (NTRS)

Clapp, R. B.

1983-01-01

Available models of bulk evaporation from a bare-surfaced soil are difficult to apply to field conditions where evaporation is complicated by two main factors: rate-limiting climatic conditions and redistribution of soil moisture following infiltration. Both factors are included in the "desorptivity model', wherein the evaporation rate during the second stage (the soil-limiting stage) of evaporation is related to the desorptivity parameter, A. Analytical approximations for A are presented. The approximations are independent of the surface soil moisture. However, calculations using the approximations indicate that both soil texture and soil moisture content at depth significantly affect A. Because the moisture content at depth decreases in time during redistribution, it follows that the A parameter also changes with time. Consequently, a method to calculate a representative value of A was developed. When applied to field data, the desorptivity model estimated cumulative evaporation well. The model is easy to calculate, but its usefulness is limited because it requires an independent estimate of the time of transition between the first and second stages of evaporation. The model shows that bulk evaporation after the transition to the second stage is largely independent of climatic conditions.

BOREAS TGB-12 Soil Carbon Data over the NSA

NASA Technical Reports Server (NTRS)

Trumbore, Susan; Hall, Forrest G. (Editor); Conrad, Sara K. (Editor); Harden, Jennifer; Sundquist, Eric; Winston, Greg

2000-01-01

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites to estimate the rates of carbon accumulation and turnover in each of the major vegetation types. TGB-12 data sets include soil properties at tower and selected auxiliary sites in the BOREAS NSA and data on the seasonal variations in the radiocarbon content of CO2 in the soil atmosphere at NSA tower sites. The sampling strategies for soils were designed to take advantage of local fire chronosequences, so that the accumulation of C in areas of moss regrowth could be determined. These data are used to calculate the inventory of C and N in moss and mineral soil layers at NSA sites and to determine the rates of input and turnover (using both accumulation since the last stand-killing fire and radiocarbon data). This data set includes physical parameters needed to determine carbon and nitrogen inventory in soils. The data were collected discontinuously from August 1993 to July 1996. The data are stored in tabular ASCII files.

Estimating Soil Moisture Using Polsar Data: a Machine Learning Approach

NASA Astrophysics Data System (ADS)

Khedri, E.; Hasanlou, M.; Tabatabaeenejad, A.

2017-09-01

Soil moisture is an important parameter that affects several environmental processes. This parameter has many important functions in numerous sciences including agriculture, hydrology, aerology, flood prediction, and drought occurrence. However, field procedures for moisture calculations are not feasible in a vast agricultural region territory. This is due to the difficulty in calculating soil moisture in vast territories and high-cost nature as well as spatial and local variability of soil moisture. Polarimetric synthetic aperture radar (PolSAR) imaging is a powerful tool for estimating soil moisture. These images provide a wide field of view and high spatial resolution. For estimating soil moisture, in this study, a model of support vector regression (SVR) is proposed based on obtained data from AIRSAR in 2003 in C, L, and P channels. In this endeavor, sequential forward selection (SFS) and sequential backward selection (SBS) are evaluated to select suitable features of polarized image dataset for high efficient modeling. We compare the obtained data with in-situ data. Output results show that the SBS-SVR method results in higher modeling accuracy compared to SFS-SVR model. Statistical parameters obtained from this method show an R2 of 97% and an RMSE of lower than 0.00041 (m3/m3) for P, L, and C channels, which has provided better accuracy compared to other feature selection algorithms.

Estimating steady-state evaporation rates from bare soils under conditions of high water table

USGS Publications Warehouse

Ripple, C.D.; Rubin, J.; Van Hylckama, T. E. A.

1970-01-01

A procedure that combines meteorological and soil equations of water transfer makes it possible to estimate approximately the steady-state evaporation from bare soils under conditions of high water table. Field data required include soil-water retention curves, water table depth and a record of air temperature, air humidity and wind velocity at one elevation. The procedure takes into account the relevant atmospheric factors and the soil's capability to conduct 'water in liquid and vapor forms. It neglects the effects of thermal transfer (except in the vapor case) and of salt accumulation. Homogeneous as well as layered soils can be treated. Results obtained with the method demonstrate how the soil evaporation rates·depend on potential evaporation, water table depth, vapor transfer and certain soil parameters.

Soil and water characteristics of a young surface mine wetland

NASA Astrophysics Data System (ADS)

Andrew Cole, C.; Lefebvre, Eugene A.

1991-05-01

Coal companies are reluctant to include wetland development in reclamation plans partly due to a lack of information on the resulting characteristics of such sites. It is easier for coal companies to recreate terrestrial habitats than to attempt experimental methods and possibly face significant regulatory disapproval. Therefore, we studied a young (10 years) wetland on a reclaimed surface coal mine in southern Illinois so as to ascertain soil and water characteristics such that the site might serve as a model for wetland development on surface mines. Water pH was not measured because of equipment problems, but evidence (plant life, fish, herpetofauna) suggests suitable pH levels. Other water parameters (conductivity, salinity, alkalinity, chloride, copper, total hardness, iron, manganese, nitrate, nitrite, phosphate, and sulfate) were measured, and only copper was seen in potentially high concentrations (but with no obvious toxic effects). Soil variables measured included pH, nitrate, nitrite, ammonia, potassium, calcium, magnesium, manganese, aluminum, iron, sulfate, chloride, and percent organic matter. Soils were slightly alkaline and most parameters fell within levels reported for other studies on both natural and manmade wetlands. Aluminum was high, but this might be indicative more of large amounts complexed with soils and therefore unavailable, than amounts actually accessible to plants. Organic matter was moderate, somewhat surprising given the age of the system.

Combined Effects of Soil Biotic and Abiotic Factors, Influenced by Sewage Sludge Incorporation, on the Incidence of Corn Stalk Rot

PubMed Central

Fortes, Nara Lúcia Perondi; Navas-Cortés, Juan A; Silva, Carlos Alberto; Bettiol, Wagner

2016-01-01

The objectives of this study were to evaluate the combined effects of soil biotic and abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two types of sewage sludge into soil in a 5-years field assay under tropical conditions and to predict the effects of these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. A multiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil. PMID:27176597

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

New generation of hydraulic pedotransfer functions for Europe

PubMed Central

Tóth, B; Weynants, M; Nemes, A; Makó, A; Bilas, G; Tóth, G

2015-01-01

A range of continental-scale soil datasets exists in Europe with different spatial representation and based on different principles. We developed comprehensive pedotransfer functions (PTFs) for applications principally on spatial datasets with continental coverage. The PTF development included the prediction of soil water retention at various matric potentials and prediction of parameters to characterize soil moisture retention and the hydraulic conductivity curve (MRC and HCC) of European soils. We developed PTFs with a hierarchical approach, determined by the input requirements. The PTFs were derived by using three statistical methods: (i) linear regression where there were quantitative input variables, (ii) a regression tree for qualitative, quantitative and mixed types of information and (iii) mean statistics of developer-defined soil groups (class PTF) when only qualitative input parameters were available. Data of the recently established European Hydropedological Data Inventory (EU-HYDI), which holds the most comprehensive geographical and thematic coverage of hydro-pedological data in Europe, were used to train and test the PTFs. The applied modelling techniques and the EU-HYDI allowed the development of hydraulic PTFs that are more reliable and applicable for a greater variety of input parameters than those previously available for Europe. Therefore the new set of PTFs offers tailored advanced tools for a wide range of applications in the continent. PMID:25866465

Analytical Results for Agricultural Soils Samples from a Monitoring Program Near Deer Trail, Colorado (USA)

USGS Publications Warehouse

Crock, J.G.; Smith, D.B.; Yager, T.J.B.

2009-01-01

Since late 1993, Metro Wastewater Reclamation District of Denver (Metro District, MWRD), a large wastewater treatment plant in Denver, Colorado, has applied Grade I, Class B biosolids to about 52,000 acres of nonirrigated farmland and rangeland near Deer Trail, Colorado, USA. In cooperation with the Metro District in 1993, the U.S. Geological Survey (USGS) began monitoring groundwater at part of this site. In 1999, the USGS began a more comprehensive monitoring study of the entire site to address stakeholder concerns about the potential chemical effects of biosolids applications to water, soil, and vegetation. This more comprehensive monitoring program has recently been extended through 2010. Monitoring components of the more comprehensive study include biosolids collected at the wastewater treatment plant, soil, crops, dust, alluvial and bedrock groundwater, and stream bed sediment. Soils for this study were defined as the plow zone of the dry land agricultural fields - the top twelve inches of the soil column. This report presents analytical results for the soil samples collected at the Metro District farm land near Deer Trail, Colorado, during three separate sampling events during 1999, 2000, and 2002. Soil samples taken in 1999 were to be a representation of the original baseline of the agricultural soils prior to any biosolids application. The soil samples taken in 2000 represent the soils after one application of biosolids to the middle field at each site and those taken in 2002 represent the soils after two applications. There have been no biosolids applied to any of the four control fields. The next soil sampling is scheduled for the spring of 2010. Priority parameters for biosolids identified by the stakeholders and also regulated by Colorado when used as an agricultural soil amendment include the total concentrations of nine trace elements (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, and zinc), plutonium isotopes, and gross alpha and beta activity (Colorado Department of Public Health and Environment, Hazardous Materials and Waste Management Division, 1997; Colorado Department of Public Health and Environment,1998; U.S. Environmental Protection Agency, 1993). Since these were the identified priority parameters for the biosolids, the soils have the same set of priority parameters. Although the composite soils' priority analytes have been reported earlier to Metro District, the remaining elemental datasets for both the composite soils samples and selected fields' individual subsamples' data are presented here for the first time. More information about the other monitoring components is presented elsewhere in the literature (http://co.water.usgs.gov/projects/CO406/CO406.html). In general, the objective of each component of the study was to determine whether concentrations of priority parameters (1) were higher than regulatory limits, (2) were increasing with time, and(or) (3) were significantly higher in biosolids-applied areas than in a similar farmed area where biosolids were not applied. The method chosen for sampling the soils proved to be an efficient and reliable representation of the average composition of each field. This was shown by analyzing individual subsamples, averaging the resulting values, and then comparing the values to the composited samples' values. The soil chemistry shows distinct differences between the two sites, most likely due to the different underlying parent material. Biosolids data were used to compile an inorganic-chemical biosolids signature that can be contrasted with the geochemical signature of the agricultural soils for this site. The biosolids signature and an understanding of the geology and hydrology of the site can be used to separate biosolids effects from natural geochemical effects. Elements of particular interest for a biosolids signature after application in the soils include bismuth, copper, silver, mercury, and phosphorus. This signat

Coupled land surface-subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

NASA Astrophysics Data System (ADS)

Phuong Tran, Anh; Dafflon, Baptiste; Hubbard, Susan S.

2017-09-01

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface-subsurface hydrological-thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon-climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological-thermal processes associated with annual freeze-thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets - including soil liquid water content, temperature and electrical resistivity tomography (ERT) data - to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological-thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface-subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice-liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological-thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological-thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface-subsurface, deterministic-stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological-thermal dynamics.

Soil properties influence kinetics of soil acid phosphatase in response to arsenic toxicity.

PubMed

Wang, Ziquan; Tan, Xiangping; Lu, Guannan; Liu, Yanju; Naidu, Ravi; He, Wenxiang

2018-01-01

Soil phosphatase, which plays an important role in phosphorus cycling, is strongly inhibited by Arsenic (As). However, the inhibition mechanism in kinetics is not adequately investigated. In this study, we investigated the kinetic characteristics of soil acid phosphatase (ACP) in 14 soils with varied properties, and also explored how kinetic properties of soil ACP changed with different spiked As concentrations. The results showed that the Michaelis constant (K m ) and maximum reaction velocity (V max ) values of soil ACP ranged from 1.18 to 3.77mM and 0.025-0.133mMh -1 in uncontaminated soils. The kinetic parameters of soil ACP in different soils changed differently with As contamination. The K m remained unchanged and V max decreased with increase of As concentration in most acid and neutral soils, indicating a noncompetitive inhibition mechanism. However, in alkaline soils, the K m increased linearly and V max decreased with increase of As concentration, indicating a mixed inhibition mechanism that include competitive and noncompetitive. The competitive inhibition constant (K ic ) and noncompetitive inhibition constant (K iu ) varied among soils and ranged from 0.38 to 3.65mM and 0.84-7.43mM respectively. The inhibitory effect of As on soil ACP was mostly affected by soil organic matter and cation exchange capacity. Those factors influenced the combination of As with enzyme, which resulted in a difference of As toxicity to soil ACP. Catalytic efficiency (V max /K m ) of soil ACP was a sensitive kinetic parameter to assess the ecological risks of soil As contamination. Copyright © 2017 Elsevier Inc. All rights reserved.

Combining supercritical fluid extraction of soil herbicides with enzyme immunoassay analysis.

PubMed

Stearman, G K

2001-10-01

Supercritical fluid extraction (SFE) of soil herbicides followed by enzyme immunoassay analysis (EIA) is explained in a step-by-step process. Extracted herbicides, include 2,4-D, simazine, atrazine, and alachlor. The herbicide, trifluralin was not successfully analyzed by EIA because of crossreacting metabolites. Problems with SFE, including uneven packing of cells, leaks, uneven flow and clogging, can largely be eliminated as the method parameters are optimized. It was necessary to add modifiers including methanol or acetone to the SF CO2 to increase the solubility of the analytes. Detection limits of 2.5 ng/g soil for atrazine and alachlor and 15 ng/g soil for simazine and 2,4-D without concentration of the sample were achieved. Recoveries above 80% and relative standard deviations (RSDs) less than 15% for 2,4-D simazine, atrazine and alachlor were achieved. Atrazine and alachlor recoveries were above 90% with RSDs below 10%. Forty soil samples could be extracted and analyzed in an 8-h day.

Biogenic nitric oxide emission from a spruce forest soil in mountainous terrain

NASA Astrophysics Data System (ADS)

Falge, Eva; Bargsten, Anika; Behrendt, Thomas; Meixner, Franz X.

2010-05-01

The process-based spatial simulation model SVAT-CN was used to estimate biogenic nitric oxide (NO) emission by soils of a Norway spruce forest (Weidenbrunnen) in the Fichtelgebirge, Germany. SVAT-CN core is a combination of a multiple-layer soil water balance model and a multi-layered canopy gas exchange model. The soil modules comprise a flexible hybrid between a layered bucket model and classical basic liquid flow theory. Further soil processes include: heat transport, distribution of transpiration demand proportionally to soil resistance, reduction of leaf physiological parameters with limiting soil moisture. Spruce forest soils usually are characterized by a thick organic layer (raw humus), with the topmost centimetres being the location where most of the biogenic NO is produced. Within individual spruce forest stands the understory might be composed of patches characterized by different species (e.g. Vaccinium myrtillus, Picea abies, Deschampsia caespitosa), and NO production potentials. The effect of soil physical and chemical parameters and understory types on NO emission from the organic layer was investigated in laboratory incubation and fumigation experiments on soils sampled below the various understory covers found at the Weidenbrunnen site. Results from the laboratory experiments were used to parameterize multi-factorial regression models of soil NO emission with respect to its response to soil temperature and moisture. Parameterization of the spatial model SVAT-CN includes horizontal heterogeneity of over- and understory PAI, understory species distribution, soil texture, bulk density, thickness of organic layer. Simulations are run for intensive observations periods of 2007 and 2008 of the EGER (ExchanGE processes in mountainous Regions) project, a late summer/fall and an early summer period, providing estimates for different understory types (young spruce, blueberry, grass, and moss/litter patches). Validation of the model is being carried out at point scale, by comparison with measured soil moisture and temperature data at 12 locations at the Weidenbrunnen site. In addition model output is compared to soil NO emission data from dynamic chambers. Understory type was found to have a strong influence on the magnitude of soil NO emissions, with emissions from blueberry and young spruce one order of magnitude larger than those from grass or moss/litter patches.

Ground Albedo Neutron Sensing (GANS) method for measurements of soil moisture in cropped fields

NASA Astrophysics Data System (ADS)

Andres Rivera Villarreyes, Carlos; Baroni, Gabriele; Oswald, Sascha E.

2013-04-01

Measurement of soil moisture at the plot or hill-slope scale is an important link between local vadose zone hydrology and catchment hydrology. However, so far only few methods are on the way to close this gap between point measurements and remote sensing. This study evaluates the applicability of the Ground Albedo Neutron Sensing (GANS) for integral quantification of seasonal soil moisture in the root zone at the scale of a field or small watershed, making use of the crucial role of hydrogen as neutron moderator relative to other landscape materials. GANS measurements were performed at two locations in Germany under different vegetative situations and seasonal conditions. Ground albedo neutrons were measured at (i) a lowland Bornim farmland (Brandenburg) cropped with sunflower in 2011 and winter rye in 2012, and (ii) a mountainous farmland catchment (Schaefertal, Harz Mountains) since middle 2011. At both sites depth profiles of soil moisture were measured at several locations in parallel by frequency domain reflectometry (FDR) for comparison and calibration. Initially, calibration parameters derived from a previous study with corn cover were tested under sunflower and winter rye periods at the same farmland. GANS soil moisture based on these parameters showed a large discrepancy compared to classical soil moisture measurements. Therefore, two new calibration approaches and four different ways of integration the soil moisture profile to an integral value for GANS were evaluated in this study. This included different sets of calibration parameters based on different growing periods of sunflower. New calibration parameters showed a good agreement with FDR network during sunflower period (RMSE = 0.023 m3 m-3), but they underestimated soil moisture in the winter rye period. The GANS approach resulted to be highly affected by temporal changes of biomass and crop types which suggest the need of neutron corrections for long-term observations with crop rotation. Finally, Bornim sunflower parameters were transferred to Schaefertal catchment for further evaluation. This study proves GANS potential to close the measurement gap between point scale and remote sensing scale; however, its calibration needs to be adapted for vegetation in cropped fields.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Comparative assessment of five water infiltration models into the soil

NASA Astrophysics Data System (ADS)

Shahsavaramir, M.

2009-04-01

The knowledge of the soil hydraulic conditions particularly soil permeability is an important issue hydrological and climatic study. Because of its high spatial and temporal variability, soil infiltration monitoring scheme was investigated in view of its application in infiltration modelling. Some of models for infiltration into the soil have been developed, in this paper; we design and describe capability of five infiltration model into the soil. We took a decision to select the best model suggested. In this research in the first time, we designed a program in Quick Basic software and wrote algorithm of five models that include Kostiakove, Modified Kostiakove, Philip, S.C.S and Horton. Afterwards we supplied amounts of factual infiltration, according of get at infiltration data, by double rings method in 12 series of Saveh plain which situated in Markazi province in Iran. After accessing to models coefficients, these equations were regenerated by Excel software and calculations related to models acuity rate in proportion to observations and also related graphs were done by this software. Amounts of infiltration parameters, such as cumulative infiltration and infiltration rate were obtained from designed models. Then we compared amounts of observation and determination parameters of infiltration. The results show that Kostiakove and Modified Kostiakove models could quantify amounts of cumulative infiltration and infiltration rate in triple period (short, middle and long time). In tree series of soils, Horton model could determine infiltration amounts better than others in time trinal treatments. The results show that Philip model in seven series had a relatively good fitness for determination of infiltration parameters. Also Philip model in five series of soils, after passing of time, had curve shape; in fact this shown that attraction coefficient (s) was less than zero. After all S.C.S model among of others had the least capability to determination of infiltration parameters.

Changes in bacterial diversity associated with bioremediation of used lubricating oil in tropical soils.

PubMed

Meeboon, Naruemon; Leewis, Mary-Cathrine; Kaewsuwan, Sireewan; Maneerat, Suppasil; Leigh, Mary Beth

2017-08-01

Used lubricating oil (ULO) is a widespread contaminant, particularly throughout tropical regions, and may be a candidate for bioremediation. However, little is known about the biodegradation potential or basic microbial ecology of ULO-contaminated soils. This study aims to determine the effects of used ULO on bacterial community structure and diversity. Using a combination of culture-based (agar plate counts) and molecular techniques (16S rRNA gene sequencing and DGGE), we investigated changes in soil bacterial communities from three different ULO-contaminated soils collected from motorcycle mechanical workshops (soil A, B, and C). We further explored the relationship between bacterial community structure, physiochemical soil parameters, and ULO composition in three ULO-contaminated soils. Results indicated that the three investigated soils had different community structures, which may be a result of the different ULO characteristics and physiochemical soil parameters of each site. Soil C had the highest ULO concentration and also the greatest diversity and richness of bacteria, which may be a result of higher nutrient retention, organic matter and cation exchange capacity, as well as freshness of oil compared to the other soils. In soils A and B, Proteobacteria (esp. Gammaproteobacteria) dominated the bacterial community, and in soil C, Actinobacteria and Firmicutes dominated. The genus Enterobacter, a member of the class Gammaproteobacteria, is known to include ULO-degraders, and this genus was the only one found in all three soils, suggesting that it could play a key role in the in situ degradation of ULO-contaminated tropical Thai soils. This study provides insights into our understanding of soil microbial richness, diversity, composition, and structure in tropical ULO-contaminated soils, and may be useful for the development of strategies to improve bioremediation.

A model-data fusion analysis for examining the response of carbon exchange to environmental variation in crop field

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Sakurai, G.; Ono, K.; Mano, M.; Miyata, A.

2011-12-01

Agricultural activities, cultivating crops, managing soil, harvesting and post-harvest treatments, are not only affected from the surrounding environment but also change the environment reversely. The changes in environment, temperature, radiation and precipitation, brings changes in crop productivity. On the other hand, the status of crops, i.e. the growth and phenological stage, change the exchange of energy, H2O and CO2 between crop vegetation surface and atmosphere. Conducting the stable agricultural harvests, reducing the Greenhouse Effect Gas (GHG) emission and enhancing carbon sequestration in soil are preferable as a win-win activity. We conducted model-data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter. The particle filter, which is one of Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this paper, we applied the model-data fusion analysis to the two datasets on paddy rice field sites in Japan: only a single rice cultivation, and a single rice and wheat cultivation. We focused on the parameters related to crop production as well as soil carbon storage. As a result, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years (Fig.1). The temperature sensitivity, Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition).

Characterizing scale- and location-dependent correlation of water retention parameters with soil physical properties using wavelet techniques.

PubMed

Shu, Qiaosheng; Liu, Zuoxin; Si, Bingcheng

2008-01-01

Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale- and location-dependent correlation between two water retention parameters (alpha and n) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location- and scale-dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between alpha and sand content was significantly different from red noise at small scales (8-20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between alpha and Bd existed mainly at medium scales (30-80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location-dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.

CO2 fluxes and ecosystem dynamics at five European treeless peatlands - merging data and process oriented modelling

NASA Astrophysics Data System (ADS)

Metzger, C.; Jansson, P.-E.; Lohila, A.; Aurela, M.; Eickenscheidt, T.; Belelli-Marchesini, L.; Dinsmore, K. J.; Drewer, J.; van Huissteden, J.; Drösler, M.

2014-06-01

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

Assessing doses to terrestrial wildlife at a radioactive waste disposal site: inter-comparison of modelling approaches.

PubMed

Johansen, M P; Barnett, C L; Beresford, N A; Brown, J E; Černe, M; Howard, B J; Kamboj, S; Keum, D-K; Smodiš, B; Twining, J R; Vandenhove, H; Vives i Batlle, J; Wood, M D; Yu, C

2012-06-15

Radiological doses to terrestrial wildlife were examined in this model inter-comparison study that emphasised factors causing variability in dose estimation. The study participants used varying modelling approaches and information sources to estimate dose rates and tissue concentrations for a range of biota types exposed to soil contamination at a shallow radionuclide waste burial site in Australia. Results indicated that the dominant factor causing variation in dose rate estimates (up to three orders of magnitude on mean total dose rates) was the soil-to-organism transfer of radionuclides that included variation in transfer parameter values as well as transfer calculation methods. Additional variation was associated with other modelling factors including: how participants conceptualised and modelled the exposure configurations (two orders of magnitude); which progeny to include with the parent radionuclide (typically less than one order of magnitude); and dose calculation parameters, including radiation weighting factors and dose conversion coefficients (typically less than one order of magnitude). Probabilistic approaches to model parameterisation were used to encompass and describe variable model parameters and outcomes. The study confirms the need for continued evaluation of the underlying mechanisms governing soil-to-organism transfer of radionuclides to improve estimation of dose rates to terrestrial wildlife. The exposure pathways and configurations available in most current codes are limited when considering instances where organisms access subsurface contamination through rooting, burrowing, or using different localised waste areas as part of their habitual routines. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Mercury in the Soil of the Tunka Depression

NASA Astrophysics Data System (ADS)

Lyapina, E. E.; Cherkashina, A. A.

2018-01-01

The work evaluates the general distribution of mercury in the soil cover of the Tunkinskaya depression (the Republic of Buryatia, the national park "Tunkinsky"). For this purpose, its gross contents in natural and agrogenically transformed soils were studied: plow lands, fallow lands, hayfields and pastures. The physico-technical characteristics of soils, the content of organic carbon, group composition of humus are determined. The method of processing the results included the calculation of the ecological and geochemical parameters: the concentration coefficient relative to the background, MAC, Clark concentration relative to the Earth’s crust, the Earth’s soils, the identification of the relationship with the physical and technical characteristics of the soil, and the content of C02, CO2 carbonates, fulvic and humic acids.

Improved ground hydrology calculations for global climate models (GCMs) - Soil water movement and evapotranspiration

NASA Technical Reports Server (NTRS)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-01-01

A physically based ground hydrology model is presented that includes the processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff. Data from the Goddard Institute for Space Studies GCM were used as inputs for off-line tests of the model in four 8 x 10 deg regions, including Brazil, Sahel, Sahara, and India. Soil and vegetation input parameters were caculated as area-weighted means over the 8 x 10 deg gridbox; the resulting hydrological quantities were compared to ground hydrology model calculations performed on the 1 x 1 deg cells which comprise the 8 x 10 deg gridbox. Results show that the compositing procedure worked well except in the Sahel, where low soil water levels and a heterogeneous land surface produce high variability in hydrological quantities; for that region, a resolution better than 8 x 10 deg is needed.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

EPA Science Inventory

We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

Why some plant species are rare.

PubMed

Wieger Wamelink, G W; Wamelink, G W Weiger; Goedhart, Paul W; Frissel, Joep; Frissel, Josep Y

2014-01-01

Biodiversity, including plant species diversity, is threatened worldwide as a result of anthropogenic pressures such as an increase of pollutants and climate change. Rare species in particular are on the verge of becoming extinct. It is still unclear as to why some plant species are rare and others are not. Are they rare due to: intrinsic reasons, dispersal capacity, the effects of management or abiotic circumstances? Habitat preference of rare plant species may play an important role in determining why some species are rare. Based on an extensive data set of soil parameters we investigated if rarity is due to a narrow habitat preference for abiotic soil parameters. For 23 different abiotic soil parameters, of which the most influential were groundwater-table, soil-pH and nutrient-contents, we estimated species responses for common and rare species. Based on the responses per species we calculated the range of occurrence, the range between the 5 and 95 percentile of the response curve giving the habitat preference. Subsequently, we calculated the average response range for common and rare species. In addition, we designed a new graphic in order to provide a better means for presentation of the results. The habitat preferences of rare species for abiotic soil conditions are significantly narrower than for common species. Twenty of the twenty-three abiotic parameters showed on average significantly narrower habitat preferences for rare species than for common species; none of the abiotic parameters showed on average a narrower habitat preference for common species. The results have major implications for the conservation of rare plant species; accordingly management and nature development should be focussed on the maintenance and creation of a broad range of environmental conditions, so that the requirements of rare species are met. The conservation of (abiotic) gradients within ecosystems is particularly important for preserving rare species.

Analytical and numerical analyses of an unconfined aquifer test considering unsaturated zone characteristics

USGS Publications Warehouse

Moench, A.F.

2008-01-01

A 7-d, constant rate aquifer test conducted by University of Waterloo researchers at Canadian Forces Base Borden in Ontario, Canada, is useful for advancing understanding of fluid flow processes in response to pumping from an unconfined aquifer. Measured data include not only drawdown in the saturated zone but also volumetric soil moisture measured at various times and distances from the pumped well. Analytical analyses were conducted with the model published in 2001 by Moench and colleagues, which allows for gradual drainage but does not include unsaturated zone characteristics, and the model published in 2006 by Mathias and Butler, which assumes that moisture retention and relative hydraulic conductivity (RHC) in the unsaturated zone are exponential functions of pressure head. Parameters estimated with either model yield good matches between measured and simulated drawdowns in piezometers. Numerical analyses were conducted with two versions of VS2DT: one that uses traditional Brooks and Corey functional relations and one that uses a RHC function introduced in 2001 by Assouline that includes an additional parameter that accounts for soil structure and texture. The analytical model of Mathias and Butler and numerical model of VS2DT with the Assouline model both show that the RHC function must contain a fitting parameter that is different from that used in the moisture retention function. Results show the influence of field-scale heterogeneity and suggest that the RHC at the Borden site declines more rapidly with elevation above the top of the capillary fringe than would be expected if the parameters were to reflect local- or core-scale soil structure and texture.

Modeling precipitation use efficiency of winter wheat using climatic parameters, soil properties and topographic indices in a semiarid region, Khodabandeh County, Iran

NASA Astrophysics Data System (ADS)

Babaei, Fatemeh; Vaezi, AliReza; Taheri, Mehdi; Zarrinabadi, Ehsan

2017-04-01

Improved understanding of the impact of crucial factors affecting on rainfed wheat precipitation use efficiency (PUE), is needed to cope with increasing demands for sustainable agriculture in semiarid regions. The present research has assessed the effects of climatic parameters, soil physiochemical characteristics and topographic indices on wheat gain yield (WGY), PUE and effective precipitation use efficiency (PUEe) of rainfed winter wheat in a research over rainfed wheat croplands of Khodabandeh County. Therefore, 289 soil samples were collected from rainfed winter wheat croplands in two replicates, totally 578 soil samples, within the county of Khodanbandeh, in (2013-2014). Also, the WGY was measured in each cropland that year. Environmental variables including some soil physiochemical characteristics, topographic indices derived from digital terrain analysis and climatic parameters including growth season precipitation and air temperature were analyzed to develop a proper model to represent WGY, PUE and PUEe. Similar to the first study, the data was divided into two dataset: model (n=238) and test dataset (n=60) and the decision tree was used to develop the best suitable model to describe WGY, PUE and PUEe. The results indicated that CK using slope as auxiliary variable played as the best model to describe the spatial variation of WGY (n=60, R2=0.92, RMSE= 77.78 kg ha-1). Although, MLR combining principal component analysis (PCA) was able to describe PUE significantly (n=238, R2=0.28, P<0.01), however all the applied methods appeared poor in spatially modeling of PUE (n=60, R2<0.05, RMSE> 1.34 kg ha-1 mm-1). Similarly, PUEe was modeled significantly (n=238, R2=0.25, P<0.01) using MLR combining PCA but the model goodness was really poor over Khodabandeh county (n=60, R2=0.11, RMSE= 1.23 kg ha-1 mm-1). In general, it can be concluded that slope was the most crucial affecting parameter on WGY. In addition to, organic matter is the most important soil properties in PUE determination. Among all models Kr and CK performed better than other spatial interpolation models. In order to the lacking of reliable climatic data especially in small scales, and complexity of effective parameters, accurate spatially modelling of PUE and PUEe appears difficult.

[Quality level assessment of lowly efficient Tamarix chinensis secondary shrubs in Laizhou Bay of Yellow River Delta].

PubMed

Xia, Jiang-Bao; Liu, Yu-Ting; Zhu, Jin-Fang; Xu, Jing-Wei; Lu, Zhao-Hua; Liu, Jing-Tao; Liu, Qing

2013-06-01

Taking the Tamarix chinensis secondary shrubs in Laizhou Bay of Yellow River Delta as test objects, and by using synthetic factor method, this paper studied the main factors causing the lowly efficiency of T. chinensis secondary shrubs as well as the main parameters for the classification of lowly efficient T. chinensis secondary shrubs. A total of 24 indices including shrubs growth and soil physical and chemical properties were selected to determine the main affecting factors and parameters in evaluating and classifying the lowly efficient shrubs. There were no obvious correlations between the indices reflecting the shrubs growth and soil quality, and thus, only using shrub growth index to reflect the lowly efficiency level of T. chinensis was not enough, and it would be necessary to combine with soil quality factors to make a comprehensive evaluation. The principal factors reflecting the quality level of lowly efficient T. chinensis shrubs included soil salt content and moisture content, stand age, single tree's aboveground stem, leaf biomass, and basal diameter, followed by soil density, porosity, and soil nutrient status. The lowly efficient T. chinensis shrubs in the Bay could be classified into five types, namely, shrub with growth potential, slightly low quality shrub, moderately lowly efficient shrub, moderately low quality and lowly efficient shrub, and seriously low quality and lowly efficient shrub. The main features, low efficiency causes, and management measures of these shrubs were discussed based on the mean cluster value.

Soil development on stable landforms and implications for landscape studies

USGS Publications Warehouse

Harden, J.W.

1990-01-01

Soil development parameters include a wide variety of morphological, chemical, and mineralogical parameters, but some of the best indicators of time and surface stability are derived from field morphology. Over long time-spans, the most common time function for soil development is exponential or logarithmic, in which rates decrease with increasing age. Over shorter time-spans in semi-arid and moister climates, Holocene and Pleistocene soil development functions appear as linear segments, with Holocene rates about 10 to 50 times those of Pleistocene rates. In contrast to significant temporal variation in rates, geographical variation in rates within (a) the southern Great Basin and (b) the east Central Valley of California is on the order of 2 or 3 times. When comparing soil development indices of the semi-arid Great Basin to those of moister central California, Holocene rates are similar, but Pleistocene rates are more than 10 times slower in the Great Basin. In a range of climatic settings, the reasons for declining rates over time are several and are complexly related to erosional history, fluxes in water and dust related to climatic changes, rates of primary mineral dissolution, and intrinsic soil processes. ?? 1990.

Effect of new organic supplement (Panchgavya) on seed germination and soil quality.

PubMed

Jain, Paras; Sharma, Ravi Chandra; Bhattacharyya, Pradip; Banik, Pabitra

2014-04-01

We studied the suitability of Panchgavya (five products of cow), new organic amendment, application on seed germination, plant growth, and soil health. After characterization, Panchgavya was mixed with water to form different concentration and was tested for seed germination, germination index, and root and shoot growth of different seedlings. Four percent solution of Panchgavya was applied to different plants to test its efficacy. Panchgavya and other two organic amendments were incorporated in soil to test the change of soil chemical and microbiological parameters. Panchgavya contained higher nutrients as compared to farm yard manure (FYM) and vermicompost. Its application on different seeds has positively influenced germination percentage, germination index, root and shoot length, and fresh and dry weight of the seedling. Water-soluble macronutrients including pH and metal were positively and negatively correlated with the growth parameters, respectively. Four percent solution of Panchgavya application on some plants showed superiority in terms of plant height and chlorophyll content. Panchgavya-applied soil had higher values of macro and micronutrients (zinc, copper, and manganese), microbial activity as compared to FYM, and vermicompost applied soils. Application of Panchgavya can be gainfully used as an alternative organic supplement in agriculture.

Local versus field scale soil heterogeneity characterization - a challenge for representative sampling in pollution studies

NASA Astrophysics Data System (ADS)

Kardanpour, Z.; Jacobsen, O. S.; Esbensen, K. H.

2015-06-01

This study is a contribution to development of a heterogeneity characterisation facility for "next generation" sampling aimed at more realistic and controllable pesticide variability in laboratory pots in experimental environmental contaminant assessment. The role of soil heterogeneity on quantification of a set of exemplar parameters, organic matter, loss on ignition (LOI), biomass, soil microbiology, MCPA sorption and mineralization is described, including a brief background on how heterogeneity affects sampling/monitoring procedures in environmental pollutant studies. The Theory of Sampling (TOS) and variographic analysis has been applied to develop a fit-for-purpose heterogeneity characterization approach. All parameters were assessed in large-scale profile (1-100 m) vs. small-scale (0.1-1 m) replication sampling pattern. Variographic profiles of experimental analytical results concludes that it is essential to sample at locations with less than a 2.5 m distance interval to benefit from spatial auto-correlation and thereby avoid unnecessary, inflated compositional variation in experimental pots; this range is an inherent characteristic of the soil heterogeneity and will differ among soils types. This study has a significant carrying-over potential for related research areas e.g. soil science, contamination studies, and environmental monitoring and environmental chemistry.

Remote sensing studies of immature soils on the Moon (Reiner-gamma formation)

NASA Technical Reports Server (NTRS)

Shevchenko, V. V.; Pinet, P.; Chevrel, S.

1993-01-01

On the base of laboratory results and telescopic data it is shown that the spectropolarization ratio P(sub max(sup B))/P(sub max(sup R)) for blue and red spectral regions is a remote sensing parameter of lunar soil maturity. It correlates with value of maturity index derived from morphological or ferromagnetic methods of exposure age determination. This parameter is equal to 0.315 for Reiner-gamma formation. So Reiner-gamma area is covered by immature soil. An extensive spectral mapping of the Reiner-gamma formation with high spatial resolution (0.2 km/pixel) was produced. This result was obtained at the 2-meter aperture telescope of Pic-du-Midi (France). The data sets consist in repeated runs comprising 10 selected narrow-band images (from 0.4 to 1.05 micron). The analysis of these data suggests that such a type of immature material includes not more than 28% of agglutinattes. We find the model grain size of fine fraction to be 40 micrometers grain size, of more immature soil 400-500 micrometers, and of the formation soil 120-150 micrometers. The exposure age of the Reiner-gamma immature soil is equal about 10 x 10(exp 6) years.

Safety assessment of a shallow foundation using the random finite element method

NASA Astrophysics Data System (ADS)

Zaskórski, Łukasz; Puła, Wojciech

2015-04-01

A complex structure of soil and its random character are reasons why soil modeling is a cumbersome task. Heterogeneity of soil has to be considered even within a homogenous layer of soil. Therefore an estimation of shear strength parameters of soil for the purposes of a geotechnical analysis causes many problems. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Only general guidelines can be found how these values should be estimated. Hence many approaches of an assessment of characteristic values of soil parameters are presented in literature and can be applied in practice. In this paper, the reliability assessment of a shallow strip footing was conducted using a reliability index β. Therefore some approaches of an estimation of characteristic values of soil properties were compared by evaluating values of reliability index β which can be achieved by applying each of them. Method of Orr and Breysse, Duncan's method, Schneider's method, Schneider's method concerning influence of fluctuation scales and method included in Eurocode 7 were examined. Design values of the bearing capacity based on these approaches were referred to the stochastic bearing capacity estimated by the random finite element method (RFEM). Design values of the bearing capacity were conducted for various widths and depths of a foundation in conjunction with design approaches DA defined in Eurocode. RFEM was presented by Griffiths and Fenton (1993). It combines deterministic finite element method, random field theory and Monte Carlo simulations. Random field theory allows to consider a random character of soil parameters within a homogenous layer of soil. For this purpose a soil property is considered as a separate random variable in every element of a mesh in the finite element method with proper correlation structure between points of given area. RFEM was applied to estimate which theoretical probability distribution fits the empirical probability distribution of bearing capacity basing on 3000 realizations. Assessed probability distribution was applied to compute design values of the bearing capacity and related reliability indices β. Conducted analysis were carried out for a cohesion soil. Hence a friction angle and a cohesion were defined as a random parameters and characterized by two dimensional random fields. A friction angle was described by a bounded distribution as it differs within limited range. While a lognormal distribution was applied in case of a cohesion. Other properties - Young's modulus, Poisson's ratio and unit weight were assumed as deterministic values because they have negligible influence on the stochastic bearing capacity. Griffiths D. V., & Fenton G. A. (1993). Seepage beneath water retaining structures founded on spatially random soil. Géotechnique, 43(6), 577-587.

Soil biological activity at European scale - two calculation concepts

NASA Astrophysics Data System (ADS)

Krüger, Janine; Rühlmann, Jörg

2014-05-01

The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. To assess the turnover conditions two model concepts are applied: (I) Biological active time (BAT) regression approach derived from CANDY model (Franko & Oelschlägel 1995) expresses the variation of air temperature, precipitation and soil texture as a timescale and an indicator of biological activity for soil organic matter (SOM) turnover. (II) Re_clim parameter within the Introductory Carbon Balance Model (Andrén & Kätterer 1997) states the soil temperature and soil water to estimate soil biological activity. The modelling includes two strategies to cover the European scale and conditions. BAT was calculated on a 20x20 km grid basis. The European data sets of precipitation and air temperature (time period 1901-2000, monthly resolution), (Mitchell et al. 2004) were used to derive long-term averages. As we focus on agricultural areas we included CORINE data (2006) to extract arable land. The resulting BATs under co-consideration of the main soil textures (clay, silt, sand and loam) were investigated per environmental zone (ENZs, Metzger et al. 2005) that represents similar conditions for precipitation, temperature and relief to identify BAT ranges and hence turnover conditions for each ENZ. Re_clim was quantified by climatic time series of more than 250 weather stations across Europe presented by Klein Tank et al. (2002). Daily temperature, precipitation and potential evapotranspiration (maximal thermal extent) were used to calculate soil temperature and water storage in the arable layer thereby differentiating soil textures exclusively in main types (clay, silt, sand and loam). Similar to the BAT investigation it was of further interest to investigate how the re_clim parameter range behaves per ENZ. We will discuss the analyzed results of both strategies in a comparative manner to assess SOM turnover conditions across Europe. Both concepts help to separate different turnover activities and to indicate organic matter input in order to maintain the given SOM. The assessment could provide local recommendations for local adaptations of soil management practices. CATCH-C is funded within the 7th Framework Programme for Research, Technological Development and Demonstration, Theme 2 - Biotechnologies, Agriculture & Food (Grant Agreement N° 289782).

Evaluation of MEDALUS model for desertification hazard zonation using GIS; study area: Iyzad Khast plain, Iran.

PubMed

Farajzadeh, Manuchehr; Egbal, Mahbobeh Nik

2007-08-15

In this study, the MEDALUS model along with GIS mapping techniques are used to determine desertification hazards for a province of Iran to determine the desertification hazard. After creating a desertification database including 20 parameters, the first steps consisted of developing maps of four indices for the MEDALUS model including climate, soil, vegetation and land use were prepared. Since these parameters have mostly been presented for the Mediterranean region in the past, the next step included the addition of other indicators such as ground water and wind erosion. Then all of the layers weighted by environmental conditions present in the area were used (following the same MEDALUS framework) before a desertification map was prepared. The comparison of two maps based on the original and modified MEDALUS models indicates that the addition of more regionally-specific parameters into the model allows for a more accurate representation of desertification processes across the Iyzad Khast plain. The major factors affecting desertification in the area are climate, wind erosion and low land quality management, vegetation degradation and the salinization of soil and water resources.

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

Sensitivity Analysis Reveals Critical Factors that Affect Wetland Methane Emissions using Soil Biogeochemistry Model

NASA Astrophysics Data System (ADS)

Alonso-Contes, C.; Gerber, S.; Bliznyuk, N.; Duerr, I.

2017-12-01

Wetlands contribute approximately 20 to 40 % to global sources of methane emissions. We build a Methane model for tropical and subtropical forests, that allows inundated conditions, following the approaches used in more complex global biogeochemical emission models (LPJWhyMe and CLM4Me). The model was designed to replace model formulations with field and remotely sensed collected data for 2 essential drivers: plant productivity and hydrology. This allows us to directly focus on the central processes of methane production, consumption and transport. One of our long term goals is to make the model available to a scientists interested in including methane modeling in their location of study. Sensitivity analysis results help in focusing field data collection efforts. Here, we present results from a pilot global sensitivity analysis of the model order to determine which parameters and processes contribute most to the model's uncertainty of methane emissions. Results show that parameters related to water table behavior, carbon input (in form of plant productivity) and rooting depth affect simulated methane emissions the most. Current efforts include to perform the sensitivity analysis again on methane emissions outputs from an updated model that incorporates a soil heat flux routine and to determine the extent by which the soil temperature parameters affect CH4 emissions. Currently we are conducting field collection of data during Summer 2017 for comparison among 3 different landscapes located in the Ordway-Swisher Biological Station in Melrose, FL. We are collecting soil moisture and CH4 emission data from 4 different wetland types. Having data from 4 wetland types allows for calibration of the model to diverse soil, water and vegetation characteristics.

[Estimation of the effect derived from wind erosion of soil and dust emission in Tianjin suburbs on the central district based on WEPS model].

PubMed

Chen, Li; Han, Ting-Ting; Li, Tao; Ji, Ya-Qin; Bai, Zhi-Peng; Wang, Bin

2012-07-01

Due to the lack of a prediction model for current wind erosion in China and the slow development for such models, this study aims to predict the wind erosion of soil and the dust emission and develop a prediction model for wind erosion in Tianjin by investigating the structure, parameter systems and the relationships among the parameter systems of the prediction models for wind erosion in typical areas, using the U.S. wind erosion prediction system (WEPS) as reference. Based on the remote sensing technique and the test data, a parameter system was established for the prediction model of wind erosion and dust emission, and a model was developed that was suitable for the prediction of wind erosion and dust emission in Tianjin. Tianjin was divided into 11 080 blocks with a resolution of 1 x 1 km2, among which 7 778 dust emitting blocks were selected. The parameters of the blocks were localized, including longitude, latitude, elevation and direction, etc.. The database files of blocks were localized, including wind file, climate file, soil file and management file. The weps. run file was edited. Based on Microsoft Visualstudio 2008, secondary development was done using C + + language, and the dust fluxes of 7 778 blocks were estimated, including creep and saltation fluxes, suspension fluxes and PM10 fluxes. Based on the parameters of wind tunnel experiments in Inner Mongolia, the soil measurement data and climate data in suburbs of Tianjin, the wind erosion module, wind erosion fluxes, dust emission release modulus and dust release fluxes were calculated for the four seasons and the whole year in suburbs of Tianjin. In 2009, the total creep and saltation fluxes, suspension fluxes and PM10 fluxes in the suburbs of Tianjin were 2.54 x 10(6) t, 1.25 x 10(7) t and 9.04 x 10(5) t, respectively, among which, the parts pointing to the central district were 5.61 x 10(5) t, 2.89 x 10(6) t and 2.03 x 10(5) t, respectively.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Optimizing available water capacity using microwave satellite data for improving irrigation management

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2015-04-01

This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into two steps during one time interval: the state variable is optimized through the state filter and the optimal parameter values are then transferred for retrieving soil moisture. However, soil moisture from sensors such as AMSR-E can only be retrieved for the top few centimeters of soil. So, for the present study, a homogeneous soil system has been considered. By assimilating this information into the model, the accuracy of model structure in relating surface moisture dynamics to deeper soil profiles can be ascertained. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments alongwith the available water capacity, the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the soil moisture simulations. The optimized parameters as compared to the pedo-transfer based parameters were found to reduce the RMSE from 0.14 to 0.04 and 0.15 to 0.07 in surface layer and root zone respectively.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

Evapotranspiration from nonuniform surfaces - A first approach for short-term numerical weather prediction

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1988-01-01

Observations of surface heterogeneity of soil moisture from scales of meters to hundreds of kilometers are discussed, and a relationship between grid element size and soil moisture variability is presented. An evapotranspiration model is presented which accounts for the variability of soil moisture, standing surface water, and vegetation internal and stomatal resistance to moisture flow from the soil. The mean values and standard deviations of these parameters are required as input to the model. Tests of this model against field observations are reported, and extensive sensitivity tests are presented which explore the importance of including subgrid-scale variability in an evapotranspiration model.

Recycled grains in lunar soils as an additional, necessary, regolith evolution parameter

NASA Technical Reports Server (NTRS)

Basu, A.

1990-01-01

Recycled lunar soil grains are defined as those soil grains that have been a part of either regolith breccias or agglutinates; thus, mineral grains, rock fragments, older agglutinates, and volcanic glass spherules, if dislodged from an agglutinate or a regolith breccia, would all qualify as recycled grains. This paper shows that it is possible to estimate the proportion of recycled material in lunar soils. Optical data from 12 soils in the Apollo 16 core 64001/2 were collected to estimate the proportion (W) of recycled crystalline grains in each of these soils. The W values show a correspondence with other independently derived parameters and the history of the core soils, indicating that W can be used as a valid soil-evolution parameter.

How far are rheological parameters from amplitude sweep tests predictable using common physicochemical soil properties?

NASA Astrophysics Data System (ADS)

Stoppe, N.; Horn, R.

2017-01-01

A basic understanding of soil behavior on the mesoscale resp. macroscale (i.e. soil aggregates resp. bulk soil) requires knowledge of the processes at the microscale (i.e. particle scale), therefore rheological investigations of natural soils receive growing attention. In the present research homogenized and sieved (< 2 mm) samples from Marshland soils of the riparian zone of the River Elbe (North Germany) were analyzed with a modular compact rheometer MCR 300 (Anton Paar, Ostfildern, Germany) with a profiled parallel-plate measuring system. Amplitude sweep tests (AST) with controlled shear deformation were conducted to investigate the viscoelastic properties of the studied soils under oszillatory stress. The gradual depletion of microstructural stiffness during AST cannot only be characterized by the well-known rheological parameters G, G″ and tan δ but also by the dimensionless area parameter integral z, which quantifies the elasticity of microstructure. To discover the physicochemical parameters, which influences the microstructural stiffness, statistical tests were used taking the combined effects of these parameters into account. Although the influence of the individual factors varies depending on soil texture, the physicochemical features significantly affecting soil micro structure were identified. Based on the determined statistical relationships between rheological and physicochemical parameters, pedotransfer functions (PTF) have been developed, which allow a mathematical estimation of the rheological target value integral z. Thus, stabilizing factors are: soil organic matter, concentration of Ca2+, content of CaCO3 and pedogenic iron oxides; whereas the concentration of Na+ and water content represent structurally unfavorable factors.

Binational digital soils map of the Ambos Nogales watershed, southern Arizona and northern Sonora, Mexico

USGS Publications Warehouse

Norman, Laura

2004-01-01

We have prepared a digital map of soil parameters for the international Ambos Nogales watershed to use as input for selected soils-erosion models. The Ambos Nogales watershed in southern Arizona and northern Sonora, Mexico, contains the Nogales wash, a tributary of the Upper Santa Cruz River. The watershed covers an area of 235 km2, just under half of which is in Mexico. Preliminary investigations of potential erosion revealed a discrepancy in soils data and mapping across the United States-Mexican border due to issues including different mapping resolutions, incompatible formatting, and varying nomenclature and classification systems. To prepare a digital soils map appropriate for input to a soils-erosion model, the historical analog soils maps for Nogales, Ariz., were scanned and merged with the larger-scale digital soils data available for Nogales, Sonora, Mexico using a geographic information system.

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Jung, B.; Gillespie, K.; Hemmat, M.; Aslam, A.; Brunfeldt, D.; Dobson, M. C.

1983-01-01

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

Relevant magnetic and soil parameters as potential indicators of soil conservation status of Mediterranean agroecosystems

NASA Astrophysics Data System (ADS)

Quijano, Laura; Chaparro, Marcos A. E.; Marié, Débora C.; Gaspar, Leticia; Navas, Ana

2014-09-01

The main sources of magnetic minerals in soils unaffected by anthropogenic pollution are iron oxides and hydroxides derived from parent materials through soil formation processes. Soil magnetic minerals can be used as indicators of environmental factors including soil forming processes, degree of pedogenesis, weathering processes and biological activities. In this study measurements of magnetic susceptibility are used to detect the presence and the concentration of soil magnetic minerals in topsoil and bulk samples in a small cultivated field, which forms a hydrological unit that can be considered to be representative of the rainfed agroecosystems of Mediterranean mountain environments. Additional magnetic studies such as isothermal remanent magnetization (IRM), anhysteretic remanent magnetization (ARM) and thermomagnetic measurements are used to identify and characterize the magnetic mineralogy of soil minerals. The objectives were to analyse the spatial variability of the magnetic parameters to assess whether topographic factors, soil redistribution processes, and soil properties such as soil texture, organic matter and carbonate contents analysed in this study, are related to the spatial distribution pattern of magnetic properties. The medians of mass specific magnetic susceptibility at low frequency (χlf) were 36.0 and 31.1 × 10-8 m3 kg-1 in bulk and topsoil samples respectively. High correlation coefficients were found between the χlf in topsoil and bulk core samples (r = 0.951, p < 0.01). In addition, volumetric magnetic susceptibility was measured in situ in the field (κis) and values varied from 13.3 to 64.0 × 10-5 SI. High correlation coefficients were found between χlf in topsoil measured in the laboratory and volumetric magnetic susceptibility field measurements (r = 0.894, p < 0.01). The results obtained from magnetic studies such as IRM, ARM and thermomagnetic measurements show the presence of magnetite, which is the predominant magnetic carrier, and hematite. The predominance of superparamagnetic minerals in upper soil layers suggests enrichment in pedogenic minerals. The finer soil particles, the organic matter content and the magnetic susceptibility values are statistically correlated and their spatial variability is related to similar physical processes. Runoff redistributes soil components including magnetic minerals and exports fine particles out the field. This research contributed to further knowledge on the application of soil magnetic properties to derive useful information on soil processes in Mediterranean cultivated soils.

A point-infiltration model for estimating runoff from rainfall on small basins in semiarid areas of Wyoming

USGS Publications Warehouse

Rankl, James G.

1990-01-01

A physically based point-infiltration model was developed for computing infiltration of rainfall into soils and the resulting runoff from small basins in Wyoming. The user describes a 'design storm' in terms of average rainfall intensity and storm duration. Information required to compute runoff for the design storm by using the model include (1) soil type and description, and (2) two infiltration parameters and a surface-retention storage parameter. Parameter values are tabulated in the report. Rainfall and runoff data for three ephemeral-stream basins that contain only one type of soil were used to develop the model. Two assumptions were necessary: antecedent soil moisture is some long-term average, and storm rainfall is uniform in both time and space. The infiltration and surface-retention storage parameters were determined for the soil of each basin. Observed rainstorm and runoff data were used to develop a separation curve, or incipient-runoff curve, which distinguishes between runoff and nonrunoff rainfall data. The position of this curve defines the infiltration and surface-retention storage parameters. A procedure for applying the model to basins that contain more than one type of soil was developed using data from 7 of the 10 study basins. For these multiple-soil basins, the incipient-runoff curve defines the infiltration and retention-storage parameters for the soil having the highest runoff potential. Parameters were defined by ranking the soils according to their relative permeabilities and optimizing the position of the incipient-runoff curve by using measured runoff as a control for the fit. Analyses of runoff from multiple-soil basins indicate that the effective contributing area of runoff is less than the drainage area of the basin. In this study, the effective drainage area ranged from 41.6 to 71.1 percent of the total drainage area. Information on effective drainage area is useful in evaluating drainage area as an independent variable in statistical analyses of hydrologic data, such as annual peak frequency distributions and sediment yield.A comparison was made of the sum of the simulated runoff and the sum of the measured runoff for all available records of runoff-producing storms in the 10 study basins. The sums of the simulated runoff ranged from 12.0 percent less than to 23.4 percent more than the sums of the measured runoff. A measure of the standard error of estimate was computed for each data set. These values ranged from 20 to 70 percent of the mean value of the measured runoff. Rainfall-simulator infiltrometer tests were made in two small basins. The amount of water uptake measured by the test in Dugout Creek tributary basin averaged about three times greater than the amount of water uptake computed from rainfall and runoff data. Therefore, infiltrometer data were not used to determine infiltration rates for this study.

Topsoil structure stability in a restored floodplain: Impacts of fluctuating water levels, soil parameters and ecosystem engineers.

PubMed

Schomburg, A; Schilling, O S; Guenat, C; Schirmer, M; Le Bayon, R C; Brunner, P

2018-10-15

Ecosystem services provided by floodplains are strongly controlled by the structural stability of soils. The development of a stable structure in floodplain soils is affected by a complex and poorly understood interplay of hydrological, physico-chemical and biological processes. This paper aims at analysing relations between fluctuating groundwater levels, soil physico-chemical and biological parameters on soil structure stability in a restored floodplain. Water level fluctuations in the soil are modelled using a numerical surface-water-groundwater flow model and correlated to soil physico-chemical parameters and abundances of plants and earthworms. Causal relations and multiple interactions between the investigated parameters are tested through structural equation modelling (SEM). Fluctuating water levels in the soil did not directly affect the topsoil structure stability, but indirectly through affecting plant roots and soil parameters that in turn determine topsoil structure stability. These relations remain significant for mean annual days of complete and partial (>25%) water saturation. Ecosystem functioning of a restored floodplain might already be affected by the fluctuation of groundwater levels alone, and not only through complete flooding by surface water during a flood period. Surprisingly, abundances of earthworms did not show any relation to other variables in the SEM. These findings emphasise that earthworms have efficiently adapted to periodic stress and harsh environmental conditions. Variability of the topsoil structure stability is thus stronger driven by the influence of fluctuating water levels on plants than by the abundance of earthworms. This knowledge about the functional network of soil engineering organisms, soil parameters and fluctuating water levels and how they affect soil structural stability is of fundamental importance to define management strategies of near-natural or restored floodplains in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

Coupled land surface–subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

DOE PAGES

Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.

2017-09-06

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological–thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon–climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological–thermal processes associated with annual freeze–thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets – including soil liquid watermore » content, temperature and electrical resistivity tomography (ERT) data – to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological–thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface–subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice–liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological–thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological–thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface–subsurface, deterministic–stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological–thermal dynamics.« less

Coupled land surface–subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.

Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological–thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon–climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological–thermal processes associated with annual freeze–thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets – including soil liquid watermore » content, temperature and electrical resistivity tomography (ERT) data – to estimate the vertical distribution of OC content. Our approach relies on the fact that OC content strongly influences soil hydrological–thermal parameters and, therefore, indirectly controls the spatiotemporal dynamics of soil liquid water content, temperature and their correlated electrical resistivity. We employ the Community Land Model to simulate nonisothermal surface–subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes (e.g., solar radiation balance, evapotranspiration, snow accumulation and melting) and ice–liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate a posteriori distributions of desired model parameters. For hydrological–thermal-to-geophysical variable transformation, the simulated subsurface temperature, liquid water content and ice content are explicitly linked to soil electrical resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantify the propagation of uncertainty from the estimated parameters to prediction of hydrological–thermal responses. We find that, compared to inversion of single dataset (temperature, liquid water content or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (top 0.3 m of soil) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (here at about 0.6 m depth), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, which is often observed in organic-rich Arctic soil, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface–subsurface, deterministic–stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological–thermal dynamics.« less

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

Development of an analytical solution for the Budyko watershed parameter in terms of catchment physical features

NASA Astrophysics Data System (ADS)

Reaver, N.; Kaplan, D. A.; Jawitz, J. W.

2017-12-01

The Budyko hypothesis states that a catchment's long-term water and energy balances are dependent on two relatively easy to measure quantities: rainfall depth and potential evaporation. This hypothesis is expressed as a simple function, the Budyko equation, which allows for the prediction of a catchment's actual evapotranspiration and discharge from measured rainfall depth and potential evaporation, data which are widely available. However, the two main analytically derived forms of the Budyko equation contain a single unknown watershed parameter, whose value varies across catchments; variation in this parameter has been used to explain the hydrological behavior of different catchments. The watershed parameter is generally thought of as a lumped quantity that represents the influence of all catchment biophysical features (e.g. soil type and depth, vegetation type, timing of rainfall, etc). Previous work has shown that the parameter is statistically correlated with catchment properties, but an explicit expression has been elusive. While the watershed parameter can be determined empirically by fitting the Budyko equation to measured data in gauged catchments where actual evapotranspiration can be estimated, this limits the utility of the framework for predicting impacts to catchment hydrology due to changing climate and land use. In this study, we developed an analytical solution for the lumped catchment parameter for both forms of the Budyko equation. We combined these solutions with a statistical soil moisture model to obtain analytical solutions for the Budyko equation parameter as a function of measurable catchment physical features, including rooting depth, soil porosity, and soil wilting point. We tested the predictive power of these solutions using the U.S. catchments in the MOPEX database. We also compared the Budyko equation parameter estimates generated from our analytical solutions (i.e. predicted parameters) with those obtained through the calibration of the Budyko equation to discharge data (i.e. empirical parameters), and found good agreement. These results suggest that it is possible to predict the Budyko equation watershed parameter directly from physical features, even for ungauged catchments.

Evolution of Pedostructure Parameters Under Tillage Practices

USDA-ARS?s Scientific Manuscript database

The pedostructure (PS) concept is a physically-based method of soil characterization that defines a soil based on its structure and the relationship between structure and soil water behavior. There are 15 unique pedostructure parameters that define the macropore and micropore soil water behavior fo...

Inference of soil hydrologic parameters from electronic soil moisture records

USDA-ARS?s Scientific Manuscript database

Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge, and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity, and permanent wilting point have been deter...

Advancement of a soil parameters geodatabase for the modeling assessment of conservation practice outcomes in the United States

USDA-ARS?s Scientific Manuscript database

US-ModSoilParms-TEMPLE is a database composed of a set of geographic databases functionally storing soil-spatial units and soil hydraulic, physical, and chemical parameters for three agriculture management simulation models, SWAT, APEX, and ALMANAC. This paper introduces the updated US-ModSoilParms-...

Soil experiment

NASA Technical Reports Server (NTRS)

Hutcheson, Linton; Butler, Todd; Smith, Mike; Cline, Charles; Scruggs, Steve; Zakhia, Nadim

1987-01-01

An experimental procedure was devised to investigate the effects of the lunar environment on the physical properties of simulated lunar soil. The test equipment and materials used consisted of a vacuum chamber, direct shear tester, static penetrometer, and fine grained basalt as the simulant. The vacuum chamber provides a medium for applying the environmental conditions to the soil experiment with the exception of gravity. The shear strength parameters are determined by the direct shear test. Strength parameters and the resistance of soil penetration by static loading will be investigated by the use of a static cone penetrometer. In order to conduct a soil experiment without going to the moon, a suitable lunar simulant must be selected. This simulant must resemble lunar soil in both composition and particle size. The soil that most resembles actual lunar soil is basalt. The soil parameters, as determined by the testing apparatus, will be used as design criteria for lunar soil engagement equipment.

Soil and vegetation parameter uncertainty on future terrestrial carbon sinks

NASA Astrophysics Data System (ADS)

Kothavala, Z.; Felzer, B. S.

2013-12-01

We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.

Representing Plant Hydraulics in a Global Model: Updates to the Community Land Model

NASA Astrophysics Data System (ADS)

Kennedy, D.; Swenson, S. C.; Oleson, K. W.; Lawrence, D. M.; Fisher, R.; Gentine, P.

2017-12-01

In previous versions, the Community Land Model has used soil moisture to stand in for plant water status, with transpiration and photosynthesis driven directly by soil water potential. This eschews significant literature demonstrating the importance of plant hydraulic traits in the dynamics of water flow through the soil-plant-atmosphere continuum and in the regulation of stomatal aperture. In this study we install a simplified hydraulic framework to represent vegetation water potential and to regulate root water uptake and turbulent fluxes. Plant hydraulics allow for a more explicit representation of plant water status, which improves the physical basis for many processes represented in CLM. This includes root water uptake and the attenuation of photosynthesis and transpiration with drought. Model description is accompanied by results from a point simulation based at the Caxiuanã flux tower site in Eastern Amazonia, covering a throughfall exclusion experiment from 2001-2003. Including plant hydraulics improves the response to drought forcing compared to previous versions of CLM. Parameter sensitivity is examined at the same site and presented in the context of estimating hydraulic parameters in a global model.

Current advancements and challenges in soil-root interactions modelling

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Huber, Katrin; Abesha, Betiglu; Meunier, Felicien; Leitner, Daniel; Roose, Tiina; Javaux, Mathieu; Vanderborght, Jan; Vereecken, Harry

2015-04-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Current Advancements and Challenges in Soil-Root Interactions Modelling

NASA Astrophysics Data System (ADS)

Schnepf, A.; Huber, K.; Abesha, B.; Meunier, F.; Leitner, D.; Roose, T.; Javaux, M.; Vanderborght, J.; Vereecken, H.

2014-12-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Enhancing soil moisture monitoring via cosmic-ray neutron sensing in farmlands by combining field site tests with an uncertainty analysis

NASA Astrophysics Data System (ADS)

Oswald, S. E.; Scheiffele, L. M.; Baroni, G.; Ingwersen, J.; Schrön, M.

2017-12-01

One application of Cosmic-Ray Neutron Sensing (CRNS) is to investigate soil moisture on agricultural fields during the crop season. This fully employs the non-invasive character of CRNS without interference with agricultural practices of the farmland. The changing influence of vegetation on CRNS has to be dealt with as well as spatio-temporal influences, e.g. by irrigation or harvest. Previous work revealed that the CRNS signal on farmland shows complex and non-unique response because of the hydrogen pools in different depths and distances. This creates a challenge for soil moisture estimation and subsequent use for irrigation management or hydrological modelling. Thus, a special aim of our study was to assess the uncertainty of CRNS in cropped fields and to identify underlying causes of uncertainty. We have applied CRNS at two field sites during the growing season that were accompanied by intensive measurements of soil moisture, vegetation parameters, and irrigation events. Sources of uncertainty were identified from the experimental data. A Monte Carlo approach was used to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis was performed to identify the most important factors explaining this uncertainty. Results showed that CRNS soil moisture compares well to the soil moisture network when the point values were converted to weighted water content with all hydrogen pools included. However, when considered as a stand-alone method to retrieve volumetric soil moisture, the performance decreased. The support volume including its penetration depth showed also a considerable uncertainty, especially in relatively dry soil moisture conditions. Of seven factors analyzed, actual soil moisture profile, bulk density, incoming neutron correction and calibrated parameter N0 were found to play an important role. One possible improvement could be a simple correction factor based on independent data of soil moisture profiles to better account for the sensitivity of the CRNS signal to the upper soil layers. This is an important step to improve the method for validation of remote sensing products or agricultural water management and establish CRNS as an applied monitoring tool on farmland.

Correlation between soil physicochemical properties and vegetation parameters in secondary tropical forest in Sabal, Sarawak, Malaysia

NASA Astrophysics Data System (ADS)

Karyati, K.; Ipor, I. B.; Jusoh, I.; Wasli, M. E.

2018-04-01

The tree growth is influenced by soil morphological and physicochemical properties in the site. The purpose of this study was to describe correlation between soil properties under various stage secondary forests and vegetation parameters, such as floristic structure parameters and floristic diversity indices. The vegetation surveys were conducted in 5, 10, and 20 years old at secondary tropical forests in Sarawak, Malaysia. Nine sub plots sized 20 m × 20 m were established within each study site. The Pearson analysis showed that soil physicochemical properties were significantly correlated to floristic structure parameters and floristic diversity indices. The result of PCA clarified the correlation among most important soil properties, floristic structure parameters, and floristic diversity indices. The PC1 represented cation retention capacity and soil texture which were little affected by the fallow age and its also were correlated by floristic structure and diversity. The PC2 was linked to the levels of soil acidity. This property reflected the remnant effects of ash addition and fallow duration, and the significant correlation were showed among pH (H2O), floristic structure and diversity. The PC3 represented the soil compactness. The soil hardness could be influenced by fallow period and it was also correlated by floristic structure.

Soil Water Retention as Indicator for Soil Physical Quality - Examples from Two SoilTrEC European Critical Zone Observatories

NASA Astrophysics Data System (ADS)

Rousseva, Svetla; Kercheva, Milena; Shishkov, Toma; Dimitrov, Emil; Nenov, Martin; Lair, Georg J.; Moraetis, Daniel

2014-05-01

Soil water retention is of primary importance for majority of soil functions. The characteristics derived from Soil Water Retention Curve (SWRC) are directly related to soil structure and soil water regime and can be used as indicators for soil physical quality. The aim of this study is to present some parameters and relationships based on the SWRC data from the soil profiles characterising the European SoilTrEC Critical Zone Observatories Fuchsenbigl and Koiliaris. The studied soils are representative for highly productive soils managed as arable land in the frame of soil formation chronosequence at "Marchfeld" (Fuchsenbigl CZO), Austria and heavily impacted soils during centuries through intensive grazing and farming, under severe risk of desertification in context of climatic and lithological gradient at Koiliaris, Crete, Greece. Soil water retention at pF ≤ 2.52 was determined using the undisturbed soil cores (100 cm3 and 50 cm3) by a suction plate method. Water retention at pF = 4.2 was determined by a membrane press method and at pF ≥ 5.6 - by adsorption of water vapour at controlled relative humidity, both using ground soil samples. The soil physical quality parameter (S-parameter) was defined as the slope of the water retention curve at its inflection point (Dexter, 2006), determined with the obtained parameters of van Genuhten (1980) water retention equation. The S-parameter values were categorised to assess soil physical quality as follows: S < 0.020 very poor, 0.020 ≤ S < 0.035 poor, 0.035 ≤ S < 0.050 good, S ≥ 0.050 very good (Dexter, 2004). The results showed that most of the studied topsoil horizons have good physical quality according to both the S-parameter and the Plant-Available Water content (PAW), with the exception of the soils from croplands at CZO Fuxenbigl (F4, F5) which are with poor soil structure. The link between the S-parameter and the indicator of soil structure stability (water stable soil aggregates with size 1-3 mm) is not well defined. The scattering is due to high values of S in subsoil, which does not always coincide with favourable physical properties, as it can be seen from the relationship with the PAW content. It was found that values of S ≥ 0.05 correspond to PAW > 20 % vol. in the topsoil horizons. The high values of S in subsoil horizons are due to the low PAW and restrict the application of the S categories in these cases. Well defined links are found between the PAW content and the S-parameter when the data from the topsoil horizons are grouped in 2 groups according to the ratio between air-filled pores (at pF 2.52) and plant available water: <2 and ≥ 2. The authors acknowledge gratefully the European Commission Research Directorate-General for funding the SoilTrEC project (Contract No 244118) under its 7th Framework Programme.

A large scale GIS geodatabase of soil parameters supporting the modeling of conservation practice alternatives in the United States

USDA-ARS?s Scientific Manuscript database

Water quality modeling requires across-scale support of combined digital soil elements and simulation parameters. This paper presents the unprecedented development of a large spatial scale (1:250,000) ArcGIS geodatabase coverage designed as a functional repository of soil-parameters for modeling an...

Combination of geo- pedo- and technogenic magnetic and geochemical signals in soil profiles - Diversification and its interpretation: A new approach.

PubMed

Szuszkiewicz, Marcin; Łukasik, Adam; Magiera, Tadeusz; Mendakiewicz, Maria

2016-07-01

Magnetic and geochemical parameters of soils are determined with respect to geology, pedogenesis and anthropopression. Depending on local conditions these factors affect magnetic and geochemical signals simultaneously or in various configurations. We examined four type of soils (Entic Podzol, Eutric Cambisol, Humic Cambisol and Dystric Cambisol) developed on various bedrock (the Tumlin Sandstone, basaltoid, amphibolite and serpentinite, respectively). Our primary aim was to characterize the origin and diversification of the magnetic and geochemical signal in soils in order to distinguish the most reliable methods for correct interpretation of measured parameters. Presented data include selected parameters, both magnetic (mass magnetic susceptibility - χ, frequency-dependent magnetic susceptibility - χfd and thermomagnetic susceptibility measurement - TSM), and geochemical (selected heavy metal contents: Co, Cr, Cu, Fe, Mn, Ni, Pb, Zn). Additionally, the enrichment factor (EF) and index of geoaccumulation (Igeo) were calculated. Our results suggest the following: (1) the χ/Fe ratio may be a reliable indicator for determining changes of magnetic signal origin in soil profiles; (2) magnetic and geochemical signals are simultaneously higher (the increment of χ and lead and zinc was noted) in topsoil horizons because of the deposition of technogenic magnetic particles (TMPs); (3) EF and Igeo evaluated for lead and zinc unambiguously showed anthropogenic influence in terms of increasing heavy metal contents in topsoil regardless of bedrock or soil type; (4) magnetic susceptibility measurements supported by TSM curves for soil samples of different genetic horizons are a helpful tool for interpreting the origin and nature of the mineral phases responsible for the changes of magnetic susceptibility values. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bioremediation of Petroleum Hydrocarbon Contaminated Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fallgren, Paul

Bioremediation has been widely applied in the restoration of petroleum hydrocarbon-contaminated. Parameters that may affect the rate and efficiency of biodegradation include temperature, moisture, salinity, nutrient availability, microbial species, and type and concentration of contaminants. Other factors can also affect the success of the bioremediation treatment of contaminants, such as climatic conditions, soil type, soil permeability, contaminant distribution and concentration, and drainage. Western Research Institute in conjunction with TechLink Environmental, Inc. and the U.S. Department of Energy conducted laboratory studies to evaluate major parameters that contribute to the bioremediation of petroleum-contaminated drill cuttings using land farming and to develop amore » biotreatment cell to expedite biodegradation of hydrocarbons. Physical characteristics such as soil texture, hydraulic conductivity, and water retention were determined for the petroleum hydrocarbon contaminated soil. Soil texture was determined to be loamy sand to sand, and high hydraulic conductivity and low water retention was observed. Temperature appeared to have the greatest influence on biodegradation rates where high temperatures (>50 C) favored biodegradation. High nitrogen content in the form of ammonium enhanced biodegradation as well did the presence of water near field water holding capacity. Urea was not a good source of nitrogen and has detrimental effects for bioremediation for this site soil. Artificial sea water had little effect on biodegradation rates, but biodegradation rates decreased after increasing the concentrations of salts. Biotreatment cell (biocell) tests demonstrated hydrocarbon biodegradation can be enhanced substantially when utilizing a leachate recirculation design where a 72% reduction of hydrocarbon concentration was observed with a 72-h period at a treatment temperature of 50 C. Overall, this study demonstrates the investigation of the effects of environmental parameters on bioremediation is important in designing a bioremediation system to reduce petroleum hydrocarbon concentrations in impacted soils.« less

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

Transfer of the nationwide Czech soil survey data to a foreign soil classification - generating input parameters for a process-based soil erosion modelling approach

NASA Astrophysics Data System (ADS)

Beitlerová, Hana; Hieke, Falk; Žížala, Daniel; Kapička, Jiří; Keiser, Andreas; Schmidt, Jürgen; Schindewolf, Marcus

2017-04-01

Process-based erosion modelling is a developing and adequate tool to assess, simulate and understand the complex mechanisms of soil loss due to surface runoff. While the current state of available models includes powerful approaches, a major drawback is given by complex parametrization. A major input parameter for the physically based soil loss and deposition model EROSION 3D is represented by soil texture. However, as the model has been developed in Germany it is dependent on the German soil classification. To exploit data generated during a massive nationwide soil survey campaign taking place in the 1960s across the entire Czech Republic, a transfer from the Czech to the German or at least international (e.g. WRB) system is mandatory. During the survey the internal differentiation of grain sizes was realized in a two fractions approach, separating texture into solely above and below 0.01 mm rather than into clayey, silty and sandy textures. Consequently, the Czech system applies a classification of seven different textures based on the respective percentage of large and small particles, while in Germany 31 groups are essential. The followed approach of matching Czech soil survey data to the German system focusses on semi-logarithmic interpolation of the cumulative soil texture curve additionally on a regression equation based on a recent database of 128 soil pits. Furthermore, for each of the seven Czech texture classes a group of typically suitable classes of the German system was derived. A GIS-based spatial analysis to test approaches of interpolation the soil texture was carried out. First results show promising matches and pave the way to a Czech model application of EROSION 3D.

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

Estimating effective soil properties of heterogeneous areas for modeling infiltration and redistribution

USDA-ARS?s Scientific Manuscript database

Field scale water infiltration and soil-water and solute transport models require spatially-averaged “effective” soil hydraulic parameters to represent the average flux and storage. The values of these effective parameters vary for different conditions, processes, and component soils in a field. For...

Global Nitrous Oxide Emissions from Agricultural Soils: Magnitude and Uncertainties Associated with Input Data and Model Parameters

NASA Astrophysics Data System (ADS)

Xu, R.; Tian, H.; Pan, S.; Yang, J.; Lu, C.; Zhang, B.

2016-12-01

Human activities have caused significant perturbations of the nitrogen (N) cycle, resulting in about 21% increase of atmospheric N2O concentration since the pre-industrial era. This large increase is mainly caused by intensive agricultural activities including the application of nitrogen fertilizer and the expansion of leguminous crops. Substantial efforts have been made to quantify the global and regional N2O emission from agricultural soils in the last several decades using a wide variety of approaches, such as ground-based observation, atmospheric inversion, and process-based model. However, large uncertainties exist in those estimates as well as methods themselves. In this study, we used a coupled biogeochemical model (DLEM) to estimate magnitude, spatial, and temporal patterns of N2O emissions from global croplands in the past five decades (1961-2012). To estimate uncertainties associated with input data and model parameters, we have implemented a number of simulation experiments with DLEM, accounting for key parameter values that affect calculation of N2O fluxes (i.e., maximum nitrification and denitrification rates, N fixation rate, and the adsorption coefficient for soil ammonium and nitrate), different sets of input data including climate, land management practices (i.e., nitrogen fertilizer types, application rates and timings, with/without irrigation), N deposition, and land use and land cover change. This work provides a robust estimate of global N2O emissions from agricultural soils as well as identifies key gaps and limitations in the existing model and data that need to be investigated in the future.

Estimating Soil and Root Parameters of Biofuel Crops using a Hydrogeophysical Inversion

NASA Astrophysics Data System (ADS)

Kuhl, A.; Kendall, A. D.; Van Dam, R. L.; Hyndman, D. W.

2017-12-01

Transpiration is the dominant pathway for continental water exchange to the atmosphere, and therefore a crucial aspect of modeling water balances at many scales. The root water uptake dynamics that control transpiration are dependent on soil water availability, as well as the root distribution. However, the root distribution is determined by many factors beyond the plant species alone, including climate conditions and soil texture. Despite the significant contribution of transpiration to global water fluxes, modelling the complex critical zone processes that drive root water uptake remains a challenge. Geophysical tools such as electrical resistivity (ER), have been shown to be highly sensitive to water dynamics in the unsaturated zone. ER data can be temporally and spatially robust, covering large areas or long time periods non-invasively, which is an advantage over in-situ methods. Previous studies have shown the value of using hydrogeophysical inversions to estimate soil properties. Others have used hydrological inversions to estimate both soil properties and root distribution parameters. In this study, we combine these two approaches to create a coupled hydrogeophysical inversion that estimates root and retention curve parameters for a HYDRUS model. To test the feasibility of this new approach, we estimated daily water fluxes and root growth for several biofuel crops at a long-term ecological research site in Southwest Michigan, using monthly ER data from 2009 through 2011. Time domain reflectometry data at seven depths was used to validate modeled soil moisture estimates throughout the model period. This hydrogeophysical inversion method shows promise for improving root distribution and transpiration estimates across a wide variety of settings.

Erosion of soil organic carbon: implications for carbon sequestration

USGS Publications Warehouse

Van Oost, Kristof; Van Hemelryck, Hendrik; Harden, Jennifer W.; McPherson, B.J.; Sundquist, E.T.

2009-01-01

Agricultural activities have substantially increased rates of soil erosion and deposition, and these processes have a significant impact on carbon (C) mineralization and burial. Here, we present a synthesis of erosion effects on carbon dynamics and discuss the implications of soil erosion for carbon sequestration strategies. We demonstrate that for a range of data-based parameters from the literature, soil erosion results in increased C storage onto land, an effect that is heterogeneous on the landscape and is variable on various timescales. We argue that the magnitude of the erosion term and soil carbon residence time, both strongly influenced by soil management, largely control the strength of the erosion-induced sink. In order to evaluate fully the effects of soil management strategies that promote carbon sequestration, a full carbon account must be made that considers the impact of erosion-enhanced disequilibrium between carbon inputs and decomposition, including effects on net primary productivity and decomposition rates.

Model structures amplify uncertainty in predicted soil carbon responses to climate change.

PubMed

Shi, Zheng; Crowell, Sean; Luo, Yiqi; Moore, Berrien

2018-06-04

Large model uncertainty in projected future soil carbon (C) dynamics has been well documented. However, our understanding of the sources of this uncertainty is limited. Here we quantify the uncertainties arising from model parameters, structures and their interactions, and how those uncertainties propagate through different models to projections of future soil carbon stocks. Both the vertically resolved model and the microbial explicit model project much greater uncertainties to climate change than the conventional soil C model, with both positive and negative C-climate feedbacks, whereas the conventional model consistently predicts positive soil C-climate feedback. Our findings suggest that diverse model structures are necessary to increase confidence in soil C projection. However, the larger uncertainty in the complex models also suggests that we need to strike a balance between model complexity and the need to include diverse model structures in order to forecast soil C dynamics with high confidence and low uncertainty.

Granular Mechanics and Surface Systems Lab

NASA Technical Reports Server (NTRS)

Randle, Leah

2007-01-01

The cratering of sand under gas jets is observed to further understanding of soil in hopes to further understand lunar soil. Lunar soil is important to understand because it is causing problems with the materials taken into space including the shuttle. Lunar soil is not rounded like beach sand. Lunar soil is sharp like little particles of glass, and some times when blown they can hook on to one another and become bigger particles. The experiments are designed to help to understand some of the basic physics in how the shuttle jets will interact with lunar soil and how to control the lunar soil. These experiments investigate the diameter of the gas jet and the size of the sand grains to determine how these parameters affect the erosion rate and the cratering processes. Therefore, the experiments preformed will point out what is dependent and what is independent.

Clay mineral type effect on bacterial enteropathogen survival in soil.

PubMed

Brennan, Fiona P; Moynihan, Emma; Griffiths, Bryan S; Hillier, Stephen; Owen, Jason; Pendlowski, Helen; Avery, Lisa M

2014-01-15

Enteropathogens released into the environment can represent a serious risk to public health. Soil clay content has long been known to have an important effect on enteropathogen survival in soil, generally enhancing survival. However, clay mineral composition in soils varies, and different clay minerals have specific physiochemical properties that would be expected to impact differentially on survival. This work investigated the effect of clay materials, with a predominance of a particular mineral type (montmorillonite, kaolinite, or illite), on the survival in soil microcosms over 96 days of Listeria monocytogenes, Salmonella Dublin, and Escherichia coli O157. Clay mineral addition was found to alter a number of physicochemical parameters in soil, including cation exchange capacity and surface area, and this was specific to the mineral type. Clay mineral addition enhanced enteropathogen survival in soil. The type of clay mineral was found to differentially affect enteropathogen survival and the effect was enteropathogen-specific. © 2013.

Modeling coupled sorption and transformation of 17β-estradiol-17-sulfate in soil-water systems

NASA Astrophysics Data System (ADS)

Bai, Xuelian; Shrestha, Suman L.; Casey, Francis X. M.; Hakk, Heldur; Fan, Zhaosheng

2014-11-01

Animal manure is the primary source of exogenous free estrogens in the environment, which are known endocrine-disrupting chemicals to disorder the reproduction system of organisms. Conjugated estrogens can act as precursors to free estrogens, which may increase the total estrogenicity in the environment. In this study, a comprehensive model was used to simultaneously simulate the coupled sorption and transformation of a sulfate estrogen conjugate, 17β-estradiol-17-sulfate (E2-17S), in various soil-water systems (non-sterile/sterile; topsoil/subsoil). The simulated processes included multiple transformation pathways (i.e. hydroxylation, hydrolysis, and oxidation) and mass transfer between the aqueous, reversibly sorbed, and irreversibly sorbed phases of all soils for E2-17S and its metabolites. The conceptual model was conceived based on a series of linear sorption and first-order transformation expressions. The model was inversely solved using finite difference to estimate process parameters. A global optimization method was applied for the inverse analysis along with variable model restrictions to estimate 36 parameters. The model provided a satisfactory simultaneous fit (R2adj = 0.93 and d = 0.87) of all the experimental data and reliable parameter estimates. This modeling study improved the understanding on fate and transport of estrogen conjugates under various soil-water conditions.

Slope Stability Estimation of the Kościuszko Mound in Cracow

NASA Astrophysics Data System (ADS)

Wrana, Bogumił; Pietrzak, Natalia

2015-06-01

In the paper, the slope stability problem of the Kościuszko Mound in Cracow, Poland is considered. The slope stability analysis was performed using Plaxis FEM program. The outer surface of the mound has complex geometry. The slope of the cone is not uniform in all directions, on the surface of the cone are pedestrian paths. Due to its complicated geometry it was impossible to do computing by Plaxis input pre-procesor. The initial element mesh was generated using Autodesk Autocad 3D and next it was updated by Plaxis program. The soil parameters were adopted in accordance with the detailed geological soil testing performed in 2012. Calculating model includes geogrids. The upper part was covered by MacMat geogrid, while the lower part of the Mound was reinforced using Terramesh Matt geogrid. The slope analysis was performed by successives reduction of φ /c parameters. The total multiplayer ΣMsf is used to define the value of the soil strength parameters. The article presents the results of slope stability before and after the rainfall during 33 days of precipitation in flood of 2010.

Soil transport parameters of potassium under a tropical saline soil condition using STANMOD

NASA Astrophysics Data System (ADS)

Suzanye da Silva Santos, Rafaelly; Honorio de Miranda, Jarbas; Previatello da Silva, Livia

2015-04-01

Environmental responsibility and concerning about the final destination of solutes in soil, so more studies allow a better understanding about the solutes behaviour in soil. Potassium is a macronutrient that is required in high concentrations, been an extremely important nutrient for all agricultural crops. It plays essential roles in physiological processes vital for plant growth, from protein synthesis to maintenance of plant water balance, and is available to plants dissolved in soil water while exchangeable K is loosely held on the exchange sites on the surface of clay particles. K will tend to be adsorbed onto the surface of negatively charged soil particles. Potassium uptake is vital for plant growth but in saline soils sodium competes with potassium for uptake across the plasma membrane of plant cells. This can result in high Na+:K+ ratios that reduce plant growth and eventually become toxic. This study aimed to obtain soil transport parameters of potassium in saline soil, such as: pore water velocity in soil (v), retardation factor (R), dispersivity (λ) and dispersion coefficient (D), in a disturbed sandy soil with different concentrations of potassium chlorate solution (KCl), which is one of the most common form of potassium fertilizer. The experiment was carried out using soil samples collected in a depth of 0 to 20 cm, applying potassium chlorate solution containing 28.6, 100, 200 and 500 mg L-1 of K. To obtain transport parameters, the data were adjusted with the software STANMOD. At low concentrations, interaction between potassium and soil occur more efficiently. It was observed that only the breakthrough curve prepared with solution of 500 mg L-1 reached the applied concentration, and the solution of 28.6 mg L-1 overestimated the parameters values. The STANMOD proved to be efficient in obtaining potassium transport parameters; KCl solution to be applied should be greater than 500 mg L-1; solutions with low concentrations tend to overestimate parameters values.

Key parameters and practices controlling pesticide degradation efficiency of biobed substrates.

PubMed

Karanasios, Evangelos; Karpouzas, Dimitrios G; Tsiropoulos, Nikolaos G

2012-01-01

We studied the contribution of each of the components of a compost-based biomixture (BX), commonly used in Europe, on pesticide degradation. The impact of other key parameters including pesticide dose, temperature and repeated applications on the degradation of eight pesticides, applied as a mixture, in a BX and a peat-based biomixture (OBX) was compared and contrasted to their degradation in soil. Incubation studies showed that straw was essential in maintaining a high pesticide degradation capacity of the biomixture, whereas compost, when mixed with soil, retarded pesticide degradation. The highest rates of degradation were shown in the biomixture composed of soil/compost/straw suggesting that all three components are essential for maximum biobed performance. Increasing doses prolonged the persistence of most pesticides with biomixtures showing a higher tolerance to high pesticide dose levels compared to soil. Increasing the incubation temperature from 15 °C to 25 °C resulted in lower t(1/2) values, with biomixtures performing better than soil at the lower temperature. Repeated applications led to a decrease in the degradation rates of most pesticides in all the substrates, with the exception of iprodione and metalaxyl. Overall, our results stress the ability of biomixtures to perform better than soil under unfavorable conditions and extreme pesticide dose levels. Copyright © Taylor & Francis Group, LLC

Retention and Migration of Chlorpyrifos in Aquatic Sediments and Soils

NASA Astrophysics Data System (ADS)

Gebremariam, S. Y.; Beutel, M.; Yonge, D.; Flury, M.; Harsh, J. B.

2010-12-01

The accurate description of the fate and transport of potentially toxic agricultural pesticides in sediments and soils is of great interest to environmental scientists and regulators. Of particular concern is the widely documented detection of agricultural pesticides and their byproducts in drinking water wells. This presentation discusses results of a study of the fate and transport of chlorpyrifos, a strongly hydrophobic organophosphate-pesticide, in sediments and soils collected from a range of aquatic environments. Using radio-labeled chlorpyrifos, this study is unique in its comprehensive nature and focus on aquatic sediments, for which studies involving pesticide fate and transport are limited. Study components include: (1) batch equilibrium experiments to evaluate sorption/desorption parameters; (2) kinetic and non-equilibrium sorption experiments using miniaturized flow-cells; (3) column experiments to understand patterns of pesticide break through; and (4) numerical modeling of chlorpyrifos transport through aquatic sediments and soils. Initial results show that chlorpyrifos sorption, when corrected for reversible sorption to container walls, exhibited two component sorption, a large irreversible fraction and a smaller reversible fraction that can act as a secondary source. In addition, of a wide range of soil parameters measured, organic carbon content exhibited the highest correlation with chlorpyrifos retention in cranberry field soils. Simulation models developed in this study, which account for hysteretic and nonlinear sorption, will help to better predict the fate of chlorpyrifos and other hydrophobic chemicals in sediments and soils.

Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

NASA Technical Reports Server (NTRS)

Brunet, Y.; Vauclin, M.

1985-01-01

The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

NASA Astrophysics Data System (ADS)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

The taste of soil: chemical investigation of soil, grape and wine in the Sopron wine region (Hungary)

NASA Astrophysics Data System (ADS)

Hofmann, Tomás; Horvàth, Imre; Bidló, András; Hofmann, Eszther

2015-04-01

The taste of soil: chemical investigation of soil, grape and wine in the Sopron wine region (Hungary) The Sopron wine region is one of the most significant and historical wine-producing regions of Hungary. 1800 hectares out of the total area of 4300 hectares of the wine region are used for grape cultivation. Kékfrankos (Blue Frankish) is the most frequent grape variety (60%) nevertheless other varieties are also grown here (including Zweigelt, Merlot, Cabernet Franc, Portugieser and Sauvignon Blanc). In this study preliminary results of the chemical analyses involving soil, grape and wine are presented, which could provide a future basis for a comprehensive terroir research in the wine region. As soil is the premanent home of grapevine, its quality is highly influencing for the growth of the plants and grape berries, and also determines future organoleptic characteristics of the wines. The investigated basic soil parameters included humus content, transition, soil structure, compactness, roots, skeletal percent, color, physical assortment, concretion, soil defects. Laboratory measurements involved the determination of pH, carbonated lime content, humus content, ammonium lactate-acetic acid soluble P and K content, KCl soluble Ca and Mg content, EDTA and DTPA soluble Cu, Fe, Mn and Zn content. Soil samples were also investigated for heavy metal contents using ICP-OES method (Thermo Scientific iCAP 7000 Series). By the use of thermoanalytical measurements (Mettler Toledo TGA/DSC 1 type thermogravimeter, 5°C/min, air atmosphere, 25-1000°C) the mineral composition of the soils was evaluated. Regarding major aroma compounds in grape berries and wine, the concentrations of organic acids (tartaric-, acetic-, succinic-, malic-, lactic acid), methanol, ethanol, glycerine, glucose and fructose were determined by high performance liquid chromatography (Shimadzu LC-20 HPLC equipment with DAD and RID detection). The density, titratable acidity, pH and total extractive content of the wine samples was also determined. With the presentation of the results the possible relationships between individual parameters will be demonstrated. The research is supported by the "Agroclimate-2" (VKSZ_12-1-2013-0034) joint EU-national research project.

Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States

NASA Astrophysics Data System (ADS)

Baldwin, D.; Manfreda, S.; Keller, K.; Smithwick, E. A. H.

2017-03-01

Satellite-based near-surface (0-2 cm) soil moisture estimates have global coverage, but do not capture variations of soil moisture in the root zone (up to 100 cm depth) and may be biased with respect to ground-based soil moisture measurements. Here, we present an ensemble Kalman filter (EnKF) hydrologic data assimilation system that predicts bias in satellite soil moisture data to support the physically based Soil Moisture Analytical Relationship (SMAR) infiltration model, which estimates root zone soil moisture with satellite soil moisture data. The SMAR-EnKF model estimates a regional-scale bias parameter using available in situ data. The regional bias parameter is added to satellite soil moisture retrievals before their use in the SMAR model, and the bias parameter is updated continuously over time with the EnKF algorithm. In this study, the SMAR-EnKF assimilates in situ soil moisture at 43 Soil Climate Analysis Network (SCAN) monitoring locations across the conterminous U.S. Multivariate regression models are developed to estimate SMAR parameters using soil physical properties and the moderate resolution imaging spectroradiometer (MODIS) evapotranspiration data product as covariates. SMAR-EnKF root zone soil moisture predictions are in relatively close agreement with in situ observations when using optimal model parameters, with root mean square errors averaging 0.051 [cm3 cm-3] (standard error, s.e. = 0.005). The average root mean square error associated with a 20-fold cross-validation analysis with permuted SMAR parameter regression models increases moderately (0.082 [cm3 cm-3], s.e. = 0.004). The expected regional-scale satellite correction bias is negative in four out of six ecoregions studied (mean = -0.12 [-], s.e. = 0.002), excluding the Great Plains and Eastern Temperate Forests (0.053 [-], s.e. = 0.001). With its capability of estimating regional-scale satellite bias, the SMAR-EnKF system can predict root zone soil moisture over broad extents and has applications in drought predictions and other operational hydrologic modeling purposes.

A review of model applications for structured soils: b) Pesticide transport.

PubMed

Köhne, John Maximilian; Köhne, Sigrid; Simůnek, Jirka

2009-02-16

The past decade has seen considerable progress in the development of models simulating pesticide transport in structured soils subject to preferential flow (PF). Most PF pesticide transport models are based on the two-region concept and usually assume one (vertical) dimensional flow and transport. Stochastic parameter sets are sometimes used to account for the effects of spatial variability at the field scale. In the past decade, PF pesticide models were also coupled with Geographical Information Systems (GIS) and groundwater flow models for application at the catchment and larger regional scales. A review of PF pesticide model applications reveals that the principal difficulty of their application is still the appropriate parameterization of PF and pesticide processes. Experimental solution strategies involve improving measurement techniques and experimental designs. Model strategies aim at enhancing process descriptions, studying parameter sensitivity, uncertainty, inverse parameter identification, model calibration, and effects of spatial variability, as well as generating model emulators and databases. Model comparison studies demonstrated that, after calibration, PF pesticide models clearly outperform chromatographic models for structured soils. Considering nonlinear and kinetic sorption reactions further enhanced the pesticide transport description. However, inverse techniques combined with typically available experimental data are often limited in their ability to simultaneously identify parameters for describing PF, sorption, degradation and other processes. On the other hand, the predictive capacity of uncalibrated PF pesticide models currently allows at best an approximate (order-of-magnitude) estimation of concentrations. Moreover, models should target the entire soil-plant-atmosphere system, including often neglected above-ground processes such as pesticide volatilization, interception, sorption to plant residues, root uptake, and losses by runoff. The conclusions compile progress, problems, and future research choices for modelling pesticide displacement in structured soils.

Acoustic waves in unsaturated soils

NASA Astrophysics Data System (ADS)

Lo, Wei-Cheng; Sposito, Garrison

2013-09-01

Seminal papers by Brutsaert (1964) and Brutsaert and Luthin (1964) provided the first rigorous theoretical framework for examining the poroelastic behavior of unsaturated soils, including an important application linking acoustic wave propagation to soil hydraulic properties. Theoretical developments during the 50 years that followed have led Lo et al., (2005) to a comprehensive model of these phenomena, but the relationship of its elasticity parameters to standard poroelasticity parameters measured in hydrogeology has not been established. In the present study, we develop this relationship for three key parameters, the Gassman modulus, Skempton coefficient, and Biot-Willis coefficient by generalizing them to an unsaturated porous medium. We demonstrate the remarkable result that well-known and widely applied relationships among these parameters for a porous medium saturated by a single fluid are also valid under very general conditions for unsaturated soils. We show further that measurement of the Biot-Willis coefficient along with three of the six elasticity coefficients in the model of Lo et al. (2005) is sufficient to characterize poroelastic behavior. The elasticity coefficients in the model of Lo et al. (2005) are sensitive to the dependence of capillary pressure on water saturation and its viscous-drag coefficients are functions of relative permeability, implying that hysteresis in the water retention curve and hydraulic conductivity function should affect acoustic wave behavior in unsaturated soils. To quantify these as-yet unknown effects, we performed numerical simulations for Dune sand at two representative wave excitation frequencies. Our results show that the acoustic wave investigated by Brutsaert and Luthin (1964) propagates at essentially the same speed during imbibition and drainage, but is attenuated more during drainage than imbibition. Overall, effects on acoustic wave behavior caused by hysteresis become more significant as the excitation frequency increases.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

A multi-scale ''soil water structure'' model based on the pedostructure concept

NASA Astrophysics Data System (ADS)

Braudeau, E.; Mohtar, R. H.; El Ghezal, N.; Crayol, M.; Salahat, M.; Martin, P.

2009-02-01

Current soil water models do not take into account the internal organization of the soil medium and, a fortiori, the physical interaction between the water film surrounding the solid particles of the soil structure, and the surface charges of this structure. In that sense they empirically deal with the physical soil properties that are all generated from this soil water-structure interaction. As a result, the thermodynamic state of the soil water medium, which constitutes the local physical conditions, namely the pedo-climate, for biological and geo-chemical processes in soil, is not defined in these models. The omission of soil structure from soil characterization and modeling does not allow for coupling disciplinary models for these processes with soil water models. This article presents a soil water structure model, Kamel®, which was developed based on a new paradigm in soil physics where the hierarchical soil structure is taken into account allowing for defining its thermodynamic properties. After a review of soil physics principles which forms the basis of the paradigm, we describe the basic relationships and functionality of the model. Kamel® runs with a set of 15 soil input parameters, the pedohydral parameters, which are parameters of the physically-based equations of four soil characteristic curves that can be measured in the laboratory. For cases where some of these parameters are not available, we show how to estimate these parameters from commonly available soil information using published pedotransfer functions. A published field experimental study on the dynamics of the soil moisture profile following a pounded infiltration rainfall event was used as an example to demonstrate soil characterization and Kamel® simulations. The simulated soil moisture profile for a period of 60 days showed very good agreement with experimental field data. Simulations using input data calculated from soil texture and pedotransfer functions were also generated and compared to simulations of the more ideal characterization. The later comparison illustrates how Kamel® can be used and adapt to any case of soil data availability. As physically based model on soil structure, it may be used as a standard reference to evaluate other soil-water models and also pedotransfer functions at a given location or agronomical situation.

Real-time soil sensing based on fiber optics and spectroscopy

NASA Astrophysics Data System (ADS)

Li, Minzan

2005-08-01

Using NIR spectroscopic techniques, correlation analysis and regression analysis for soil parameter estimation was conducted with raw soil samples collected in a cornfield and a forage field. Soil parameters analyzed were soil moisture, soil organic matter, nitrate nitrogen, soil electrical conductivity and pH. Results showed that all soil parameters could be evaluated by NIR spectral reflectance. For soil moisture, a linear regression model was available at low moisture contents below 30 % db, while an exponential model can be used in a wide range of moisture content up to 100 % db. Nitrate nitrogen estimation required a multi-spectral exponential model and electrical conductivity could be evaluated by a single spectral regression. According to the result above mentioned, a real time soil sensor system based on fiber optics and spectroscopy was developed. The sensor system was composed of a soil subsoiler with four optical fiber probes, a spectrometer, and a control unit. Two optical fiber probes were used for illumination and the other two optical fiber probes for collecting soil reflectance from visible to NIR wavebands at depths around 30 cm. The spectrometer was used to obtain the spectra of reflected lights. The control unit consisted of a data logging device, a personal computer, and a pulse generator. The experiment showed that clear photo-spectral reflectance was obtained from the underground soil. The soil reflectance was equal to that obtained by the desktop spectrophotometer in laboratory tests. Using the spectral reflectance, the soil parameters, such as soil moisture, pH, EC and SOM, were evaluated.

Use of gas push-pull tests for the measurement of methane oxidation in different landfill cover soils.

PubMed

Streese-Kleeberg, Jan; Rachor, Ingke; Gebert, Julia; Stegmann, Rainer

2011-05-01

In order to optimise methane oxidation in landfill cover soils, it is important to be able to accurately quantify the amount of methane oxidised. This research considers the gas push-pull test (GPPT) as a possible method to quantify oxidation rates in situ. During a GPPT, a gas mixture consisting of one or more reactive gases (e.g., CH(4), O(2)) and one or more conservative tracers (e.g., argon), is injected into the soil. Following this, the mixture of injected gas and soil air is extracted from the same location and periodically sampled. The kinetic parameters for the biological oxidation taking place in the soil can be derived from the differences in the breakthrough curves. The original method of Urmann et al. (2005) was optimised for application in landfill cover soils and modified to reduce the analytical effort required. Optimised parameters included the flow rate during the injection phase and the duration of the experiment. 50 GPPTs have been conducted at different landfills in Germany during different seasons. Generally, methane oxidation rates ranged between 0 and 150 g m(soil air)(-3)h(-1). At one location, rates up to 440 g m(soil air)(-3)h(-1) were measured under particularly favourable conditions. The method is simple in operation and does not require expensive equipment besides standard laboratory gas chromatographs. Copyright © 2010 Elsevier Ltd. All rights reserved.

High resolution digital soil mapping as a future instrument for developing sustainable landuse strategies

NASA Astrophysics Data System (ADS)

Gries, Philipp; Funke, Lisa-Marie; Baumann, Frank; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2016-04-01

Climate change, increase in population and intensification of land use pose a great challenge for sustainable handling of soils. Intelligent landuse systems are able to minimize and/or avoid soil erosion and loss of soil fertility. A successful application of such systems requires area-wide soil information with high resolution. Containing three consecutive steps, the project INE-2-H („innovative sustainable landuse") at the University of Tuebingen is about creating high-resolution soil information using Digital Soil Mapping (DSM) techniques to develop sustainable landuse strategies. Input data includes soil data from fieldwork (texture and carbon content), the official digital soil and geological map (1:50.000) as well as a wide selection of local, complex and combined terrain parameters. First, soil maps have been created using the DSM approach and Random Forest (RF). Due to high resolution (10x10 m pixels), those maps show a more detailed spatial variability of soil information compared to the official maps used. Root mean square errors (RMSE) of the modelled maps vary from 2.11 % to 6.87 % and the coefficients of determination (R²) go from 0.42 to 0.68. Second, soil erosion potentials have been estimated according to the Universal Soil Loss Equation (USLE). Long-term average annual soil loss ranges from 0.56 to 24.23 [t/ha/a]. Third, combining high-resolution erosion potentials with expert-knowledge of local farmers will result in a landuse system adapted to local conditions. This system will include sustainable strategies reducing soil erosion and conserving soil fertility.

Simulation of future groundwater recharge using a climate model ensemble and SAR-image based soil parameter distributions - A case study in an intensively-used Mediterranean catchment.

PubMed

Herrmann, Frank; Baghdadi, Nicolas; Blaschek, Michael; Deidda, Roberto; Duttmann, Rainer; La Jeunesse, Isabelle; Sellami, Haykel; Vereecken, Harry; Wendland, Frank

2016-02-01

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. Copyright © 2015 Elsevier B.V. All rights reserved.

Investigating the initial stages of soil formation in glacier forefields using the new biogeochemical model: SHIMMER

NASA Astrophysics Data System (ADS)

Bradley, James; Anesio, Alexandre; Arndt, Sandra; Sabacka, Marie; Barker, Gary; Benning, Liane; Blacker, Joshua; Singarayer, Joy; Tranter, Martyn; Yallop, Marian

2016-04-01

Glaciers and ice sheets in Polar and alpine regions are retreating in response to recent climate warming, exposing terrestrial ecosystems that have been locked under the ice for thousands of years. Exposed soils exhibit successional characteristics that can be characterised using a chronosequence approach. Decades of empirical research in glacier forefields has shown that soils are quickly colonised by microbes which drive biogeochemical cycling of elements and affect soil properties including nutrient concentrations, carbon fluxes and soil stability (Bradley et al, 2014). The characterisation of these soils is important for our understanding of the cycling of organic matter under extreme environmental and nutrient limiting conditions, and their potential contribution to global biogeochemical cycles. This is particularly important as these new areas will become more geographically expansive with continued ice retreat. SHIMMER (Soil biogeocHemIcal Model of Microbial Ecosystem Response) (Bradley et al, 2015) is a new mathematical model that simulates biogeochemical and microbial dynamics in glacier forefields. The model captures, explores and predicts the growth of different microbial groups (classified by function), and the associated cycling of carbon, nitrogen and phosphorus along a chronosequence. SHIMMER improves typical soil model formulations by including explicit representation of microbial dynamics, and those processes which are shown to be important for glacier forefields. For example, we categorise microbial groups by function to represent the diversity of soil microbial communities, and include the different metabolic needs and physiological pathways of microbial organisms commonly found in glacier forefields (e.g. microbes derived from underneath the glacier, typical soil bacteria, and microbes that can fix atmospheric nitrogen and assimilate soil nitrogen). Here, we present data from a study where we integrated modelling using SHIMMER with empirical observations from chronosequences from the forefield of Midtre Lovénbreen, Svalbard (78°N), to investigate the first 120 years of soil development. We carried out an in depth analysis of the model dynamics and determined the most sensitive parameters. We then used laboratory measurements to derive values for those parameters: bacterial growth rate, growth efficiency and temperature dependency. By applying the model to the High-Arctic forefield and integrating the measured parameter values, we could refine the model and easily predict the rapid accumulation of microbial biomass that was observed in our field data. Furthermore, we show that the bacterial production is dominated by autotrophy (rather than heterotrophy). Heterotrophic production in young soils (0-20 years) is supported by labile substrate, whereas carbon stocks in older soils (60-120 years) are more refractory. Nitrogen fixing organisms are responsible for the initial accumulation of available nitrates in the soil. However, microbial processes alone do not explain the build-up of organic matter observed in the field data record. Consequently, the model infers that allochthonous deposition of organic material may play a significant contributory role that could accelerate or facilitate further microbial growth. SHIMMER provides a quantitative evaluation on the dynamics of glacier forefield systems that have previously largely been explored through qualitative interpretation of datasets. References Bradley J.A., Singarayer J.S., Anesio A.M. (2014) Microbial community dynamics in the forefield of glaciers. Proceedings Biological sciences / The Royal Society 281(1795), 2793-2802. (doi:10.1098/rspb.2014.0882). Bradley J.A., Anesio A.M., Singarayer J.S., Heath M.R., Arndt S. (2015) SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems. Geosci Model Dev 8(10), 3441-3470. (doi:10.5194/gmd-8-3441-2015).

Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model

NASA Astrophysics Data System (ADS)

Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.

2014-04-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need for including agricultural management options in the coupled model.

Retention of silver nano-particles and silver ions in calcareous soils: Influence of soil properties.

PubMed

Rahmatpour, Samaneh; Shirvani, Mehran; Mosaddeghi, Mohammad R; Bazarganipour, Mehdi

2017-05-15

The rapid production and application of silver nanoparticles (AgNPs) have led to significant release of AgNPs into the terrestrial environments. Once released into the soil, AgNPs could enter into different interactions with soil particles which play key roles in controlling the fate and transport of these nanoparticles. In spite of that, experimental studies on the retention of AgNPs in soils are very scarce. Hence, the key objective of this research was to find out the retention behavior of AgNPs and Ag(I) ions in a range of calcareous soils. A second objective was to determine the extent to which the physico-chemical properties of the soils influence the Ag retention parameters. To this end, isothermal batch experiments were used to determine the retention of Poly(vinylpyrrolidinone)-capped AgNPs (PVP-AgNPs) and Ag(I) ions by nine calcareous soils with a diversity of physico-chemical properties. The results revealed that the retention data for both PVP-AgNPs and Ag(I) ions were well described by the classical Freundlich and Langmuir isothermal equations. The retention of PVP-AgNPs and Ag(I) ions was positively correlated to clay and organic carbon (OC) contents as well as electrical conductivity (EC), pH, and cation exchange capacity (CEC) of the soils. Due to multicolinearity among the soil properties, principal component analysis (PCA) was used to group the soil properties which affect the retention of PVP-AgNPs and Ag(I) ions. Accordingly, we identified two groups of soil properties controlling retention of PVP-AgNPs and Ag(I) ions in the calcareous soils. The first group comprised soil solid phase parameters like clay, OC, and CEC, which generally control hetero-aggregation and adsorption reactions and the second group included soil solution variables such as EC and pH as well as Cl - and Ca 2+ concentrations, which are supposed to mainly affect homo-aggregation and precipitation reactions. Copyright © 2017. Published by Elsevier Ltd.

Determination of Matric Suction and Saturation Degree for Unsaturated Soils, Comparative Study - Numerical Method versus Analytical Method

NASA Astrophysics Data System (ADS)

Chiorean, Vasile-Florin

2017-10-01

Matric suction is a soil parameter which influences the behaviour of unsaturated soils in both terms of shear strength and permeability. It is a necessary aspect to know the variation of matric suction in unsaturated soil zone for solving geotechnical issues like unsaturated soil slopes stability or bearing capacity for unsaturated foundation ground. Mathematical expression of the dependency between soil moisture content and it’s matric suction (soil water characteristic curve) has a powerful character of nonlinearity. This paper presents two methods to determine the variation of matric suction along the depth included between groundwater level and soil level. First method is an analytical approach to emphasize one direction steady state unsaturated infiltration phenomenon that occurs between the groundwater level and the soil level. There were simulated three different situations in terms of border conditions: precipitations (inflow conditions on ground surface), evaporation (outflow conditions on ground surface), and perfect equilibrium (no flow on ground surface). Numerical method is finite element method used for steady state, two-dimensional, unsaturated infiltration calculus. Regarding boundary conditions there were simulated identical situations as in analytical approach. For both methods, was adopted the equation proposed by van Genuchten-Mualen (1980) for mathematical expression of soil water characteristic curve. Also for the unsaturated soil permeability prediction model was adopted the equation proposed by van Genuchten-Mualen. The fitting parameters of these models were adopted according to RETC 6.02 software in function of soil type. The analyses were performed in both methods for three major soil types: clay, silt and sand. For each soil type were concluded analyses for three situations in terms of border conditions applied on soil surface: inflow, outflow, and no flow. The obtained results are presented in order to highlight the differences/similarities between the methods and the advantages / disadvantages of each one.

Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands

NASA Astrophysics Data System (ADS)

Anne, Naveen J. P.; Abd-Elrahman, Amr H.; Lewis, David B.; Hewitt, Nicole A.

2014-12-01

Developing spectral models of soil properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the partitioning of mineral and organic soil between particulate (>53 μm) and fine size classes, and the partitioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD > 1.4) predicted particulate organic matter (POM), silt + clay, labile carbon (C), and labile nitrogen (N) (where RPD = ratio of standard deviation to root mean square error of cross-validation [RMSECV]). The SR (0.53 μm, 2.11 μm) model of labile N with R2 = 0.81, RMSECV= 0.28, and RPD = 1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense canopy cover.

Suitable Site Selection of Small Dams Using Geo-Spatial Technique: a Case Study of Dadu Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Decision making about identifying suitable sites for any project by considering different parameters, is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30 meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pair wise comparison method, also known as Analytical Hierarchy Process (AHP) is took into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision making about suitable sites analysis for small dams using geo-spatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

[Effects of soil properties on the stabilization process of cadmium in Cd alone and Cd-Pb contaminated soils].

PubMed

Wu, Man; Xu, Ming-Gang; Zhang, Wen-Ju; Wu, Hai-Wen

2012-07-01

In order to clarify the effects of soil properties on the stabilization process of the cadmium (Cd) added, 11 different soils were collected and incubated under a moisture content of 65%-70% at 25 degrees C. The changes of available Cd contents with incubation time (in 360 days) in Cd and Cd-Pb contaminated treatments were determined. The stabilization process was simulated using dynamic equations. The results showed that after 1.0 mg x kg(-1) Cd or 500 mg x kg(-1) Pb + 1.0 mg x kg(-1) Cd were added into the soil, the available Cd content decreased rapidly during the first 15 days, and then the decreasing rate slowed down, with an equilibrium content reached after 60 days' incubation. In Cd-Pb contaminated soils, the presence of Pb increased the content of available Cd. The stabilization process of Cd could be well described by the second-order equation and the first order exponential decay; meanwhile, dynamic parameters including equilibrium content and stabilization velocity were used to characterize the stabilization process of Cd. These two key dynamic parameters were significantly affected by soil properties. Correlation analysis and stepwise regression suggested that high pH and high cation exchange capacity (CEC) significantly retarded the availability of Cd. High pH had the paramount effect on the equilibrium content. The stabilization velocity of Cd was influenced by the soil texture. It took shorter time for Cd to get stabilized in sandy soil than in the clay.

Few effects of invasive plants Reynoutria japonica, Rudbeckia laciniata and Solidago gigantea on soil physical and chemical properties.

PubMed

Stefanowicz, Anna M; Stanek, Małgorzata; Nobis, Marcin; Zubek, Szymon

2017-01-01

Biological invasions are an important problem of human-induced changes at a global scale. Invasive plants can modify soil nutrient pools and element cycling, creating feedbacks that potentially stabilize current or accelerate further invasion, and prevent re-establishment of native species. The aim of this study was to compare the effects of Reynoutria japonica, Rudbeckia laciniata and Solidago gigantea, invading non-forest areas located within or outside river valleys, on soil physical and chemical parameters, including soil moisture, element concentrations, organic matter content and pH. Additionally, invasion effects on plant species number and total plant cover were assessed. The concentrations of elements in shoots and roots of invasive and native plants were also measured. Split-plot ANOVA revealed that the invasions significantly reduced plant species number, but did not affect most soil physical and chemical properties. The invasions decreased total P concentration and increased N-NO 3 concentration in soil in comparison to native vegetation, though the latter only in the case of R. japonica. The influence of invasion on soil properties did not depend on location (within- or outside valleys). The lack of invasion effects on most soil properties does not necessarily imply the lack of influence of invasive plants, but may suggest that the direction of the changes varies among replicate sites and there are no general patterns of invasion-induced alterations for these parameters. Tissue element concentrations, with the exception of Mg, did not differ between invasive and native plants, and were not related to soil element concentrations. Copyright © 2016 Elsevier B.V. All rights reserved.

Beyond clay - using selective extractions to improve predictions of soil carbon content

NASA Astrophysics Data System (ADS)

Rasmussen, C.; Berhe, A. A.; Blankinship, J. C.; Crow, S. E.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Plante, A. F.; Schaedel, C.; Schimel, J.; Sierra, C. A.; Thompson, A.; Wagai, R.; Wieder, W. R.

2016-12-01

A central component of modern soil carbon (C) models is the use of clay content to scale the relative partitioning of decomposing plant material to respiration and mineral stabilized soil C. However, numerous pedon to plot scale studies indicate that other soil mineral parameters, such as Fe- or Al-oxyhydroxide content and specific surface area, may be more effective than clay alone for predicting soil C content and stabilization. Here we directly address the following question: Are there soil physicochemical parameters that represent mineral C association and soil C content that can replace or be used in conjunction with clay content as scalars in soil C models. We explored the relationship of soil C content to a number of soil physicochemical and physiographic parameters using the National Cooperative Soil Survey database that contains horizon level data for > 62,000 pedons spanning global ecoregions and geographic areas. The data indicated significant variation in the degree of correlation among soil C, clay and Fe-/Al-oxyhydroxides with increasing moisture variability. Specifically, dry, water-limited systems (PET/MAP > 1) presented strong positive correlations between clay and soil C, that decreased significantly to little or no correlation in wet, energy-limited systems (PET/MAP < 1). In contrast, the correlation of soil C to oxalate extractable Al+Fe increased significantly with increasing moisture availability. This pattern was particularly well expressed for subsurface B horizons. Multivariate analyses indicated similar patterns, with clear climate and ecosystem level variation in the degree of correlation among soil C and soil physicochemical properties. The results indicate a need to modify current soil C models to incorporate additional C partitioning parameters that better account for climate and ecoregion variability in C stabilization mechanisms.

Global Soil Moisture Estimation through a Coupled CLM4-RTM-DART Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Zhao, L.; Yang, Z. L.; Hoar, T. J.

2016-12-01

Very few frameworks exist that estimate global-scale soil moisture through microwave land data assimilation (DA). Toward this goal, we have developed such a framework by linking the Community Land Model version 4 (CLM4) and a microwave radiative transfer model (RTM) with the Data Assimilation Research Testbed (DART). The deterministic Ensemble Adjustment Kalman Filter (EAKF) within the DART is utilized to estimate global multi-layer soil moisture by assimilating brightness temperature observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). A 40-member of Community Atmosphere Model version 4 (CAM4) reanalysis is adopted to drive CLM4 simulations. Spatial-specific time-invariant microwave parameters are pre-calibrated to minimize uncertainties in RTM. Besides, various methods are designed in consideration of computational efficiency. A series of experiments are conducted to quantify the DA sensitivity to microwave parameters, choice of assimilated observations, and different CLM4 updating schemes. Evaluation results indicate that the newly established CLM4-RTM-DART framework improves the open-loop CLM4 simulated soil moisture. Pre-calibrated microwave parameters, rather than their default values, can ensure a more robust global-scale performance. In addition, updating near-surface soil moisture is capable of improving soil moisture in deeper layers, while simultaneously updating multi-layer soil moisture fails to obtain intended improvements. We will show in this presentation the architecture of the CLM4-RTM-DART system and the evaluations on AMSR-E DA. Preliminary results on multi-sensor DA that integrates various satellite observations including GRACE, MODIS, and AMSR-E will also be presented. ReferenceZhao, L., Z.-L. Yang, and T. J. Hoar, 2016. Global Soil Moisture Estimation by Assimilating AMSR-E Brightness Temperatures in a Coupled CLM4-RTM-DART System. Journal of Hydrometeorology, DOI: 10.1175/JHM-D-15-0218.1.

Validation of SMAP Radar Vegetation Data Cubes from Agricultural Field Measurements

NASA Astrophysics Data System (ADS)

Tsang, L.; Xu, X.; Liao, T.; Kim, S.; Njoku, E. G.

2012-12-01

The NASA Soil Moisture Active/Passive (SMAP) Mission will be launched in October 2014. The objective of the SMAP mission is to provide global measurements of soil moisture and its freeze/thaw state. These measurements will be used to enhance understanding of processes that link the water, energy and carbon cycles, and to extend the capabilities of weather and climate prediction models. In the active algorithm, the retrieval is performed based on the backscattering data cube, which are characterized by two surface parameters, which are soil moisture and soil surface rms height, and one vegetation parameter, the vegetation water content. We have developed a physical-based forward scattering model to generate the data cube for agricultural fields. To represent the agricultural crops, we include a layer of cylinders and disks on top of the rough surface. The scattering cross section of the vegetation layer and its interaction with the underground soil surface were calculated by the distorted Born approximation, which give explicitly three scattering mechanisms. A) The direct volume scattering B) The double bounce effect as, and C) The double bouncing effects. The direct volume scattering is calculated by using the Body of Revolution code. The double bounce effects, exhibited by the interaction of rough surface with the vegetation layer is considered by modifying the rough surface reflectivity using the coherent wave as computed by Numerical solution of Maxwell equations of 3 Dimensional simulations (NMM3D) of bare soil scattering. The rough surface scattering of the soil was calculated by NMM3D. We have compared the physical scattering models with field measurements. In the field campaign, the measurements were made on soil moisture, rough surface rms heights and vegetation water content as well as geometric parameters of vegetation. The three main crops lands are grassland, cornfield and soybean fields. The corresponding data cubes are validated using SGP99, SMEX02 and SMEX 08 field experiments.

Soil and geologic controls on recharge and groundwater flow response to climate perturbation: A case study of the Yakima River Basin

NASA Astrophysics Data System (ADS)

Nguyen, T. T.; Pham, H. V.; Bachmann, M.; Tague, C.; Adam, J. C.

2017-12-01

The Yakima River Basin (YRB) is one of the most important agricultural basins in Washington State with annual revenues in excess of $3.2 billion. This intensively irrigated basin is, however, one of the state's most climatically sensitive water resources system as it heavily relies on winter snowpack and limited reservoir storage. Water shortages and drought are expected to be more frequent with climate change, population growth and increasing agricultural demand. This could result in significant impacts on the groundwater system and subsequently the Yakima River. The goal of this study is to assess how soil and geologic characteristics affect catchment recharge and groundwater flow across three catchments within the YRB using a coupled framework including a physically based hydro-ecological model, the Regional Hydro-Ecologic Simulation System (RHESSys) and a groundwater model, MODFLOW. Soil and geologic-related parameters were randomly sampled to use within the Distributed Evaluation of Local Sensitivity Analysis (DELSA) framework to explore their roles in governing catchment recharge and groundwater flow to climate perturbation. Preliminarily results show that catchment recharge is most sensitive to variation in soil transmissivity in two catchments. However, in the other catchment, recharge is more influenced by soil field capacity and bypass recharge. Recharge is also more sensitive to geologic related parameters in catchments where a portion of its flow comes from deep groundwater. When including the effect of climate perturbations, the sensitivity of recharge responses to soil and geologic characteristics varies with temperature and precipitation change. On the other hand, horizontal hydraulic conductivity is the dominant factor that controls groundwater flow responses in catchments with low permeability soil; alternatively, specific storage (and, to some extent, vertical anisotropy) are important in catchments with more conductive soil. The modeling framework developed in this study will be used to investigate the impacts of both climate and drought-relief supplemental pumping on potential recharge, groundwater and streamflow changes in the YRB.

Retracing recurring vine mortality patterns over a long duration: case study of a Mediterranean viticultural estate

NASA Astrophysics Data System (ADS)

Vaudour, Emmanuelle; Leclercq, Léa; Gilliot, Jean-Marc; Chaignon, Benoît

2017-04-01

This study was aimed at performing both long term historical and spatial tracing, focusing on the vine mortality patterns and their temporal repetition, across a 6 ha-farm, "Domaine des Chauvets", mainly planted with rainfed black Grenache and Syrah varieties in the Southern Rhone Valley in France. In this estate of long-standing wine-growing history, were mortality patterns randomly distributed or were they related to soil or historical management? Along with soil parameters, soil surface condition, vine biological parameters including vigour, presence of diseases, stock-unearthing were collected in the field at a total of 112 sampling locations. A total of 25 aerial photographs in digitized format from the French National Institute of Geographic and Forest Information (IGN) were examined over the 1947-2010 period, of which 7 were retained for further rectification and processing. This dataset was used to retrace the landuse and planting history for each plot, and then extract the frequency of missing vines. Within-field terroir units were demarcated using support vector machine classification of a set of present-day very high resolution data, including soil apparent electrical conductivity EM38 maps and very high resolution Pléiades satellite images of May 2014 and July 2015. Field and recent data revealed important soil erosion rates which are likely to ruin terroir sustainability and pointed out those units for which soil restoration practices are urgently needed, while the temporal dataset exhibited a repeated spatial pattern of missing vines, throughout several plantings, uprootings, and vine replacements. The frequency of missing vines was related to within-field terroir units and also to past landuse, particularly forest or orchard dating back the 1940s, and current soil organic carbon content. This brings renewed questions about the determinism of vine decline, suggesting contribution of soil degradation processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Napier, Bruce A.; Fellows, Robert J.; Krupka, Kenneth M.

This report describes work performed for the U.S. Nuclear Regulatory Commission’s project Assessment of Food Chain Pathway Parameters in Biosphere Models, which was established to assess and evaluate a number of key parameters used in the food-chain models used in performance assessments of radioactive waste disposal facilities. Section 2 of this report summarizes characteristics of samples of soils and groundwater from three geographical regions of the United States, the Southeast, Northwest, and Southwest, and analyses performed to characterize their physical and chemical properties. Because the uptake and behavior of radionuclides in plant roots, plant leaves, and animal products depends onmore » the chemistry of the water and soil coming in contact with plants and animals, water and soil samples collected from these regions of the United States were used in experiments at Pacific Northwest National Laboratory to determine radionuclide soil-to-plant concentration ratios. Crops and forage used in the experiments were grown in the soils, and long-lived radionuclides introduced into the groundwater provide the contaminated water used to water the grown plants. The radionuclides evaluated include 99Tc, 238Pu, and 241Am. Plant varieties include alfalfa, corn, onion, and potato. The radionuclide uptake results from this research study show how regional variations in water quality and soil chemistry affect radionuclide uptake. Section 3 summarizes the procedures and results of the uptake experiments, and relates the soil-to-plant uptake factors derived. In Section 4, the results found in this study are compared with similar values found in the biosphere modeling literature; the study’s results are generally in line with current literature, but soil- and plant-specific differences are noticeable. This food-chain pathway data may be used by the NRC staff to assess dose to persons in the reference biosphere (e.g., persons who live and work in an area potentially affected by radionuclide releases) of waste disposal facilities and decommissioning sites.« less

Transformation of humus substances in the long-drained surface-gleyed soddy-podzolic soils under conditions of pronounced microrelief and different agrogenic loads

NASA Astrophysics Data System (ADS)

Ovchinnikova, M. F.

2016-08-01

The transformation of humus substances resulting from artificial drainage of the surface-gleyed soddy-podzolic soils under conditions of pronounced microtopography and different agrogenic loads was studied. The studied soil characteristics included acid-base conditions, the content and group composition of humus, the ratios between the fractions of humus acids, and optical density of humic acids. The features attesting to humus degradation were found in the soils of microdepressions periodically subjected to excessive surface moistening, in the soils of different landforms upon the construction of drainage trenches, and in the plowed non-fertilized soils. The response of humus characteristics to the changes in the ecological situation in the period of active application of agrochemicals for reclamation of the agrotechnogenically disturbed soils was traced. It was shown that the long-term dynamics of the particular parameters of the biological productivity of the soil depend on the hydrological and agrogenic factors, as well as on the weather conditions.

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates

NASA Astrophysics Data System (ADS)

Fenton, O.; Vero, S.; Ibrahim, T. G.; Murphy, P. N. C.; Sherriff, S. C.; Ó hUallacháin, D.

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (tT) is divided into unsaturated (tu) and saturated (ts) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of tT. In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of tu were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When tu estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments.

Resolving model parameter values from carbon and nitrogen stock measurements in a wide range of tropical mature forests using nonlinear inversion and regression trees

USGS Publications Warehouse

Liu, S.; Anderson, P.; Zhou, G.; Kauffman, B.; Hughes, F.; Schimel, D.; Watson, Vicente; Tosi, Joseph

2008-01-01

Objectively assessing the performance of a model and deriving model parameter values from observations are critical and challenging in landscape to regional modeling. In this paper, we applied a nonlinear inversion technique to calibrate the ecosystem model CENTURY against carbon (C) and nitrogen (N) stock measurements collected from 39 mature tropical forest sites in seven life zones in Costa Rica. Net primary productivity from the Moderate-Resolution Imaging Spectroradiometer (MODIS), C and N stocks in aboveground live biomass, litter, coarse woody debris (CWD), and in soils were used to calibrate the model. To investigate the resolution of available observations on the number of adjustable parameters, inversion was performed using nine setups of adjustable parameters. Statistics including observation sensitivity, parameter correlation coefficient, parameter sensitivity, and parameter confidence limits were used to evaluate the information content of observations, resolution of model parameters, and overall model performance. Results indicated that soil organic carbon content, soil nitrogen content, and total aboveground biomass carbon had the highest information contents, while measurements of carbon in litter and nitrogen in CWD contributed little to the parameter estimation processes. The available information could resolve the values of 2-4 parameters. Adjusting just one parameter resulted in under-fitting and unacceptable model performance, while adjusting five parameters simultaneously led to over-fitting. Results further indicated that the MODIS NPP values were compressed as compared with the spatial variability of net primary production (NPP) values inferred from inverse modeling. Using inverse modeling to infer NPP and other sensitive model parameters from C and N stock observations provides an opportunity to utilize data collected by national to regional forest inventory systems to reduce the uncertainties in the carbon cycle and generate valuable databases to validate and improve MODIS NPP algorithms.

Stochastic Modeling of Soil Salinity

NASA Astrophysics Data System (ADS)

Suweis, Samir; Rinaldo, Andrea; van der Zee, Sjoerd E. A. T. M.; Maritan, Amos; Porporato, Amilcare

2010-05-01

Large areas of cultivated land worldwide are affected by soil salinity. Estimates report that 10% of arable land in over 100 countries, and nine million km2 are salt affected, especially in arid and semi-arid regions. High salinity causes both ion specific and osmotic stress effects, with important consequences for plant production and quality. Salt accumulation in the root zone may be due to natural factors (primary salinization) or due to irrigation (secondary salinization). Simple (e.g., vertically averaged over the soil depth) coupled soil moisture and salt balance equations have been used in the past. Despite their approximations, these models have the advantage of parsimony, thus allowing a direct analysis of the interplay of the main processes. They also provide the ideal starting point to include external, random hydro-climatic fluctuations in the analysis of long-term salinization trends. We propose a minimalist stochastic model of primary soil salinity, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In fact, soil salinity statistics are obtained as a function of climate, soil and vegetation parameters. These, in turn, can be combined with soil moisture statistics to obtain a full characterization of soil salt concentrations and the ensuing risk of primary salinization. In particular, the solutions show the existence of two quite distinct regimes, the first one where the mean salt mass remains nearly constant with increasing rainfall frequency, and the second one where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e.g. for climate change impacts on rain-fed agriculture. The analytical nature of the solution allows direct estimation of the impact of changes in the climatic drivers on soil salinity and makes it suitable for computations of salinity risk at the global scale as a function of simple parameters. Moreover it facilitates their coupling with other models of long-term soil-plant biogeochemistry.

Determination of nitrogen balance in agroecosystems.

PubMed

Sainju, Upendra M

2017-01-01

Nitrogen balance in agroecosystems provides a quantitative framework of N inputs and outputs and retention in the soil that examines the sustainability of agricultural productivity and soil and environmental quality. Nitrogen inputs include N additions from manures and fertilizers, atmospheric depositions including wet and dry depositions, irrigation water, and biological N fixation. Nitrogen outputs include N removal in crop grain and biomass and N losses through leaching, denitrification, volatilization, surface runoff, erosion, gas emissions, and plant senescence. Nitrogen balance, which is the difference between N inputs and outputs, can be reflected in changes in soil total (organic + inorganic) N during the course of the experiment duration due to N immobilization and mineralization. While increased soil N retention and mineralization can enhance crop yields and decrease N fertilization rate, reduced N losses through N leaching and gas emissions (primarily NH 4 and NO x emissions, out of which N 2 O is a potent greenhouse gas) can improve water and air quality. •This paper discusses measurements and estimations (for non-measurable parameters due to complexity) of all inputs and outputs of N as well as changes in soil N storage during the course of the experiment to calculate N balance.•The method shows N flows, retention in the soil, and losses to the environment from agroecosystems.•The method can be used to measure agroecosystem performance and soil and environmental quality from agricultural practices.

Functional Diversity of Microbial Communities in Sludge-Amended Soils

NASA Astrophysics Data System (ADS)

Sun, Y. H.; Yang, Z. H.; Zhao, J. J.; Li, Q.

The BIOLOG method was applied to exploration of functional diversity of soil microbial communities in sludge-amended soils sampled from the Yangtze River Delta. Results indicated that metabolic profile, functional diversity indexes and Kinetic parameters of the soil microbial communities changed following soil amendment with sewage sludge, suggesting that the changes occurred in population of the microbes capable of exploiting carbon substrates and in this capability as well. The kinetic study of the functional diversity revealed that the metabolic profile of the soil microbial communities exhibited non-linear correlation with the incubation time, showing a curse of sigmoid that fits the dynamic model of growth of the soil microbial communities. In all the treatments, except for treatments of coastal fluvo-aquic soil amended with fresh sludge and dried sludge from Hangzhou, kinetic parameters K and r of the functional diversity of the soil microbial communities decreased significantly and parameter S increased. Changes in characteristics of the functional diversity well reflected differences in C utilizing capacity and model of the soil microbial communities in the sludge-amended soils, and changes in functional diversity of the soil microbial communities in a particular eco-environment, like soil amended with sewage sludge.

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

2000-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or 'time to drying' (t(sub d)) is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage I drying (as water is removed from storage), and then become more or less constant during soil limited, or 'stage II' drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Thermal and Hydrologic Signatures of Soil Controls on Evaporation: A Combined Energy and Water Balance Approach with Implications for Remote Sensing of Evaporation

NASA Technical Reports Server (NTRS)

Salvucci, Guido D.

1997-01-01

The overall goal of this research is to examine the feasibility of applying a newly developed diagnostic model of soil water evaporation to large land areas using remotely sensed input parameters. The model estimates the rate of soil evaporation during periods when it is limited by the net transport resulting from competing effects of capillary rise and drainage. The critical soil hydraulic properties are implicitly estimated via the intensity and duration of the first stage (energy limited) evaporation, removing a major obstacle in the remote estimation of evaporation over large areas. This duration, or "time to drying" (t(sub d)), is revealed through three signatures detectable in time series of remote sensing variables. The first is a break in soil albedo that occurs as a small vapor transmission zone develops near the surface. The second is a break in either surface to air temperature differences or in the diurnal surface temperature range, both of which indicate increased sensible heat flux (and/or storage) required to balance the decrease in latent heat flux. The third is a break in the temporal pattern of near surface soil moisture. Soil moisture tends to decrease rapidly during stage 1 drying (as water is removed from storage), and then become more or less constant during soil limited, or "stage 2" drying (as water is merely transmitted from deeper soil storage). The research tasks address: (1) improvements in model structure, including extensions to transpiration and aggregation over spatially variable soil and topographic landscape attributes; and (2) applications of the model using remotely sensed input parameters.

Interactive initialization of heat flux parameters for numerical models using satellite temperature measurements

NASA Technical Reports Server (NTRS)

Carlson, T. N. (Principal Investigator)

1982-01-01

Progress made in HCMM research, including testing the interactive minicomputer system and preparation of a paper on the analysis of regional scale soil moisture patterns, is summarized. An exhibit on remote sensing including a videotape display of HCMM images, most of them of the State College area, was prepared.

Do lab-derived distribution coefficient values of pesticides match distribution coefficient values determined from column and field-scale experiments? A critical analysis of relevant literature.

PubMed

Vereecken, H; Vanderborght, J; Kasteel, R; Spiteller, M; Schäffer, A; Close, M

2011-01-01

In this study, we analyzed sorption parameters for pesticides that were derived from batch and column or batch and field experiments. The batch experiments analyzed in this study were run with the same pesticide and soil as in the column and field experiments. We analyzed the relationship between the pore water velocity of the column and field experiments, solute residence times, and sorption parameters, such as the organic carbon normalized distribution coefficient ( ) and the mass exchange coefficient in kinetic models, as well as the predictability of sorption parameters from basic soil properties. The batch/column analysis included 38 studies with a total of 139 observations. The batch/field analysis included five studies, resulting in a dataset of 24 observations. For the batch/column data, power law relationships between pore water velocity, residence time, and sorption constants were derived. The unexplained variability in these equations was reduced, taking into account the saturation status and the packing status (disturbed-undisturbed) of the soil sample. A new regression equation was derived that allows estimating the values derived from column experiments using organic matter and bulk density with an value of 0.56. Regression analysis of the batch/column data showed that the relationship between batch- and column-derived values depends on the saturation status and packing of the soil column. Analysis of the batch/field data showed that as the batch-derived value becomes larger, field-derived values tend to be lower than the corresponding batch-derived values, and vice versa. The present dataset also showed that the variability in the ratio of batch- to column-derived value increases with increasing pore water velocity, with a maximum value approaching 3.5. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Investigating local controls on temporal stability of soil water content using sensor network data and an inverse modeling approach

NASA Astrophysics Data System (ADS)

Qu, W.; Bogena, H. R.; Huisman, J. A.; Martinez, G.; Pachepsky, Y. A.; Vereecken, H.

2013-12-01

Soil water content is a key variable in the soil, vegetation and atmosphere continuum with high spatial and temporal variability. Temporal stability of soil water content (SWC) has been observed in multiple monitoring studies and the quantification of controls on soil moisture variability and temporal stability presents substantial interest. The objective of this work was to assess the effect of soil hydraulic parameters on the temporal stability. The inverse modeling based on large observed time series SWC with in-situ sensor network was used to estimate the van Genuchten-Mualem (VGM) soil hydraulic parameters in a small grassland catchment located in western Germany. For the inverse modeling, the shuffled complex evaluation (SCE) optimization algorithm was coupled with the HYDRUS 1D code. We considered two cases: without and with prior information about the correlation between VGM parameters. The temporal stability of observed SWC was well pronounced at all observation depths. Both the spatial variability of SWC and the robustness of temporal stability increased with depth. Calibrated models both with and without prior information provided reasonable correspondence between simulated and measured time series of SWC. Furthermore, we found a linear relationship between the mean relative difference (MRD) of SWC and the saturated SWC (θs). Also, the logarithm of saturated hydraulic conductivity (Ks), the VGM parameter n and logarithm of α were strongly correlated with the MRD of saturation degree for the prior information case, but no correlation was found for the non-prior information case except at the 50cm depth. Based on these results we propose that establishing relationships between temporal stability and spatial variability of soil properties presents a promising research avenue for a better understanding of the controls on soil moisture variability. Correlation between Mean Relative Difference of soil water content (or saturation degree) and inversely estimated soil hydraulic parameters (log10(Ks), log10(α), n, and θs) at 5-cm, 20-cm and 50-cm depths. Solid circles represent parameters estimated by using prior information; open circles represent parameters estimated without using prior information.

Utilization of downscaled microwave satellite data and GRACE Total Water Storage anomalies for improving streamflow prediction in the Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Gupta, M.; Bolten, J. D.

2016-12-01

The Mekong river is the world's eighth largest in discharge with draining an area of 795,000 km² from the Eastern watershed of the Tibetan Plateau to the Mekong Delta including, Myanmar, Laos PDR, Thailand, Cambodia, Vietnam and three provinces of China. The populations in these countries are highly dependent on the Mekong River and they are vulnerable to the availability and quality of the water resources within the Mekong River Basin. Soil moisture is one of the most important hydrological cycle variables and is available from passive microwave satellite sensors (such as AMSR-E, SMOS and SMAP), but their spatial resolution is frequently too coarse for effective use by land managers and decision makers. The merging of satellite observations with numerical models has led to improved land surface predictions. Although performance of the models have been continuously improving, the laboratory methods for determining key hydraulic parameters are time consuming and expensive. The present study assesses a method to determine the effective soil hydraulic parameters using a downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E). The soil moisture downscaling algorithm is based on a regression relationship between 1-km MODIS land surface temperature and 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) to produce an enhanced spatial resolution ASMR-E-based soil moisture product. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the land surface model. This work improves the hydrological fluxes and the state variables are optimized and the optimal parameter values are then transferred for retrieving hydrological fluxes. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Kim, M.

2016-12-01

The continuous water stress caused by decrease of soil water has a direct influence to the crop growth in a upland crop area. The agricultural drought is occured if water requirement is not supplied timely in crop growh process. It is more important to understand the soil characteristics for high accuracy soil moisture estimation because of the soil water contents largely depends on soil properties. The RDA(Rural Development Administration) has provided real-time soil moisture observations corrected for 71 points in the South Korea. In this study, we developed a soil water content estimation method that considered soil hydraulic parameters for the observation points of soil water content in agricultural regions operated by the RDA. SWAP(Soil-Water-Atmosphere-Plant) model was used in the estimation of soil water contents. The soil hydraulic parameters that is the input data of the SWAP model were estimated using the ROSETTA model developed by the U.S. Department of Agriculture(USDA). Meteorological data observed from AWS(Automatic Weather Station) were used including daily maximum temperature(°), daily minimum temperature(°), relative humidity(%), solar radiation, wind speed and precipitation data. We choosed 56 stations there are no missing of meteorological data and have soil physical properties. For the verification of soil water content estimation method, we used Haenam KoFlux observation data that are observed long-term soil water contents over 2009-2015(2014 missing) years. In the case of 2015, there are good reproducibility between observation of soil water contents and results of SWAP model simulation with R2=0.72, RMSE=0.026 and TCC=0.849. In the case of precipitation event, the simulation results were slightly overestimated more than observation. However there are good reproducibility in the case of soil water reduction due to continuous non-precipitation periods. We have simulated the soil water contents of the 56 stations that being operated in the RDA from 4 January 2015 to 31 October 2015 using the SWAP model. The environmental setting of SWAP modle according to the station applied it equally. The results showed a significant difference to the reproducibility according to the observation station.

Factors associated with plant species richness in a coastal tall-grass prairie

USGS Publications Warehouse

Grace, James B.; Allain, Larry K.; Allen, Charles

2000-01-01

In this study we examine the factors associated with variations in species richness within a remnant tall-grass prairie in order to gain insight into the relative importance of controlling variables. The study area was a small, isolated prairie surrounded by wetlands and located within the coastal prairie region, which occurs along the northwestern Gulf of Mexico coastal plain. Samples were taken along three transects that spanned the prairie. Parameters measured included micro-elevation, soil characteristics, indications of recent disturbance, above-ground biomass (including litter), light penetration through the plant canopy, and species richness. Species richness was found to correlate with micro-elevation, certain soil parameters, and light penetration through the canopy, but not with above-ground biomass. Structural equation analysis was used to assess the direct and indirect effects of micro-elevation, soil properties, disturbance, and indicators of plant abundance on species richness. The results of this analysis showed that observed variations in species richness were primarily associated with variations in environmental effects (from soil and microtopography) and were largely unrelated to variations in measures of plant abundance (biomass and light penetration). These findings suggest that observed variations in species richness in this system primarily resulted from environmental effects on the species pool. These results fit with a growing body of information that suggests that environmental effects on species richness are of widespread importance.

IT-based soil quality evaluation for agroecologically smart land-use planning in RF conditions

NASA Astrophysics Data System (ADS)

Vasenev, Ivan

2016-04-01

Activated in the first decades of XXI century global climate, economy and farming changes sharply actualized novel IT-based approaches in soil quality evaluation to address modern agricultural issues with agroecologically smart land-use planning. Despite global projected climate changes will affect a general decline of crop yields (IPCC 2014), RF boreal and subboreal regions will benefit from predicted and already particularly verified temperature warming and increased precipitation (Valentini, Vasenev, 2015) due to essential increasing of growing season length and mild climate conditions favorable for most prospective crops and best available agrotechnologies. However, the essential spatial heterogeneity is mutual feature for most natural and man-changed soils at the Central European region of Russia which is one of the biggest «food baskets» in RF. In these conditions potentially favorable climate circumstances will increase not only soil fertility and workability features but also their dynamics and spatial variability that determine crucial issues of IT-based soil quality evaluation systems development and agroecologically smart farming planning. Developed and verified within the LAMP project (RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) regionally adapted DSS (ACORD-R - RF #2012612944) gives effective informational and methodological support for smart farming agroecological optimization in global climate and farming changes challenges. Information basis for agroecologically smart land-use planning consists of crops and agrotechnologies requirements, regional and local systems of agroecological zoning, local landscape and soil cover patterns, land quality and degradation risk assessments, current and previous farming practices results, agroclimatic predictions and production agroecological models, environmental limitations and planned profitability, fertilizing efficiency DSS ACORD-R. Smart land-use practice refers to sustainable balance among soil 7 principal types of agroecological functions: (a) Agroclimatic ones of plant supply with photosynthetic active radiation, effective heat and available moisture; (b) Agrochemical functions of crop supply with available macro- and micro-nutrients; (c) Agrophysical ones of favorable condition support for farming effective workability and trafficability; (d) Hydrophysical functions of plant seasonal supply with available moisture and soil air exchange; (e) Phyto-sanitary functions of favorable condition support for crop minimum damage by pathogens, pests and weeds; (f) Ecogeochemical ones of soil resistance to contamination; (g) Ecopedomorphogenetic functions of plant and farming support with soil agroecological quasi-homogeneity in space and time. The IT-based soil evaluation algorithm includes 4 particular ones: (i) the principal agroecological parameters assessment by their modelling or adapted to concrete soil type logistic equation; (ii) agroecological function assessment as corrected harmonic mean from its parameters assessment values; (iii) homogeneous land unit assessment as combination of its functions values; (iv) heterogeneous land unit assessment as weighted average value corrected by soil cover patterns contrast and boundary complexity - with their results visualization. The principal limitations for sustainable land use practices are usually determined by the level of photosynthetic active radiation or soil available water deficit, soil fertility and agrotechnological parameters, risks of soil degradation processes development, crop physiological stress, production or environmental contamination. The agriculture intensification often leads to the raised issue of greenhouse gases, including CO2 (as a result of soil organic carbon mineralization), CH4 (animal production) and N2O (mineral fertilizing), to changes of the profitability and decrease in soil potential of the atmospheric carbon sequestration. The consequence of agricultural land degradation due to non-rational land-use can be disturbance of soil organic matter fluxes and traditional transformation processes. So, agroecosystems are very sensitive to global changes and their IT-based timely adaptation is the necessary condition for their sustainable functioning and ecosystem services support, including an inhabitancy, water and foodstuffs stocks.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

SWAT: Model use, calibration, and validation

USDA-ARS?s Scientific Manuscript database

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT including manual calibration procedures...

Simulating soil moisture change in a semiarid rangeland watershed with a process-based water-balance model

Treesearch

Howard Evan Canfield; Vicente L. Lopes

2000-01-01

A process-based, simulation model for evaporation, soil water and streamflow (BROOK903) was used to estimate soil moisture change on a semiarid rangeland watershed in southeastern Arizona. A sensitivity analysis was performed to select parameters affecting ET and soil moisture for calibration. Automatic parameter calibration was performed using a procedure based on a...

Automated Microbial Metabolism Laboratory

NASA Technical Reports Server (NTRS)

1971-01-01

The effect of several environmental parameters on previously developed life detection systems is explored. Initial attempts were made to conduct all the experiments in a moist mode (high soil volume to water volume ratio). However, only labeled release and measurement of ATP were found to be feasible under conditions of low moisture. Therefore, these two life detection experiments were used for most of the environmental effects studies. Three soils, Mojave (California desert), Wyaconda (Maryland, sandy loam) and Victoria Valley (Antarctic desert) were generally used throughout. The environmental conditions studied included: incubation temperature 3 C to 80 C, ultraviolet irradiation of soils, variations in soil/liquid ratio, specific atmospheric gases, various antimetabolites, specific substrates, and variation in pH. An experiment designed to monitor nitrogen metabolism was also investigated.

A combined approach of physicochemical and biological methods for the characterization of petroleum hydrocarbon-contaminated soil.

PubMed

Masakorala, Kanaji; Yao, Jun; Chandankere, Radhika; Liu, Haijun; Liu, Wenjuan; Cai, Minmin; Choi, Martin M F

2014-01-01

Main physicochemical and microbiological parameters of collected petroleum-contaminated soils with different degrees of contamination from DaGang oil field (southeast of Tianjin, northeast China) were comparatively analyzed in order to assess the influence of petroleum contaminants on the physicochemical and microbiological properties of soil. An integration of microcalorimetric technique with urease enzyme analysis was used with the aim to assess a general status of soil metabolism and the potential availability of nitrogen nutrient in soils stressed by petroleum-derived contaminants. The total petroleum hydrocarbon (TPH) content of contaminated soils varied from 752.3 to 29,114 mg kg(−1). Although the studied physicochemical and biological parameters showed variations dependent on TPH content, the correlation matrix showed also highly significant correlation coefficients among parameters, suggesting their utility in describing a complex matrix such as soil even in the presence of a high level of contaminants. The microcalorimetric measures gave evidence of microbial adaptation under highest TPH concentration; this would help in assessing the potential of a polluted soil to promote self-degradation of oil-derived hydrocarbon under natural or assisted remediation. The results highlighted the importance of the application of combined approach in the study of those parameters driving the soil amelioration and bioremediation.

Deriving the suction stress of unsaturated soils from water retention curve, based on wetted surface area in pores

NASA Astrophysics Data System (ADS)

Greco, Roberto; Gargano, Rudy

2016-04-01

The evaluation of suction stress in unsaturated soils has important implications in several practical applications. Suction stress affects soil aggregate stability and soil erosion. Furthermore, the equilibrium of shallow unsaturated soil deposits along steep slopes is often possible only thanks to the contribution of suction to soil effective stress. Experimental evidence, as well as theoretical arguments, shows that suction stress is a nonlinear function of matric suction. The relationship expressing the dependence of suction stress on soil matric suction is usually indicated as Soil Stress Characteristic Curve (SSCC). In this study, a novel equation for the evaluation of the suction stress of an unsaturated soil is proposed, assuming that the exchange of stress between soil water and solid particles occurs only through the part of the surface of the solid particles which is in direct contact with water. The proposed equation, based only upon geometric considerations related to soil pore-size distribution, allows to easily derive the SSCC from the water retention curve (SWRC), with the assignment of two additional parameters. The first parameter, representing the projection of the external surface area of the soil over a generic plane surface, can be reasonably estimated from the residual water content of the soil. The second parameter, indicated as H0, is the water potential, below which adsorption significantly contributes to water retention. For the experimental verification of the proposed approach such a parameter is considered as a fitting parameter. The proposed equation is applied to the interpretation of suction stress experimental data, taken from the literature, spanning over a wide range of soil textures. The obtained results show that in all cases the proposed relationships closely reproduces the experimental data, performing better than other currently used expressions. The obtained results also show that the adopted values of the parameter H0, allowing for a good fitting of the experimental data, are in agreement with the values of water potential marking the limit between capillary and adsorptive soil water retention, which can be estimated from the shape of the water retention curve. Therefore, with the proposed approach, at least in principle it is possible to derive the SSSC directly from the knowledge of the SWRC.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

Using rainfall simulations to understand the relationship between precipitation, soil crust and infiltration in four agricultural soils

NASA Astrophysics Data System (ADS)

Angulo-Martinez, Marta; Alastrué, Juan; Moret-Fernández, David; Beguería, Santiago; López, Mariví; Navas, Ana

2017-04-01

Rainfall simulation experiments were carried out in order to study soil crust formation and its relation with soil infiltration parameters—sorptivity (S) and hydraulic conductivity (K)—on four common agricultural soils with contrasted properties; namely, Cambisol, Gypsisol, Solonchak, and Solonetz. Three different rainfall simulations, replicated three times each of them, were performed over the soils. Prior to rainfall simulations all soils were mechanically tilled with a rototiller to create similar soil surface conditions and homogeneous soils. Rainfall simulation parameters were monitored in real time by a Thies Laser Precipitation Monitor, allowing a complete characterization of simulated rainfall microphysics (drop size and velocity distributions) and integrated variables (accumulated rainfall, intensity and kinetic energy). Once soils dried after the simulations, soil penetration resistance was measured and soil hydraulic parameters, S and K, were estimated using the disc infiltrometry technique. There was little variation in rainfall parameters among simulations. Mean intensity and mean median diameter (D50) varied in simulations 1 ( 0.5 bar), 2 ( 0.8 bar) and 3 ( 1.2 bar) from 26.5 mm h-1 and 0.43 mm (s1) to 40.5 mm h-1 and 0.54 mm (s2) and 41.1 mm h-1 and 0.56 mm for (s3), respectively. Crust formation by soil was explained by D50 and subsequently by the total precipitation amount and the percentage of silt and clay in soil, being Cambisol and Gypsisol the soils that showed more increase in penetration resistance by simulation. All soils showed similar S values by simulations which were explained by rainfall intensity. Different patterns of K were shown by the four soils, which were explained by the combined effect of D50 and intensity, together with soil physico-chemical properties. This study highlights the importance of monitoring all precipitation parameters to determine their effect on different soil processes.

Carbon dioxide diffuse emission from the soil: ten years of observations at Vesuvio and Campi Flegrei (Pozzuoli), and linkages with volcanic activity

NASA Astrophysics Data System (ADS)

Granieri, D.; Avino, R.; Chiodini, G.

2010-01-01

Carbon dioxide flux from the soil is regularly monitored in selected areas of Vesuvio and Solfatara (Campi Flegrei, Pozzuoli) with the twofold aim of i) monitoring spatial and temporal variations of the degassing process and ii) investigating if the surface phenomena could provide information about the processes occurring at depth. At present, the surveyed areas include 15 fixed points around the rim of Vesuvio and 71 fixed points in the floor of Solfatara crater. Soil CO2 flux has been measured since 1998, at least once a month, in both areas. In addition, two automatic permanent stations, located at Vesuvio and Solfatara, measure the CO2 flux and some environmental parameters that can potentially influence the CO2 diffuse degassing. Series acquired by continuous stations are characterized by an annual periodicity that is related to the typical periodicities of some meteorological parameters. Conversely, series of CO2 flux data arising from periodic measurements over the arrays of Vesuvio and Solfatara are less dependent on external factors such as meteorological parameters, local soil properties (porosity, hydraulic conductivity) and topographic effects (high or low ground). Therefore we argue that the long-term trend of this signal contains the “best” possible representation of the endogenous signal related to the upflow of deep hydrothermal fluids.

Deforestation effects on soil quality and water retention curve parameters in eastern Ardabil, Iran

NASA Astrophysics Data System (ADS)

Asghari, Sh.; Ahmadnejad, S.; Keivan Behjou, F.

2016-03-01

The land use change from natural to managed ecosystems causes serious soil degradation. The main objective of this research was to assess deforestation effects on soil physical quality attributes and soil water retention curve (SWRC) parameters in the Fandoghlou region of Ardabil province, Iran. Totally 36 surface and subsurface soil samples were taken and soil water contents measured at 13 suctions. Alfa (α) and n parameters in van Genuchten (1980) model were estimated by fitting SWRC data by using RETC software. The slope of SWRC at inflection point (SP) was calculated by Dexter (2004) equation. The results indicated that with changing land use from forest (F) to range land (R) and cultivated land (C), and also with increasing soil depth from 0-25 to 75-100 cm in each land use, organic carbon, micropores, saturated and available water contents decreased and macropores and bulk density increased significantly ( P < 0.05). The position of SWRC shape in F was higher than R and C lands at all soil depths. Changing F to R and C lands and also increasing soil depth in each land use significantly ( P < 0.05) increased α and decreased n and SP. The average values of SP were obtained 0.093, 0.051 and 0.031 for F, R and C, respectively. As a result, deforestation reduced soil physical quality by affecting SWRC parameters.

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

NASA Technical Reports Server (NTRS)

Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

2013-01-01

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Soil Moisture and Temperature Measuring Networks in the Tibetan Plateau and Their Hydrological Applications

NASA Astrophysics Data System (ADS)

Yang, Kun; Chen, Yingying; Qin, Jun; Lu, Hui

2017-04-01

Multi-sphere interactions over the Tibetan Plateau directly impact its surrounding climate and environment at a variety of spatiotemporal scales. Remote sensing and modeling are expected to provide hydro-meteorological data needed for these process studies, but in situ observations are required to support their calibration and validation. For this purpose, we have established two networks on the Tibetan Plateau to measure densely two state variables (soil moisture and temperature) and four soil depths (0 5, 10, 20, and 40 cm). The experimental area is characterized by low biomass, high soil moisture dynamic range, and typical freeze-thaw cycle. As auxiliary parameters of these networks, soil texture and soil organic carbon content are measured at each station to support further studies. In order to guarantee continuous and high-quality data, tremendous efforts have been made to protect the data logger from soil water intrusion, to calibrate soil moisture sensors, and to upscale the point measurements. One soil moisture network is located in a semi-humid area in central Tibetan Plateau (Naqu), which consists of 56 stations with their elevation varying over 4470 4950 m and covers three spatial scales (1.0, 0.3, 0.1 degree). The other is located in a semi-arid area in southern Tibetan Plateau (Pali), which consists of 25 stations and covers an area of 0.25 degree. The spatiotemporal characteristics of the former network were analyzed, and a new spatial upscaling method was developed to obtain the regional mean soil moisture truth from the point measurements. Our networks meet the requirement for evaluating a variety of soil moisture products, developing new algorithms, and analyzing soil moisture scaling. Three applications with the network data are presented in this paper. 1. Evaluation of Current remote sensing and LSM products. The in situ data have been used to evaluate AMSR-E, AMSR2, SMOS and SMAP products and four modeled outputs by the Global Land Data Assimilation System (GLDAS). 2. Development of New Products. We developed a dual-pass land data assimilation system. The essential idea of the system is to calibrate a land data assimilation system before a normal data assimilation. The calibration is based on satellite data rather than in situ data. Through this way, we may alleviate the impact of uncertainties in determining the error covariance of both observation operator and model operation, as it is always tough to determine the covariance. The performance of the data assimilation system is presented through comparison against the Tibetan Plateau soil moisture measuring networks. And the results are encouraging. 3. Estimation of Soil Parameter Values in a Land Surface Model. We explored the possibility to estimate soil parameter values by assimilating AMSR-E brightness temperature (TB) data. In the assimilation system, the TB is simulated by the coupled system of a land surface model (LSM) and a radiative transfer model (RTM), and the simulation errors highly depend on parameters in both the LSM and the RTM. Thus, sensitive soil parameters may be inversely estimated through minimizing the TB errors. The effectiveness of the estimated parameter values is evaluated against intensive measurements of soil parameters and soil moisture in three grasslands of the Tibetan Plateau and the Mongolian Plateau. The results indicate that this satellite data-based approach can improve the data quality of soil porosity, a key parameter for soil moisture modeling, and LSM simulations with the estimated parameter values reasonably reproduce the measured soil moisture. This demonstrates it is feasible to calibrate LSMs for soil moisture simulations at grid scale by assimilating microwave satellite data, although more efforts are expected to improve the robustness of the model calibration.

Simultaneous quantification of soil phosphorus labile pool and desorption kinetics using DGTs and 3D-DIFS

NASA Astrophysics Data System (ADS)

Menezes-Blackburn, Daniel; Sun, Jiahui; Lehto, Niklas; Zhang, Hao; Stutter, Marc; Giles, Courtney D.; Darch, Tegan; George, Timothy S.; Shand, Charles; Lumsdon, David; Blackwell, Martin; Wearing, Catherine; Cooper, Patricia; Wendler, Renate; Brown, Lawrie; Haygarth, Philip M.

2017-04-01

The phosphorus (P) labile pool and desorption kinetics were simultaneously evaluated in ten representative UK soils using the technique of Diffusive gradients in thin films (DGT). The DGT-induced fluxes in soil and sediments model (DIFS) was fitted to the time series of DGT deployment (1h to 240h). The desorbable P concentration (labile P) was obtained by multiplying the fitted Kd by the soil solution P concentration obtained using Diffusive Equilibration in Thin Films (DET) devices. The labile P was then compared to several soil P extracts including Olsen P, Resin P, FeO-P and water extractable P, in order to assess if these analytical procedures can be used to represent the labile P across different soils. The Olsen P, commonly used as a representation of the soil labile P pool, overestimated the desorbable P concentration by a seven fold factor. The use of this approach for the quantification of soil P desorption kinetics parameters was somewhat unprecise, showing a wide range of equally valid solutions for the response of the system P equilibration time (Tc). Additionally, the performance of different DIFS model versions (1D, 2D and 3D) was compared. Although these models had a good fit to experimental DGT time series data, the fitted parameters showed a poor agreement between different model versions. The limitations of the DIFS model family are associated with the assumptions taken in the modelling approach and the 3D version is here considered to be the most precise among them.

Combining Forces - The Use of Landsat TM Satellite Imagery, Soil Parameter Information, and Multiplex PCR to Detect Coccidioides immitis Growth Sites in Kern County, California

PubMed Central

Lauer, Antje; Talamantes, Jorge; Castañón Olivares, Laura Rosío; Medina, Luis Jaime; Baal, Joe Daryl Hugo; Casimiro, Kayla; Shroff, Natasha; Emery, Kirt W.

2014-01-01

Coccidioidomycosis is a fungal disease acquired through the inhalation of spores of Coccidioides spp., which afflicts primarily humans and other mammals. It is endemic to areas in the southwestern United States, including the San Joaquin Valley portion of Kern County, California, our region of interest (ROI). Recently, incidence of coccidioidomycosis, also known as valley fever, has increased significantly, and several factors including climate change have been suggested as possible drivers for this observation. Up to date details about the ecological niche of C. immitis have escaped full characterization. In our project, we chose a three-step approach to investigate this niche: 1) We examined Landsat-5-Thematic-Mapper multispectral images of our ROI by using training pixels at a 750 m×750 m section of Sharktooth Hill, a site confirmed to be a C. immitis growth site, to implement a Maximum Likelihood Classification scheme to map out the locations that could be suitable to support the growth of the pathogen; 2) We used the websoilsurvey database of the US Department of Agriculture to obtain soil parameter data; and 3) We investigated soil samples from 23 sites around Bakersfield, California using a multiplex Polymerase Chain Reaction (PCR) based method to detect the pathogen. Our results indicated that a combination of satellite imagery, soil type information, and multiplex PCR are powerful tools to predict and identify growth sites of C. immitis. This approach can be used as a basis for systematic sampling and investigation of soils to detect Coccidioides spp. PMID:25380290

Automated system for generation of soil moisture products for agricultural drought assessment

NASA Astrophysics Data System (ADS)

Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically download requisite input parameters like rainfall, Potential Evapotranspiration (PET) from respective servers. It can import file formats like .grd, .hdf, .img, generic binary etc, perform geometric correction and re-project the files to native projection system. The software takes into account the weather, crop and soil parameters to run the designed soil water balance model. The software also has additional features like time compositing of outputs to generate weekly, fortnightly profiles for further analysis. Other tools to generate "Area Favorable for Crop Sowing" using the daily soil moisture with highly customizable parameters interface has been provided. A whole India analysis would now take a mere 20 seconds for generation of soil moisture products which would normally take one hour per day using commercial software.

The Scottish way - getting results in soil spectroscopy without spending money

NASA Astrophysics Data System (ADS)

Aitkenhead, Matt; Cameron, Clare; Gaskin, Graham; Choisy, Bastien; Coull, Malcolm; Black, Helaina

2016-04-01

Achieving soil characterisation using spectroscopy requires several things. These include soil data to develop or train a calibration model, a method of capturing spectra, the ability to actually develop a calibration model and also additional data to reinforce the model by introducing some form of stratification or site-specific information. Each of these steps requires investment in both time and money. Here we present an approach developed at the James Hutton Institute that achieves the end goal with minimal cost, by making as much use as possible of existing soil and environmental datasets for Scotland. The spectroscopy device that has been developed is PHYLIS (Prototype HYperspectral Low-cost Imaging System) that was constructed using inexpensive optical components, and uses a basic digital camera to produce visible-range spectra. The results show that for a large number of soil parameters, it is possible to estimate values either very well (RSQ > 0.9) (LOI, C, exchangeable H), well (RSQ > 0.75) (N, pH) or moderately (RSQ > 0.5) (Mg, Na, K, Fe, Al, sand, silt, clay). The methods used to achieve these results are described. A number of additional parameters were not well estimated (elemental concentrations), and we describe how work is ongoing to improve our ability to estimate these using similar technology and data.

The effects of temperature on decomposition and allelopathic phytotoxicity of boneseed litter.

PubMed

Al Harun, Md Abdullah Yousuf; Johnson, Joshua; Uddin, Md Nazim; Robinson, Randall W

2015-07-01

Decomposition of plant litter is a fundamental process in ecosystem function, carbon and nutrient cycling and, by extension, climate change. This study aimed to investigate the role of temperature on the decomposition of water soluble phenolics (WSP), carbon and soil nutrients in conjunction with the phytotoxicity dynamics of Chrysanthemoides monilifera subsp. monilifera (boneseed) litter. Treatments consisted of three factors including decomposition materials (litter alone, litter with soil and soil alone), decomposition periods and temperatures (5-15, 15-25 and 25-35°C (night/day)). Leachates were collected on 0, 5, 10, 20, 40 and 60th days to analyse physico-chemical parameters and phytotoxicity. Water soluble phenolics and dissolved organic carbon (DOC) increased with increasing temperature while nutrients like SO4(-2) and NO3(-1) decreased. Speed of germination, hypocotyl and radical length and weight of Lactuca sativa exposed to leachates were decreased with increasing decomposition temperature. All treatment components had significant effects on these parameters. There had a strong correlation between DOC and WSP, and WSP content of the leachates with radical length of test species. This study identified complex interactivity among temperature, WSP, DOC and soil nutrient dynamics of litter occupied soil and that these factors work together to influence phytotoxicity. Copyright © 2015. Published by Elsevier B.V.

On the treatment of evapotranspiration, soil moisture accounting, and aquifer recharge in monthly water balance models

USGS Publications Warehouse

Alley, William M.

1984-01-01

Several two- to six-parameter regional water balance models are examined by using 50-year records of monthly streamflow at 10 sites in New Jersey. These models include variants of the Thornthwaite-Mather model, the Palmer model, and the more recent Thomas abcd model. Prediction errors are relatively similar among the models. However, simulated values of state variables such as soil moisture storage differ substantially among the models, and fitted parameter values for different models sometimes indicated an entirely different type of basin response to precipitation. Some problems in parameter identification are noted, including difficulties in identifying an appropriate time lag factor for the Thornthwaite-Mather-type model for basins with little groundwater storage, very high correlations between upper and lower storages in the Palmer-type model, and large sensitivity of parameter a of the abcd model to bias in estimates of precipitation and potential evapotranspiration. Modifications to the threshold concept of the Thornthwaite-Mather model were statistically valid for the six stations in northern New Jersey. The abcd model resulted in a simulated seasonal cycle of groundwater levels similar to fluctuations observed in nearby wells but with greater persistence. These results suggest that extreme caution should be used in attaching physical significance to model parameters and in using the state variables of the models in indices of drought and basin productivity.

Predicting first-year bare-root seedling establishment with soil and community dominance factors

Treesearch

Robin E. Durham; Benjamin A. Zamora; Michael R. Sackschewsky; Jason C. Ritter

2001-01-01

The usefulness of measuring community dominance factors and the soil parameters of geometric mean particle size and percent fines as predictors of first-year bare-root establishment of Wyoming big sagebrush seedlings was investigated. The study was conducted on six sandy soils in south-central Washington. Soil parameters that could affect the distribution of Sandberg’s...

Evaluation of the Validated Soil Moisture Product from the SMAP Radiometer

NASA Technical Reports Server (NTRS)

O'Neill, P.; Chan, S.; Colliander, A.; Dunbar, S.; Njoku, E.; Bindlish, R.; Chen, F.; Jackson, T.; Burgin, M.; Piepmeier, J.;

Do biochars influence the availability and human oral bioaccessibility of Cd, Pb, and Zn in a contaminated slightly alkaline soil?

PubMed

Janus, Adeline; Waterlot, Christophe; Heymans, Sophie; Deboffe, Christophe; Douay, Francis; Pelfrêne, Aurélie

2018-03-14

Different remediation techniques have been used to restore metal-contaminated sites, including stabilizing metals by adding amendments to the soils. This study experimented three biochars, made from wood and miscanthus, cultivated on contaminated and uncontaminated soils, used as amendments at a 2% application rate on a metal-contaminated soil for 9 months in laboratory-controlled conditions. The objective was to evaluate whether biochars were able to decrease the availability and human oral bioaccessibility of metals in an alkaline soil. To meet this goal, the modifications of the soil's physicochemical parameters, metal distribution in soil, and human bioaccessibility were evaluated at different sampling times. The results showed that biochar application to the alkaline soil did not always decrease the soil metal availability, which challenges the value of using biochars in already slightly alkaline soils at a low application rate. However, differences in efficiency between the three biochars tested were highlighted. The biochar produced with miscanthus cultivated on uncontaminated soil led to higher soil metal bioaccessibility. Moreover, because of the absence of any increase in soil metal availability with the biochar produced from biomass cultivated on contaminated soil, the use of such biochars can be recommended for the remediation of contaminated soil.

Seasonal and geothermal production variations in concentrations of He and CO2 in soil gases, Roosevelt Hot Springs Known Geothermal Resource Area, Utah, U.S.A.

USGS Publications Warehouse

Hinkle, M.E.

1991-01-01

To increase understanding of natural variations in soil gas concentrations, CO2, He, O2 and N2 were measured in soil gases collected regularly for several months from four sites at the Roosevelt Hot Springs Known Geothermal Resource Area, Utah. Soil temperature, air temperature, per cent relative humidity, barometric pressure and amounts of rain and snowfall were also monitored to determine the effect of meteorological parameters on concentrations of the measured gases. Considerable seasonal variation existed in concentrations of CO2 and He. The parameters that most affected the soil-gas concentrations were soil and air temperatures. Moisture from rain and snow probably affected the soil-gas concentrations also. However, annual variations in meteorological parameters did not appear to affect measurements of anomalous concentrations in samples collected within a time period of a few days. Production from some of the geothermal wells probably affected the soil-gas concentrations. ?? 1990.

Modeling nonlinear responses of DOC transport in boreal catchments in Sweden

NASA Astrophysics Data System (ADS)

Kasurinen, Ville; Alfredsen, Knut; Ojala, Anne; Pumpanen, Jukka; Weyhenmeyer, Gesa A.; Futter, Martyn N.; Laudon, Hjalmar; Berninger, Frank

2016-07-01

Stream water dissolved organic carbon (DOC) concentrations display high spatial and temporal variation in boreal catchments. Understanding and predicting these patterns is a challenge with great implications for water quality projections and carbon balance estimates. Although several biogeochemical models have been used to estimate stream water DOC dynamics, model biases common during both rain and snow melt-driven events. The parsimonious DOC-model, K-DOC, with 10 calibrated parameters, uses a nonlinear discharge and catchment water storage relationship including soil temperature dependencies of DOC release and consumption. K-DOC was used to estimate the stream water DOC concentrations over 5 years for eighteen nested boreal catchments having total area of 68 km2 (varying from 0.04 to 67.9 km2). The model successfully simulated DOC concentrations during base flow conditions, as well as, hydrological events in catchments dominated by organic and mineral soils reaching NSEs from 0.46 to 0.76. Our semimechanistic model was parsimonious enough to have all parameters estimated using statistical methods. We did not find any clear differences between forest and mire-dominated catchments that could be explained by soil type or tree species composition. However, parameters controlling slow release and consumption of DOC from soil water behaved differently for small headwater catchments (less than 2 km2) than for those that integrate larger areas of different ecosystem types (10-68 km2). Our results emphasize that it is important to account for nonlinear dependencies of both, soil temperature, and catchment water storage, when simulating DOC dynamics of boreal catchments.

Sensitivity of ecological soil-screening levels for metals to exposure model parameterization and toxicity reference values.

PubMed

Sample, Bradley E; Fairbrother, Anne; Kaiser, Ashley; Law, Sheryl; Adams, Bill

2014-10-01

Ecological soil-screening levels (Eco-SSLs) were developed by the United States Environmental Protection Agency (USEPA) for the purposes of setting conservative soil screening values that can be used to eliminate the need for further ecological assessment for specific analytes at a given site. Ecological soil-screening levels for wildlife represent a simplified dietary exposure model solved in terms of soil concentrations to produce exposure equal to a no-observed-adverse-effect toxicity reference value (TRV). Sensitivity analyses were performed for 6 avian and mammalian model species, and 16 metals/metalloids for which Eco-SSLs have been developed. The relative influence of model parameters was expressed as the absolute value of the range of variation observed in the resulting soil concentration when exposure is equal to the TRV. Rank analysis of variance was used to identify parameters with greatest influence on model output. For both birds and mammals, soil ingestion displayed the broadest overall range (variability), although TRVs consistently had the greatest influence on calculated soil concentrations; bioavailability in food was consistently the least influential parameter, although an important site-specific variable. Relative importance of parameters differed by trophic group. Soil ingestion ranked 2nd for carnivores and herbivores, but was 4th for invertivores. Different patterns were exhibited, depending on which parameter, trophic group, and analyte combination was considered. The approach for TRV selection was also examined in detail, with Cu as the representative analyte. The underlying assumption that generic body-weight-normalized TRVs can be used to derive protective levels for any species is not supported by the data. Whereas the use of site-, species-, and analyte-specific exposure parameters is recommended to reduce variation in exposure estimates (soil protection level), improvement of TRVs is more problematic. © 2014 The Authors. Environmental Toxicology and Chemistry Published by Wiley Periodicals, Inc.

Sensitivity of ecological soil-screening levels for metals to exposure model parameterization and toxicity reference values

PubMed Central

Sample, Bradley E; Fairbrother, Anne; Kaiser, Ashley; Law, Sheryl; Adams, Bill

2014-01-01

Ecological soil-screening levels (Eco-SSLs) were developed by the United States Environmental Protection Agency (USEPA) for the purposes of setting conservative soil screening values that can be used to eliminate the need for further ecological assessment for specific analytes at a given site. Ecological soil-screening levels for wildlife represent a simplified dietary exposure model solved in terms of soil concentrations to produce exposure equal to a no-observed-adverse-effect toxicity reference value (TRV). Sensitivity analyses were performed for 6 avian and mammalian model species, and 16 metals/metalloids for which Eco-SSLs have been developed. The relative influence of model parameters was expressed as the absolute value of the range of variation observed in the resulting soil concentration when exposure is equal to the TRV. Rank analysis of variance was used to identify parameters with greatest influence on model output. For both birds and mammals, soil ingestion displayed the broadest overall range (variability), although TRVs consistently had the greatest influence on calculated soil concentrations; bioavailability in food was consistently the least influential parameter, although an important site-specific variable. Relative importance of parameters differed by trophic group. Soil ingestion ranked 2nd for carnivores and herbivores, but was 4th for invertivores. Different patterns were exhibited, depending on which parameter, trophic group, and analyte combination was considered. The approach for TRV selection was also examined in detail, with Cu as the representative analyte. The underlying assumption that generic body-weight–normalized TRVs can be used to derive protective levels for any species is not supported by the data. Whereas the use of site-, species-, and analyte-specific exposure parameters is recommended to reduce variation in exposure estimates (soil protection level), improvement of TRVs is more problematic. Environ Toxicol Chem 2014;33:2386–2398. PMID:24944000

On the assimilation of satellite derived soil moisture in numerical weather prediction models

NASA Astrophysics Data System (ADS)

Drusch, M.

2006-12-01

Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

Prediction of the wetting-induced collapse behaviour using the soil-water characteristic curve

NASA Astrophysics Data System (ADS)

Xie, Wan-Li; Li, Ping; Vanapalli, Sai K.; Wang, Jia-Ding

2018-01-01

Collapsible soils go through three distinct phases in response to matric suction decrease during wetting: pre-collapse phase, collapse phase and post-collapse phase. It is reasonable and conservative to consider a strain path that includes a pre-collapse phase in which constant volume is maintained and a collapse phase that extends to the final matric suction to be experienced by collapsible soils during wetting. Upon this assumption, a method is proposed for predicting the collapse behaviour due to wetting. To use the proposed method, two parameters, critical suction and collapse rate, are required. The former is the suction value below which significant collapse deformations take place in response to matric suction decease, and the later is the rate at which void ratio reduces with matric suction in the collapse phase. The value of critical suction can be estimated from the water-entry value taking account of both the microstructure characteristics and collapse mechanism of fine-grained collapsible soils; the wetting soil-water characteristic curve thus can be used as a tool. Five sets of data of wetting tests on both compacted and natural collapsible soils reported in the literature were used to validate the proposed method. The critical suction values were estimated from the water-entry value with parameter a that is suggested to vary between 0.10 and 0.25 for compacted soils and to be lower for natural collapsible soils. The results of a field permeation test in collapsible loess soils were also used to validate the proposed method. The relatively good agreement between the measured and estimated collapse deformations suggests that the proposed method can provide reasonable prediction of the collapse behaviour due to wetting.

Soil- and crop-dependent variation in correlation lag between precipitation and agricultural drought indices as predicted by the SWAP model

NASA Astrophysics Data System (ADS)

Wright, Azin; Cloke, Hannah; Verhoef, Anne

2017-04-01

Droughts have a devastating impact on agriculture and economy. The risk of more frequent and more severe droughts is increasing due to global warming and certain anthropogenic activities. At the same time, the global population continues to rise and the need for sustainable food production is becoming more and more pressing. In light of this, drought prediction can be of great value; in the context of early warning, preparedness and mitigation of drought impacts. Prediction of meteorological drought is associated with uncertainties around precipitation variability. As meteorological drought propagates, it can transform into agricultural drought. Determination of the maximum correlation lag between precipitation and agricultural drought indices can be useful for prediction of agricultural drought. However, the influence of soil and crop type on the lag needs to be considered, which we explored using a 1-D Soil-Vegetation-Atmosphere-Transfer model (SWAP (http://www.swap.alterra.nl/), with the following configurations, all forced with ERA-Interim weather data (1979 to 2014): i) different crop types in the UK; ii) three generic soil types (clay, loam and sand) were considered. A Sobol sensitivity analysis was carried out (perturbing the SWAP model van Genuchten soil hydraulic parameters) to study the effect of soil type uncertainty on the water balance variables. Based on the sensitivity analysis results, a few variations of each soil type were selected. Agricultural drought indices including Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) were calculated. The maximum correlation lag between precipitation and these drought indices was calculated, and analysed in the context of crop and soil model parameters. The findings of this research can be useful to UK farming, by guiding government bodies such as the Environment Agency when issuing drought warnings and implementing drought measures.

Uncertainty in dual permeability model parameters for structured soils.

PubMed

Arora, B; Mohanty, B P; McGuire, J T

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface ( K sa ) and macropore tortuosity ( l f ) but also of other parameters of the matrix and macropore domains.

Uncertainty in dual permeability model parameters for structured soils

NASA Astrophysics Data System (ADS)

Arora, B.; Mohanty, B. P.; McGuire, J. T.

2012-01-01

Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.

Ethnopedology and soil quality of bamboo (Bambusa sp.) based agroforestry system.

PubMed

Arun Jyoti, Nath; Lal, Rattan; Das, Ashesh Kumar

2015-07-15

It is widely recognized that farmers' hold important knowledge of folk soil classification for agricultural land for its uses, yet little has been studied for traditional agroforestry systems. This article explores the ethnopedology of bamboo (Bambusa sp.) based agroforestry system in North East India, and establishes the relationship of soil quality index (SQI) with bamboo productivity. The study revealed four basic folk soil (mati) types: kalo (black soil), lal (red soil), pathal (stony soil) and balu (sandy soil). Of these, lal mati soil was the most predominant soil type (~ 40%) in bamboo-based agroforestry system. Soil physio-chemical parameters were studied to validate the farmers' soil hierarchal classification and also to correlate with productivity of the bamboo stand. Farmers' hierarchal folk soil classification was consistent with the laboratory scientific analysis. Culm production (i.e. measure of productivity of bamboo) was the highest (27culmsclump(-1)) in kalo mati (black soil) and the lowest (19culmsclump(-1)) in balu mati (sandy soil). Linear correlation of individual soil quality parameter with bamboo productivity explained 16 to 49% of the variability. A multiple correlation of the best fitted linear soil quality parameter (soil organic carbon or SOC, water holding capacity or WHC, total nitrogen) with productivity improved explanatory power to 53%. Development of SQI from ten relevant soil quality parameters and its correlation with bamboo productivity explained the 64% of the variation and therefore, suggest SQI as the best determinant of bamboo yield. Data presented indicate that the kalo mati (black soil) is sustainable or sustainable with high input. However, the other three folk soil types (red, stony and sandy soil) are also sustainable but for other land uses. Therefore, ethnopedological studies may move beyond routine laboratory analysis and incorporate SQI for assessing the sustainability of land uses managed by the farmers'. Additional research is required to incorporate principal component analysis for improving the SQI and site potential assessment. It is also important to evaluate the minimum data set (MDS) required for SQI and productivity assessment in agroforestry systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Cultural Patterns of Soil Understanding

NASA Astrophysics Data System (ADS)

Patzel, Nikola; Feller, Christian

2017-04-01

Living soil supports all terrestrial ecosystems. The only global threat to earth's soils comes from human societies' land use and resource consuming activities. Soil perception and understanding by soil scientists are mainly drawn from biophysical parameters and found within Cartesian rationality, and not, or much less consciously from its rather intangible cultural dimension. But nevertheless, human soil perception, soil awareness, and soil relation are a cultural phenomenon, too. Aiming at soil awareness and education, it is of first order importance for the soil science community and the IUSS to study, discuss and communicate also about the cultural perceptions and representations of soil. For any society, cultural patterns in their relation to soil encompass: (i) General culturally underlying structures like (religious or 'secular') myths and belief systems. (ii) The personal, individual relation to/with and behaviour towards soil. This includes implicit concepts of soil being part integral concepts of landscape because the large majority of humans don't see soil as a distinct object. This communication would be to make evident: (i) the importance of cultural patterns and psychic/psychological background concerning soil, by case studies and overviews on different cultural areas, (ii) the necessity to develop reflections on this topic as well to communicate about soil with large public, as to raise awareness soil scientists to the cultural dimension of soils. A working group was recently founded at IUSS (Division 4) on this topic.

Microbial functional diversity and enzymatic activity of soil degraded by sulphur mining reclaimed with various waste

NASA Astrophysics Data System (ADS)

Joniec, Jolanta; Frąc, Magdalena

2017-10-01

The aim of the study was to evaluate microbial functional diversity based on community level physiological profiling and β-glucosidase activity changes in soil degraded by sulphur mining and subjected to reclamation with various waste. The experiment was set up in the area of the former `Jeziórko' Sulphur Mine (Poland), on a soilless substrate with a particle size distribution of slightly loamy sand. The experimental variants included the application of post-flotation lime, sewage sludge and mineral wool. The analyses of soil samples included the assessment of the following microbiological indices: β-glucosidase activity and functional diversity average well color development and richness). The results indicate that sewage sludge did not exert a significant impact on the functional diversity of microorganisms present in the reclaimed soil. In turn, the application of other types of waste contributed to a significant increase in the parameters of total metabolic activity and functional diversity of the reclaimed soil. However, the temporal analysis of the metabolic profile of soil microorganisms demonstrated that a single application of waste did not yield a durable, stable metabolic profile in the reclaimed soil. Still, there was an increase in β-glucosidase activity, especially in objects treated with sewage sludge.

Evaluation of GIS Technology in Assessing and Modeling Land Management Practices

NASA Technical Reports Server (NTRS)

Archer, F.; Coleman, T. L.; Manu, A.; Tadesse, W.; Liu, G.

1997-01-01

There is an increasing concern of land owners to protect and maintain healthy and sustainable agroecosystems through the implementation of best management practices (BMP). The objectives of this study were: (1) To develop and evaluate the use of a Geographic Information System (GIS) technology for enhancing field-scale management practices; (2) evaluate the use of 2-dimensional displays of the landscape and (3) define spatial classes of variables from interpretation of geostatistical parameters. Soil samples were collected to a depth of 2 m at 15 cm increments. Existing data from topographic, land use, and soil survey maps of the Winfred Thomas Agricultural Research Station were converted to digital format. Additional soils data which included texture, pH, and organic matter were also generated. The digitized parameters were used to create a multilayered field-scale GIS. Two dimensional (2-D) displays of the parameters were generated using the ARC/INFO software. The spatial distribution of the parameters evaluated in both fields were similar which could be attributed to the similarity in vegetation and surface elevation. The ratio of the nugget to total semivariance, expressed as a percentage, was used to assess the degree of spatial variability. The results indicated that most of the parameters were moderate spatially dependent Biophysical constraint maps were generated from the database layers, and used in multiple combination to visualize results of the BMP. Understanding the spatial relationships of physical and chemical parameters that exists within a field should enable land managers to more effectively implement BMP to ensure a safe and sustainable environment.

Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

NASA Astrophysics Data System (ADS)

Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

2014-10-01

Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

Modelling the effect of soil moisture and organic matter degradation on biogenic NO emissions from soils in Sahel rangeland (Mali)

NASA Astrophysics Data System (ADS)

Delon, C.; Mougin, E.; Serça, D.; Grippa, M.; Hiernaux, P.; Diawara, M.; Galy-Lacaux, C.; Kergoat, L.

2014-08-01

This work is an attempt to provide seasonal variation of biogenic NO emission fluxes in a sahelian rangeland in Mali (Agoufou, 15.34° N, 1.48° W) for years 2004, 2005, 2006, 2007 and 2008. Indeed, NO is one of the most important precursor for tropospheric ozone, and the contribution of the Sahel region in emitting NO is no more considered as negligible. The link between NO production in the soil and NO release to the atmosphere is investigated in this study, by taking into account vegetation litter production and degradation, microbial processes in the soil, emission fluxes, and environmental variables influencing these processes, using a coupled vegetation-litter decomposition-emission model. This model includes the Sahelian-Transpiration-Evaporation-Productivity (STEP) model for the simulation of herbaceous, tree leaf and fecal masses, the GENDEC model (GENeral DEComposition) for the simulation of the buried litter decomposition, and the NO emission model for the simulation of the NO flux to the atmosphere. Physical parameters (soil moisture and temperature, wind speed, sand percentage) which affect substrate diffusion and oxygen supply in the soil and influence the microbial activity, and biogeochemical parameters (pH and fertilization rate related to N content) are necessary to simulate the NO flux. The reliability of the simulated parameters is checked, in order to assess the robustness of the simulated NO flux. Simulated yearly average of NO flux ranges from 0.69 to 1.09 kg(N) ha-1 yr-1, and wet season average ranges from 1.16 to 2.08 kg(N) ha-1 yr-1. These results are in the same order as previous measurements made in several sites where the vegetation and the soil are comparable to the ones in Agoufou. This coupled vegetation-litter decomposition-emission model could be generalized at the scale of the Sahel region, and provide information where little data is available.

Modelling the effect of soil moisture and organic matter degradation on biogenic NO emissions from soils in Sahel rangeland (Mali)

NASA Astrophysics Data System (ADS)

Delon, C.; Mougin, E.; Serça, D.; Grippa, M.; Hiernaux, P.; Diawara, M.; Galy-Lacaux, C.; Kergoat, L.

2015-01-01

This work is an attempt to provide seasonal variation of biogenic NO emission fluxes in a sahelian rangeland in Mali (Agoufou, 15.34° N, 1.48° W) for years 2004-2008. Indeed, NO is one of the most important precursor for tropospheric ozone, and the contribution of the Sahel region in emitting NO is no more considered as negligible. The link between NO production in the soil and NO release to the atmosphere is investigated in this study, by taking into account vegetation litter production and degradation, microbial processes in the soil, emission fluxes, and environmental variables influencing these processes, using a coupled vegetation-litter decomposition-emission model. This model includes the Sahelian-Transpiration-Evaporation-Productivity (STEP) model for the simulation of herbaceous, tree leaf and fecal masses, the GENDEC model (GENeral DEComposition) for the simulation of the buried litter decomposition and microbial dynamics, and the NO emission model (NOFlux) for the simulation of the NO release to the atmosphere. Physical parameters (soil moisture and temperature, wind speed, sand percentage) which affect substrate diffusion and oxygen supply in the soil and influence the microbial activity, and biogeochemical parameters (pH and fertilization rate related to N content) are necessary to simulate the NO flux. The reliability of the simulated parameters is checked, in order to assess the robustness of the simulated NO flux. Simulated yearly average of NO flux ranges from 0.66 to 0.96 kg(N) ha-1 yr-1, and wet season average ranges from 1.06 to 1.73 kg(N) ha-1 yr-1. These results are in the same order as previous measurements made in several sites where the vegetation and the soil are comparable to the ones in Agoufou. This coupled vegetation-litter decomposition-emission model could be generalized at the scale of the Sahel region, and provide information where little data is available.

Treatment of Explosives Residues From Range Activities

DTIC Science & Technology

2010-01-01

plus 5 kg crude soybean oil), while three plots served as controls and received no PMSO (designated CON ). PMSO was prepared by thoroughly mixing...compounds. The topmost layers of soil in the CON plots were removed in 1.25 cm lifts. The PMSO in the PO1 and PO2 plots was collected in two portions...soil plots ( CON -2) was not behaving the same as the other two control plots based on a careful assessment of several parameters, including higher

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Karssenberg, D.; Wanders, N.; de Roo, A.; de Jong, S.; Bierkens, M. F.

2013-12-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system that is not directly linked to discharge, in particular the unsaturated zone, remains uncalibrated, or might be modified unrealistically. Soil moisture observations from satellites have the potential to fill this gap, as these provide the closest thing to a direct measurement of the state of the unsaturated zone, and thus are potentially useful in calibrating unsaturated zone model parameters. This is expected to result in a better identification of the complete hydrological system, potentially leading to improved forecasts of the hydrograph as well. Here we evaluate this added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: 1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? 2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to approaches that calibrate only with discharge, such that this leads to improved forecasts of soil moisture content and discharge as well? To answer these questions we use a dual state and parameter ensemble Kalman filter to calibrate the hydrological model LISFLOOD for the Upper Danube area. Calibration is done with discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS and ASCAT. Four scenarios are studied: no calibration (expert knowledge), calibration on discharge, calibration on remote sensing data (three satellites) and calibration on both discharge and remote sensing data. Using a split-sample approach, the model is calibrated for a period of 2 years and validated for the calibrated model parameters on a validation period of 10 years. Results show that calibration with discharge data improves the estimation of groundwater parameters (e.g., groundwater reservoir constant) and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate calibration of parameters related to land surface process (e.g., the saturated conductivity of the soil), which is not possible when calibrating on discharge alone. For the upstream area up to 40000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30 % in the RMSE for discharge simulations, compared to calibration on discharge alone. For discharge in the downstream area, the model performance due to assimilation of remotely sensed soil moisture is not increased or slightly decreased, most probably due to the longer relative importance of the routing and contribution of groundwater in downstream areas. When microwave soil moisture is used for calibration the RMSE of soil moisture simulations decreases from 0.072 m3m-3 to 0.062 m3m-3. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models leading to a better simulation of soil moisture content throughout and a better simulation of discharge in upstream areas, particularly if discharge observations are sparse.

Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models

NASA Astrophysics Data System (ADS)

Brunner, Philip; Doherty, J.; Simmons, Craig T.

2012-07-01

The data set used for calibration of regional numerical models which simulate groundwater flow and vadose zone processes is often dominated by head observations. It is to be expected therefore, that parameters describing vadose zone processes are poorly constrained. A number of studies on small spatial scales explored how additional data types used in calibration constrain vadose zone parameters or reduce predictive uncertainty. However, available studies focused on subsets of observation types and did not jointly account for different measurement accuracies or different hydrologic conditions. In this study, parameter identifiability and predictive uncertainty are quantified in simulation of a 1-D vadose zone soil system driven by infiltration, evaporation and transpiration. The worth of different types of observation data (employed individually, in combination, and with different measurement accuracies) is evaluated by using a linear methodology and a nonlinear Pareto-based methodology under different hydrological conditions. Our main conclusions are (1) Linear analysis provides valuable information on comparative parameter and predictive uncertainty reduction accrued through acquisition of different data types. Its use can be supplemented by nonlinear methods. (2) Measurements of water table elevation can support future water table predictions, even if such measurements inform the individual parameters of vadose zone models to only a small degree. (3) The benefits of including ET and soil moisture observations in the calibration data set are heavily dependent on depth to groundwater. (4) Measurements of groundwater levels, measurements of vadose ET or soil moisture poorly constrain regional groundwater system forcing functions.

Assessing the fate of radioactive nickel in cultivated soil cores.

PubMed

Denys, Sébastien; Echevarria, Guillaume; Florentin, Louis; Leclerc, Elisabeth; Morel, Jean-Louis

2009-10-01

Parameters regarding fate of (63)Ni in the soil-plant system (soil: solution distribution coefficient, K(d) and soil plant concentration ratio, CR) are mostly determined in controlled pot experiments or from simple models involving a limited set of soil parameters. However, as migration of pollutants in soil is strongly linked to the water migration, variation of soil structure in the field and seasonal variation of evapotranspiration will affect these two parameters. The aim of this work was to explore to what extent the downward transfer of (63)Ni and its uptake by plants from surface-contaminated undisturbed soil cores under cultivation can be explained by isotopic dilution of this radionuclide in the pool of stable Ni of soils. Undisturbed soil cores (50 cm x 50 cm) were sampled from a brown rendzina (Rendzic Leptosol), a colluvial brown soil (Fluvic Cambisol) and an acidic brown soil (Dystric Cambisol) using PVC lysimeter tubes (three lysimeters sampled per soil type). Each core was equipped with a leachate collector. Cores were placed in a greenhouse and maize (DEA, Pioneer) was sown. After 44 days, an irrigation was simulated at the core surfaces to supply 10 000 Bq (63)NiCl(2). Maize was harvested 135 days after (63)Ni input and radioactivity determined in both vegetal and water samples. Effective uptake of (63)Ni by maize was calculated for leaves and kernels. Water drainage and leaching of (63)Ni were monitored over the course of the experiment. Values of K(d) in surface soil samples were calculated from measured parameters of isotopic exchange kinetics. Results confirmed that (63)Ni was strongly retained at the soil surface. Prediction of the (63)Ni downward transfer could not be reliably assessed using the K(d) values, since the soil structure, which controls local water fluxes, also affected both water and Ni transport. In terms of (63)Ni plant uptake, the effective uptake in undisturbed soil cores is controlled by isotope dilution as previously shown at the pot experiment scale.

Generic reactive transport codes as flexible tools to integrate soil organic matter degradation models with water, transport and geochemistry in soils

NASA Astrophysics Data System (ADS)

Jacques, Diederik; Gérard, Fréderic; Mayer, Uli; Simunek, Jirka; Leterme, Bertrand

2016-04-01

A large number of organic matter degradation, CO2 transport and dissolved organic matter models have been developed during the last decades. However, organic matter degradation models are in many cases strictly hard-coded in terms of organic pools, degradation kinetics and dependency on environmental variables. The scientific input of the model user is typically limited to the adjustment of input parameters. In addition, the coupling with geochemical soil processes including aqueous speciation, pH-dependent sorption and colloid-facilitated transport are not incorporated in many of these models, strongly limiting the scope of their application. Furthermore, the most comprehensive organic matter degradation models are combined with simplified representations of flow and transport processes in the soil system. We illustrate the capability of generic reactive transport codes to overcome these shortcomings. The formulations of reactive transport codes include a physics-based continuum representation of flow and transport processes, while biogeochemical reactions can be described as equilibrium processes constrained by thermodynamic principles and/or kinetic reaction networks. The flexibility of these type of codes allows for straight-forward extension of reaction networks, permits the inclusion of new model components (e.g.: organic matter pools, rate equations, parameter dependency on environmental conditions) and in such a way facilitates an application-tailored implementation of organic matter degradation models and related processes. A numerical benchmark involving two reactive transport codes (HPx and MIN3P) demonstrates how the process-based simulation of transient variably saturated water flow (Richards equation), solute transport (advection-dispersion equation), heat transfer and diffusion in the gas phase can be combined with a flexible implementation of a soil organic matter degradation model. The benchmark includes the production of leachable organic matter and inorganic carbon in the aqueous and gaseous phases, as well as different decomposition functions with first-order, linear dependence or nonlinear dependence on a biomass pool. In addition, we show how processes such as local bioturbation (bio-diffusion) can be included implicitly through a Fickian formulation of transport of soil organic matter. Coupling soil organic matter models with generic and flexible reactive transport codes offers a valuable tool to enhance insights into coupled physico-chemical processes at different scales within the scope of C-biogeochemical cycles, possibly linked with other chemical elements such as plant nutrients and pollutants.

Can Physiological Endpoints Improve the Sensitivity of Assays with Plants in the Risk Assessment of Contaminated Soils?

PubMed Central

Gavina, Ana; Antunes, Sara C.; Pinto, Glória; Claro, Maria Teresa; Santos, Conceição; Gonçalves, Fernando; Pereira, Ruth

2013-01-01

Site-specific risk assessment of contaminated areas indicates prior areas for intervention, and provides helpful information for risk managers. This study was conducted in the Ervedosa mine area (Bragança, Portugal), where both underground and open pit exploration of tin and arsenic minerals were performed for about one century (1857 – 1969). We aimed at obtaining ecotoxicological information with terrestrial and aquatic plant species to integrate in the risk assessment of this mine area. Further we also intended to evaluate if the assessment of other parameters, in standard assays with terrestrial plants, can improve the identification of phytotoxic soils. For this purpose, soil samples were collected on 16 sampling sites distributed along four transects, defined within the mine area, and in one reference site. General soil physical and chemical parameters, total and extractable metal contents were analyzed. Assays were performed for soil elutriates and for the whole soil matrix following standard guidelines for growth inhibition assay with Lemna minor and emergence and seedling growth assay with Zea mays. At the end of the Z. mays assay, relative water content, membrane permeability, leaf area, content of photosynthetic pigments (chlorophylls and carotenoids), malondialdehyde levels, proline content, and chlorophyll fluorescence (Fv/Fm and ΦPSII) parameters were evaluated. In general, the soils near the exploration area revealed high levels of Al, Mn, Fe and Cu. Almost all the soils from transepts C, D and F presented total concentrations of arsenic well above soils screening benchmark values available. Elutriates of several soils from sampling sites near the exploration and ore treatment areas were toxic to L. minor, suggesting that the retention function of these soils was seriously compromised. In Z. mays assay, plant performance parameters (other than those recommended by standard protocols), allowed the identification of more phytotoxic soils. The results suggest that these parameters could improve the sensitivity of the standard assays. PMID:23565165

Iron Compounds and the Color of Soils in the Sakhalin Island

NASA Astrophysics Data System (ADS)

Vodyanitskii, Yu. N.; Kirillova, N. P.; Manakhov, D. V.; Karpukhin, M. M.

2018-02-01

Numerical parameters of soil color were studied according to the CIE-L*a*b color system before and after the Tamm's and Mehra-Jackson's treatments; we also determined the total Fe content in the samples from the main genetic horizons of the alluvial gray-humus soil, two profiles of burozems, and two profiles of podzols in the Sakhalin Island. In the analyzed samples, the numerical color parameters L* (lightness), a* (redness) and b* (yellowness) are found to vary within 46-73, 3-11, and 8-28, respectively. A linear relationship is revealed between the numerical values of a* parameters and Fe content in the Mehra-Jackson extracts; the regression equations are derived with the determination coefficients ( R 2): 0.49 (typical burozem), 0.79 (podzolized burozem), 0.96 (shallow-podzolic mucky podzol), 0.98 (gray-humus gley alluvial soil). For the surface-podzolic mucky podzol contaminated with petroleum hydrocarbons, R 2 was equal to only 0.03. In the gray humus (AY) and structural-metamorphic (BM) horizons of the studied soils, a* and b* parameters decrease after their treatment with the Tamm's reagent by 2 points on average. After the Mehra-Jackson treatment, the a* parameter decreased by 6 (AY) and 8 (BM) points; whereas b* parameter, by 10 and 15 points, respectively. In the E horizons of podzols, the Tamm's treatment increased a* and b* parameters by 1 point; whereas the Mehra-Jackson's treatment decreased these parameters by only 1 and 3 points, respectively. The redness (a*) decreased maximally in the lower gley horizon of the alluvial gray humus soil, i.e., by 6 (in the Tamm's extract) and 10 points (in the Mehra-Jackson's) extract. Yellowness (b*) decreased by 12 and 17 points, respectively. The revealed color specifics in the untreated samples and the color transformation under the impact of reagents in the studied soils and horizons may serve as an additional parameter that characterizes quantitatively the object of investigation in the reference databases.

Simultaneous Assimilation of AMSR-E Brightness Temperature and MODIS LST to Improve Soil Moisture with Dual Ensemble Kalman Smoother

NASA Astrophysics Data System (ADS)

Huang, Chunlin; Chen, Weijin; Wang, Weizhen; Gu, Juan

2017-04-01

Uncertainties in model parameters can easily cause systematic differences between model states and observations from ground or satellites, which significantly affect the accuracy of soil moisture estimation in data assimilation systems. In this paper, a novel soil moisture assimilation scheme is developed to simultaneously assimilate AMSR-E brightness temperature (TB) and MODIS Land Surface Temperature (LST), which can correct model bias by simultaneously updating model states and parameters with dual ensemble Kalman filter (DEnKS). The Common Land Model (CoLM) and a Q-h Radiative Transfer Model (RTM) are adopted as model operator and observation operator, respectively. The assimilation experiment is conducted in Naqu, Tibet Plateau, from May 31 to September 27, 2011. Compared with in-situ measurements, the accuracy of soil moisture estimation is tremendously improved in terms of a variety of scales. The updated soil temperature by assimilating MODIS LST as input of RTM can reduce the differences between the simulated and observed brightness temperatures to a certain degree, which helps to improve the estimation of soil moisture and model parameters. The updated parameters show large discrepancy with the default ones and the former effectively reduces the states bias of CoLM. Results demonstrate the potential of assimilating both microwave TB and MODIS LST to improve the estimation of soil moisture and related parameters. Furthermore, this study also indicates that the developed scheme is an effective soil moisture downscaling approach for coarse-scale microwave TB.

Soil erosion model predictions using parent material/soil texture-based parameters compared to using site-specific parameters

Treesearch

R. B. Foltz; W. J. Elliot; N. S. Wagenbrenner

2011-01-01

Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent...

Critical state of sand matrix soils.

PubMed

Marto, Aminaton; Tan, Choy Soon; Makhtar, Ahmad Mahir; Kung Leong, Tiong

2014-01-01

The Critical State Soil Mechanic (CSSM) is a globally recognised framework while the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking. This paper discusses the development of critical state lines and corresponding critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper can be used as an interpretation framework for the research on liquefaction susceptibility of sand matrix soils in the future. The strain controlled triaxial test apparatus was used to provide the monotonic loading onto the reconstituted soil specimens. All tested soils were subjected to isotropic consolidation and sheared under undrained condition until critical state was ascertain. Based on the results of 32 test specimens, the critical state lines for eight different sand matrix soils were developed together with the corresponding values of critical state parameters, M, λ, and Γ. The range of the value of M, λ, and Γ is 0.803-0.998, 0.144-0.248, and 1.727-2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay. However, the relationship between fines percentages and these critical state parameters is too scattered to be correlated.

Critical State of Sand Matrix Soils

PubMed Central

Marto, Aminaton; Tan, Choy Soon; Makhtar, Ahmad Mahir; Kung Leong, Tiong

2014-01-01

The Critical State Soil Mechanic (CSSM) is a globally recognised framework while the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking. This paper discusses the development of critical state lines and corresponding critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper can be used as an interpretation framework for the research on liquefaction susceptibility of sand matrix soils in the future. The strain controlled triaxial test apparatus was used to provide the monotonic loading onto the reconstituted soil specimens. All tested soils were subjected to isotropic consolidation and sheared under undrained condition until critical state was ascertain. Based on the results of 32 test specimens, the critical state lines for eight different sand matrix soils were developed together with the corresponding values of critical state parameters, M, λ, and Γ. The range of the value of M, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay. However, the relationship between fines percentages and these critical state parameters is too scattered to be correlated. PMID:24757417

Predicted Infiltration for Sodic/Saline Soils from Reclaimed Coastal Areas: Sensitivity to Model Parameters

PubMed Central

She, Dongli; Yu, Shuang'en; Shao, Guangcheng

2014-01-01

This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ 0 was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils. PMID:25197699

Predicted infiltration for sodic/saline soils from reclaimed coastal areas: sensitivity to model parameters.

PubMed

Liu, Dongdong; She, Dongli; Yu, Shuang'en; Shao, Guangcheng; Chen, Dan

2014-01-01

This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm(3). A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ₀ was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.

Using satellite image data to estimate soil moisture

NASA Astrophysics Data System (ADS)

Chuang, Chi-Hung; Yu, Hwa-Lung

2017-04-01

Soil moisture is considered as an important parameter in various study fields, such as hydrology, phenology, and agriculture. In hydrology, soil moisture is an significant parameter to decide how much rainfall that will infiltrate into permeable layer and become groundwater resource. Although soil moisture is a critical role in many environmental studies, so far the measurement of soil moisture is using ground instrument such as electromagnetic soil moisture sensor. Use of ground instrumentation can directly obtain the information, but the instrument needs maintenance and consume manpower to operation. If we need wide range region information, ground instrumentation probably is not suitable. To measure wide region soil moisture information, we need other method to achieve this purpose. Satellite remote sensing techniques can obtain satellite image on Earth, this can be a way to solve the spatial restriction on instrument measurement. In this study, we used MODIS data to retrieve daily soil moisture pattern estimation, i.e., crop water stress index (cwsi), over the year of 2015. The estimations are compared with the observations at the soil moisture stations from Taiwan Bureau of soil and water conservation. Results show that the satellite remote sensing data can be helpful to the soil moisture estimation. Further analysis can be required to obtain the optimal parameters for soil moisture estimation in Taiwan.

Stochastic analysis of uncertain thermal parameters for random thermal regime of frozen soil around a single freezing pipe

NASA Astrophysics Data System (ADS)

Wang, Tao; Zhou, Guoqing; Wang, Jianzhou; Zhou, Lei

2018-03-01

The artificial ground freezing method (AGF) is widely used in civil and mining engineering, and the thermal regime of frozen soil around the freezing pipe affects the safety of design and construction. The thermal parameters can be truly random due to heterogeneity of the soil properties, which lead to the randomness of thermal regime of frozen soil around the freezing pipe. The purpose of this paper is to study the one-dimensional (1D) random thermal regime problem on the basis of a stochastic analysis model and the Monte Carlo (MC) method. Considering the uncertain thermal parameters of frozen soil as random variables, stochastic processes and random fields, the corresponding stochastic thermal regime of frozen soil around a single freezing pipe are obtained and analyzed. Taking the variability of each stochastic parameter into account individually, the influences of each stochastic thermal parameter on stochastic thermal regime are investigated. The results show that the mean temperatures of frozen soil around the single freezing pipe with three analogy method are the same while the standard deviations are different. The distributions of standard deviation have a great difference at different radial coordinate location and the larger standard deviations are mainly at the phase change area. The computed data with random variable method and stochastic process method have a great difference from the measured data while the computed data with random field method well agree with the measured data. Each uncertain thermal parameter has a different effect on the standard deviation of frozen soil temperature around the single freezing pipe. These results can provide a theoretical basis for the design and construction of AGF.

Effects of heavy metal contamination of soils on micronucleus induction in Tradescantia and on microbial enzyme activities: a comparative investigation.

PubMed

Majer, Bernhard J; Tscherko, Dagmar; Paschke, Albrecht; Wennrich, Rainer; Kundi, Michael; Kandeler, Ellen; Knasmüller, Siegfried

2002-03-25

The aim of this study was to investigate correlation between genotoxic effects and changes of microbial parameters caused by metal contamination in soils. In total, 20 soils from nine locations were examined; metal contents and physicochemical soil parameters were measured with standard methods. In general, a pronounced induction of the frequency of micronuclei (MN) in the Tradescantia micronucleus (Trad-MN) assay was seen with increasing metal concentration in soils from identical locations. However, no correlations were found between metal contents and genotoxicity of soils from different locations. These discrepancies are probably due to differences of the physicochemical characteristics of the samples. Also, the microbial parameters depended on the metal content in soils from identical sampling locations. Inconsistent responses of the individual enzymes were seen in soils from different locations, indicating that it is not possible to define a specific marker enzyme for metal contamination. The most sensitive microbial parameters were dehydrogenase and arylsulfatase activity, biomass C, and biomass N. Statistical analyses showed an overall correlation between genotoxicity in Tradescantia on the one hand and dehydrogenase activity, biomass C, and the metabolic quotient on the other hand. In conclusion, the results of the present study show that the Trad-MN assay is suitable for the detection of genotoxic effects of metal contamination in soils and furthermore, that the DNA-damaging potential of soils from different origin cannot be predicted on the basis of chemical analyses of their metal concentrations.

DOE-EPSCOR SPONSORED PROJECT FINAL REPORT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Jianting

Concern over the quality of environmental management and restoration has motivated the model development for predicting water and solute transport in the vadose zone. Soil hydraulic properties are required inputs to subsurface models of water flow and contaminant transport in the vadose zone. Computer models are now routinely used in research and management to predict the movement of water and solutes into and through the vadose zone of soils. Such models can be used successfully only if reliable estimates of the soil hydraulic parameters are available. The hydraulic parameters considered in this project consist of the saturated hydraulic conductivity andmore » four parameters of the water retention curves. To quantify hydraulic parameters for heterogeneous soils is both difficult and time consuming. The overall objective of this project was to better quantify soil hydraulic parameters which are critical in predicting water flows and contaminant transport in the vadose zone through a comprehensive and quantitative study to predict heterogeneous soil hydraulic properties and the associated uncertainties. Systematic and quantitative consideration of the parametric heterogeneity and uncertainty can properly address and further reduce predictive uncertainty for contamination characterization and environmental restoration at DOE-managed sites. We conducted a comprehensive study to assess soil hydraulic parameter heterogeneity and uncertainty. We have addressed a number of important issues related to the soil hydraulic property characterizations. The main focus centered on new methods to characterize anisotropy of unsaturated hydraulic property typical of layered soil formations, uncertainty updating method, and artificial neural network base pedo-transfer functions to predict hydraulic parameters from easily available data. The work also involved upscaling of hydraulic properties applicable to large scale flow and contaminant transport modeling in the vadose zone and geostatistical characterization of hydraulic parameter heterogeneity. The project also examined the validity of the some simple average schemes for unsaturated hydraulic properties widely used in previous studies. A new suite of pedo-transfer functions were developed to improve the predictability of hydraulic parameters. We also explored the concept of tension-dependent hydraulic conductivity anisotropy of unsaturated layered soils. This project strengthens collaboration between researchers at the Desert Research Institute in the EPSCoR State of Nevada and their colleagues at the Pacific Northwest National Laboratory. The results of numerical simulations of a field injection experiment at Hanford site in this project could be used to provide insights to the DOE mission of appropriate contamination characterization and environmental remediation.« less

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Garcia, Matthew E.; Mocko, David M.; Tischler, Michael A.; Moran, M. Susan; Thoma, D. P.

2007-01-01

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Detection of Soil Nitrogen Using Near Infrared Sensors Based on Soil Pretreatment and Algorithms

PubMed Central

Nie, Pengcheng; Dong, Tao; He, Yong; Qu, Fangfang

2017-01-01

Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly by using a near-infrared sensor. The data can be analyzed in the detection process, which is nondestructive and non-polluting. In order to investigate the effect of soil pretreatment on nitrogen content by near infrared sensor, 16 nitrogen concentrations were mixed with soil and the soil samples were divided into three groups with different pretreatment. The first group of soil samples with strict pretreatment were dried, ground, sieved and pressed. The second group of soil samples were dried and ground. The third group of soil samples were simply dried. Three linear different modeling methods are used to analyze the spectrum, including partial least squares (PLS), uninformative variable elimination (UVE), competitive adaptive reweighted algorithm (CARS). The model of nonlinear partial least squares which supports vector machine (LS-SVM) is also used to analyze the soil reflectance spectrum. The results show that the soil samples with strict pretreatment have the best accuracy in predicting nitrogen content by near-infrared sensor, and the pretreatment method is suitable for practical application. PMID:28492480

Assessing phytotoxicity of heavy metals in remediated soil.

PubMed

Branzini, A; Zubillaga, M S

2010-01-01

Copper (Cu), zinc (Zn) and chromium (Cr) are pollutants that usually are accumulated in soils. Their toxicity can be decreased by applying amendments. We proposed to evaluate changes in Cu, Zn, and Cr availability, due to the application of amendments, through chemical analysis and phytotoxicity tests. The phytotoxicity test was carried out using species belonging to Sesbania genus; plant parameters were measured 48, 72, 96, and 168 hours after the start of incubation. The treatments included enriched soil, in addition to biosolid compost and triple superphosphate. Cu and Zn amounts were higher in treatments without amendments, indicating immobilization on the part of these. The amounts of Cr tended to decrease with amendments application. The amendments increased pH values and decreased EC; however, this had no impact on the results. No relationship was found among pH, EC, and plant parameters. Different behaviors were observed. S. virgata showed germination seed delay. In addition, while in S. virgata the IG increased during the assay, in S. punicea it diminished. The application of compost, fertilizer or both combined could be of interest for contaminated soils remediation. The use of chemical analysis and phytotoxicity tests allowed to estimate heavy metal availability and the effect on both Sesbania species.

Impacts of LUCC on soil properties in the riparian zones of desert oasis with remote sensing data: a case study of the middle Heihe River basin, China.

PubMed

Jiang, Penghui; Cheng, Liang; Li, Manchun; Zhao, Ruifeng; Duan, Yuewei

2015-02-15

Large-scale changes in land use and land cover over long timescales can induce significant variations in soil physicochemical properties, particularly in the riparian zones of arid regions. Frequent reclamation of wetlands and grasslands and intensive agricultural activity have induced significant changes in both land use/cover and soil physicochemical properties in the riparian zones of the middle Heihe River basin of China. The present study aims to explore whether land use/land cover change (LUCC) can well explain the variations in soil properties in the riparian zones of the middle Heihe River basin. To achieve this, we mapped LUCC and quantified the type of land use change using remote sensing images, topographic maps, and GIS analysis techniques. Forty-two sites were selected for soil and vegetation sampling. Then, physical and chemical experiments were employed to determine soil moisture, soil bulk density, soil pH, soil organic carbon, total nitrogen, total potassium, total phosphorous, available nitrogen, available potassium, and available phosphorous. The Independent-Samples Kruskal-Wallis Test, principal component analysis, and a scatter matrix were used to analyze the effects of LUCC on soil properties. The results indicate that the majority of the parameters investigated were affected significantly by LUCC. In particular, soil moisture and soil organic carbon can be explained well by land cover change and land use change, respectively. Furthermore, changes in soil moisture could be attributed primarily to land cover changes. Changes in soil organic carbon were correlated closely with the following land use change types: wetlands-arable, forest-grasslands, and grasslands-desert. Other parameters, including pH and total K, were also found to exhibit significant correlations with LUCC. However, changes in soil nutrients were shown to be induced most probably by human agricultural activity (i.e. fertilize, irrigation, tillage, etc.), rather than by simple conversions from one land use/cover types to the others. Copyright © 2014 Elsevier B.V. All rights reserved.

EXPERIMENTAL EVALUATION OF GEOMETRICAL SHAPE FACTORS FOR SHORT CYLINDRICAL PROBES USED TO MEASURE SOIL PERMEABILITY TO AIR

EPA Science Inventory

Permeability of soil has become recognized as an important parameter in determining the rate of transport and entry of radon from the soil into indoor environments. This parameter is usually measured in the field by inserting a cylindrical tube with a short porous section into th...

Soil moisture retrieval by active/passive microwave remote sensing data

NASA Astrophysics Data System (ADS)

Wu, Shengli; Yang, Lijuan

2012-09-01

This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

Comparing simple and complex approaches to simulate the impacts of soil water repellency on runoff and erosion in burnt Mediterranean forest slopes

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Catarina Simões Vieira, Diana; Keizer, Jan Jacob

2017-04-01

Fires impact soil hydrological properties, enhancing soil water repellency and therefore increasing the potential for surface runoff generation and soil erosion. In consequence, the successful application of hydrological models to post-fire conditions requires the appropriate simulation of the effects of soil water repellency on soil hydrology. This work compared three approaches to model soil water repellency impacts on soil hydrology in burnt eucalypt and pine forest slopes in central Portugal: 1) Daily approach, simulating repellency as a function of soil moisture, and influencing the maximum soil available water holding capacity. It is based on the Thornthwaite-Mather soil water modelling approach, and is parameterized with the soil's wilting point and field capacity, and a parameter relating soil water repellency with water holding capacity. It was tested with soil moisture data from burnt and unburnt hillslopes. This approach was able to simulate post-fire soil moisture patterns, which the model without repellency was unable to do. However, model parameters were different between the burnt and unburnt slopes, indicating that more research is needed to derive standardized parameters from commonly measured soil and vegetation properties. 2) Seasonal approach, pre-determining repellency at the seasonal scale (3 months) in four classes (from none to extreme). It is based on the Morgan-Morgan-Finney (MMF) runoff and erosion model, applied at the seasonal scale and is parameterized with a parameter relating repellency class with field capacity. It was tested with runoff and erosion data from several experimental plots, and led to important improvements on runoff prediction over an approach with constant field capacity for all seasons (calibrated for repellency effects), but only slight improvements in erosion predictions. In contrast with the daily approach, the parameters could be reproduced between different sites 3) Constant approach, specifying values for soil water repellency for the three years after the fire, and keeping them constant throughout the year. It is based on a daily Curve Number (CN) approach, and was incorporated directly in the Soil and Water Assessment Tool (SWAT) model and tested with erosion data from a burnt hillslope. This approach was able to successfully reproduce soil erosion. The results indicate that simplified approaches can be used to adapt existing models for post-fire simulation, taking repellency into account. Taking into account the seasonality of repellency seems more important to simulate surface runoff than erosion, possibly since simulating the larger runoff rates correctly is sufficient for erosion simulation. The constant approach can be applied directly in the parameterization of existing runoff and erosion models for soil loss and sediment yield prediction, while the seasonal approach can readily be developed as a next step, with further work being needed to assess if the approach and associated parameters can be applied in multiple post-fire environments.

Sustainability of an in situ aided phytostabilisation on highly contaminated soils using fly ashes: Effects on the vertical distribution of physicochemical parameters and trace elements.

PubMed

Bidar, Géraldine; Waterlot, Christophe; Verdin, Anthony; Proix, Nicolas; Courcot, Dominique; Détriché, Sébastien; Fourrier, Hervé; Richard, Antoine; Douay, Francis

2016-04-15

Aided phytostabilisation using trees and fly ashes is a promising technique which has shown its effectiveness in the management of highly metal-contaminated soils. However, this success is generally established based on topsoil physicochemical analysis and short-term experiments. This paper focuses on the long-term effects of the afforestation and two fly ashes (silico-aluminous and sulfo-calcic called FA1 and FA2, respectively) by assessing the integrity of fly ashes 10 years after their incorporation into the soil as well as the vertical distribution of the physicochemical parameters and trace elements (TEs) in the amended soils (F1 and F2) in comparison with a non-amended soil (R). Ten years after the soil treatment, the particle size distribution analysis between fly ashes and their corresponding masses (fly ash + soil particles) showed a loss or an agglomeration of finer particles. This evolution matches with the appearance of gypsum (CaSO4 2H2O) in FA2m instead of anhydrite (CaSO4), which is the major compound of FA2. This finding corresponds well with the dissolution and the lixiviation of Ca, S and P included in FA2 along the F2 soil profile, generating an accumulation of these elements at 30 cm depth. However, no variation of TE contamination was found between 0 and 25 cm depth in F2 soil except for Cd. Conversely, Cd, Pb, Zn and Hg enrichment was observed at 25 cm depth in the F1 soil, whereas no enrichment was observed for As. The fly ashes studied, and notably FA2, were able to reduce Cd, Pb and Zn availability in soil and this capacity persists over the time despite their structural and chemical changes. Copyright © 2016 Elsevier Ltd. All rights reserved.

An evaluation of soil chemistry in human cadaver decomposition islands: Potential for estimating postmortem interval (PMI).

PubMed

Fancher, J P; Aitkenhead-Peterson, J A; Farris, T; Mix, K; Schwab, A P; Wescott, D J; Hamilton, M D

2017-10-01

Soil samples from the Forensic Anthropology Research Facility (FARF) at Texas State University, San Marcos, TX, were analyzed for multiple soil characteristics from cadaver decomposition islands to a depth of 5centimeters (cm) from 63 human decomposition sites, as well as depths up to 15cm in a subset of 11 of the cadaver decomposition islands plus control soils. Postmortem interval (PMI) of the cadaver decomposition islands ranged from 6 to 1752 days. Some soil chemistry, including nitrate-N (NO 3 -N), ammonium-N (NH 4 -N), and dissolved inorganic carbon (DIC), peaked at early PMI values and their concentrations at 0-5cm returned to near control values over time likely due to translocation down the soil profile. Other soil chemistry, including dissolved organic carbon (DOC), dissolved organic nitrogen (DON), orthophosphate-P (PO 4 -P), sodium (Na + ), and potassium (K + ), remained higher than the control soil up to a PMI of 1752days postmortem. The body mass index (BMI) of the cadaver appeared to have some effect on the cadaver decomposition island chemistry. To estimate PMI using soil chemistry, backward, stepwise multiple regression analysis was used with PMI as the dependent variable and soil chemistry, body mass index (BMI) and physical soil characteristics such as saturated hydraulic conductivity as independent variables. Measures of soil parameters derived from predator and microbial mediated decomposition of human remains shows promise in estimating PMI to within 365days for a period up to nearly five years. This persistent change in soil chemistry extends the ability to estimate PMI beyond the traditionally utilized methods of entomology and taphonomy in support of medical-legal investigations, humanitarian recovery efforts, and criminal and civil cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling Bacteria-Water Interactions in Soil: EPS Dynamics Under Evaporative Conditions

NASA Astrophysics Data System (ADS)

Furrer, J.; Hinestroza, H. F.; Guo, Y. S.; Gage, D. J.; Cho, Y. K.; Shor, L. M.

2017-12-01

The soil habitat represents a major linkage between the water and carbon cycles: the ability of soils to sequester or release carbon is determined primarily by soil moisture. Water retention and distribution in soils controls the abundance and activity of soil microbes. Microbes in turn impact water retention by creating biofilms, composed of extracellular polymeric substances (EPS). We model the effects of bacterial EPS on water retention at the pore scale. We use the lattice Boltzmann method (LBM), a well-established fluid dynamics modeling platform, and modify it to include the effects of water uptake and release by the swelling/shrinking EPS phase. The LB model is implemented in 2-D, with a non-ideal gas equation of state that allows condensation and evaporation of fluid in pore spaces. Soil particles are modeled according to experimentally determined particle size distributions and include realistic pore geometries, in contrast to many soil models which use spherical soil particles for simplicity. Model results are compared with evaporation experiments in soil micromodels and other simpler experimental systems, and model parameters are tuned to match experimental results. Drying behavior and solid-gel contact angle of EPS produced by the soil bacteria Sinorhizobium meliloti has been characterized and compared to the behavior of deionized water under the same conditions. The difference in behavior between the fluids is used to parameterize the model. The model shows excellent qualitative agreement for soil micromodels with both aggregated and non-aggregated particle arrangements under no-EPS conditions, and reproduces realistic drying behavior for EPS. This work represents a multi-disciplinary approach to understanding microbe-soil interactions at the pore scale.

Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

PubMed

El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

2007-02-01

We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

The effect of Bahiagrass roots on soil erosion resistance of Aquults in subtropical China

NASA Astrophysics Data System (ADS)

Ye, Chao; Guo, Zhonglu; Li, Zhaoxia; Cai, Chongfa

2017-05-01

Herbaceous species, especially their roots, are believed to have an important role in enhancing soil strength and protecting soil against erosion. This study evaluated the effects of root distribution characteristics on soil shear resistance and soil detachment rates, correlations among root mechanical properties, root chemical composition and root parameters, and whether the Wu-Waldron model can accurately estimate soil reinforcement by roots. Bahiagrass (Paspalum notatum) was planted in planter boxes by overlapping four rectangle frames (0.4 × 0.1 × 0.1 m). A series of laboratory tests of direct shear strength and soil detachment were conducted on two soils that were derived from granite and shale with different soil depths and sowing densities. The results indicated that soil aggregate stability was positively correlated with root characteristics. Over 70% of the total measured root parameters were distributed in the upper 20 cm of the soil, and they decreased with increasing soil depth and decreasing sowing density. The tensile properties (root tensile strength and root tensile force) were significantly correlated with root diameter. The contents of root main chemical compositions were significantly correlated with root diameter while hemicellulose showed no obvious trend with root diameter (P = 0.12). Root tensile strength and root tensile force were also significantly correlated with the contents of these four compositions, except hemicellulose. The relative soil detachment demonstrated a significant negative correlation with root parameters with sowing densities from 5 to 30 g m- 2, and it remained at a relatively low value when the sowing density was > 20 g m- 2. The soil detachment rate, erodibility factor and critical flow shear stress were well correlated with the root area ratio, sowing density, and soil depth. The Wu-Waldron model was found to be inappropriate for these soils, as it overestimated additional soil shear strength due to roots by 152-366% in the upper 20 cm, and 11-48% in deeper soil layers. This study demonstrated that the root area ratio was a more suitable root characteristic parameter that contributes to soil reinforcement.

Investigating local controls on soil moisture temporal stability using an inverse modeling approach

NASA Astrophysics Data System (ADS)

Bogena, Heye; Qu, Wei; Huisman, Sander; Vereecken, Harry

2013-04-01

A better understanding of the temporal stability of soil moisture and its relation to local and nonlocal controls is a major challenge in modern hydrology. Both local controls, such as soil and vegetation properties, and non-local controls, such as topography and climate variability, affect soil moisture dynamics. Wireless sensor networks are becoming more readily available, which opens up opportunities to investigate spatial and temporal variability of soil moisture with unprecedented resolution. In this study, we employed the wireless sensor network SoilNet developed by the Forschungszentrum Jülich to investigate soil moisture variability of a grassland headwater catchment in Western Germany within the framework of the TERENO initiative. In particular, we investigated the effect of soil hydraulic parameters on the temporal stability of soil moisture. For this, the HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate Mualem-van Genuchten parameters from soil moisture observations at three depths under natural (transient) boundary conditions for 83 locations in the headwater catchment. On the basis of the optimized parameter sets, we then evaluated to which extent the variability in soil hydraulic conductivity, pore size distribution, air entry suction and soil depth between these 83 locations controlled the temporal stability of soil moisture, which was independently determined from the observed soil moisture data. It was found that the saturated hydraulic conductivity (Ks) was the most significant attribute to explain temporal stability of soil moisture as expressed by the mean relative difference (MRD).

Global Scale Simultaneous Retrieval of Smoothened Vegetation Optical Depth and Surface Roughness Parameter using AMSR-E X-band Observations

NASA Astrophysics Data System (ADS)

Lanka, Karthikeyan; Pan, Ming; Konings, Alexandra; Piles, María; D, Nagesh Kumar; Wood, Eric

2017-04-01

Traditionally, passive microwave retrieval algorithms such as Land Parameter Retrieval Model (LPRM) estimate simultaneously soil moisture and Vegetation Optical Depth (VOD) using brightness temperature (Tb) data. The algorithm requires a surface roughness parameter which - despite implications - is generally assumed to be constant at global scale. Due to inherent noise in the satellite data and retrieval algorithm, the VOD retrievals are usually observed to be highly fluctuating at daily scale which may not occur in reality. Such noisy VOD retrievals along with spatially invariable roughness parameter may affect the quality of soil moisture retrievals. The current work aims to smoothen the VOD retrievals (with an assumption that VOD remains constant over a period of time) and simultaneously generate, for the first time, global surface roughness map using multiple descending X-band Tb observations of AMSR-E. The methodology utilizes Tb values under a moving-time-window-setup to estimate concurrently the soil moisture of each day and a constant VOD in the window. Prior to this step, surface roughness parameter is estimated using the complete time series of Tb record. Upon carrying out the necessary sensitivity analysis, the smoothened VOD along with soil moisture retrievals is generated for the 10-year duration of AMSR-E (2002-2011) with a 7-day moving window using the LPRM framework. The spatial patterns of resulted global VOD maps are in coherence with vegetation biomass and climate conditions. The VOD results also exhibit a smoothening effect in terms of lower values of standard deviation. This is also evident from time series comparison of VOD and LPRM VOD retrievals without optimization over moving windows at several grid locations across the globe. The global surface roughness map also exhibited spatial patterns that are strongly influenced by topography and land use conditions. Some of the noticeable features include high roughness over mountainous regions and heavily vegetated tropical rainforests, low roughness in desert areas and moderate roughness value over higher latitudes. The new datasets of VOD and surface roughness can help improving the quality of soil moisture retrievals. Also, the methodology proposed is generic by nature and can be implemented over currently operating AMSR2, SMOS, and SMAP soil moisture missions.

Bare soil erosion modelling with rainfall simulations: experiments on crop and recently burned areas

NASA Astrophysics Data System (ADS)

Catani, F.; Menci, S.; Moretti, S.; Keizer, J.

2006-12-01

The use of numerical models is of fundamental importance in the comprehension and prediction of soil erosion. At the very basis of the calibration process of the numerical models are the direct measurements of the governing parameters, carried out during field or laboratory tests. To measure and model soil erosion rainfall simulations can be used, that allow the reproduction of project rainfall having chosen characteristics of intensity and duration. The main parameters that rainfall simulators can measure are hydraulic conductivity, parameters of soil erodibility, rate and features of splash erosion, discharge coefficient and sediment yield. Other important parameters can be estimated during the rainfall simulations through the use of photogrammetric instruments able to memorize high definition stereographic models of the soil plot under analysis at different time steps. In this research rainfall simulator experiments (rse) were conducted to measure and quantify runoff and erosion processes on selected bare soil plots. The selected plots are located in some vineyards, olive groves and crops in central Italy and in some recently burned areas in north-central Portugal, affected by a wildfire during early July 2005 and, at the time, largely covered by commercial eucalypt plantations. On the Italian crops the choice of the rainfall intensities and durations were performed on the basis of the previous knowledge of the selected test areas. The procedure was based on an initial phase of soil wetting and a following phase of 3 erosion cycles. The first should reproduce the effects of a normal rainfall with a return time of 2 years (23 mm/h). The second should represent a serious episode with a return time of 10 years (34 mm/h). The third has the objective to reproduce and understand the effects of an intense precipitation event, with a return time of 50 years (41 mm/h). During vineyards experiments some photogrammetric surveys were carried out as well. In the Portugal burned areas, to measure the influence of rain intensities, two rainfall simulations have been carried out simultaneously, one with an intensity of 45 mm/h and one with 85 mm/h. In both cases, before the experiments, soil and vegetation cover description have been made and soil samples have been taken. During the simulations soil samples leaving the parcels were taken at suitable time intervals to measure the sediment yield and the runoff. The rse data have been thought to provide a sufficient basis for erosion modelling at the small-plot scale and, through upscaling, for predicting erosion rates at the slope scale. For this purpose two soil erosion models, WEPP and MEFIDIS, have been selected and then compared. The comparison has shown a certain degree of uncertainty in numeric erosion prediction, due to the non linearity of the overland erosion processes, and to technical and conceptual difficulties, including the data collection. In the following laboratory phase high resolution (2 by 2 mm) DEMs of the vineyards plot are being produced for each meaningful processing phase. The digital elevation models will then be analysed to asses calibration parameters such as soil roughness (expressed by standard deviation of elevations, fractal dimension and local relief energy), soil and sediment transfer (hypsometric curves, local elevation and volume differences) and rill network evolution (Horton ordering, stream lengths, contributing area, drainage density, Hack's law)

What are the most crucial soil factors for predicting the distribution of alpine plant species?

NASA Astrophysics Data System (ADS)

Buri, A.; Pinto-Figueroa, E.; Yashiro, E.; Guisan, A.

2017-12-01

Nowadays the use of species distribution models (SDM) is common to predict in space and time the distribution of organisms living in the critical zone. The realized environmental niche concept behind the development of SDM imply that many environmental factors must be accounted for simultaneously to predict species distributions. Climatic and topographic factors are often primary included, whereas soil factors are frequently neglected, mainly due to the paucity of soil information available spatially and temporally. Furthermore, among existing studies, most included soil pH only, or few other soil parameters. In this study we aimed at identifying what are the most crucial soil factors for explaining alpine plant distributions and, among those identified, which ones further improve the predictive power of plant SDMs. To test the relative importance of the soil factors, we performed plant SDMs using as predictors 52 measured soil properties of various types such as organic/inorganic compounds, chemical/physical properties, water related variables, mineral composition or grain size distribution. We added them separately to a standard set of topo-climatic predictors (temperature, slope, solar radiation and topographic position). We used ensemble forecasting techniques combining together several predictive algorithms to model the distribution of 116 plant species over 250 sites in the Swiss Alps. We recorded the variable importance for each model and compared the quality of the models including different soil proprieties (one at a time) as predictors to models having only topo-climatic variables as predictors. Results show that 46% of the soil proprieties tested become the second most important variable, after air temperature, to explain spatial distribution of alpine plants species. Moreover, we also assessed that addition of certain soil factors, such as bulk soil water density, could improve over 80% the quality of some plant species models. We confirm that soil pH remains one of the most important soil factor for predicting plant species distributions, closely followed by water, organic and inorganic carbon related properties. Finally, we were able to extract three main categories of important soil properties for plant species distributions: grain size distribution, acidity and water in the soil.

Monte Carlo Based Calibration and Uncertainty Analysis of a Coupled Plant Growth and Hydrological Model

NASA Astrophysics Data System (ADS)

Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz

2014-05-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of 58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE=0.79, bias=221.7 kg ha-1, R2=0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.

Monte Carlo based calibration and uncertainty analysis of a coupled plant growth and hydrological model

NASA Astrophysics Data System (ADS)

Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.

2013-12-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape parameter of the retention curve n was highly constrained whilst other parameters of the retention curve showed a large equifinality. The root and storage dry matter observations were predicted with a NSE of 0.94, a low bias of -58.2 kg ha-1 and a high R2 of 0.98. Dry matters of stem and leaves were predicted with less, but still high accuracy (NSE = 0.79, bias = 221.7 kg ha-1, R2 = 0.87). We attribute this slightly poorer model performance to missing leaf senescence which is currently not implemented in PMF. The most constrained parameters for the plant growth model were the radiation-use-efficiency and the base temperature. Cross validation helped to identify deficits in the model structure, pointing out the need of including agricultural management options in the coupled model.

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates.

PubMed

Fenton, O; Vero, S; Ibrahim, T G; Murphy, P N C; Sherriff, S C; Ó hUallacháin, D

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (t(T)) is divided into unsaturated (t(u)) and saturated (t(s)) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of t(T). In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of t(u) were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When t(u) estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments. Copyright © 2015 Elsevier B.V. All rights reserved.

Small scale variability of soil parameters in different land uses on the southern slopes of Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Bogner, Christina; Kühnel, Anna; Hepp, Johannes; Huwe, Bernd

2016-04-01

The Kilimanjaro region in Tanzania constitutes a particularity compared to other areas in the country. Because enough water is available the population grows rapidly and large areas are converted from natural ecosystems to agricultural areas. Therefore, the southern slopes of Mt. Kilimanjaro encompass a complex mosaic of different land uses like coffee plantations, maize, agroforestry or natural savannah. Coffee is an important cash crop in the region and is owned mostly by large companies. In contrast, the agroforestry is a traditional way of agriculture and has been sustained by the Chagga tribe for centuries. These so called homegardens are organised as multi-level systems and contain a mixture of different crops. Correlations in soil and vegetation data may serve as indicators for crop and management impacts associated to different types of land use. We hypothesize that Chagga homegardens, for example, show a more pronounced spatial autocorrelation compared to coffee plantations due to manifold above and belowground crop structures, whereas the degree of anisotropy is assumed to be higher in the coffee sites due to linear elements in management. Furthermore, we hypothesize that the overall diversity of soil parameters in homegardens on a larger scale is higher, as individual owners manage their field differently, whereas coffee plantation management often follows general rules. From these general hypotheses we derive two specific research questions: a) Are there characteristic differences in the spatial organisation of soil physical parameters of different land uses? b) Is there a recognizable relationship between vegetation structure and soil physical parameters of topsoils? We measured soil physical parameters in the topsoil (bulk density, stone content, texture, soil moisture and penetration resistance). Additionally, we took spectra of soil samples with a portable VIS-NIR spectrometer to determine C and N and measured leaf area index and troughfall as an indicator of vegetation patterns. First results support our general hypotheses. In the coffee plantation anisotropic variation of soil parameters clearly showed the anthropogenic influence like compaction due to agricultural machinery. However, soil bulk density and penetration resistance in the homegarden were also quite variable at the sites. The larger variability of throughfall in the homegarden is reflected in the patterns of soil moisture. Regarding the larger scale, where we compared different homegardens and coffee plantations along the southern slope of the mountain, soil parameters of the coffee plots were less diverse than those of the homegardens.

Oxygen and iron production by electrolytic smelting of lunar soil

NASA Technical Reports Server (NTRS)

Haskin, Larry A.

1989-01-01

Previous work has shown that Fe(sup 0) and O2 can be derived by electrolysis from silicate smelt of a composition typical of lunar soils (Lindstrom and Haskin 1979). In the present study, the goal is to refine further the conditions necessary to optimize production and to determine efficiencies of production (how much product is derived for a given current) and purity of products. These depend on several factors, including potential imposed between electrodes, configuration and surface area of the electrodes, composition of the electrolyzed silicate melt, and oxygen fugacity. Experiments were designed to measure the dependence on these variables of three parameters that must be known before production by electrolysis can be optimized. These parameters are: Limiting Current; Actual Current; and Efficiencies of Production.

Terahertz Spectroscopy for Proximal Soil Sensing: An Approach to Particle Size Analysis

PubMed Central

Dworak, Volker; Mahns, Benjamin; Selbeck, Jörn; Weltzien, Cornelia

2017-01-01

Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range. PMID:29048392

Arbuscular mycorrhizal fungi associated with vegetation and soil parameters under rest grazing management in a desert steppe ecosystem.

PubMed

Bai, Gegenbaoleer; Bao, Yuying; Du, Guoxin; Qi, Yunlong

2013-05-01

The impact of rest grazing on arbuscular mycorrhizal fungi (AMF) and the interactions of AMF with vegetation and soil parameters under rest grazing condition were investigated between spring and late summer in a desert steppe ecosystem with different grazing managements (rest grazing with different lengths of resting period, banned or continuous grazing) in Inner Mongolia, China. AMF diversity and colonization, vegetation biomass, soil properties and soil phosphatase activity were examined. In rest grazing areas of 60 days, AMF spore number and diversity index at a 0-10 cm soil depth as well as vesicular and hyphal colonization rates were higher compared with other grazing treatments. In addition, soil organic matter and total N contents were highest and soil alkaline phosphatase was most active under 60-day rest grazing. In August and September, these areas also had the highest amount of aboveground vegetation. The results indicated that resting grazing for an appropriate period of time in spring has a positive effect on AMF sporulation, colonization and diversity, and that under rest grazing conditions, AMF parameters are positively correlated with some soil characteristics.

Application of Modular Modeling System to Predict Evaporation, Infiltration, Air Temperature, and Soil Moisture

NASA Technical Reports Server (NTRS)

Boggs, Johnny; Birgan, Latricia J.; Tsegaye, Teferi; Coleman, Tommy; Soman, Vishwas

1997-01-01

Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: Sensitivity analysis and site-level model calibration

NASA Astrophysics Data System (ADS)

Dantec-Nédélec, S.; Ottlé, C.; Wang, T.; Guglielmo, F.; Maignan, F.; Delbart, N.; Valdayskikh, V.; Radchenko, T.; Nekrasova, O.; Zakharov, V.; Jouzel, J.

2017-06-01

The ORCHIDEE land surface model has recently been updated to improve the representation of high-latitude environments. The model now includes improved soil thermodynamics and the representation of permafrost physical processes (soil thawing and freezing), as well as a new snow model to improve the representation of the seasonal evolution of the snow pack and the resulting insulation effects. The model was evaluated against data from the experimental sites of the WSibIso-Megagrant project (www.wsibiso.ru). ORCHIDEE was applied in stand-alone mode, on two experimental sites located in the Yamal Peninsula in the northwestern part of Siberia. These sites are representative of circumpolar-Arctic tundra environments and differ by their respective fractions of shrub/tree cover and soil type. After performing a global sensitivity analysis to identify those parameters that have most influence on the simulation of energy and water transfers, the model was calibrated at local scale and evaluated against in situ measurements (vertical profiles of soil temperature and moisture, as well as active layer thickness) acquired during summer 2012. The results show how sensitivity analysis can identify the dominant processes and thereby reduce the parameter space for the calibration process. We also discuss the model performance at simulating the soil temperature and water content (i.e., energy and water transfers in the soil-vegetation-atmosphere continuum) and the contribution of the vertical discretization of the hydrothermal properties. This work clearly shows, at least at the two sites used for validation, that the new ORCHIDEE vertical discretization can represent the water and heat transfers through complex cryogenic Arctic soils—soils which present multiple horizons sometimes with peat inclusions. The improved model allows us to prescribe the vertical heterogeneity of the soil hydrothermal properties.

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Effects of wastewater irrigation on chemical and physical properties of Petroselinum crispum.

PubMed

Keser, Gonca; Buyuk, Gokhan

2012-06-01

The present study was carried out to assess the impact of wastewater on parsley (Petroselinum crispum). The parameters determined for soil were pH, electrical conductivity (EC), soil organic matter (SOM), nutrient elements (Ca, Mg, Na, K, Mn, Cu, Zn, and Fe), and heavy metals (Cd, Cr, Ni, and Pb), while the parameters determined for the plant included pigment content, dry matter, nutrient element, and heavy metals. SOM, EC, and clay contents were higher, and pH was slightly acidic in soil treated with wastewater compared to control soil. The enrichment factors (EF) of the nutrient elements in contaminated soil are in the sequence of Na (2) > Ca (1.32) > Mn = Mg (1.17) > Cu (1.11) > Zn (1.08) > Fe (1.07) > K (0.93), while EF in parsley are Na (6.63) > Ca (1.60) > Mg (1.34) > Zn (1.15) > Fe (0.95) > Cu = K (0.90) > Mn (0.85). Application of wastewater significantly decreased dry matter, while photosynthetic pigment content increased in parsley. The enrichment of the heavy metals is in the sequence: Cd (1.142) > Pb (1.131) > Ni (1.112) > Cr (1.095). P. crispum shows a high transfer factor (TF > 1) for Cd signifying a high mobility of Cd from soil to plant. Thus, although the wastewater irrigation in parsley production aims to produce socioeconomic benefits, study results indicated that municipal wastewater is not suitable for irrigation of parsley because it has negative effects on plant and causes heavy metal accumulation.

In-field experiment of electro-hydraulic tillage depth draft-position mixed control on tractor

NASA Astrophysics Data System (ADS)

Han, Jiangyi; Xia, Changgao; Shang, Gaogao; Gao, Xiang

2017-12-01

The soil condition and condition of the plow affect the tillage resistance and the maximum traction of tractor. In order to improve the adaptability of tractor tillage depth control, a multi-parameter control strategy is proposed that included tillage depth target, draft force aim and draft-position mixed ratio. In the strategy, the resistance coefficient was used to adjust the draft force target. Then, based on a JINMA1204 tractor, the electro-hydraulic hitch prototype is constructed that could set control parameters.. The fuzzy controller of draft-position mixed control is designed. After that, in-field experiments of position control was carried on, and the result of experiment shows the error of tillage depth was less than ±20mm. The experiment of draft-position control shown that the draft force and the tillage depth could be adjust by multi-parameter such as tillage depth, resistance coefficient and draft-position mixed coefficient. So that, the multi-parameter control strategy could improve the adaptability of tillage depth control in various soils and plow condition.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

NASA Astrophysics Data System (ADS)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.

Do agricultural terraces and forest fires recurrence in Mediterranean afforested micro-catchments alter soil quality and soil nutrient content?

NASA Astrophysics Data System (ADS)

E Lucas-Borja, Manuel; Calsamiglia, Aleix; Fortesa, Josep; García-Comendador, Julián; Gago, Jorge; Estrany, Joan

2017-04-01

Bioclimatic characteristics and intense human pressure promote Mediterranean ecosystems to be fire-prone. Afforestation processes resulting from the progressive land abandonment during the last decades led to greater biomass availability increasing the risk of large forest fires. Likewise, the abandonment and lack of maintenance in the terraced lands constitute a risk of land degradation in terms of soil quantity and quality. Despite the effects of fire and the abandonment of terraced lands on soil loss and physico-chemical properties are identified, it is not clearly understood how wildfires and abandonment of terraces affect soil quality and nutrients content. Microbiological soil parameters and soil enzymes activities are biomarkers of the soil microbial communitýs functional ability, which potentially enables them as indicators of change, disturbance or stress within the soil community. The objective of this study was to investigate the effects of terracing (abandoned and non-abandoned) on the soil enzyme activities, microbiological soil parameters and soil nutrients dynamics in three Mediterranean afforested micro-catchments (i.e., < 2 ha) under different forest fire recurrence in the last 20 years; i.e., unburned areas, burned once and burned twice. The combination of the presence of terraces and the recurrence of forest fire, thirty-six plots of 25 m2 were sampled along the these three micro-catchments collecting four replicas at the corners of each plot. The results elucidated how non-terraced and unburned plots presented the highest values of soil respiration rate and extracellular soil enzymes. Differences between experimental plots with different forest fire recurrence or comparing terraced and unburned plots with burned plots were weaker in relation to biochemical and microbiological parameters. Soil nutrient content showed an opposite trend with higher values in terraced plots, although differences were weaker. We conclude that terraced landscapes present poorer soil quality parameters due to land abandonment and the lack of terraced management. In addition, forest fire recurrence exacerbates soil degradation processes due to the direct effects on vegetation and soil properties.

Estimating soil hydraulic properties from soil moisture time series by inversion of a dual-permeability model

NASA Astrophysics Data System (ADS)

Dalla Valle, Nicolas; Wutzler, Thomas; Meyer, Stefanie; Potthast, Karin; Michalzik, Beate

2017-04-01

Dual-permeability type models are widely used to simulate water fluxes and solute transport in structured soils. These models contain two spatially overlapping flow domains with different parameterizations or even entirely different conceptual descriptions of flow processes. They are usually able to capture preferential flow phenomena, but a large set of parameters is needed, which are very laborious to obtain or cannot be measured at all. Therefore, model inversions are often used to derive the necessary parameters. Although these require sufficient input data themselves, they can use measurements of state variables instead, which are often easier to obtain and can be monitored by automated measurement systems. In this work we show a method to estimate soil hydraulic parameters from high frequency soil moisture time series data gathered at two different measurement depths by inversion of a simple one dimensional dual-permeability model. The model uses an advection equation based on the kinematic wave theory to describe the flow in the fracture domain and a Richards equation for the flow in the matrix domain. The soil moisture time series data were measured in mesocosms during sprinkling experiments. The inversion consists of three consecutive steps: First, the parameters of the water retention function were assessed using vertical soil moisture profiles in hydraulic equilibrium. This was done using two different exponential retention functions and the Campbell function. Second, the soil sorptivity and diffusivity functions were estimated from Boltzmann-transformed soil moisture data, which allowed the calculation of the hydraulic conductivity function. Third, the parameters governing flow in the fracture domain were determined using the whole soil moisture time series. The resulting retention functions were within the range of values predicted by pedotransfer functions apart from very dry conditions, where all retention functions predicted lower matrix potentials. The diffusivity function predicted values of a similar range as shown in other studies. Overall, the model was able to emulate soil moisture time series for low measurement depths, but deviated increasingly at larger depths. This indicates that some of the model parameters are not constant throughout the profile. However, overall seepage fluxes were still predicted correctly. In the near future we will apply the inversion method to lower frequency soil moisture data from different sites to evaluate the model's ability to predict preferential flow seepage fluxes at the field scale.

Application of SWAT and CAST model on Damma Glacier CZO

NASA Astrophysics Data System (ADS)

Andrianaki, Maria; Bernasconi, Stefano; Kobierska, Florian; Nikolaidis, Nikolaos

2014-05-01

Damma Glacier is one of the Critical Zone Observatories, located at the central Swiss Alps, Switzerland and is characterized by a 150-year soil chronosequence. In this study, we used the Soil and Water Assessment Tool (SWAT) to simulate the hydrology of the watershed of Damma glacier, Switzerland and of the extended area that feeds Goescheneralpsee and includes Damma watershed. SWAT was calibrated for the watershed of Damma glacier with the stream flow data collected between 2009 and 2011. Subsequently and in order to study the up-scalling effect, SWAT was run for the greater area using the same parameters. Carbon accumulation and aggregate formation along Damma soil chronosequence was modelled using ROTH-C and CAST models.

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Concerning the relationship between evapotranspiration and soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, Peter J.; Chang, Jy-Tai

1987-01-01

The relationship between the evapotranspiration and soil moisture during the drying, supply-limited phase is studied. A second scaling parameter, based on the evapotranspirational supply and demand concept of Federer (1982), is defined; the parameter, referred to as the threshold evapotranspiration, occurs in vegetation-covered surfaces just before leaf stomata close and when surface tension restricts moisture release from bare soil pores. A simple model for evapotranspiration is proposed. The effects of natural soil heterogeneities on evapotranspiration computed from the model are investigated. It is observed that the natural variability in soil moisture, caused by the heterogeneities, alters the relationship between regional evapotranspiration and the area average soil moisture.

The GLORIE Campaign: Assessment of the Capabilities of Airborne GNSS-R for Land Remote Sensing.

NASA Astrophysics Data System (ADS)

Mangiarotti, S.; Motte, E.; Zribi, M., Sr.; Fanise, P., Sr.

2015-12-01

In June and July 2015 an intensive flight campaign was conducted over the south west of France to test the sensitivity of Global Navigation Satellite System Reflectometry (GNSS-R) to the geophysical parameters of continental surfaces. Namely, the parameters of interest were soil moisture, soil roughness, plant water content, forest biomass and level of inland water bodies and rivers. We used the GLORI polarimetric GNSS-R instrument, collecting raw 10MSPS 2-bit IQ direct (RHCP, zenith) and reflected (RHCP and LHCP, nadir) signals at GPS L1 frequency aboard the ATR-42 aircraft of the SAFIRE fleet. Simultaneous measurement of aircraft attitude and position were recorded. The flight plan included flyovers of several areas of interests, with collocated ground truth measurements of soil moisture, soil roughness, cultivated biomass, and forest biomass. Also flyovers of ponds, lakes and river were included for power calibration and altimetry retrievals. In total, 6 flights were performed between June 19th and July 6th, representing more than 15 hours of raw data. A conventional GNSS-R processing of the data was performed in order to compute the direct and reflected complex waveforms. A preliminary data analysis based on the variations of the ratio of reflected maximum correlation amplitude in the LHCP antenna to direct maximum correlated amplitude shows measurements sensitivity to soil type, land use and incidence angle. Also, first altimetric retrievals using phase-delay techniques shows very promising results over calm waters. Current work is ongoing in order to fit the observed polarimetric measurements with innovative bistatic scattering models capable of taking into account complex geometries and land use configurations.

The effect on performance and biochemical parameters when soil was added to aflatoxin-contaminated poultry rations.

PubMed

Madden, U A; Stahr, H M; Stino, F K

1999-08-01

The effects of silty clay loam soil on the performance and biochemical parameters of chicks were investigated when the soil was added to aflatoxin B1 (AFB1)-contaminated diets. One hundred 14-d-old White Leghorn chicks were fed a control ration (clean corn), a low aflatoxin-contaminated ration (120 ng AFB1/g), a high aflatoxin-contaminated ration (700 ng AFB1/g), or high aflatoxin-contaminated rations (700 ng AFB1/g) +10% or 25% soil. Body weight, feed consumption and blood samples were monitored weekly. Decreased feed consumption, body weight gain and efficiency of feed utilization, increased SGOT and LDH activities, and cholesterol and triglyceride concentrations, and decreased uric acid concentrations and ALP activity were observed in the chicks fed the high aflatoxin-contaminated ration without soil. Hepatomegaly was prominent in chicks fed the high aflatoxin-contaminated ration without soil, and some livers had extensive hepatocyte vacuolation, hepatocellular swelling, fatty change and hydropic degeneration, and stained positive for fat accumulation. Addition of soil reduced the detrimental effects of AFB1 for some parameters, although the reduction was less when 10% soil was fed compared with the 25% soil feeding.

Importance of Soil Temperature for the Growth of Temperate Crops under a Tropical Climate and Functional Role of Soil Microbial Diversity.

PubMed

Sabri, Nurul Syazwani Ahmad; Zakaria, Zuriati; Mohamad, Shaza Eva; Jaafar, A Bakar; Hara, Hirofumi

2018-04-28

A soil cooling system that prepares soil for temperate soil temperatures for the growth of temperate crops under a tropical climate is described herein. Temperate agriculture has been threatened by the negative impact of temperature increases caused by climate change. Soil temperature closely correlates with the growth of temperate crops, and affects plant processes and soil microbial diversity. The present study focuses on the effects of soil temperatures on lettuce growth and soil microbial diversity that maintains the growth of lettuce at low soil temperatures. A model temperate crop, loose leaf lettuce, was grown on eutrophic soil under soil cooling and a number of parameters, such as fresh weight, height, the number of leaves, and root length, were evaluated upon harvest. Under soil cooling, significant differences were observed in the average fresh weight (P<0.05) and positive development of the roots, shoots, and leaves of lettuce. Janthinobacterium (8.142%), Rhodoplanes (1.991%), Arthrospira (1.138%), Flavobacterium (0.857%), Sphingomonas (0.790%), Mycoplana (0.726%), and Pseudomonas (0.688%) were the dominant bacterial genera present in cooled soil. Key soil fungal communities, including Pseudaleuria (18.307%), Phoma (9.968%), Eocronartium (3.527%), Trichosporon (1.791%), and Pyrenochaeta (0.171%), were also recovered from cooled soil. The present results demonstrate that the growth of temperate crops is dependent on soil temperature, which subsequently affects the abundance and diversity of soil microbial communities that maintain the growth of temperate crops at low soil temperatures.

Environmental and management influences on temporal variability of near saturated soil hydraulic properties.

PubMed

Bodner, G; Scholl, P; Loiskandl, W; Kaul, H-P

2013-08-01

Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (- 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r 2  = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters.

Environmental and management influences on temporal variability of near saturated soil hydraulic properties☆

PubMed Central

Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.

2013-01-01

Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (− 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r2 = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters. PMID:24748683

Health risk profile for terrestrial radionuclides in soil around artisanal gold mining area at Alsopag, Sudan

NASA Astrophysics Data System (ADS)

Idriss, Hajo; Salih, Isam; Alaamer, Abdulaziz S.; AL-Rajhi, M. A.; Osman, Alshfia; Adreani, Tahir Elamin; Abdelgalil, M. Y.; Ali, Nagi I.

2018-06-01

This study shows the assessment of radiation hazard parameters due to terrestrial radionuclides in the soil around artisanal gold mining for addressing the issue of natural radioactivity in mining areas. Hence, the levels 238U, 232Th, 40K and 226Ra in soil (using gamma spectrometry), 222Rn in soil and 222Rn in air were determined. Radiation hazard parameters were then computed. These include absorbed dose D, annual effective dose E, radium equivalent activity Raeq, external hazard H ex, annual gonadal dose equivalent hazard index AGDE and excess lifetime cancer risk ELCR due to the inhalation of radon (222Rn) and consumption of radium (226Ra) in vegetation. Uranium (238U), thorium (232Th) and potassium (40K) averages were, respectively, 26, 36 and 685 Becquerel per kilogram (Bq kg-1). Soil radon (4671 Bq m-3) and radon in air (14.77 Bq m-3) were found to be less than worldwide data. Nevertheless, the average 40K concentration was 685 Bq kg-1. This is slightly higher than the United Nations Scientific Committee on the Effects of Atomic Radiation average value of 412 Bq kg-1. The obtained result indicates that some of the radiation hazard parameters seem unsavory. The mean value of absorbed dose rate (62.49 nGy h-1) was slightly higher than average value of 57 nGy h-1 ( 45% from 40K), and that of AGDE (444 μSv year-1) was higher than worldwide average reported value (300 μSv year-1). This study highlights the necessity to launch extensive nationwide radiation protection program in the mining areas for regulatory control.

The estimation of parameter compaction values for pavement subgrade stabilized with lime

NASA Astrophysics Data System (ADS)

Lubis, A. S.; Muis, Z. A.; Simbolon, C. A.

2018-02-01

The type of soil material, field control, maintenance and availability of funds are several factors that must be considered in compaction of the pavement subgrade. In determining the compaction parameters in laboratory desperately requires considerable materials, time and funds, and reliable laboratory operators. If the result of soil classification values can be used to estimate the compaction parameters of a subgrade material, so it would save time, energy, materials and cost on the execution of this work. This is also a clarification (cross check) of the work that has been done by technicians in the laboratory. The study aims to estimate the compaction parameter values ie. maximum dry unit weight (γdmax) and optimum water content (Wopt) of the soil subgrade that stabilized with lime. The tests that conducted in the laboratory of soil mechanics were to determine the index properties (Fines and Liquid Limit/LL) and Standard Compaction Test. Soil samples that have Plasticity Index (PI) > 10% were made with additional 3% lime for 30 samples. By using the Goswami equation, the compaction parameter values can be estimated by equation γd max # = -0,1686 Log G + 1,8434 and Wopt # = 2,9178 log G + 17,086. From the validation calculation, there was a significant positive correlation between the compaction parameter values laboratory and the compaction parameter values estimated, with a 95% confidence interval as a strong relationship.

Context dependency and saturating effects of loss of rare soil microbes on plant productivity.

PubMed

Hol, W H Gera; de Boer, Wietse; de Hollander, Mattias; Kuramae, Eiko E; Meisner, Annelein; van der Putten, Wim H

2015-01-01

Land use intensification is associated with loss of biodiversity and altered ecosystem functioning. Until now most studies on the relationship between biodiversity and ecosystem functioning focused on random loss of species, while loss of rare species that usually are the first to disappear received less attention. Here we test if the effect of rare microbial species loss on plant productivity depends on the origin of the microbial soil community. Soils were sampled from three land use types at two farms. Microbial communities with increasing loss of rare species were created by inoculating sterilized soils with serially diluted soil suspensions. After 8 months of incubation, the effects of the different soil communities on abiotic soil properties, soil processes, microbial community composition, and plant productivity was measured. Dilution treatments resulted in increasing species loss, which was in relation to abundance of bacteria in the original field soil, without affecting most of the other soil parameters and processes. Microbial species loss affected plant biomass positively, negatively or not at all, depending on soil origin, but not on land use history. Even within fields the effects of dilution on plant biomass varied between replicates, suggesting heterogeneity in microbial community composition. The effects of medium and severe species loss on plant biomass were similar, pointing toward a saturating effect of species loss. We conclude that changes in the composition of the soil microbial community, including rare species loss, can affect plant productivity, depending on the composition of the initial microbial community. Future work on the relation between function and species loss effects should address this variation by including multiple sampling origins.

Effects of soil tillage on the microwave emission of soils

NASA Technical Reports Server (NTRS)

Jackson, T. J.; Koopman, G. J.; Oneill, P. E.; Wang, J. R.

1985-01-01

In order to understand the interactions of soil properties and microwave emission better, a series of field experiments were conducted in 1984. Small plots were measured with a truck-mounted passive microwave radiometer operating at 1.4 GHz. These data were collected concurrent with ground observations of soil moisture and bulk density. Treatment effects studied included different soil moisture contents and bulk densities. Evaluations of the data have shown that commonly used models of the dielectric properties of wet soils do not explain the observations obtained in these experiments. This conclusion was based on the fact that the roughness parameters determined through optimization were significantly larger than those observed in similar investigations. These discrepancies are most likely due to the soil structure. Commonly used models assume a homogeneous three phase mixture of soil solids, air and water. Under tilled conditions the soil is actually a two phase mixture of aggregates and voids. Appropriate dielectric models for this tilled condition were evaluated and found to explain the observations. These results indicate that previous conclusions concerning the effects of surface roughness in tilled fields may be incorrect, and they may explain some of the inconsistencies encountered in roughness modeling.

Sensitivity and uncertainty analysis for Abreu & Johnson numerical vapor intrusion model.

PubMed

Ma, Jie; Yan, Guangxu; Li, Haiyan; Guo, Shaohui

2016-03-05

This study conducted one-at-a-time (OAT) sensitivity and uncertainty analysis for a numerical vapor intrusion model for nine input parameters, including soil porosity, soil moisture, soil air permeability, aerobic biodegradation rate, building depressurization, crack width, floor thickness, building volume, and indoor air exchange rate. Simulations were performed for three soil types (clay, silt, and sand), two source depths (3 and 8m), and two source concentrations (1 and 400 g/m(3)). Model sensitivity and uncertainty for shallow and high-concentration vapor sources (3m and 400 g/m(3)) are much smaller than for deep and low-concentration sources (8m and 1g/m(3)). For high-concentration sources, soil air permeability, indoor air exchange rate, and building depressurization (for high permeable soil like sand) are key contributors to model output uncertainty. For low-concentration sources, soil porosity, soil moisture, aerobic biodegradation rate and soil gas permeability are key contributors to model output uncertainty. Another important finding is that impacts of aerobic biodegradation on vapor intrusion potential of petroleum hydrocarbons are negligible when vapor source concentration is high, because of insufficient oxygen supply that limits aerobic biodegradation activities. Copyright © 2015 Elsevier B.V. All rights reserved.

Frozen soil parameterization in a distributed biosphere hydrological model

NASA Astrophysics Data System (ADS)

Wang, L.; Koike, T.; Yang, K.; Jin, R.; Li, H.

2010-03-01

In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). First, by using the original WEB-DHM without the frozen scheme, the land surface parameters and two van Genuchten parameters were optimized using the observed surface radiation fluxes and the soil moistures at upper layers (5, 10 and 20 cm depths) at the DY station in July. Second, by using the WEB-DHM with the frozen scheme, two frozen soil parameters were calibrated using the observed soil temperature at 5 cm depth at the DY station from 21 November 2007 to 20 April 2008; while the other soil hydraulic parameters were optimized by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak in 2008. With these calibrated parameters, the WEB-DHM with the frozen scheme was then used for a yearlong validation from 21 November 2007 to 20 November 2008. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the cold regions catchment and the discharges at the basin outlet in the yearlong simulation.

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in adequately representing the relevant process to capture limiting resources or manage atypical environmental conditions. These results may inform future experimental work by focusing efforts on quantifying specific parameters under various environmental conditions or across diverse plant functional types.

Modeling Stand-Scale Patterns in Evapotranspiration and Soil Moisture in a Heterogeneous Plant Canopy: A Coupled Subsurface-Land Surface Approach

NASA Astrophysics Data System (ADS)

Miller, G. R.; Gou, S.; Ferguson, I. M.; Maxwell, R. M.

2011-12-01

Savanna ecosystems present a well-known modeling challenge; understory grasses and overstory woody vegetation combine to form an open, heterogeneous canopy that creates strong spatial differences in soil moisture and evapotranspiration rates. In this analysis, we used ParFlow.CLM to create a stand-scale model of the Tonzi Ranch oak savanna, based on extensive topography, vegetation, soil, and hydrogeology data collected at the site. Measurements included canopy distribution and ground surface elevation from airborne Lidar, depth to groundwater from deep piezometers, soil and rock hydraulic conductivity, and leaf area index. We then compared the results to the site's long-term data records of radiative flux partitioning, obtained using the eddy-covariance method, and soil moisture, collected via a distributed network of capacitance probes. In order to obtain good agreement between the measured and modeled values, we identified several necessary modifications to the current CLM parameterization. These changes included the addition of a "winter grass" type and the alteration of the root structure and water stress functions to accommodate uptake of groundwater by deep roots. Finally, we compared variograms of site parameters and response variables and performed a scaling analysis relating ET and soil moisture variance to sampling size.

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, Bertrand; Esteban Moyano, Fernando; Peylin, Philippe; Ciais, Philippe; Janssens, Ivan A.

2016-03-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, B.; Moyano, F. E.; Peylin, P.; Ciais, P.; Janssens, I. A.

2015-10-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

DOE Data Explorer

Atchley, Adam; Painter, Scott; Harp, Dylan; Coon, Ethan; Wilson, Cathy; Liljedahl, Anna; Romanovsky, Vladimir

2015-01-29

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active thaw layer (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

Jatropha curcas L. Root Structure and Growth in Diverse Soils

PubMed Central

Valdés-Rodríguez, Ofelia Andrea; Sánchez-Sánchez, Odilón; Pérez-Vázquez, Arturo; Caplan, Joshua S.; Danjon, Frédéric

2013-01-01

Unlike most biofuel species, Jatropha curcas has promise for use in marginal lands, but it may serve an additional role by stabilizing soils. We evaluated the growth and structural responsiveness of young J. curcas plants to diverse soil conditions. Soils included a sand, a sandy-loam, and a clay-loam from eastern Mexico. Growth and structural parameters were analyzed for shoots and roots, although the focus was the plasticity of the primary root system architecture (the taproot and four lateral roots). The sandy soil reduced the growth of both shoot and root systems significantly more than sandy-loam or clay-loam soils; there was particularly high plasticity in root and shoot thickness, as well as shoot length. However, the architecture of the primary root system did not vary with soil type; the departure of the primary root system from an index of perfect symmetry was 14 ± 5% (mean ± standard deviation). Although J. curcas developed more extensively in the sandy-loam and clay-loam soils than in sandy soil, it maintained a consistent root to shoot ratio and root system architecture across all types of soil. This strong genetic determination would make the species useful for soil stabilization purposes, even while being cultivated primarily for seed oil. PMID:23844412

Jatropha curcas L. root structure and growth in diverse soils.

PubMed

Valdés-Rodríguez, Ofelia Andrea; Sánchez-Sánchez, Odilón; Pérez-Vázquez, Arturo; Caplan, Joshua S; Danjon, Frédéric

2013-01-01

Unlike most biofuel species, Jatropha curcas has promise for use in marginal lands, but it may serve an additional role by stabilizing soils. We evaluated the growth and structural responsiveness of young J. curcas plants to diverse soil conditions. Soils included a sand, a sandy-loam, and a clay-loam from eastern Mexico. Growth and structural parameters were analyzed for shoots and roots, although the focus was the plasticity of the primary root system architecture (the taproot and four lateral roots). The sandy soil reduced the growth of both shoot and root systems significantly more than sandy-loam or clay-loam soils; there was particularly high plasticity in root and shoot thickness, as well as shoot length. However, the architecture of the primary root system did not vary with soil type; the departure of the primary root system from an index of perfect symmetry was 14 ± 5% (mean ± standard deviation). Although J. curcas developed more extensively in the sandy-loam and clay-loam soils than in sandy soil, it maintained a consistent root to shoot ratio and root system architecture across all types of soil. This strong genetic determination would make the species useful for soil stabilization purposes, even while being cultivated primarily for seed oil.

Fate and transport of mercury in soil systems : a numerical model in HP1 and sensitivity analysis

NASA Astrophysics Data System (ADS)

Leterme, Bertrand; Jacques, Diederik

2013-04-01

Mercury (Hg) poses threats for human health and the environment, notably due to its persistence and its ability to bioaccumulate in ecosystems. Anthropogenic activities are major contributors of mercury release to soils. Main sources of contamination include manufacturing (chlor-alkali plants, manometer spill), mine tailings from mercury, gold and silver mining industries, wood preservation. The objective of this study was to develop a reactive transport model for simulating mercury fate and transport in the unsaturated zone, and to gain insight in the fate and transport of Hg following anthropogenic soil contamination. The present work is done in the framework of the IMaHg project, which aims at providing recommendations to improve management of sites contaminated by mercury within the SNOWMAN funding framework. A model of mercury fate and transport in soil systems was developed using the reactive transport code HP1 (Jacques and Šimůnek, 2010). The geochemical database THERMODDEM (Blanc et al., 2012) is used, augmented with some speciation data from (Skyllberg, 2012). The main processes accounted for in the model are : Hg aqueous speciation (including complexation with dissolved organic matter (DOM) - humic and fulvic acids, and thiol groups), Hg sorption to solid organic matter (SOM), dissolution of solid phase Hg (e.g. cinnabar HgS(s)), dissolution of Hg non-aqueous liquid phase (NAPL), sunlight-driven Hg(II) reduction to Hg(0), Hg(0) diffusion in the gas phase and volatilization, DOM sorption to soil minerals. Colloid facilitated transport is implicitly accounted for by solute transport of Hg-DOM complexes. Because we focused on soil systems having a high Hg contamination, some processes showing relatively smaller Hg fluxes could be neglected such as vegetation uptake and atmospheric wet and dry deposition. NAPL migration and entrapment is not modelled, as pollution is assumed to be historical and only residual NAPL to be present. Mercury methylation and demethylation was not implemented, because it could be neglected in an oxidising environment. However, if the model is to be tested in more reducing conditions (e.g. shallow groundwater table), methyl- and dimethylmercury formation can be non negligible. Using 50 year time series of daily weather observations in Dessel (Belgium) and a typical sandy soil with deep groundwater (free drainage, oxic conditions), a sensitivity analysis was performed to assess the relative importance of processes and parameters within the model. We used the elementary effects method (Morris, 1991; Campolongo et al., 2007), which draws trajectories across the parameter space to derive information on the global sensitivity of the selected input parameters. The impact of different initial contamination phases (solid, NAPL, aqueous and combinations of these) was also tested. Simulation results are presented in terms of (i) Hg volatilized to the atmosphere; (ii) Hg leached out of the soil profile; (iii) Hg still present in the soil horizon originally polluted; and (iv) Hg still present in the soil profile but below the original contaminated horizon. Processes and parameters identified as critical based on the sensitivity analysis differ from one scenario to the other ; depending on pollution type (cinnabar, NAPL, aqueous Hg), on the indicator assessed and on time (after 5, 25 or 50 years). However, in general DOM in soil water was the most critical parameter. Other important parameters were those related to Hg sorption on SOM (thiols, and humic and fulvic acids), and to Hg complexation with DOM. Initial Hg concentration was also often identified as a sensitive parameter. Interactions between factors and non linear effects as measured by the elementary effect method were generally important, but also dependent on the type of contamination and on time. No model calibration was performed until now. The numerical tool could greatly benefit from partial model calibration and/or validation. Ideally, detailed speciation data on a contaminated sites would be required, together with a good characterization of the pollution source. References : Blanc, P., Lassin, A. and Piantone, P. (2012), THERMODDEM a database devoted to waste minerals, BRGM, Orléans, France. http://thermoddem.brgm.fr Campolongo, F., Cariboni, J. and Saltelli, A. (2007), An effective screening design for sensitivity analysis of large models, Environmental Modelling & Software 22(10): 1509-1518. Jacques, D. and Šimůnek, J. (2010), Notes on HP1 - a software package for simulating variably-saturated water flow, heat transport, solute transport and biogeochemistry in porous media, HP1 Version 2.2 SCK•CEN-BLG-1068, Waste & Disposal Department, SCK•CEN, Mol, Belgium: 113 p. Morris, M. D. (1991), Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics 33(2): 161-174. Skyllberg, U. (2012), Chemical Speciation of Mercury in Soil and Sediment. Environmental Chemistry and Toxicology of Mercury, John Wiley & Sons, Inc.: 219-258.

Soil CO2 Dynamics in a Tree Island Soil of the Pantanal: The Role of Soil Water Potential

PubMed Central

Johnson, Mark S.; Couto, Eduardo Guimarães; Pinto Jr, Osvaldo B.; Milesi, Juliana; Santos Amorim, Ricardo S.; Messias, Indira A. M.; Biudes, Marcelo Sacardi

2013-01-01

The Pantanal is a biodiversity hotspot comprised of a mosaic of landforms that differ in vegetative assemblages and flooding dynamics. Tree islands provide refuge for terrestrial fauna during the flooding period and are particularly important to the regional ecosystem structure. Little soil CO2 research has been conducted in this region. We evaluated soil CO2 dynamics in relation to primary controlling environmental parameters (soil temperature and soil water). Soil respiration was computed using the gradient method using in situ infrared gas analyzers to directly measure CO2 concentration within the soil profile. Due to the cost of the sensors and associated equipment, this study was unreplicated. Rather, we focus on the temporal relationships between soil CO2 efflux and related environmental parameters. Soil CO2 efflux during the study averaged 3.53 µmol CO2 m−2 s−1, and was equivalent to an annual soil respiration of 1220 g C m−2 y−1. This efflux value, integrated over a year, is comparable to soil C stocks for 0–20 cm. Soil water potential was the measured parameter most strongly associated with soil CO2 concentrations, with high CO2 values observed only once soil water potential at the 10 cm depth approached zero. This relationship was exhibited across a spectrum of timescales and was found to be significant at a daily timescale across all seasons using conditional nonparametric spectral Granger causality analysis. Hydrology plays a significant role in controlling CO2 efflux from the tree island soil, with soil CO2 dynamics differing by wetting mechanism. During the wet-up period, direct precipitation infiltrates soil from above and results in pulses of CO2 efflux from soil. The annual flood arrives later, and saturates soil from below. While CO2 concentrations in soil grew very high under both wetting mechanisms, the change in soil CO2 efflux was only significant when soils were wet from above. PMID:23762259

Soil CO₂ dynamics in a tree island soil of the Pantanal: the role of soil water potential.

PubMed

Johnson, Mark S; Couto, Eduardo Guimarães; Pinto, Osvaldo B; Milesi, Juliana; Santos Amorim, Ricardo S; Messias, Indira A M; Biudes, Marcelo Sacardi

2013-01-01

The Pantanal is a biodiversity hotspot comprised of a mosaic of landforms that differ in vegetative assemblages and flooding dynamics. Tree islands provide refuge for terrestrial fauna during the flooding period and are particularly important to the regional ecosystem structure. Little soil CO₂ research has been conducted in this region. We evaluated soil CO₂ dynamics in relation to primary controlling environmental parameters (soil temperature and soil water). Soil respiration was computed using the gradient method using in situ infrared gas analyzers to directly measure CO₂ concentration within the soil profile. Due to the cost of the sensors and associated equipment, this study was unreplicated. Rather, we focus on the temporal relationships between soil CO₂ efflux and related environmental parameters. Soil CO₂ efflux during the study averaged 3.53 µmol CO₂ m⁻² s⁻¹, and was equivalent to an annual soil respiration of 1220 g C m⁻² y⁻¹. This efflux value, integrated over a year, is comparable to soil C stocks for 0-20 cm. Soil water potential was the measured parameter most strongly associated with soil CO₂ concentrations, with high CO₂ values observed only once soil water potential at the 10 cm depth approached zero. This relationship was exhibited across a spectrum of timescales and was found to be significant at a daily timescale across all seasons using conditional nonparametric spectral Granger causality analysis. Hydrology plays a significant role in controlling CO₂ efflux from the tree island soil, with soil CO₂ dynamics differing by wetting mechanism. During the wet-up period, direct precipitation infiltrates soil from above and results in pulses of CO₂ efflux from soil. The annual flood arrives later, and saturates soil from below. While CO₂ concentrations in soil grew very high under both wetting mechanisms, the change in soil CO₂ efflux was only significant when soils were wet from above.

Oligotyping reveals stronger relationship of organic soil bacterial community structure with N-amendments and soil chemistry in comparison to that of mineral soil at Harvard Forest, MA, USA.

PubMed

Turlapati, Swathi A; Minocha, Rakesh; Long, Stephanie; Ramsdell, Jordan; Minocha, Subhash C

2015-01-01

The impact of chronic nitrogen amendments on bacterial communities was evaluated at Harvard Forest, Petersham, MA, USA. Thirty soil samples (3 treatments × 2 soil horizons × 5 subplots) were collected in 2009 from untreated (control), low nitrogen-amended (LN; 50 kg NH4NO3 ha(-1) yr(-1)) and high nitrogen-amended (HN; 150 kg NH4NO3 ha(-1) yr(-1)) plots. PCR-amplified partial 16S rRNA gene sequences made from soil DNA were subjected to pyrosequencing (Turlapati et al., 2013) and analyses using oligotyping. The parameters M (the minimum count of the most abundant unique sequence in an oligotype) and s (the minimum number of samples in which an oligotype is expected to be present) had to be optimized for forest soils because of high diversity and the presence of rare organisms. Comparative analyses of the pyrosequencing data by oligotyping and operational taxonomic unit clustering tools indicated that the former yields more refined units of taxonomy with sequence similarity of ≥99.5%. Sequences affiliated with four new phyla and 73 genera were identified in the present study as compared to 27 genera reported earlier from the same data (Turlapati et al., 2013). Significant rearrangements in the bacterial community structure were observed with N-amendments revealing the presence of additional genera in N-amended plots with the absence of some that were present in the control plots. Permutational MANOVA analyses indicated significant variation associated with soil horizon and N treatment for a majority of the phyla. In most cases soil horizon partitioned more variation relative to treatment and treatment effects were more evident for the organic (Org) horizon. Mantel test results for Org soil showed significant positive correlations between bacterial communities and most soil parameters including NH4 and NO3. In mineral soil, correlations were seen only with pH, NH4, and NO3. Regardless of the pipeline used, a major hindrance for such a study remains to be the lack of reference databases for forest soils.

Obtaining soil hydraulic parameters from data assimilation under different climatic/soil conditions

USDA-ARS?s Scientific Manuscript database

Obtaining reliable soil hydraulic properties is essential to correctly simulating soil water content (SWC), which is a key component of countless applications such as agricultural management, soil remediation, aquifer protection, etc. Soil hydraulic properties can be measured in the laboratory; howe...

Development of a predictive model for lead, cadmium and fluorine soil-water partition coefficients using sparse multiple linear regression analysis.

PubMed

Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi

2017-11-01

In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of two methods for calculating the P sorption capacity parameter in soils

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) cycling in soils is an important process affecting P movement through the landscape. The P cycling routines in many computer models are based on the relationships developed for the EPIC model. An important parameter required for this model is the P sorption capacity parameter (PSP). I...

Inferring soil salinity in a drip irrigation system from multi-configuration EMI measurements using adaptive Markov chain Monte Carlo

NASA Astrophysics Data System (ADS)

Zaib Jadoon, Khan; Umer Altaf, Muhammad; McCabe, Matthew Francis; Hoteit, Ibrahim; Muhammad, Nisar; Moghadas, Davood; Weihermüller, Lutz

2017-10-01

A substantial interpretation of electromagnetic induction (EMI) measurements requires quantifying optimal model parameters and uncertainty of a nonlinear inverse problem. For this purpose, an adaptive Bayesian Markov chain Monte Carlo (MCMC) algorithm is used to assess multi-orientation and multi-offset EMI measurements in an agriculture field with non-saline and saline soil. In MCMC the posterior distribution is computed using Bayes' rule. The electromagnetic forward model based on the full solution of Maxwell's equations was used to simulate the apparent electrical conductivity measured with the configurations of EMI instrument, the CMD Mini-Explorer. Uncertainty in the parameters for the three-layered earth model are investigated by using synthetic data. Our results show that in the scenario of non-saline soil, the parameters of layer thickness as compared to layers electrical conductivity are not very informative and are therefore difficult to resolve. Application of the proposed MCMC-based inversion to field measurements in a drip irrigation system demonstrates that the parameters of the model can be well estimated for the saline soil as compared to the non-saline soil, and provides useful insight about parameter uncertainty for the assessment of the model outputs.

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

NASA Astrophysics Data System (ADS)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.

Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

NASA Astrophysics Data System (ADS)

Drusch, M.

2007-02-01

Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

Using a Mechanistic Reactive Transport Model to Represent Soil Organic Matter Dynamics and Climate Sensitivity

NASA Astrophysics Data System (ADS)

Guerry, N.; Riley, W. J.; Maggi, F.; Torn, M. S.; Kleber, M.

2011-12-01

The nature of long term Soil Organic Matter (SOM) dynamics is uncertain and the mechanisms involved are crudely represented in site, regional, and global models. Recent work challenging the paradigm that SOM is stabilized because of its sequential transformations to more intrinsically recalcitrant compounds motivated us to develop a mechanistic modeling framework that can be used to test hypotheses of SOM dynamics. We developed our C cycling model in TOUGHREACT, an established 3-dimensional reactive transport solver that accounts for multiple phases (aqueous, gaseous, sorbed), multiple species, advection and diffusion, and multiple microbial populations. Energy and mass exchange through the soil boundaries are accounted for via ground heat flux, rainfall, C sources (e.g., exudation, woody, leaf, root litter) and C losses (e.g., CO2 emissions and DOC deep percolation). SOM is categorized according to the various types of compounds commonly found in the above mentioned C sources and microbial byproducts, including poly- and monosaccharides, lignin, amino compounds, organic acids, nucleic acids, lipids, and phenols. Each of these compounds is accounted for by one or more representative species in the model. A reaction network was developed to describe the microbially-mediated processes and chemical interactions of these species, including depolymerization, microbial assimilation, respiration and deposition of byproducts, and incorporation of dead biomass into SOM stocks. Enzymatic reactions are characterized by Michaelis-Menten kinetics, with maximum reaction rates determined by the species' O/C ratio. Microbial activity is further regulated by soil moisture content, O2 availability, pH, and temperature. For the initial set of simulations, literature values were used to constrain microbial Monod parameters, Michaelis-Menten parameters, sorption parameters, physical protection, partitioning of microbial byproducts, and partitioning of litter inputs, although there is substantial uncertainty in how these relationships should be represented. We also developed several other model formulations, including one that represents SOM in pools of varying decomposability, but lacking explicit protection mechanisms. We tested the model against several observational and experimental datasets. An important conclusion of our analysis is that although several of the model structural formulations were able to represent the bulk SOM observations, including 14C vertical profiles, the temperature, moisture, and soil chemistry sensitivity of decomposition varied strongly between each formulation. Finally, we applied the model to design observations that would be required to better constrain process representation and improve predictions of changes in SOM under changing climate.

Fine and coarse root parameters from mature black spruce displaying genetic x soil moisture interaction in growth

Treesearch

John E. Major; Kurt H. Johnsen; Debby C. Barsi; Moira Campbell

2012-01-01

Fine and coarse root biomass, C, and N mass parameters were assessed by root size and soil depths from soil cores in plots of 32-year-old black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) from four full-sib families studied previously for drought tolerance and differential productivity on a dry and wet...

Inventory of File ndas.t12z.awip3d00.tm03.grib2

Science.gov Websites

parameter in canopy conductance [Fraction] 529 surface RCSOL analysis Soil moisture parameter in canopy -0.1 m below ground TSOIL analysis Soil Temperature Validation to deprecate [K] 532 0-0.1 m below ground SOILW analysis Volumetric Soil Moisture Content [Fraction] 533 0.1-0.4 m below ground TSOIL

Spatial distribution patterns of soil mite communities and their relationships with edaphic factors in a 30-year tillage cornfield in northeast China.

PubMed

Liu, Jie; Gao, Meixiang; Liu, Jinwen; Guo, Yuxi; Liu, Dong; Zhu, Xinyu; Wu, Donghui

2018-01-01

Spatial distribution is an important topic in community ecology and a key to understanding the structure and dynamics of populations and communities. However, the available information related to the spatial patterns of soil mite communities in long-term tillage agroecosystems remains insufficient. In this study, we examined the spatial patterns of soil mite communities to explain the spatial relationships between soil mite communities and soil parameters. Soil fauna were sampled three times (August, September and October 2015) at 121 locations arranged regularly within a 400 m × 400 m monitoring plot. Additionally, we estimated the physical and chemical parameters of the same sampling locations. The distribution patterns of the soil mite community and the edaphic parameters were analyzed using a range of geostatistical tools. Moran's I coefficient showed that, during each sampling period, the total abundance of the soil mite communities and the abundance of the dominant mite populations were spatially autocorrelated. The soil mite communities demonstrated clear patchy distribution patterns within the study plot. These patterns were sampling period-specific. Cross-semivariograms showed both negative and positive cross-correlations between soil mite communities and environmental factors. Mantel tests showed a significant and positive relationship between soil mite community and soil organic matter and soil pH only in August. This study demonstrated that in the cornfield, the soil mite distribution exhibited strong or moderate spatial dependence, and the mites formed patches with sizes less than one hundred meters. In addition, in this long-term tillage agroecosystem, soil factors had less influence on the observed pattern of soil mite communities. Further experiments that take into account human activity and spatial factors should be performed to study the factors that drive the spatial distribution of soil microarthropods.

Towards soil property retrieval from space: Proof of concept using in situ observations

NASA Astrophysics Data System (ADS)

Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph

2014-05-01

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.

Evaluation of Uncertainty in Constituent Input Parameters for Modeling the Fate of RDX

DTIC Science & Technology

2015-07-01

exercise was to evaluate the importance of chemical -specific model input parameters, the impacts of their uncertainty, and the potential benefits of... chemical -specific inputs for RDX that were determined to be sensitive with relatively high uncertainty: these included the soil-water linear...Koc for organic chemicals . The EFS values provided for log Koc of RDX were 1.72 and 1.95. OBJECTIVE: TREECS™ (http://el.erdc.usace.army.mil/treecs

Morpho-physiological analysis of tolerance to aluminum toxicity in rice varieties of North East India

PubMed Central

Awasthi, Jay Prakash; Saha, Bedabrata; Regon, Preetom; Sahoo, Smita; Chowra, Umakanta; Pradhan, Amit; Roy, Anupam; Panda, Sanjib Kumar

2017-01-01

Aluminum (Al) is the third most abundant metal in earth crust, whose chemical form is mainly dependent on soil pH. The most toxic form of Al with respect to plants is Al3+, which exists in soil pH <5. Acidic soil significantly limits crop production mainly due to Al3+ toxicity worldwide, impacting approximately 50% of the world’s arable land (in North-Eastern India 80% soil are acidic). Al3+ toxicity in plants ensues root growth inhibition leading to less nutrient and water uptake impacting crop productivity as a whole. Rice is one of the chief grains which constitutes the staple food of two-third of the world population including India and is not untouched by Al3+ toxicity. Al contamination is a critical constraint to plant production in agricultural soils of North East India. 24 indigenous Indica rice varieties (including Badshahbhog as tolerant check and Mashuri as sensitive check) were screened for Al stress tolerance in hydroponic plant growth system. Results show marked difference in growth parameters (relative growth rate, Root tolerance index, fresh and dry weight of root) of rice seedlings due to Al (100 μM) toxicity. Al3+ uptake and lipid peroxidation level also increased concomitantly under Al treatment. Histochemical assay were also performed to elucidate uptake of aluminum, loss of membrane integrity and lipid peroxidation, which were found to be more in sensitive genotypes at higher Al concentration. This study revealed that aluminum toxicity is a serious harmful problem for rice crop productivity in acid soil. Based on various parameters studied it’s concluded that Disang is a comparatively tolerant variety whereas Joymati a sensitive variety. Western blot hybridization further strengthened the claim, as it demonstrated more accumulation of Glutathione reductase (GR) protein in Disang rice variety than Joymati under stressed condition. This study also observed that the emergence of lethal toxic symptoms occurs only after 48h irrespective of the dose used in the study. PMID:28448589

Modeling the Environmental Impacts of Potential Oil Pipeline Leaks in the PÁRAMO Region upon the Water Supply for Quito, Ecuador

NASA Astrophysics Data System (ADS)

Gherasim, J.; Sanjinez Guzman, V.; Emerman, S. H.; Tebbs, K. C.

2017-12-01

The Trans-Ecuadorian Pipeline carries crude oil from oilfields in eastern Ecuador to refineries on the Pacific coast, crossing the Páramo region, an alpine tundra ecosystem within the province of Pichincha, which also serves as the water supply for the capital city of Quito. The objective of this study has been to create a model for predicting the likelihood that the effects of a crude oil spill in the Páramo region would impact the water supply of Quito by comparing the residence times of organic compounds in soil with the time required for microbial degradation. A custom MATLAB script included linear partitioning of multiple organic compounds among the water, air, soil and NAPL phases. The three organic compounds considered were anthracene, benzene, and naphthalene. The relevant soil parameters for the Páramo region were obtained from the ISRIC-WISE Harmonized Global Soil Profile Dataset. The soil organic matter content is a critical parameter that was estimated from a very small number of measurements. Residence time half-lives were calculated for depths of penetration of the initial spill ranging from 0.1-5 m. For a depth of penetration of 1 m, residence time half-lives for benzene, naphthalene and anthracene were 1.5, 23.1 and 247.8 years, respectively. Comparing with typical biodegradation half-lives of 10-730 days for benzene, 1-258 days for naphthalene, and 199-252 days for anthracene, it can be seen that penetration to groundwater and transport to the reservoir that supplies water to Quito is unlikely for naphthalene and anthracene, but is a distinct possibility for benzene. Current modeling involves including the effect of volatilization within the soil and improving the estimates of biodegradation rates within an alpine tundra ecosystem. Further results will be reported at the meeting.

Supporting the operational use of process based hydrological models and NASA Earth Observations for use in land management and post-fire remediation through a Rapid Response Erosion Database (RRED).

NASA Astrophysics Data System (ADS)

Miller, M. E.; Elliot, W.; Billmire, M.; Robichaud, P. R.; Banach, D. M.

2017-12-01

We have built a Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) for the continental United States to allow land managers to access properly formatted spatial model inputs for the Water Erosion Prediction Project (WEPP). Spatially-explicit process-based models like WEPP require spatial inputs that include digital elevation models (DEMs), soil, climate and land cover. The online database delivers either a 10m or 30m USGS DEM, land cover derived from the Landfire project, and soil data derived from SSURGO and STATSGO datasets. The spatial layers are projected into UTM coordinates and pre-registered for modeling. WEPP soil parameter files are also created along with linkage files to match both spatial land cover and soils data with the appropriate WEPP parameter files. Our goal is to make process-based models more accessible by preparing spatial inputs ahead of time allowing modelers to focus on addressing scenarios of concern. The database provides comprehensive support for post-fire hydrological modeling by allowing users to upload spatial soil burn severity maps, and within moments returns spatial model inputs. Rapid response is critical following natural disasters. After moderate and high severity wildfires, flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies. Mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fire, runoff, and erosion risks also are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. The database has been used to help assess and plan remediation on over a dozen wildfires in the Western US. Future plans include expanding spatial coverage, improving model input data and supporting additional models. Our goal is to facilitate the use of the best possible datasets and models to support the conservation of soil and water.

A universal method to assess the potential of phosphorus loss from soil to aquatic ecosystems.

PubMed

Pöthig, Rosemarie; Behrendt, Horst; Opitz, Dieter; Furrer, Gerhard

2010-02-01

Phosphorus loss from terrestrial to the aquatic ecosystems contributes to eutrophication of surface waters. To maintain the world's vital freshwater ecosystems, the reduction of eutrophication is crucial. This needs the prevention of overfertilization of agricultural soils with phosphorus. However, the methods of risk assessment for the P loss potential from soils lack uniformity and are difficult for routine analysis. Therefore, the efficient detection of areas with a high risk of P loss requires a simple and universal soil test method that is cost effective and applicable in both industrialized and developing countries. Soils from areas which varied highly in land use and soil type were investigated regarding the degree of P saturation (DPS) as well as the equilibrium P concentration (EPC(0)) and water-soluble P (WSP) as indicators for the potential of P loss. The parameters DPS and EPC(0) were determined from P sorption isotherms. Our investigation of more than 400 soil samples revealed coherent relationships between DPS and EPC(0) as well as WSP. The complex parameter DPS, characterizing the actual P status of soil, is accessible from a simple standard measurement of WSP based on the equation [Formula: see text]. The parameter WSP in this equation is a function of remaining phosphorous sorption capacity/total accumulated phosphorous (SP/TP). This quotient is independent of soil type due to the mutual compensation of the factors SP and TP. Thus, the relationship between DPS and WSP is also independent of soil type. The degree of P saturation, which reflects the actual state of P fertilization of soil, can be calculated from the easily accessible parameter WSP. Due to the independence from soil type and land use, the relation is valid for all soils. Values of WSP, which exceed 5 mg P/kg soil, signalize a P saturation between 70% and 80% and thus a high risk of P loss from soil. These results reveal a new approach of risk assessment for P loss from soils to surface and ground waters. The consequent application of this method may globally help to save the vital resources of our terrestrial and aquatic ecosystems.

Soil Erodibility Parameters Under Various Cropping Systems of Maize

NASA Astrophysics Data System (ADS)

van Dijk, P. M.; van der Zijp, M.; Kwaad, F. J. P. M.

1996-08-01

For four years, runoff and soil loss from seven cropping systems of fodder maize have been measured on experimental plots under natural and simulated rainfall. Besides runoff and soil loss, several variables have also been measured, including rainfall kinetic energy, degree of slaking, surface roughness, aggregate stability, soil moisture content, crop cover, shear strength and topsoil porosity. These variables explain a large part of the variance in measured runoff, soil loss and splash erosion under the various cropping systems. The following conclusions were drawn from the erosion measurements on the experimental plots (these conclusions apply to the spatial level at which the measurements were carried out). (1) Soil tillage after maize harvest strongly reduced surface runoff and soil loss during the winter; sowing of winter rye further reduced winter erosion, though the difference with a merely tilled soil is small. (2) During spring and the growing season, soil loss is reduced strongly if the soil surface is partly covered by plant residues; the presence of plant residue on the surface appeared to be essential in achieving erosion reduction in summer. (3) Soil loss reductions were much higher than runoff reductions; significant runoff reduction is only achieved by the straw system having flat-lying, non-fixed plant residue on the soil surface; the other systems, though effective in reducing soil loss, were not effective in reducing runoff.

Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters.

PubMed

Bousbih, Safa; Zribi, Mehrez; Lili-Chabaane, Zohra; Baghdadi, Nicolas; El Hajj, Mohammad; Gao, Qi; Mougenot, Bernard

2017-11-14

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects.

Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters

PubMed Central

Bousbih, Safa; Lili-Chabaane, Zohra; El Hajj, Mohammad; Gao, Qi

2017-01-01

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects. PMID:29135929

Nonlinear soil parameter effects on dynamic embedment of offshore pipeline on soft clay

NASA Astrophysics Data System (ADS)

Yu, Su Young; Choi, Han Suk; Lee, Seung Keon; Park, Kyu-Sik; Kim, Do Kyun

2015-06-01

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

Enzyme activities by indicator of quality in organic soil

NASA Astrophysics Data System (ADS)

Raigon Jiménez, Mo; Fita, Ana Delores; Rodriguez Burruezo, Adrián

2016-04-01

The analytical determination of biochemical parameters, as soil enzyme activities and those related to the microbial biomass is growing importance by biological indicator in soil science studies. The metabolic activity in soil is responsible of important processes such as mineralization and humification of organic matter. These biological reactions will affect other key processes involved with elements like carbon, nitrogen and phosphorus , and all transformations related in soil microbial biomass. The determination of biochemical parameters is useful in studies carried out on organic soil where microbial processes that are key to their conservation can be analyzed through parameters of the metabolic activity of these soils. The main objective of this work is to apply analytical methodologies of enzyme activities in soil collections of different physicochemical characteristics. There have been selective sampling of natural soils, organic farming soils, conventional farming soils and urban soils. The soils have been properly identified conserved at 4 ° C until analysis. The enzyme activities determinations have been: catalase, urease, cellulase, dehydrogenase and alkaline phosphatase, which bring together a representative group of biological transformations that occur in the soil environment. The results indicate that for natural and agronomic soil collections, the values of the enzymatic activities are within the ranges established for forestry and agricultural soils. Organic soils are generally higher level of enzymatic, regardless activity of the enzyme involved. Soil near an urban area, levels of activities have been significantly reduced. The vegetation cover applied to organic soils, results in greater enzymatic activity. So the quality of these soils, defined as the ability to maintain their biological productivity is increased with the use of cover crops, whether or spontaneous species. The practice of cover based on legumes could be used as an ideal choice for the recovery of degraded soils, because these soils have the highest levels of enzymatic activities.

Antecedent wetness conditions based on ERS scatterometer data

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2009-01-01

SummarySoil moisture is widely recognized as a key parameter in environmental processes mainly for the role of rainfall partitioning into runoff and infiltration. Therefore, for storm rainfall-runoff modeling the estimation of the antecedent wetness conditions ( AWC) is one of the most important aspect. In this context, this study investigates the potential of scatterometer on board of the ERS satellites for the assessment of wetness conditions in three Tiber sub-catchments (Central Italy), of which one includes an experimental area for soil moisture monitoring. The satellite soil moisture data are taken from the ERS/METOP soil moisture archive. First, the scatterometer-derived soil wetness index ( SWI) data are compared with two on-site soil moisture data sets acquired by different methodologies on areas of different extension ranging from 0.01 km 2 to ˜60 km 2. Moreover, the reliability of SWI to estimate the AWC at a catchment scale is investigated considering the relationship between SWI and the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. Several flood events occurred from 1992 to 2005 are selected for this purpose. Specifically, the performance of the SWI for S estimation is compared with two antecedent precipitation indices ( API) and one base flow index ( BFI). The S values obtained through the observed direct runoff volume and rainfall depth are used as benchmark. Results show the great reliability of the SWI for the estimation of wetness conditions both at the plot and catchment scale despite the complex orography of the investigated areas. As far as the comparison with on site soil moisture data set is concerned, the SWI is found quite reliable in representing the soil moisture at layer depth of 15 cm, with a mean correlation coefficient equal to 0.81. The characteristic time length parameter variations, as expected, is depended on soil type, with values in accordance with previous studies. In terms of AWC assessment at catchment scale, based on selected flood events, the SWI is found highly correlated with the observed maximum potential retention of the SCS-CN method with a correlation coefficient R equal to -0.90. Besides, SWI in representing the AWC of the three investigated catchments, outperformed both API indices, poorly representative of AWC, and BFI. Finally, the classical SCS-CN method applied for direct runoff depth estimation, where S is assessed by SWI, provided good performance with a percentage error not exceeding ˜25% for 80% of investigated rainfall-runoff events.

Ground Data System Analysis Tools to Track Flight System State Parameters for the Mars Science Laboratory (MSL) and Beyond

NASA Technical Reports Server (NTRS)

Allard, Dan; Deforrest, Lloyd

2014-01-01

Flight software parameters enable space mission operators fine-tuned control over flight system configurations, enabling rapid and dynamic changes to ongoing science activities in a much more flexible manner than can be accomplished with (otherwise broadly used) configuration file based approaches. The Mars Science Laboratory (MSL), Curiosity, makes extensive use of parameters to support complex, daily activities via commanded changes to said parameters in memory. However, as the loss of Mars Global Surveyor (MGS) in 2006 demonstrated, flight system management by parameters brings with it risks, including the possibility of losing track of the flight system configuration and the threat of invalid command executions. To mitigate this risk a growing number of missions have funded efforts to implement parameter tracking parameter state software tools and services including MSL and the Soil Moisture Active Passive (SMAP) mission. This paper will discuss the engineering challenges and resulting software architecture of MSL's onboard parameter state tracking software and discuss the road forward to make parameter management tools suitable for use on multiple missions.

Experimental study of nonlinear ultrasonic behavior of soil materials during the compaction.

PubMed

Chen, Jun; Wang, Hao; Yao, Yangping

2016-07-01

In this paper, the nonlinear ultrasonic behavior of unconsolidated granular medium - soil during the compaction is experimentally studied. The second harmonic generation technique is adopted to investigate the change of microstructural void in materials during the compaction process of loose soils. The nonlinear parameter is measured with the change of two important environmental factors i.e. moisture content and impact energy of compaction. It is found the nonlinear parameter of soil material presents a similar variation pattern with the void ratio of soil samples, corresponding to the increased moisture content and impact energy. A same optimum moisture content is found by observing the variation of nonlinear parameter and void ratio with respect to moisture content. The results indicate that the unconsolidated soil is manipulated by a strong material nonlinearity during the compaction procedure. The developed experimental technique based on the second harmonic generation could be a fast and convenient testing method for the determination of optimum moisture content of soil materials, which is very useful for the better compaction effect of filled embankment for civil infrastructures in-situ. Copyright © 2016 Elsevier B.V. All rights reserved.

Soil Parameters Drive the Structure, Diversity and Metabolic Potentials of the Bacterial Communities Across Temperate Beech Forest Soil Sequences.

PubMed

Jeanbille, M; Buée, M; Bach, C; Cébron, A; Frey-Klett, P; Turpault, M P; Uroz, S

2016-02-01

Soil and climatic conditions as well as land cover and land management have been shown to strongly impact the structure and diversity of the soil bacterial communities. Here, we addressed under a same land cover the potential effect of the edaphic parameters on the soil bacterial communities, excluding potential confounding factors as climate. To do this, we characterized two natural soil sequences occurring in the Montiers experimental site. Spatially distant soil samples were collected below Fagus sylvatica tree stands to assess the effect of soil sequences on the edaphic parameters, as well as the structure and diversity of the bacterial communities. Soil analyses revealed that the two soil sequences were characterized by higher pH and calcium and magnesium contents in the lower plots. Metabolic assays based on Biolog Ecoplates highlighted higher intensity and richness in usable carbon substrates in the lower plots than in the middle and upper plots, although no significant differences occurred in the abundance of bacterial and fungal communities along the soil sequences as assessed using quantitative PCR. Pyrosequencing analysis of 16S ribosomal RNA (rRNA) gene amplicons revealed that Proteobacteria, Acidobacteria and Bacteroidetes were the most abundantly represented phyla. Acidobacteria, Proteobacteria and Chlamydiae were significantly enriched in the most acidic and nutrient-poor soils compared to the Bacteroidetes, which were significantly enriched in the soils presenting the higher pH and nutrient contents. Interestingly, aluminium, nitrogen, calcium, nutrient availability and pH appeared to be the best predictors of the bacterial community structures along the soil sequences.

Preliminary study of soil permeability properties using principal component analysis

NASA Astrophysics Data System (ADS)

Yulianti, M.; Sudriani, Y.; Rustini, H. A.

2018-02-01

Soil permeability measurement is undoubtedly important in carrying out soil-water research such as rainfall-runoff modelling, irrigation water distribution systems, etc. It is also known that acquiring reliable soil permeability data is rather laborious, time-consuming, and costly. Therefore, it is desirable to develop the prediction model. Several studies of empirical equations for predicting permeability have been undertaken by many researchers. These studies derived the models from areas which soil characteristics are different from Indonesian soil, which suggest a possibility that these permeability models are site-specific. The purpose of this study is to identify which soil parameters correspond strongly to soil permeability and propose a preliminary model for permeability prediction. Principal component analysis (PCA) was applied to 16 parameters analysed from 37 sites consist of 91 samples obtained from Batanghari Watershed. Findings indicated five variables that have strong correlation with soil permeability, and we recommend a preliminary permeability model, which is potential for further development.

Linear Regression between CIE-Lab Color Parameters and Organic Matter in Soils of Tea Plantations

NASA Astrophysics Data System (ADS)

Chen, Yonggen; Zhang, Min; Fan, Dongmei; Fan, Kai; Wang, Xiaochang

2018-02-01

To quantify the relationship between the soil organic matter and color parameters using the CIE-Lab system, 62 soil samples (0-10 cm, Ferralic Acrisols) from tea plantations were collected from southern China. After air-drying and sieving, numerical color information and reflectance spectra of soil samples were measured under laboratory conditions using an UltraScan VIS (HunterLab) spectrophotometer equipped with CIE-Lab color models. We found that soil total organic carbon (TOC) and nitrogen (TN) contents were negatively correlated with the L* value (lightness) ( r = -0.84 and -0.80, respectively), a* value (correlation coefficient r = -0.51 and -0.46, respectively) and b* value ( r = -0.76 and -0.70, respectively). There were also linear regressions between TOC and TN contents with the L* value and b* value. Results showed that color parameters from a spectrophotometer equipped with CIE-Lab color models can predict TOC contents well for soils in tea plantations. The linear regression model between color values and soil organic carbon contents showed it can be used as a rapid, cost-effective method to evaluate content of soil organic matter in Chinese tea plantations.

Effects of poultry manure on soil biochemical properties in phthalic acid esters contaminated soil.

PubMed

Gao, Jun; Qin, Xiaojian; Ren, Xuqin; Zhou, Haifeng

2015-12-01

This study aimed to evaluate the effects of poultry manure (PM) on soil biological properties in DBP- and DEHP-contaminated soils. An indoor incubation experiment was conducted. Soil microbial biomass C (Cmic), soil enzymatic activities, and microbial phospholipid fatty acid (PLFA) concentrations were measured during incubation period. The results indicated that except alkaline phosphatase activity, DBP and DEHP had negative effects on Cmic, dehydrogenase, urease, protease activities, and contents of total PLFA. However, 5 % PM treatment alleviated the negative effects of PAEs on the above biochemical parameters. In DBP-contaminated soil, 5 % PM amendment even resulted in dehydroenase activity and Cmic content increasing by 17.8 and 11.8 % on the day 15 of incubation, respectively. During the incubation periods, the total PLFA contents decreased maximumly by 17.2 and 11.6 % in DBP- and DEHP-contaminated soils without PM amendments, respectively. Compared with those in uncontaminated soil, the total PLFA contents increased slightly and the value of bacPLFA/fugalPLFA increased significantly in PAE-contaminated soils with 5 % PM amendment. Nevertheless, in both contaminated soils, the effects of 5 % PM amendment on the biochemical parameters were not observed with 10 % PM amendment. In 10 % PM-amended soils, DBP and DEHP had little effect on Cmic, soil enzymatic activities, and microbial community composition. At the end of incubation, the effects of PAEs on these parameters disappeared, irrespective of PM amendment. The application of PM ameliorated the negative effect of PAEs on soil biological environment. However, further work is needed to study the effect of PM on soil microbial gene expression in order to explain the change mechanisms of soil biological properties.

Application of Terahertz Radiation to Soil Measurements: Initial Results

PubMed Central

Dworak, Volker; Augustin, Sven; Gebbers, Robin

2011-01-01

Developing soil sensors with the possibility of continuous online measurement is a major challenge in soil science. Terahertz (THz) electromagnetic radiation may provide the opportunity for the measurement of organic material density, water content and other soil parameters at different soil depths. Penetration depth and information content is important for a functional soil sensor. Therefore, we present initial research on the analysis of absorption coefficients of four different soil samples by means of THz transmission measurements. An optimized soil sample holder to determine absorption coefficients was used. This setup improves data acquisition because interface reflections can be neglected. Frequencies of 340 GHz to 360 GHz and 1.627 THz to 2.523 THz provided information about an existing frequency dependency. The results demonstrate the potential of this THz approach for both soil analysis and imaging of buried objects. Therefore, the THz approach allows different soil samples to be distinguished according to their different absorption properties so that relations among soil parameters may be established in future. PMID:22163737

Using Weighted Least Squares Regression for Obtaining Langmuir Sorption Constants

USDA-ARS?s Scientific Manuscript database

One of the most commonly used models for describing phosphorus (P) sorption to soils is the Langmuir model. To obtain model parameters, the Langmuir model is fit to measured sorption data using least squares regression. Least squares regression is based on several assumptions including normally dist...

An improved Rosetta pedotransfer function and evaluation in earth system models

NASA Astrophysics Data System (ADS)

Zhang, Y.; Schaap, M. G.

2017-12-01

Soil hydraulic parameters are often difficult and expensive to measure, leading to the pedotransfer functions (PTFs) an alternative to predict those parameters. Rosetta (Schaap et al., 2001, denoted as Rosetta1) are widely used PTFs, which is based on artificial neural network (ANN) analysis coupled with the bootstrap re-sampling method, allowing the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), as well as their uncertainties. We present an improved hierarchical pedotransfer functions (Rosetta3) that unify the VG water retention and Ks submodels into one, thus allowing the estimation of uni-variate and bi-variate probability distributions of estimated parameters. Results show that the estimation bias of moisture content was reduced significantly. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code are available online. Based on different soil water retention equations, there are diverse PTFs used in different disciplines of earth system modelings. PTFs based on Campbell [1974] or Clapp and Hornberger [1978] are frequently used in land surface models and general circulation models, while van Genuchten [1980] based PTFs are more widely used in hydrology and soil sciences. We use an independent global scale soil database to evaluate the performance of diverse PTFs used in different disciplines of earth system modelings. PTFs are evaluated based on different soil characteristics and environmental characteristics, such as soil textural data, soil organic carbon, soil pH, as well as precipitation and soil temperature. This analysis provides more quantitative estimation error information for PTF predictions in different disciplines of earth system modelings.

Soil-plant-microbial relations in hydrothermally altered soils of Northern California

USGS Publications Warehouse

Blecker, S.W.; Stillings, L.L.; DeCrappeo, N.M.; Ippolito, J.A.

2014-01-01

Soils developed on relict hydrothermally altered soils throughout the Western USA present unique opportunities to study the role of geology on above and belowground biotic activity and composition. Soil and vegetation samples were taken at three unaltered andesite and three hydrothermally altered (acid-sulfate) sites located in and around Lassen VolcanicNational Park in northeastern California. In addition, three different types of disturbed areas (clearcut, thinned, and pipeline) were sampled in acid-sulfate altered sites. Soils were sampled (0–15 cm) in mid-summer 2010 from both under-canopy and between-canopy areas within each of the sites. Soils were analyzed for numerous physical and chemical properties along with soil enzyme assays, C and N mineralization potential, microbial biomass-C and C-substrate utilization. Field vegetation measurements consisted of canopy cover by life form (tree, shrub, forb, and grass), tree and shrub density, and above-ground net primary productivity of the understory. Overall, parameters at the clearcut sites were more similar to the unaltered sites, while parameters at the thinned and pipeline sites were more similar to the altered sites. We employed principal components analysis (PCA) to develop two soil quality indices (SQI) to help quantify the differences among the sites: one based on the correlation between soil parameters and canopy cover, and the second based on six sub-indices. Soil quality indices developed in these systems could provide a means for monitoring and identifying key relations between the vegetation, soils, and microorganisms.

The response of arid soil communities to climate change: Chapter 8

USGS Publications Warehouse

Steven, Blaire; McHugh, Theresa Ann; Reed, Sasha C.

2017-01-01

Arid and semiarid ecosystems cover approximately 40% of Earth’s terrestrial surface and are present on each of the planet’s continents [1]. Drylands are characterized by their aridity, but there is substantial geographic, edaphic, and climatic variability among these vast ecosystems, and these differences underscore substantial variation in dryland soil microbial communities, as well as in the future climates predicted among arid and semiarid systems globally. Furthermore, arid ecosystems are commonly patchy at a variety of spatial scales [2,3]. Vascular plants are widely interspersed in drylands and bare soil, or soil that is covered with biological soil crusts, fill these spaces. The variability acts to further enhance spatial heterogeneity, as these different zones within dryland ecosystems differ in characteristics such as water retention, albedo, and nutrient cycling [4–6]. Importantly, the various soil patches of an arid landscape may be differentially sensitive to climate change. Soil communities are only active when enough moisture is available, and drylands show large spatial variability in soil moisture, with potentially long dry periods followed by pulses of moisture. The pulse dynamics associated with this wetting and drying affect the composition, structure, and function of dryland soil communities, and integrate biotic and abiotic processes via pulse-driven exchanges, interactions, transitions, and transfers. Climate change will likely alter the size, frequency, and intensity of future precipitation pulses, as well as influence non-rainfall sources of soil moisture, and aridland ecosystems are known to be highly sensitive to such climate variability. Despite great heterogeneity, arid ecosystems are united by a key parameter: a limitation in water availability. This characteristic may help to uncover unifying aspects of dryland soil responses to global change. The dryness of an ecosystem can be described by its aridity index (AI). Several AIs have been proposed, but the most widely used metrics determine the difference between average precipitation and potential evapotranspiration, where evapotranspiration is the sum of evaporation and plant transpiration, both of which move water from the ecosystem to the atmosphere [7–9]. Because evapotranspiration can be affected by various environmental factors such as temperature and incident radiation (Fig. 10.1), regions that receive the same average precipitation may have significantly different AI values [10,11]. Multiple studies have documented that mean annual precipitation, and thus AI, is highly correlated with biological diversity and net primary productivity [12–15]. Accordingly, AI is considered to be a central regulator of the diversity, structure, and productivity of an ecosystem, playing an especially influential role in arid ecosystems. Thus, the climate parameters that drive alterations in the AI of a region are likely to play an disproportionate role in shaping the response of arid soil communities to a changing climate. In this chapter we consider climate parameters that have been shown to be altered through climate change, with a focus on how these parameters are likely to affect dryland soil communities, including microorganisms and invertebrates. In particular, our goal is to highlight dryland soil community structure and function in the context of climate change, and we will focus on community relationships with increased atmospheric CO2 concentrations (a primary driver of climate change), temperature, and sources of soil moisture.

Characterization of soil spatial variability for site-specific management using soil electrical conductivity and other remotely sensed data

NASA Astrophysics Data System (ADS)

Bang, Jisu

Field-scale characterization of soil spatial variability using remote sensing technology has potential for achieving the successful implementation of site-specific management (SSM). The objectives of this study were to: (i) examine the spatial relationships between apparent soil electrical conductivity (EC a) and soil chemical and physical properties to determine if EC a could be useful to characterize soil properties related to crop productivity in the Coastal Plain and Piedmont of North Carolina; (ii) evaluate the effects of in-situ soil moisture variation on ECa mapping as a basis for characterization of soil spatial variability and as a data layer in cluster analysis as a means of delineating sampling zones; (iii) evaluate clustering approaches using different variable sets for management zone delineation to characterize spatial variability in soil nutrient levels and crop yields. Studies were conducted in two fields in the Piedmont and three fields in the Coastal Plain of North Carolina. Spatial measurements of ECa via electromagnetic induction (EMI) were compared with soil chemical parameters (extractable P, K, and micronutrients; pH, cation exchange capacity [CEC], humic matter or soil organic matter; and physical parameters (percentage sand, silt, and clay; and plant-available water [PAW] content; bulk density; cone index; saturated hydraulic conductivity [Ksat] in one of the coastal plain fields) using correlation analysis across fields. We also collected ECa measurements in one coastal plain field on four days with significantly different naturally occurring soil moisture conditions measured in five increments to 0.75 m using profiling time-domain reflectometry probes to evaluate the temporal variability of ECa associated with changes in in-situ soil moisture content. Nonhierarchical k-means cluster analysis using sensor-based field attributes including vertical ECa, near-infrared (NIR) radiance of bare-soil from an aerial color infrared (CIR) image, elevation, slope, and their combinations was performed to delineate management zones. The strengths and signs of the correlations between ECa and measured soil properties varied among fields. Few strong direct correlations were found between ECa and the soil chemical and physical properties studied (r2 < 0.50), but correlations improved considerably when zone mean ECa and zone means of selected soil properties among ECa zones were compared. The results suggested that field-scale ECa survey is not able to directly predict soil nutrient levels at any specific location, but could delimit distinct zones of soil condition among which soil nutrient levels differ, providing an effective basis for soil sampling on a zone basis. (Abstract shortened by UMI.)

Short-Term Effect of Vermicompost Application on Biological Properties of an Alkaline Soil with High Lime Content from Mediterranean Region of Turkey

PubMed Central

Uz, Ilker; Tavali, Ismail Emrah

2014-01-01

This study was conducted to investigate direct short-term impact of vermicompost on some soil biological properties by monitoring changes after addition of vermicompost as compared to farmyard manure in an alkaline soil with high lime content from semiarid Mediterranean region of Turkey. For this purpose, mixtures of soil and organic fertilizers in different doses were incubated under greenhouse condition. Soil samples collected in regular intervals were analyzed for biological parameters including dehydrogenase, β-glucosidase, urease, alkaline phosphatase activities, and total number of aerobic mesophilic bacteria. Even though soil dehydrogenase activity appeared to be dose-independent based on overall evaluation, organic amendments were found to elevate dehydrogenase activity when sampling periods are evaluated individually. β-glucosidase, urease, alkaline phosphatase activity, and aerobic mesophilic bacterial numbers in vermicompost treatments fluctuated but remained significantly above the control. A slight but statistically significant difference was detected between organic amendments in terms of urease activity. Vermicompost appeared to more significantly increase bacterial number in soil. Clearly, vermicompost has a potential to be used as an alternative to farmyard manure to improve and maintain soil biological activity in alkaline calcareous soils from the Mediterranean region of Turkey. Further studies are needed to assess its full potential for these soils. PMID:25254238

Expanding soil health assessment methods for agricultural systems of the southern great plains

USDA-ARS?s Scientific Manuscript database

In agricultural systems, soil health (also referred as soil quality) is critical for sustainable production and ecosystem services. Soil health analyses dependent upon singular parameters fail to account for the host of interactions occurring within the soil ecosystem. Soil health is in flux with m...

Assessing quality of citizen scientists’ soil texture estimates to evaluate land potential

USDA-ARS?s Scientific Manuscript database

Texture influences nearly all soil processes and is often the most measured parameter in soil science. Estimating soil texture is a universal and fundamental practice applied by resource scientists to classify and understand the behavior and management of soil systems. While trained soil scientist c...

Natural recovery of biological soil crusts after disturbance

USGS Publications Warehouse

Weber, Bettina; Bowker, Matthew A.; Zhang, Yuanming; Belnap, Jayne

2016-01-01

Natural recovery of biological soil crusts (biocrusts) is influenced by a number of different parameters, such as climate, soil conditions, the severity of disturbance, and the timing of disturbance relative to the climatic conditions. In recent studies, it has been shown that recovery is often not linear, but a highly dynamic process directly influenced by non-linear external parameters as extraordinary climatic conditions (e.g., particularly dry or wet year). Natural recovery often follows a general succession pattern, starting out with cyanobacteria and algae, which is then followed by lichens and bryophytes at a later stage. However, this general sequence can be altered by parameters like dust deposition, fire effects, and special climatic conditions as in fog deserts and under mesic climates. Recent studies have proposed that under favorable, stable soil conditions, the initial soil-stabilizing cyanobacteria-dominated succession stages may be omitted and moss-dominated biocrusts can develop in the initial phases of biocrust development. During natural recovery of biocrusts, soil properties change, e.g., soil nutrient and organic matter contents increase. Also, silt and clay contents of encrusted soils increase with biocrust maturity, which may be caused by two mechanisms, i.e. entrapment of fine soil particles by biocrusts and the new formation of smaller particles by weathering of the existing substrate.

Temporal changes of soil physic-chemical properties at different soil depths during larch afforestation by multivariate analysis of covariance.

PubMed

Wang, Hui-Mei; Wang, Wen-Jie; Chen, Huanfeng; Zhang, Zhonghua; Mao, Zijun; Zu, Yuan-Gang

2014-04-01

Soil physic-chemical properties differ at different depths; however, differences in afforestation-induced temporal changes at different soil depths are seldom reported. By examining 19 parameters, the temporal changes and their interactions with soil depth in a large chronosequence dataset (159 plots; 636 profiles; 2544 samples) of larch plantations were checked by multivariate analysis of covariance (MANCOVA). No linear temporal changes were found in 9 parameters (N, K, N:P, available forms of N, P, K and ratios of N: available N, P: available P and K: available K), while marked linear changes were found in the rest 10 parameters. Four of them showed divergent temporal changes between surface and deep soils. At surface soils, changing rates were 262.1 g·kg(-1)·year(-1) for SOM, 438.9 mg·g(-1)·year(-1) for C:P, 5.3 mg·g(-1)·year(-1) for C:K, and -3.23 mg·cm(-3)·year(-1) for bulk density, while contrary tendencies were found in deeper soils. These divergences resulted in much moderated or no changes in the overall 80-cm soil profile. The other six parameters showed significant temporal changes for overall 0-80-cm soil profile (P: -4.10 mg·kg(-1)·year(-1); pH: -0.0061 unit·year(-1); C:N: 167.1 mg·g(-1)·year(-1); K:P: 371.5 mg·g(-1) year(-1); N:K: -0.242 mg·g(-1)·year(-1); EC: 0.169 μS·cm(-1)·year(-1)), but without significant differences at different soil depths (P > 0.05). Our findings highlight the importance of deep soils in studying physic-chemical changes of soil properties, and the temporal changes occurred in both surface and deep soils should be fully considered for forest management and soil nutrient balance.

Residence time revisited: The role of radiocarbon in reactive transport modeling

NASA Astrophysics Data System (ADS)

Lawrence, C. R.; Druhan, J. L.; Schulz, M. S.

2016-12-01

In recent years, our changing understanding of the dominant controls on soil carbon (C) storage and stability has cast a greater emphasis on the importance of physical and hydrological processes. These shifts in our understanding of C cycling have fostered increasingly commonplace measurements of soil physical and hydrological parameters in soil C studies (e.g. specific surface area, quantitative mineralogy, porosity) that reflect the importance of microbial accessibility to soil C. As a result, we are now poised to reassess the applicability of our approaches for conceptualizing and modeling soil C dynamics, particularly with regard to our representation of soil C pools. The goal of this work is to explore how the quantity and turnover of C, as approximated by radiocarbon measurements, is mechanistically linked to the physical and hydrologic parameters of soils. We utilize a reactive transport (RT) approach to link hydrologic transport, geochemical transformations and microbial activity influencing the magnitude and residence time of different carbon pools under variably saturated conditions. A newly developed version of the CrunchTope software is used to explicitly simulate the coupled transport, transformation, fractionation and decay of the three isotopes of carbon (12C, 13C and 14C) through a mechanistic framework. We constrain this model with a high-resolution dataset of soil carbon content, stable isotope composition and radiocarbon ages as well as physical and hydrologic data measured from a chronosequence of soils located near Santa Cruz, California. The Santa Cruz dataset is highly amenable to this task in that it demonstrates both seasonal and millennial variations in soil C distributions and associated soil properties. We present data from a series of simulations examining the sensitivity of C stocks, fluxes and mean residence times to transient processes spanning a range of temporal scales, including redox conditions, fluid flow and the distribution of reactive mineral surfaces. The results of these efforts show the promise of a modeling approach where the varied residence time of soil C emerges from the dynamic physical and hydrologic properties of the model rather than from an a priori assignment of operationally defined pools.

[Effect of environmental factors on bacterial community structure in petroleum contaminated soil of Karamay oil field].

PubMed

Liang, Jianfang; Yang, Jiangke; Yang, Yang; Chao, Qunfang; Yin, Yalan; Zhao, Yaguan

2016-08-04

This study aimed to study the phylogenetic diversity and community structure of bacteria in petroleum contaminated soils from Karamay oil field, and to analyze the relationship between the community variation and the environment parameters, to provide a reference for bioremediation of petroleum contaminated soils. We collected samples from petroleum contaminated soils in 5 cm, 20 cm and 50 cm depth layers, and measured the environment parameters subsequently. We constructed three 16S rRNA gene clone libraries of these soil samples, and then determined the operation taxonomy units (OTUs) restriction fragment length polymorphism method, and finally sequenced the representative clones of every OUT. The diversity, richness and evenness index of the bacteria communities were calculated by using Biodap software. Neighbor-Joining phylogenetic tree was constructed based on 16S rRNA gene sequences of bacteria from Karamay oil field and the references from related environments. Canonial correspondence analysis (CCA) was used to analyze the relationship between environment parameters and species by using CANOCO 4.5 software. Environment parameters showed that 50 cm deep soil contained the highest amount of total nitrogen (TN) and total phosphorus (TP), whereas the 20 cm depth soil contained the lowest amount. The 5 cm depth soil contained the highest amount of total organic carbon (TOC), whereas the 50 cm depth soil contained the lowest amount. Among the 3 layers, 20 cm depth had the highest diversity and richness of bacteria, whereas the bacteria in 50 cm depth was the lowest. Phylogenic analyses suggested that the bacteria in Karamay oil field could be distributed into five groups at the level of phylum, Cluster I to V, respectively belong to Proteobacteria, Actinobacteria, Firmicute, Bacteroidetes, Planctomycetes. Cluster I accounts for 78.57% of all tested communities. CCA results showed that TN, TP, TOC significantly affected the bacteria community structure. Especially, TOC content is significantly related to the distribution of Pseudomonas. The petroleum-contaminated soil inhabited abundant of bacteria. The diversity index and spatial distribution of these communities were affected by the environment parameters in the soil.

Spectral element modelling of seismic wave propagation in visco-elastoplastic media including excess-pore pressure development

NASA Astrophysics Data System (ADS)

Oral, Elif; Gélis, Céline; Bonilla, Luis Fabián; Delavaud, Elise

2017-12-01

Numerical modelling of seismic wave propagation, considering soil nonlinearity, has become a major topic in seismic hazard studies when strong shaking is involved under particular soil conditions. Indeed, when strong ground motion propagates in saturated soils, pore pressure is another important parameter to take into account when successive phases of contractive and dilatant soil behaviour are expected. Here, we model 1-D seismic wave propagation in linear and nonlinear media using the spectral element numerical method. The study uses a three-component (3C) nonlinear rheology and includes pore-pressure excess. The 1-D-3C model is used to study the 1987 Superstition Hills earthquake (ML 6.6), which was recorded at the Wildlife Refuge Liquefaction Array, USA. The data of this event present strong soil nonlinearity involving pore-pressure effects. The ground motion is numerically modelled for different assumptions on soil rheology and input motion (1C versus 3C), using the recorded borehole signals as input motion. The computed acceleration-time histories show low-frequency amplification and strong high-frequency damping due to the development of pore pressure in one of the soil layers. Furthermore, the soil is found to be more nonlinear and more dilatant under triaxial loading compared to the classical 1C analysis, and significant differences in surface displacements are observed between the 1C and 3C approaches. This study contributes to identify and understand the dominant phenomena occurring in superficial layers, depending on local soil properties and input motions, conditions relevant for site-specific studies.

Spatial effects of aboveground biomass on soil ecological parameters and trace gas fluxes in a savannah ecosystem of Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Becker, Joscha; Gütlein, Adrian; Sierra Cornejo, Natalia; Kiese, Ralf; Hertel, Dietrich; Kuzyakov, Yakov

2015-04-01

The savannah biome is a hotspot for biodiversity and wildlife conservation in Africa and recently got in the focus of research on carbon sequestration. Savannah ecosystems are under strong pressure from climate and land-use change, especially around populous areas like the Mt. Kilimanjaro region. Savannah vegetation in this area consists of grassland with isolated trees and is therefore characterized by high spatial variation of canopy cover, aboveground biomass and root structure. Canopy structure is known to affect microclimate, throughfall and evapotranspiration and thereby controls soil moisture conditions. Consequently, the canopy structure is a major regulator for soil ecological parameters and soil-atmospheric trace gas exchange (CO2, N2O, CH4) in water limited environments. The spatial distribution of these parameters and the connection between above and belowground processes are important to understand and predict ecosystem changes and estimate its vulnerability. Our objective was to determine trends and changes of soil parameters and relate their spatial variability to the vegetation structure. We chose three trees from each of the two most dominant species (Acacia nilotica and Balanites aegyptiaca) in our research area. For each tree, we selected transects with nine sampling points of the same relative distances to the stem. Distances were calculated in relation to the crown radius. At these each sampling point a soil core was taken and separated in 0-10 cm and 10-30 cm depth. We measured soil carbon (C) and nitrogen (N) storage, microbial biomass carbon C and N, soil respiration as well as root biomass and -density, soil temperature and soil water content. Each tree was characterized by crown spread, leaf area index and basal area. Preliminary results show that C and N stocks decreased about 50% with depth independently of distance to the tree. Soil water content under the tree crown increased with depth while it decreased under grass cover. Microbial Biomass C and N in the upper 10 cm decreased with distance (C: r²=0.22, p<0.001; N: r²=0.3, p<0.001) as well as total soil respiration. This decrease was affected by tree size but independent from tree species. We conclude that savannah ecosystems exhibit a large spatial variability of soil parameters within the upper horizons which is strongly depend on the structure of aboveground biomass.

Indicators of grazing impact in Inner Mongolian steppe ecosystems

NASA Astrophysics Data System (ADS)

Blank, B.; Breuer, L.; Butterbach-Bahl, K.; Frede, H.-G.

2009-04-01

The DFG research group 536 MAGIM (Matter fluxes in grasslands of Inner Mongolia as influenced by stocking rate) investigates the influence of grazing intensity on matter and water cycles in grazed steppe ecosystems of Inner Mongolia. This Sino-German co-operation applies an interdisciplinary approach to investigate major ecosystem functions and how they are affected by grazing and overgrazing. Within the research group an indicator system is developed to systemize the feedback of ecosystem parameters to the influence of grazing and to analyse, which parameter or parameter group reacts most sensitively. Parameters were measured at up to five different grazing intensities (from ungrazed to heavy grazed) and are related to four thematic indicator groups (plant productivity, atmosphere, pedosphere, hydrosphere). The parameters were scaled to allow assessing the influence of grazing intensity between different sets of parameters. For this the average value of a parameter at the lowest grazing intensity (ungrazed) was set 100%, so that the values at the other intensities could be scaled scaled adequately. Then the difference between highest and lowest grazing intensity was determined. According to this difference the influence of grazing was characterized as weak (< 20% difference), medium (20-40%), strong (40-60%) and very strong (> 60%). Impact of grazing on the parameters will be marked as weak (w), medium (m), strong (s) and very strong (vs) in the text. The group plant productivity includes the vegetation parameters aboveground biomass and belowground biomass. Belowground biomass (s) was significantly different between grazing treatments with the highest value at the ungrazed site (399.00 g m-2 a-1) and the lowest at the heavy grazed site (208.00 g m-2 a-1). Aboveground biomass (m) ranged between 91.33-131.67 g m-2 a-1 and differed significantly between the ungrazed and the heavy grazed site, again with higher values at the ungrazed site (Gao et al. 2008). The group atmosphere consists of micrometeorological parameters, dust flux and deposition as measure of erosive processes and trace gas fluxes. Available energy and soil temperature were always significantly different between two simultaneously measured grazing intensities. Available energy was higher at the ungrazed site in all years measured (mean difference of about 19 W m-2). Soil temperature was lower at the ungrazed site (Ketzer et al. 2008). Dust deposition is important for the C and N balance in semi-arid grasslands and was investigated during the dust storm period from March to May. The largest matter deposition of C (vs) and N (vs) was measured at the ungrazed site with 328.7 (mg Corg m-2 d-1) and 30.30 (mg Nt m-2 d-1) on average. Heavy grazing resulted in average organic carbon and nitrogen deposition of 106.67 (mg Corg m-2 d-1) and 9.8 (mg N m-2 d-1) in average (Hoffmann et al. 2008). Wind driven soil deposition and erosion were influenced heavily by grazing. The critical vegetation cover is about 20-30%, at which net soil losses occur. No significant differences in N trace gas fluxes were found between plots. Mean values of N2O fluxes (s) varied between 0.39 and 1.60 μg N2O-N m-2 h-1 (Holst et al. 2007). During all measuring periods, significantly lower mean soil CH4 uptake at moderate grazing (28 mg C m-2 h-1) as compared to ungrazed (56 μg C m-2 h-1) was found (Liu et al. 2007). The pedosphere indicator group includes soil chemical, soil physical and microbiological parameters. Organic carbon (s) and total N (s) concentrations decreased significantly with increasing grazing intensity. No effect of grazing on pH (w) or soil C/N ratio (w) was detected. Bulk density (m) significantly increased with increasing grazing intensity, from 0.94 g cm-3 at the ungrazed site to 1.28 g cm-3 at the heavily grazed site (Steffens et al. 2008). Also shear strength (m) increased with increasing grazing intensity (Zhao et al. 2007). Gross rates of N mineralization (vs) and nitrification (vs) determined at in situ soil moisture and soil temperature conditions were in a range of 0.5-4.1 mg N kg-1 soil dry weight day)1. In 2005, gross N turnover rates were significantly higher at the ungrazed plots than at the moderately and overgrazed plots (Holst et al. 2007). In the hydrosphere group soil water content (w) was the highest at the ungrazed site and lowest at the heavy grazed site. Compared with moderately grazed treatments, soil water content was little higher in ungrazed treatments after long dryness but lower under wet conditions. Water drop penetration time (s) was higher in the ungrazed plots showing a slight to strong water repellency than in the grazed plots (Zhao et al. 2007). References Gao, Y., Giese, M., Lin, S., Sattelmacher, B., Zhao, Y. and Brueck, H. Belowground net primary productivity and biomass allocation of a grassland in Inner Mongolia is affected by grazing intensity. 2008. Plant and Soil DOI 10.1007/s11104-008-9579-3. Hoffmann, C., Funk, R., Li, Y. and Sommer, M. Effect of grazing on wind driven carbon and nitrogen ratios in the grasslands of Inner Mongolia. 2008. Catena 75: 182-190. Holst, J., Liu, C., Brueggemann, N., Butterbach-Bahl, K., Zheng, X., Wang, Y., Han, S., Yao, Z., Yue, J. and Han, X. Microbial N Turnover and N-Oxide (N2O/NO/NO2) Fluxes in Semi-arid Grassland of Inner Mongolia as influenced by grazing intensity. 2007. Ecosystems. Ketzer, B., Bernhofer, Ch. and Liu, H. Sensitivity of micrometeorological measurements to detect surface characteristics of grasslands in Inner Mongolia. 2008. Int. J. Biometeorol. Liu, C., Holst, J., Brueggemann, N., Butterbach-Bahl, K., Yao, Z., Yue, J., Han, S., Han, X., Kruemmelbein, J., Horn, R. and Zheng, X. Winter-grazing reduces methane uptake by soils of a typical semi-arid steppe in Inner Mongolia, China. 2007. Journal of Atmospheric Environment doi:10.1016/j.atmosenv.2007.03.017. Steffens, M., Koelbl, A., Totsche, K. U. and Koegel-Knabner, I. Grazing effects on soil chemical and physical properties in a semiarid steppe of Inner Mongolia (P.R. China). 2008. Geoderma 143: 63-72. Zhao, Y., Peth, S., Kruemmelbein, J., Horn, R., Wang, Z., Steffens, M., Hoffmann, C. and Peng, X. Spatial variability of soil properties affected by grazing intensity in Inner Mongolia grassland. 2007. Ecological Modelling 205: 241-254.

Impact of runoff infiltration on contaminant accumulation and transport in the soil/filter media of Sustainable Urban Drainage Systems: A literature review.

PubMed

Tedoldi, Damien; Chebbo, Ghassan; Pierlot, Daniel; Kovacs, Yves; Gromaire, Marie-Christine

2016-11-01

The increasing use of Sustainable Urban Drainage Systems (SUDS) for stormwater management raises some concerns about the fate of ubiquitous runoff micropollutants in soils and their potential threat to groundwater. This question may be addressed either experimentally, by sampling and analyzing SUDS soil after a given operating time, or with a modeling approach to simulate the fate and transport of contaminants. After briefly reminding the processes responsible for the retention, degradation, or leaching of several urban-sourced contaminants in soils, this paper presents the state of the art about both experimental and modeling assessments. In spite of noteworthy differences in the sampling protocols, the soil parameters chosen as explanatory variables, and the methods used to evaluate the site-specific initial concentrations, most investigations undoubtedly evidenced a significant accumulation of metals and/or hydrocarbons in SUDS soils, which in the majority of the cases appears to be restricted to the upper 10 to 30cm. These results may suggest that SUDS exhibit an interesting potential for pollution control, but antinomic observations have also been made in several specific cases, and the inter-site concentration variability is still difficult to appraise. There seems to be no consensus regarding the level of complexity to be used in models. However, the available data deriving from experimental studies is generally limited to the contamination profiles and a few parameters of the soil, as a result of which "complex" models (including colloid-facilitated transport for example) appear to be difficult to validate before using them for predictive evaluations. Copyright © 2016 Elsevier B.V. All rights reserved.

Denitrification in Agricultural Soils: Integrated control and Modelling at various scales (DASIM)

NASA Astrophysics Data System (ADS)

Müller, Christoph; Well, Reinhard; Böttcher, Jürgen; Butterbach-Bahl, Klaus; Dannenmann, Michael; Deppe, Marianna; Dittert, Klaus; Dörsch, Peter; Horn, Marcus; Ippisch, Olaf; Mikutta, Robert; Senbayram, Mehmet; Vogel, Hans-Jörg; Wrage-Mönnig, Nicole; Müller, Carsten

2016-04-01

The new research unit DASIM brings together the expertise of 11 working groups to study the process of denitrification at unprecedented spatial and temporal resolution. Based on state-of-the art analytical techniques our aim is to develop improved denitrification models ranging from the microscale to the field/plot scale. Denitrification, the process of nitrate reduction allowing microbes to sustain respiration under anaerobic conditions, is the key process returning reactive nitrogen as N2to the atmosphere. Actively denitrifying communities in soil show distinct regulatory phenotypes (DRP) with characteristic controls on the single reaction steps and end-products. It is unresolved whether DRPs are anchored in the taxonomic composition of denitrifier communities and how environmental conditions shape them. Despite being intensively studied for more than 100 years, denitrification rates and emissions of its gaseous products can still not be satisfactorily predicted. While the impact of single environmental parameters is well understood, the complexity of the process itself with its intricate cellular regulation in response to highly variable factors in the soil matrix prevents robust prediction of gaseous emissions. Key parameters in soil are pO2, organic matter content and quality, pH and the microbial community structure, which in turn are affected by the soil structure, chemistry and soil-plant interactions. In the DASIM research unit, we aim at the quantitative prediction of denitrification rates as a function of microscale soil structure, organic matter quality, DRPs and atmospheric boundary conditions via a combination of state-of-the-art experimental and analytical tools (X-ray μCT, 15N tracing, NanoSIMS, microsensors, advanced flux detection, NMR spectroscopy, and molecular methods including next generation sequencing of functional gene transcripts). We actively seek collaboration with researchers working in the field of denitrification.

A critical evaluation of phosphate retardation and leaching in Hapludults

NASA Astrophysics Data System (ADS)

Dao, Thanh

2016-04-01

Nutrients used in production agriculture, in particular bioactive phosphorus (P), continue to present challenges in trying to reverse the degradation of fragile aquatic ecosystems. Soils treated with large amounts of nutrient-enriched animal manure have elevated P levels in regions of intensive animal agriculture and the residual effects of past large P additions were found to be long-lived. Mathematical models are increasingly used in the evaluation and development of mitigation strategies and sustainable management practices. A large number of predictive tools are currently used in the U.S. for simulating phosphorus environmental fate, including models such AGNPS (Agricultural Non-Point Source), FHANTM Field Hydrologic And Nutrient Transport Model (Field Hydrologic And Nutrient Transport Model), SWAT (Soil & Water Assessment Tool), or APEX (Agric. Policy/Environmental EXtender). The P routines in these models have had limited changes in spite of the advances in our understanding of speciation and transport of various P forms in soil and water systems that have occurred over the last three decades. We conducted soil sorption isotherm experiments that yielded basic information for estimating the Phosphorus Sorption coefficient (PSP) a key parameter used to allocate mineral P into soil labile, active, and stable pools. We compare these coefficients to parameters derived from breakthrough curves (BTC) for determining the extent of retardation and transport of phosphate supplied as KH2PO4 under a constant hydraulic head. Sigmoidal and multi-reaction rate models were observed in the BTCs of the anion, which undermine the rationale for using an overall simple partition coefficient to describe the transport and dispersal of phosphate in soil. Minimizing such generalities used in estimating nutrient availability and transport gives a more accurate picture of status of P in soil to conserve nutrients and minimize loss of excess P inputs to the environment.

Dielectric properties of soils as a function of moisture content

NASA Technical Reports Server (NTRS)

Cihlar, J.; Ulaby, F. T.

1974-01-01

Soil dielectric constant measurements are reviewed and the dependence of the dielectric constant on various soil parameters is determined. Moisture content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as soil dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric soil water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three soil textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and soil texture.

Kinetics of trichloroethylene cometabolism and toluene biodegradation: Model application to soil batch experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

El-Farhan, Y.H.; Scow, K.M.; Fan, S.

Trichloroethylene (TCE) biodegradation in soil under aerobic conditions requires the presence of another compound, such as toluene, to support growth of microbial populations and enzyme induction. The biodegradation kinetics of TCE and toluene were examined by conducting three groups of experiments in soil: toluene only, toluene combined with low TCE concentrations, and toluene with TCE concentrations similar to or higher than toluene. The biodegradation of TCE and toluene and their interrelationships were modeled using a combination of several biodegradation functions. In the model, the pollutants were described as existing in the solid, liquid, and gas phases of soil, with biodegradationmore » occurring only in the liquid phase. The distribution of the chemicals between the solid and liquid phase was described by a linear sorption isotherm, whereas liquid-vapor partitioning was described by Henry's law. Results from 12 experiments with toluene only could be described by a single set of kinetic parameters. The same set of parameters could describe toluene degradation in 10 experiments where low TCE concentrations were present. From these 10 experiments a set of parameters describing TCE cometabolism induced by toluene also was obtained. The complete set of parameters was used to describe the biodegradation of both compounds in 15 additional experiments, where significant TCE toxicity and inhibition effects were expected. Toluene parameters were similar to values reported for pure culture systems. Parameters describing the interaction of TCE with toluene and biomass were different from reported values for pure cultures, suggesting that the presence of soil may have affected the cometabolic ability of the indigenous soil microbial populations.« less

Snow Water Equivalent Retrieval By Markov Chain Monte Carlo Based on Memls and Hut Snow Emission Model

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2014-12-01

The Markov chain Monte Carlo (MCMC) method had been proved to be successful in snow water equivalent retrieval based on synthetic point-scale passive microwave brightness temperature (TB) observations. This method needs only general prior information about distribution of snow parameters, and could estimate layered snow properties, including the thickness, temperature, density and snow grain size (or exponential correlation length) of each layer. In this study, the multi-layer HUT (Helsinki University of Technology) model and the MEMLS (Microwave Emission Model of Layered Snowpacks) will be used as observation models to assimilate the observed TB into snow parameter prediction. Previous studies had shown that the multi-layer HUT model tends to underestimate TB at 37 GHz for deep snow, while the MEMLS does not show sensitivity of model bias to snow depth. Therefore, results using HUT model and MEMLS will be compared to see how the observation model will influence the retrieval of snow parameters. The radiometric measurements at 10.65, 18.7, 36.5 and 90 GHz at Sodankyla, Finland will be used as MCMC input, and the statistics of all snow property measurement will be used to calculate the prior information. 43 dry snowpits with complete measurements of all snow parameters will be used for validation. The entire dataset are from NorSREx (Nordic Snow Radar Experiment) experiments carried out by Juha Lemmetyinen, Anna Kontu and Jouni Pulliainen in FMI in 2009-2011 winters, and continued two more winters from 2011 to Spring of 2013. Besides the snow thickness and snow density that are directly related to snow water equivalent, other parameters will be compared with observations, too. For thin snow, the previous studies showed that influence of underlying soil is considerable, especially when the soil is half frozen with part of unfrozen liquid water and part of ice. Therefore, this study will also try to employ a simple frozen soil permittivity model to improve the performance of retrieval. The behavior of the Markov chain in soil parameters will be studied.

Mercury dispersion in soils of an abandoned lead-zinc-silver mine, San Quintín (Spain)

NASA Astrophysics Data System (ADS)

Esbrí, José Maria; Martín-Crespo, T.; Gómez-Ortiz, D.; Monescillo, C. I.; Lorenzo, S.; Higueras, P.

2010-05-01

The mine considered on this work, namely San Quintín, is a filonian field with hydrothermal ores exploited during almost fifty years (1887-1934), producing 550.000Tm of galena, 550Tm of silver and 5.000 of sphalerite. Some rewashing works of tailings muds was achieved in recent times (1973-1985), including flotation tests of cinnabar ore from Almadén mines. The main problems remaining on the site are an active acid mine drainage (with pH ~ 2) and heavy metal dispersion on soils including gaseous mercury emissions. We present here results of a survey including soils sampling with mercury analysis and other pedological parameters, as well as determinations of mercury inmission in the atmosphere, using a common sampling grid. Analysis of soils samples has been carried out using an atomic absorption spectrometer AMA254, while air determinations were made by the same technique, using a Lumex RA-915+. The maps have been obtained by means of SURFER 8 software, as well as by ArcGIS software, and puts forward dispersion of mercury from cinnabar ore dump (108 ?g×g-1) to nearby soils (0.3 ?g×g-1 at 700 m of distance). The dispersion of mercury vapor exceed WHO level for chronic exposure (200 ng×m-3) in a small area (250 meters from cinnabar dump).

An investigation of the key parameters for predicting PV soiling losses

DOE PAGES

Micheli, Leonardo; Muller, Matthew

2017-01-25

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of drymore » periods had the best correlation with the soiling ratio. Lastly, a preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.« less

Ecological optimality in water-limited natural soil-vegetation systems. II - Tests and applications

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Tellers, T. E.

1982-01-01

The long-term optimal climatic climax soil-vegetation system is defined for several climates according to previous hypotheses in terms of two free parameters, effective porosity and plant water use coefficient. The free parameters are chosen by matching the predicted and observed average annual water yield. The resulting climax soil and vegetation properties are tested by comparison with independent observations of canopy density and average annual surface runoff. The climax properties are shown also to satisfy a previous hypothesis for short-term optimization of canopy density and water use coefficient. Using these hypotheses, a relationship between average evapotranspiration and optimum vegetation canopy density is derived and is compared with additional field observations. An algorithm is suggested by which the climax soil and vegetation properties can be calculated given only the climate parameters and the soil effective porosity. Sensitivity of the climax properties to the effective porosity is explored.

Science Data System Contribution to Calibrating and Validating SMAP Data Products

NASA Astrophysics Data System (ADS)

Cuddy, D.

2015-12-01

NASA's Soil Moisture Active Passive (SMAP) mission retrieves global surface soil moisture and freeze/thaw state using measurements acquired by a radiometer and a synthetic aperture radar that fly on an Earth orbiting satellite. The SMAP observatory launched from Vandenberg Air Force Base on January 31, 2015 into a near-polar, sun-synchronous orbit. This paper describes the contribution of the SMAP Science Data System (SDS) to the calibration and on-going validation of the radar backscatter and radiometer brightness temperatures. The Science Data System designed, implemented and operated the software that generates data products that contain various geophysical parameters including soil moisture and freeze/thaw states, daily maps of these geophysical parameters, as well as modeled analyses of global soil moisture and carbon flux in Boreal regions. The SDS is a fully automated system that processes the incoming raw data from the instruments, incorporates spacecraft and instrument engineering data, and uses both dynamic and static ancillary products provided by the scientific community. The standard data products appear in Hierarchical Data Format-5 (HDF5) format. These products contain metadata that conform to the ISO 19115 standard. The Alaska Satellite Facility (ASF) hosts and distributes SMAP radar data products. The National Snow and Ice Data Center (NSIDC) hosts and distributes all of the other SMAP data products.

Atlas of soil reflectance properties

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Baumgardner, M. F.; Biehl, L. L.; Robinson, B. F.

1979-01-01

A compendium of soil spectral reflectance curves together with soil test results and site information is presented in an abbreviated manner listing those soil properties most important in influencing soil reflectance. Results are presented for 251 soils from 39 states and Brazil. A narrative key describes relationships between soil parameters and reflectance curves. All soils are classified according to the U.S. soil taxonomy and soil series name for ease of identification.

Identifying mechanical property parameters of planetary soil using in-situ data obtained from exploration rovers

NASA Astrophysics Data System (ADS)

Ding, Liang; Gao, Haibo; Liu, Zhen; Deng, Zongquan; Liu, Guangjun

2015-12-01

Identifying the mechanical property parameters of planetary soil based on terramechanics models using in-situ data obtained from autonomous planetary exploration rovers is both an important scientific goal and essential for control strategy optimization and high-fidelity simulations of rovers. However, identifying all the terrain parameters is a challenging task because of the nonlinear and coupling nature of the involved functions. Three parameter identification methods are presented in this paper to serve different purposes based on an improved terramechanics model that takes into account the effects of slip, wheel lugs, etc. Parameter sensitivity and coupling of the equations are analyzed, and the parameters are grouped according to their sensitivity to the normal force, resistance moment and drawbar pull. An iterative identification method using the original integral model is developed first. In order to realize real-time identification, the model is then simplified by linearizing the normal and shearing stresses to derive decoupled closed-form analytical equations. Each equation contains one or two groups of soil parameters, making step-by-step identification of all the unknowns feasible. Experiments were performed using six different types of single-wheels as well as a four-wheeled rover moving on planetary soil simulant. All the unknown model parameters were identified using the measured data and compared with the values obtained by conventional experiments. It is verified that the proposed iterative identification method provides improved accuracy, making it suitable for scientific studies of soil properties, whereas the step-by-step identification methods based on simplified models require less calculation time, making them more suitable for real-time applications. The models have less than 10% margin of error comparing with the measured results when predicting the interaction forces and moments using the corresponding identified parameters.

Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS

NASA Technical Reports Server (NTRS)

Trease, Brian P.; Lindeman, Randel A.; Arvidson, Raymond E.; Bennett, Keith; VanDyke, Lauren P.; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine

2013-01-01

The Mars Exploration Rovers (MERs), Spirit and Opportunity, far exceeded their original drive distance expectations and have traveled, at the time of this reporting, a combined 29 kilometers across the surface of Mars. The Rover Sequencing and Visualization Program (RSVP), the current program used to plan drives for MERs, is only a kinematic simulator of rover movement. Therefore, rover response to various terrains and soil types cannot be modeled. Although sandbox experiments attempt to model rover-terrain interaction, these experiments are time-intensive and costly, and they cannot be used within the tactical timeline of rover driving. Imaging techniques and hazard avoidance features on MER help to prevent the rover from traveling over dangerous terrains, but mobility issues have shown that these methods are not always sufficient. ARTEMIS, a dynamic modeling tool for MER, allows planned drives to be simulated before commands are sent to the rover. The deformable soils component of this model allows rover-terrain interactions to be simulated to determine if a particular drive path would take the rover over terrain that would induce hazardous levels of slip or sink. When used in the rover drive planning process, dynamic modeling reduces the likelihood of future mobility issues because high-risk areas could be identified before drive commands are sent to the rover, and drives planned over these areas could be rerouted. The ARTEMIS software consists of several components. These include a preprocessor, Digital Elevation Models (DEMs), Adams rover model, wheel and soil parameter files, MSC Adams GUI (commercial), MSC Adams dynamics solver (commercial), terramechanics subroutines (FORTRAN), a contact detection engine, a soil modification engine, and output DEMs of deformed soil. The preprocessor is used to define the terrain (from a DEM) and define the soil parameters for the terrain file. The Adams rover model is placed in this terrain. Wheel and soil parameter files can be altered in the respective text files. The rover model and terrain are viewed in Adams View, the GUI for ARTEMIS. The Adams dynamics solver calls terramechanics subroutines in FORTRAN containing the Bekker-Wong equations.

[Optimization of application parameters of soil seed bank in vegetation recovery via response surface methodology].

PubMed

He, Meng-Xuan; Li, Hong-Yuan; Mo, Xun-Qiang; Meng, Wei-Qing; Yang, Jia-Nan

2014-08-01

The thickness of surface soil, the covering thickness and the number of adding arbor seeds are all important factors to be considered in the application of soil seed bank (SSB) for vegetation recovery. To determine the optimal conditions, the Box-Behnken central composite design with three parameters and three levels was conducted and Design-Expert was used for response surface optimization. Finally, the optimal model and optimal level of each parameter were selected. The quadratic model was more suitable for response surface optimization (P < 0.0001), indicating the model had good statistical significance which could express ideal relations between all the independent variable and dependent variable. For the optimum condition, the thickness of surface soil was 4.3 cm, the covering thickness was 2 cm, and the number of adding arbor seeds was 224 ind x m(-2), under which the number of germinated seedlings could be reached up to 6222 plants x m(-2). During the process of seed germination, significant interactions between the thickness of surface soil and the covering thickness, as well as the thickness of surface soil and the number of adding arbor seeds were found, but the relationship between the covering thickness and the number of adding arbor seeds was relatively unremarkable. Among all the parameters, the thickness of surface soil was the most important one, which had the steepest curve and the largest standardized coefficient.

Satellite Based Soil Moisture Product Validation Using NOAA-CREST Ground and L-Band Observations

NASA Astrophysics Data System (ADS)

Norouzi, H.; Campo, C.; Temimi, M.; Lakhankar, T.; Khanbilvardi, R.

2015-12-01

Soil moisture content is among most important physical parameters in hydrology, climate, and environmental studies. Many microwave-based satellite observations have been utilized to estimate this parameter. The Advanced Microwave Scanning Radiometer 2 (AMSR2) is one of many remotely sensors that collects daily information of land surface soil moisture. However, many factors such as ancillary data and vegetation scattering can affect the signal and the estimation. Therefore, this information needs to be validated against some "ground-truth" observations. NOAA - Cooperative Remote Sensing and Technology (CREST) center at the City University of New York has a site located at Millbrook, NY with several insitu soil moisture probes and an L-Band radiometer similar to Soil Moisture Passive and Active (SMAP) one. This site is among SMAP Cal/Val sites. Soil moisture information was measured at seven different locations from 2012 to 2015. Hydra probes are used to measure six of these locations. This study utilizes the observations from insitu data and the L-Band radiometer close to ground (at 3 meters height) to validate and to compare soil moisture estimates from AMSR2. Analysis of the measurements and AMSR2 indicated a weak correlation with the hydra probes and a moderate correlation with Cosmic-ray Soil Moisture Observing System (COSMOS probes). Several differences including the differences between pixel size and point measurements can cause these discrepancies. Some interpolation techniques are used to expand point measurements from 6 locations to AMSR2 footprint. Finally, the effect of penetration depth in microwave signal and inconsistencies with other ancillary data such as skin temperature is investigated to provide a better understanding in the analysis. The results show that the retrieval algorithm of AMSR2 is appropriate under certain circumstances. This validation algorithm and similar study will be conducted for SMAP mission. Keywords: Remote Sensing, Soil Moisture, AMSR2, SMAP, L-Band.

The seasonal behaviour of carbon fluxes in the Amazon: fusion of FLUXNET data and the ORCHIDEE model

NASA Astrophysics Data System (ADS)

Verbeeck, H.; Peylin, P.; Bacour, C.; Ciais, P.

2009-04-01

Eddy covariance measurements at the Santarém (km 67) site revealed an unexpected seasonal pattern in carbon fluxes which could not be simulated by existing state-of-the-art global ecosystem models (Saleska et al., Sciece 2003). An unexpected high carbon uptake was measured during dry season. In contrast, carbon release was observed in the wet season. There are several possible (combined) underlying mechanisms of this phenomenon: (1) an increased soil respiration due to soil moisture in the wet season, (2) increased photosynthesis during the dry season due to deep rooting, hydraulic lift, increased radiation and/or a leaf flush. The objective of this study is to optimise the ORCHIDEE model using eddy covariance data in order to be able to mimic the seasonal response of carbon fluxes to dry/wet conditions in tropical forest ecosystems. By doing this, we try to identify the underlying mechanisms of this seasonal response. The ORCHIDEE model is a state of the art mechanistic global vegetation model that can be run at local or global scale. It calculates the carbon and water cycle in the different soil and vegetation pools and resolves the diurnal cycle of fluxes. ORCHIDEE is built on the concept of plant functional types (PFT) to describe vegetation. To bring the different carbon pool sizes to realistic values, spin-up runs are used. ORCHIDEE uses climate variables as drivers together with a number of ecosystem parameters that have been assessed from laboratory and in situ experiments. These parameters are still associated with a large uncertainty and may vary between and within PFTs in a way that is currently not informed or captured by the model. Recently, the development of assimilation techniques allows the objective use of eddy covariance data to improve our knowledge of these parameters in a statistically coherent approach. We use a Bayesian optimisation approach. This approach is based on the minimization of a cost function containing the mismatch between simulated model output and observations as well as the mismatch between a priori and optimized parameters. The parameters can be optimized on different time scales (annually, monthly, daily). For this study the model is optimised at local scale for 5 eddy flux sites: 4 sites in Brazil and one in French Guyana. The seasonal behaviour of C fluxes in response to wet and dry conditions differs among these sites. Key processes that are optimised include: the effect of the soil water on heterotrophic soil respiration, the effect of soil water availability on stomatal conductance and photosynthesis, and phenology. By optimising several key parameters we could improve the simulation of the seasonal pattern of NEE significantly. Nevertheless, posterior parameters should be interpreted with care, because resulting parameter values might compensate for uncertainties on the model structure or other parameters. Moreover, several critical issues appeared during this study e.g. how to assimilate latent and sensible heat data, when the energy balance is not closed in the data? Optimisation of the Q10 parameter showed that on some sites respiration was not sensitive at all to temperature, which show only small variations in this region. Considering this, one could question the reliability of the partitioned fluxes (GPP/Reco) at these sites. This study also tests if there is coherence between optimised parameter values of different sites within the tropical forest PFT and if the forward model response to climate variations is similar between sites.

Selection of Optimal Auxiliary Soil Nutrient Variables for Cokriging Interpolation

PubMed Central

Song, Genxin; Zhang, Jing; Wang, Ke

2014-01-01

In order to explore the selection of the best auxiliary variables (BAVs) when using the Cokriging method for soil attribute interpolation, this paper investigated the selection of BAVs from terrain parameters, soil trace elements, and soil nutrient attributes when applying Cokriging interpolation to soil nutrients (organic matter, total N, available P, and available K). In total, 670 soil samples were collected in Fuyang, and the nutrient and trace element attributes of the soil samples were determined. Based on the spatial autocorrelation of soil attributes, the Digital Elevation Model (DEM) data for Fuyang was combined to explore the coordinate relationship among terrain parameters, trace elements, and soil nutrient attributes. Variables with a high correlation to soil nutrient attributes were selected as BAVs for Cokriging interpolation of soil nutrients, and variables with poor correlation were selected as poor auxiliary variables (PAVs). The results of Cokriging interpolations using BAVs and PAVs were then compared. The results indicated that Cokriging interpolation with BAVs yielded more accurate results than Cokriging interpolation with PAVs (the mean absolute error of BAV interpolation results for organic matter, total N, available P, and available K were 0.020, 0.002, 7.616, and 12.4702, respectively, and the mean absolute error of PAV interpolation results were 0.052, 0.037, 15.619, and 0.037, respectively). The results indicated that Cokriging interpolation with BAVs can significantly improve the accuracy of Cokriging interpolation for soil nutrient attributes. This study provides meaningful guidance and reference for the selection of auxiliary parameters for the application of Cokriging interpolation to soil nutrient attributes. PMID:24927129

Topological data analysis (TDA) applied to reveal pedogenetic principles of European topsoil system.

PubMed

Savic, Aleksandar; Toth, Gergely; Duponchel, Ludovic

2017-05-15

Recent developments in applied mathematics are bringing new tools that are capable to synthesize knowledge in various disciplines, and help in finding hidden relationships between variables. One such technique is topological data analysis (TDA), a fusion of classical exploration techniques such as principal component analysis (PCA), and a topological point of view applied to clustering of results. Various phenomena have already received new interpretations thanks to TDA, from the proper choice of sport teams to cancer treatments. For the first time, this technique has been applied in soil science, to show the interaction between physical and chemical soil attributes and main soil-forming factors, such as climate and land use. The topsoil data set of the Land Use/Land Cover Area Frame survey (LUCAS) was used as a comprehensive database that consists of approximately 20,000 samples, each described by 12 physical and chemical parameters. After the application of TDA, results obtained were cross-checked against known grouping parameters including five types of land cover, nine types of climate and the organic carbon content of soil. Some of the grouping characteristics observed using standard approaches were confirmed by TDA (e.g., organic carbon content) but novel subtle relationships (e.g., magnitude of anthropogenic effect in soil formation), were discovered as well. The importance of this finding is that TDA is a unique mathematical technique capable of extracting complex relations hidden in soil science data sets, giving the opportunity to see the influence of physicochemical, biotic and abiotic factors on topsoil formation through fresh eyes. Copyright © 2017 Elsevier B.V. All rights reserved.

Thermal signature characteristics of vehicle/terrain interaction disturbances: implications for battlefield vehicle classification.

PubMed

Eastes, John W; Mason, George L; Kusinger, Alan E

2004-05-01

Thermal emissivity spectra (8-14 microm) of track impressions/background were determined in conjunction with operation of six military vehicle types, T-72 and M1 Tanks, an M2 Bradley Fighting Vehicle, a 5-ton truck, a D7 tractor, and a High Mobility Multipurpose Wheeled Vehicle (HMMWV), over diverse soil surfaces to determine if vehicle type could be related to track thermal signatures. Results suggest soil compaction and fragmentation/pulverization are primary parameters affecting track signatures and that soil and vehicle/terrain-contact type determine which parameter dominates. Steel-tracked vehicles exert relatively low ground-contact pressure but tend to fragment/pulverize soil more so than do rubber-tired vehicles, which tend mainly to compact. In quartz-rich, lean clay soil tracked vehicles produced impressions with spectral contrast of the quartz reststrahlen features decreased from that of the background. At the same time, 5-ton truck tracks exhibited increased contrast on the same surface, suggesting that steel tracks fragmented soil while rubber tires mainly produced compaction. The structure of materials such as sand and moist clay-rich river sediment makes them less subject to further fragmentation/pulverization; thus, compaction was the main factor affecting signatures in these media, and both tracked and wheeled vehicles created impressions with increased spectral contrast on these surfaces. These results suggest that remotely sensed thermal signatures could differentiate tracked and wheeled vehicles on terrain in many areas of the world of strategic interest. Significant applications include distinguishing visually/spectrally identical lightweight decoys from actual threat vehicles.

Assessment of the levels of potentially toxic substances around a transect of anthrosols in Aqaba shoreline, Jordan

NASA Astrophysics Data System (ADS)

Wahsha, Mohammad; Al-Rousan, Saber; Al-Jawasreh, Raid

2016-04-01

Soils are the major sink for potentially toxic substances (PTSs) such as heavy metals released into the environment by emissions from the quickly increasing of human impact including industrial mine tailings, disposal of high metal wastes, land misuse, wastewater irrigation, spillage of petrochemicals, and atmospheric deposition. The present study concerns the properties variability and soil biological health status in abandoned salt transportation port site in the Jordanian coast of the Gulf of Aqaba, Red Sea. Seven sites were selected according to different morphological and pedological conditions, anthropogenic impact and the same climate conditions. Successively, all locations were sampled for topsoil in the period between spring-summer 2014. Field observations as well as laboratory analysis including heavy metal concentrations (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn); soil chemo-physical parameters (pH, soil dry mass, carbonate, water holding, organic carbon content, soil particle size distribution), and quality of soil's biological community were determined. The anthropogenic influence related to former port activity on soils of the studied area is evident. Soils in the studied area site are highly contaminated by PTSs, mainly Cu and Zn, by 648, 298.6 mgKg-1respectively. Former activities proved to affect the microarthropods community altering both quantity and quality of soil and the chemo-physical structure of the microhabitats. The evaluation of soil biological quality index (QBS-ar) of the surface horizons from the study area is demonstrated that the area is "sufferings" since it is affected by PTSs contamination resulting in a failure in the ecological success of secondary recolonization after abandonment. However, there is an increasing need for further research in the soils of Aqaba focusing on soil health management , combining QBS-ar index with soil chemo-physical properties. Key words: Potentially Toxic Substances, Heavy Metals, Soil Quality.

Determination of soil degradation from flooding for estimating ecosystem services in Slovakia

NASA Astrophysics Data System (ADS)

Hlavcova, Kamila; Szolgay, Jan; Karabova, Beata; Kohnova, Silvia

2015-04-01

Floods as natural hazards are related to soil health, land-use and land management. They not only represent threats on their own, but can also be triggered, controlled and amplified by interactions with other soil threats and soil degradation processes. Among the many direct impacts of flooding on soil health, including soil texture, structure, changes in the soil's chemical properties, deterioration of soil aggregation and water holding capacity, etc., are soil erosion, mudflows, depositions of sediment and debris. Flooding is initiated by a combination of predispositive and triggering factors and apart from climate drivers it is related to the physiographic conditions of the land, state of the soil, land use and land management. Due to the diversity and complexity of their potential interactions, diverse methodologies and approaches are needed for describing a particular type of event in a specific environment, especially in ungauged sites. In engineering studies and also in many rainfall-runoff models, the SCS-CN method has remained widely applied for soil and land use-based estimations of direct runoff and flooding potential. The SCS-CN method is an empirical rainfall-runoff model developed by the USDA Natural Resources Conservation Service (formerly called the Soil Conservation Service or SCS). The runoff curve number (CN) is based on the hydrological soil characteristics, land use, land management and antecedent saturation conditions of soil. Since the method and curve numbers were derived on the basis of an empirical analysis of rainfall-runoff events from small catchments and hillslope plots monitored by the USDA, the use of the method for the conditions of Slovakia raises uncertainty and can cause inaccurate results in determining direct runoff. The objective of the study presented (also within the framework of the EU-FP7 RECARE Project) was to develop the SCS - CN methodology for the flood conditions in Slovakia (and especially for the RECARE pilot site of Myjava), with an emphasis on the determination of soil degradation from flooding for estimating ecosystem services. The parameters of the SCS-CN methodology were regionalised empirically based on actual rainfall and discharge measurements. Since there has been no appropriate methodology provided for the regionalisation of SCS-CN method parameters in Slovakia, such as runoff curve numbers and initial abstraction coefficients (λ), the work presented is important for the correct application of the SCS-CN method in our conditions.

Response of Partially Saturated Non-cohesive Soils

NASA Astrophysics Data System (ADS)

Świdziński, Waldemar; Mierczyński, Jacek; Mikos, Agata

2017-12-01

This paper analyses and discusses experimental results of undrained triaxial tests. The tests were performed on non-cohesive partially saturated soil samples subjected to monotonic and cyclic loading. The tests were aimed at determining the influence of saturation degree on soil's undrained response (shear strength, excess pore pressure generation). The saturation of samples was monitored by checking Skempton's parameter B. Additionally, seismic P-wave velocity measurements were carried out on samples characterized by various degrees of saturation. The tests clearly showed that liquefaction may also take place in non-cohesive soils that are not fully saturated and that the liquefaction potential of such soils strongly depends on the B parameter.

Carbon dynamics in an almond orchard soil amended with raw and treated pig slurry

NASA Astrophysics Data System (ADS)

Domínguez, Sara G.; Zornoza, Raúl; Faz, Ángel

2010-05-01

In SE Spain, intensive farming is very common which supposes the generation of great amounts of pig slurries. These residues cause many storage problems due to their pollution capacity. A good management of them is necessary to avoid damages to the environment. The use of this effluent as fertilizer is a usual practice that in the correct dose is a good amend and important for sustainable development, but in excess can be a risk of polluting and damaging soil, water and crop conditions. Pig slurry is a source of many nutrients and specially rich in organic matter. The main objective of this study is to determine changes in soil organic carbon dynamics resulting from raw and treated slurry amendments applied in different doses. The experimental area is an almond orchard located in Cartagena (SE Spain). The climate of the area is semiarid Mediterranean with mean annual temperature of 18°C and mean annual rainfall of 275 mm. A total of 10 plots (12 m x 30 m) were designed, one of them being the control without fertilizer. Surface soil samples (0-25 cm) were collected in September 2009. Three different treatments were applied, raw slurry, the effluent obtained after solid-liquid separation and solid manure, all of them in three doses being the first one of 170 kg N/ha, (maximum permitted in nitrates directive 91/676/CEE), and the others two and three times the first one. Soil biochemical parameters are rapid indicators of changes in soil quality. According to this, total organic carbon, soil microbial biomass carbon, soluble carbon, and β-glucosidase, β-galactosidase and arylesterase activities were measured in order to assess some soil biochemical conditions and carbon dynamics in terms of the different treatments. As we expected, the use of these organic fertilizers rich in organic matter, had an effect on soil carbon and soil microbial activity resulting in an increase in most of the parameters; total organic carbon and β-galactosidase activity showed the biggest increment comparing to control. No pattern was observed among fertilizer doses, without big differences among them in most properties. We can conclude that the use of pig slurry as organic fertilizer incorporates great amounts of organic matter to the soil in its different forms, including soluble and microorganisms biomass, which has a positive effect encouraging the application of this agricultural management so that soil can act as C sink, in order to mitigate global warming. Thus, this procedure can be included in the strategies to increase the soil carbon sequestration. According to carbon dynamics, doses are not important, without risks of soluble carbon leaching.

Factors influencing the contents of metals and as in soils around the watershed of Guanting Reservoir, China.

PubMed

Xu, Li; Wang, Tieyu; Luo, Wei; Ni, Kun; Liu, Shijie; Wang, Lin; Li, Qiushuang; Lu, Yonglong

2013-03-01

Topsoil samples from 61 sites around the Guanting Reservoir, China, were measured for Cu, Zn, Cr, Ni, Cd, Pb and As concentrations. The mean concentrations of Cu, Zn, Cr, Ni, Cd, Pb and As were 16.8, 59.4, 37.8, 18.3, 0.32, 20.1 and 8.67 mg/kg dry weight, respectively. Factors that influence the dynamics of these metals in soils around the watersheds of Beijing reservoirs were examined. The influence of atmospheric deposition, land use, soil texture, soil type and soil chemical parameters on metal contents in soils was investigated. Atmospheric deposition, land use and soil texture were the important factors affecting heavy metal residues. Soil type and soil chemical parameters were also involved in heavy metal retention in soils. The data provided in this study are considered crucial for reservoir remediation, especially since the Guanting Reservoir will serve as one of the main drinking water sources for Beijing in the foreseeable future.

Can we predict uranium bioavailability based on soil parameters? Part 2: soil solution uranium concentration is not a good bioavailability index.

PubMed

Vandenhove, H; Van Hees, M; Wannijn, J; Wouters, K; Wang, L

2007-01-01

The present study aimed to quantify the influence of soil parameters on uranium uptake by ryegrass. Ryegrass was established on eighteen distinct soils, spiked with (238)U. Uranium soil-to-plant transfer factors (TF) ranged from 0.0003 to 0.0340kgkg(-1). There was no significant relation between the U soil-to-plant transfer (or total U uptake or flux) and the uranium concentration in the soil solution or any other soil factor measured, nor with the U recovered following selective soil extractions. Multiple linear regression analysis resulted in a significant though complex model explaining up to 99% of variation in TF. The influence of uranium speciation on uranium uptake observed was featured: UO(2)(+2), uranyl carbonate complexes and UO(2)PO(4)(-) seem the U species being preferentially taken up by the roots and transferred to the shoots. Improved correlations were obtained when relating the uranium TF with the summed soil solution concentrations of mentioned uranium species.

Quantitative framework for preferential flow initiation and partitioning

USGS Publications Warehouse

Nimmo, John R.

2016-01-01

A model for preferential flow in macropores is based on the short-range spatial distribution of soil matrix infiltrability. It uses elementary areas at two different scales. One is the traditional representative elementary area (REA), which includes a sufficient heterogeneity to typify larger areas, as for measuring field-scale infiltrability. The other, called an elementary matrix area (EMA), is smaller, but large enough to represent the local infiltrability of soil matrix material, between macropores. When water is applied to the land surface, each EMA absorbs water up to the rate of its matrix infiltrability. Excess water flows into a macropore, becoming preferential flow. The land surface then can be represented by a mesoscale (EMA-scale) distribution of matrix infiltrabilities. Total preferential flow at a given depth is the sum of contributions from all EMAs. Applying the model, one case study with multi-year field measurements of both preferential and diffuse fluxes at a specific depth was used to obtain parameter values by inverse calculation. The results quantify the preferential–diffuse partition of flow from individual storms that differed in rainfall amount, intensity, antecedent soil water, and other factors. Another case study provided measured values of matrix infiltrability to estimate parameter values for comparison and illustrative predictions. These examples give a self-consistent picture from the combination of parameter values, directions of sensitivities, and magnitudes of differences caused by different variables. One major practical use of this model is to calculate the dependence of preferential flow on climate-related factors, such as varying soil wetness and rainfall intensity.

Soil and geomorphological parameters to characterize natural environmental and human induced changes within the Guadarrama Range (Central Spain)

NASA Astrophysics Data System (ADS)

Schmid, Thomas; Inclán-Cuartas, Rosa M.; Santolaria-Canales, Edmundo; Saa, Antonio; Rodríguez-Rastrero, Manuel; Tanarro-Garcia, Luis M.; Luque, Esperanza; Pelayo, Marta; Ubeda, Jose; Tarquis, Ana; Diaz-Puente, Javier; De Marcos, Javier; Rodriguez-Alonso, Javier; Hernandez, Carlos; Palacios, David; Gallardo-Díaz, Juan; Fidel González-Rouco, J.

2016-04-01

Mediterranean mountain ecosystems are often complex and remarkably diverse and are seen as important sources of biological diversity. They play a key role in the water and sediment cycle for lowland regions as well as preventing and mitigating natural hazards especially those related to drought such as fire risk. However, these ecosystems are fragile and vulnerable to changes due to their particular and extreme climatic and biogeographic conditions. Some of the main pressures on mountain biodiversity are caused by changes in land use practices, infrastructure and urban development, unsustainable tourism, overexploitation of natural resources, fragmentation of habitats, particularly when located close to large population centers, as well as by pressures related toclimate change. The objective of this work is to select soil and geomorphological parameters in order to characterize natural environmental and human induced changes within the newly created National Park of the Sierra de Guadarrama in Central Spain, where the presence of the Madrid metropolitan area is the main factor of impact. This is carried out within the framework of the Guadarrama Monitoring Network (GuMNet) of the Campus de ExcelenciaInternacionalMoncloa, where long-term monitoring of the atmosphere, soil and bedrock are priority. This network has a total of ten stations located to the NW of Madrid and in this case, three stations have been selected to represent different ecosystems that include: 1) an alluvial plain in a lowland pasture area (La Herreria at 920 m a.s.l.), 2) mid mountain pine-forested and pasture area (Raso del Pino at 1801 m a.s.l.) and 3) high mountain grassland and rock area (Dos Hermanas at 2225 m a.s.l.). At each station a site geomorphological description, soil profile description and sampling was carried out. In the high mountain area information was obtained for monitoring frost heave activity and downslope soil movement. Basic soil laboratory analyses have been carried out to determine the physical and chemical soil properties. The parent material is gneiss andassociated deposits and, as a result, soils are acid. The soils have a low to medium organic matter content and are non-saline. They are moderately to well drained soils and have no or slight evidence of erosion. The soil within the high mountain area has clear evidence of frost heave that has a vertical displacement of the surface in the centimeter range. The stations within the lowland and mid mountain areas represent the most degraded sites as a result of the livestock keeping, whereas the high mountain area is mainly influenced by natural environmental conditions. These soil and geomorphological parameters will constitute a basis for site characterization in future studies regarding soil degradation; determining the interaction between soil, vegetation and atmosphere with respect to human induced activities (e.g. atmospheric contamination and effects of fires); determining the nitrogen and carbon cycles; and the influence of heavy metal contaminants in the soils.

Virtual geotechnical laboratory experiments using a simulator

NASA Astrophysics Data System (ADS)

Penumadu, Dayakar; Zhao, Rongda; Frost, David

2000-04-01

The details of a test simulator that provides a realistic environment for performing virtual laboratory experimentals in soil mechanics is presented. A computer program Geo-Sim that can be used to perform virtual experiments, and allow for real-time observations of material response is presented. The results of experiments, for a given set of input parameters, are obtained with the test simulator using well-trained artificial neural-network-based soil models for different soil types and stress paths. Multimedia capabilities are integrated in Geo-Sim, using software that links and controls a laser disc player with a real-time parallel processing ability. During the simulation of a virtual experiment, relevant portions of the video image of a previously recorded test on an actual soil specimen are dispalyed along with the graphical presentation of response from the feedforward ANN model predictions. The pilot simulator developed to date includes all aspects related to performing a triaxial test on cohesionless soil under undrained and drained conditions. The benefits of the test simulator are also presented.

Calculation of Excavation Force for ISRU on Lunar Surface

NASA Technical Reports Server (NTRS)

Zeng, Xiangwu (David); Burnoski, Louis; Agui, Juan H.; Wilkinson, Allen

2007-01-01

Accurately predicting the excavation force that will be encountered by digging tools on the lunar surface is a crucial element of in-situ resource utilization (ISRU). Based on principles of soil mechanics, this paper develops an analytical model that is relatively simple to apply and uses soil parameters that can be determined by traditional soil strength tests. The influence of important parameters on the excavation force is investigated. The results are compared with that predicted by other available theories. Results of preliminary soil tests on lunar stimulant are also reported.

Soil biota and agriculture production in conventional and organic farming

NASA Astrophysics Data System (ADS)

Schrama, Maarten; de Haan, Joj; Carvalho, Sabrina; Kroonen, Mark; Verstegen, Harry; Van der Putten, Wim

2015-04-01

Sustainable food production for a growing world population requires a healthy soil that can buffer environmental extremes and minimize its losses. There are currently two views on how to achieve this: by intensifying conventional agriculture or by developing organically based agriculture. It has been established that yields of conventional agriculture can be 20% higher than of organic agriculture. However, high yields of intensified conventional agriculture trade off with loss of soil biodiversity, leaching of nutrients, and other unwanted ecosystem dis-services. One of the key explanations for the loss of nutrients and GHG from intensive agriculture is that it results in high dynamics of nutrient losses, and policy has aimed at reducing temporal variation. However, little is known about how different agricultural practices affect spatial variation, and it is unknown how soil fauna acts this. In this study we compare the spatial and temporal variation of physical, chemical and biological parameters in a long term (13-year) field experiment with two conventional farming systems (low and medium organic matter input) and one organic farming system (high organic matter input) and we evaluate the impact on ecosystem services that these farming systems provide. Soil chemical (N availability, N mineralization, pH) and soil biological parameters (nematode abundance, bacterial and fungal biomass) show considerably higher spatial variation under conventional farming than under organic farming. Higher variation in soil chemical and biological parameters coincides with the presence of 'leaky' spots (high nitrate leaching) in conventional farming systems, which shift unpredictably over the course of one season. Although variation in soil physical factors (soil organic matter, soil aggregation, soil moisture) was similar between treatments, but averages were higher under organic farming, indicating more buffered conditions for nutrient cycling. All these changes coincide with pronounced shifts in soil fauna composition (nematodes, earthworms) and an increase in earthworm activity. Hence, more buffered conditions and shifts in soil fauna composition under organic farming may underlie the observed reduction in spatial variation of soil chemical and biological parameters, which in turn correlates positively with a long-term increase in yield. Our study highlights the need for both policymakers and farmers alike to support spatial stability-increasing farming.

Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters

NASA Astrophysics Data System (ADS)

Mitova, Milena; Rousseva, Svetla

2014-05-01

Soil erosion is recognized as one of the most serious soil threats worldwide. Soil erosion prediction is the first step in soil conservation planning. The Universal Soil Loss Equation (USLE) is one of the most widely used models for soil erosion predictions. One of the five USLE predictors is the soil erodibility factor (K-factor), which evaluates the impact of soil characteristics on soil erosion rates. Soil erodibility nomograph defines K-factor depending on soil characteristics, such as: particle size distribution (fractions finer that 0.002 mm and from 0.1 to 0.002 mm), organic matter content, soil structure and soil profile water permeability. Identifying the soil characteristics, which mostly influence the K-factor would give an opportunity to control the soil loss through erosion by controlling the parameters, which reduce the K-factor value. The aim of the report is to present the results of analysis of the relative weight of these soil characteristics in the K-factor values. The relative impact of the soil characteristics on K-factor was studied through a series of statistical analyses of data from the geographic database for soil erosion risk assessments in Bulgaria. Degree of correlation between K-factor values and the parameters that determine it was studied by correlation analysis. The sensitivity of the K-factor was determined by studying the variance of each parameter within the range between minimum and maximum possible values considering average value of the other factors. Normalizing transformation of data sets was applied because of the different dimensions and the orders of variation of the values of the various parameters. The results show that the content of particles finer than 0.002 mm has the most significant relative impact on the soil erodibility, followed by the content of particles with size from 0.1 mm to 0.002 mm, the class of the water permeability of the soil profile, the content of organic matter and the aggregation class. The relationships of the K-factor with the relative content of particle size from 0.1 to 0.002 mm and the class of aggregation are linear, directly proportional. When the content of particles sized from 0.1 to 0.002 mm increases with one relative unit, the K-factor increases with 0.0091 t ha h / ha MJ mm, while the same relative increase of the class of aggregation, results to an increase of the K-factor by 0.0034 t ha h / ha MJ mm. On the other side, the relationships between the K-factor values and the contents of clay and organic matter, and the class of profile water permeability, are linear, inversely proportional. When the clay content increases with one relative unit, the K-factor value decreases by 0.0099 t ha h / ha MJ mm. The same relative increases in the content of soil organic matter and the class of soil profile water permeability, result to a decrease of the values of K-factor respectively by 0.0042 and 0.0045 t ha h / ha MJ mm.

Surfactant enhanced recovery of tetrachloroethylene from a porous medium containing low permeability lenses. 2. Numerical simulation.

PubMed

Rathfelder, K M; Abriola, L M; Taylor, T P; Pennell, K D

2001-04-01

A numerical model of surfactant enhanced solubilization was developed and applied to the simulation of nonaqueous phase liquid recovery in two-dimensional heterogeneous laboratory sand tank systems. Model parameters were derived from independent, small-scale, batch and column experiments. These parameters included viscosity, density, solubilization capacity, surfactant sorption, interfacial tension, permeability, capillary retention functions, and interphase mass transfer correlations. Model predictive capability was assessed for the evaluation of the micellar solubilization of tetrachloroethylene (PCE) in the two-dimensional systems. Predicted effluent concentrations and mass recovery agreed reasonably well with measured values. Accurate prediction of enhanced solubilization behavior in the sand tanks was found to require the incorporation of pore-scale, system-dependent, interphase mass transfer limitations, including an explicit representation of specific interfacial contact area. Predicted effluent concentrations and mass recovery were also found to depend strongly upon the initial NAPL entrapment configuration. Numerical results collectively indicate that enhanced solubilization processes in heterogeneous, laboratory sand tank systems can be successfully simulated using independently measured soil parameters and column-measured mass transfer coefficients, provided that permeability and NAPL distributions are accurately known. This implies that the accuracy of model predictions at the field scale will be constrained by our ability to quantify soil heterogeneity and NAPL distribution.

Implementation of the century ecosystem model for an eroding hillslope in Mississippi

USGS Publications Warehouse

Sharpe, Jodie; Harden, Jennifer W.; Dabney, Seth M.; Ojima, Dennis; Parton, William

1998-01-01

The objective of this study was to parameterize and implement the Century ecosystem model for an eroding, cultivated site near Senatobia, in Panola County, Mississippi, in order to understand the loss and replacement of soil organic carbon on an eroding cropland. The sites chosen for this study are located on highly eroded loess soils where USDA has conducted studies on rates of soil erosion. We used USDA sediment data from the study site and historical erosion estimates from the nearby area as model input for soil loss; in addition, inputs for parametization include particle-size data, climate data, and rainfall/runoff data that were collected and reported in companion papers. A cropping scenario was implemented to simulate a research site at the USDA watershed 2 at the Nelson Farm. Model output was compiled for comparison with data collected and reported in companion reports; interpretive comparisons are reported in Harden et al, in press.

Space-Time Dynamics of Soil Moisture and Temperature: Scale issues

NASA Technical Reports Server (NTRS)

Mohanty, Binayak P.; Miller, Douglas A.; Th.vanGenuchten, M.

2003-01-01

The goal of this project is to gain further understanding of soil moisture/temperature dynamics at different spatio-temporal scales and physical controls/parameters.We created a comprehensive GIS database, which has been accessed extensively by NASA Land Surface Hydrology investigators (and others), is located at the following URL: http://www.essc.psu.edu/nasalsh. For soil moisture field experiments such as SGP97, SGP99, SMEX02, and SMEX03, cartographic products were designed for multiple applications, both pre- and post-mission. Premission applications included flight line planning and field operations logistics, as well as general insight into the extent and distribution of soil, vegetation, and topographic properties for the study areas. The cartographic products were created from original spatial information resources that were imported into Adobe Illustrator, where the maps were created and PDF versions were made for distribution and download.

Influence of different forms of acidities on soil microbiological properties and enzyme activities at an acid mine drainage contaminated site.

PubMed

Sahoo, Prafulla Kumar; Bhattacharyya, Pradip; Tripathy, Subhasish; Equeenuddin, Sk Md; Panigrahi, M K

2010-07-15

Assessment of microbial parameters, viz. microbial biomass, fluorescence diacetate, microbial respiration, acid phosphatase, beta-glucosidase and urease with respect to acidity helps in evaluating the quality of soils. This study was conducted to investigate the effects of different forms of acidities on soil microbial parameters in an acid mine drainage contaminated site around coal deposits in Jainta Hills of India. Total potential and exchangeable acidity, extractable and exchangeable aluminium were significantly higher in contaminated soil compared to the baseline (p<0.01). Different forms of acidity were significantly and positively correlated with each other (p<0.05). Further, all microbial properties were positively and significantly correlated with organic carbon and clay (p<0.05). The ratios of microbial parameters with organic carbon were negatively correlated with different forms of acidity. Principal component analysis and cluster analyses showed that the microbial activities are not directly influenced by the total potential acidity and extractable aluminium. Though acid mine drainage affected soils had higher microbial biomass and activities due to higher organic matter content than those of the baseline soils, the ratios of microbial parameters/organic carbon indicated suppression of microbial growth and activities due to acidity stress. 2010 Elsevier B.V. All rights reserved.

Pore-Water Carbonate and Phosphate As Predictors of Arsenate Toxicity in Soil.

PubMed

Lamb, Dane T; Kader, Mohammed; Wang, Liang; Choppala, Girish; Rahman, Mohammad Mahmudur; Megharaj, Mallavarapu; Naidu, Ravi

2016-12-06

Phytotoxicity of inorganic contaminants is influenced by the presence of competing ions at the site of uptake. In this study, interaction of soil pore-water constituents with arsenate toxicity was investigated in cucumber (Cucumis sativa L) using 10 contrasting soils. Arsenate phytotoxicity was shown to be related to soluble carbonate and phosphate. The data indicated that dissolved phosphate and carbonate had an antagonistic impact on arsenate toxicity to cucumber. To predict arsenate phytotoxicity in soils with a diverse range of soil solution properties, both carbonate and phosphate were required. The relationship between arsenic and pore-water toxicity parameters was established initially using multiple regression. In addition, based on the relationship with carbonate and phosphate we successively applied a terrestrial biotic ligand-like model (BLM) including carbonate and phosphate. Estimated effective concentrations from the BLM-like parametrization were strongly correlated to measured arsenate values in pore-water (R 2 = 0.76, P < 0.001). The data indicates that an ion interaction model similar to the BLM for arsenate is possible, potentially improving current risk assessments at arsenic and co-contaminated soils.

Synergy of the SimSphere land surface process model with ASTER imagery for the retrieval of spatially distributed estimates of surface turbulent heat fluxes and soil moisture content

NASA Astrophysics Data System (ADS)

Petropoulos, George; Wooster, Martin J.; Carlson, Toby N.; Drake, Nick

2010-05-01

Accurate information on spatially explicit distributed estimates of key land-atmosphere fluxes and related land surface parameters is of key importance in a range of disciplines including hydrology, meteorology, agriculture and ecology. Estimation of those parameters from remote sensing frequently employs the integration of such data with mathematical representations of the transfers of energy, mass and radiation between soil, vegetation and atmosphere continuum, known as Soil Vegetation Atmosphere Transfer (SVAT) models. The ability of one such inversion modelling scheme to resolve for key surface energy fluxes and of soil surface moisture content is examined here using data from a multispectral high spatial resolution imaging instrument, the Advanced Spaceborne Thermal Emission and Reflection Scanning Radiometer (ASTER) and SimSphere one-dimensional SVAT model. Accuracy of the investigated methodology, so-called as the "triangle" method, is verified using validated ground observations obtained from selected days collected from nine CARBOEUROPE IP sites representing a variety of climatic, topographic and environmental conditions. Subsequently, a new framework is suggested for the retrieval of two additional parameters by the investigated method, namely the Evaporative (EF) and the Non-Evaporative (NEF) Fractions. Results indicated a close agreement between the inverted surface fluxes and surface moisture availability maps as well as of the EF and NEF parameters with the observations both spatially and temporally with accuracies comparable to those obtained in similar experiments with high spatial resolution data. Inspection of the inverted surface fluxes maps regionally, showed an explainable distribution in the range of the inverted parameters in relation with the surface heterogeneity. Overall performance of the "triangle" inversion methodology was found to be affected predominantly by the SVAT model "correct" initialisation representative of the test site environment, most importantly the atmospheric conditions required in the SVAT model initial conditions. This study represents the first comprehensive evaluation of the performance of this particular methodological implementation at a European setting using the SimSphere SVAT with the ASTER data. The present work is also very timely in that, a variation of this specific inversion methodology has been proposed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2012. KEYWORDS: micrometeorology, surface heat fluxes, soil moisture content, ASTER, triangle method, SimSphere, CarboEurope IP

Ecological effects of combined pollution associated with e-waste recycling on the composition and diversity of soil microbial communities.

PubMed

Liu, Jun; He, Xiao-Xin; Lin, Xue-Rui; Chen, Wen-Ce; Zhou, Qi-Xing; Shu, Wen-Sheng; Huang, Li-Nan

2015-06-02

The crude processing of electronic waste (e-waste) has led to serious contamination in soils. While microorganisms may play a key role in remediation of the contaminated soils, the ecological effects of combined pollution (heavy metals, polychlorinated biphenyls, and polybrominated diphenyl ethers) on the composition and diversity of microbial communities remain unknown. In this study, a suite of e-waste contaminated soils were collected from Guiyu, China, and the indigenous microbial assemblages were profiled by 16S rRNA high-throughput sequencing and clone library analysis. Our data revealed significant differences in microbial taxonomic composition between the contaminated and the reference soils, with Proteobacteria, Acidobacteria, Bacteroidetes, and Firmicutes dominating the e-waste-affected communities. Genera previously identified as organic pollutants-degrading bacteria, such as Acinetobacter, Pseudomonas, and Alcanivorax, were frequently detected. Canonical correspondence analysis revealed that approximately 70% of the observed variation in microbial assemblages in the contaminated soils was explained by eight environmental variables (including soil physiochemical parameters and organic pollutants) together, among which moisture content, decabromodiphenyl ether (BDE-209), and copper were the major factors. These results provide the first detailed phylogenetic look at the microbial communities in e-waste contaminated soils, demonstrating that the complex combined pollution resulting from improper e-waste recycling may significantly alter soil microbiota.

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

Data on the effect of geological and meteorological parameters on indoor radon and thoron level- case study: Kermanshah, Iran.

PubMed

Pirsaheb, Meghdad; Najafi, Farid; Hemati, Lida; Khosravi, Touba; Sharafi, Hooshmand

2018-06-01

The present study was aimed to evaluate the relationship between indoor radon and thoron concentrations, geological and meteorological parameters. The radon and thoron concentrations were determined in three hospitals in Kermanshah, the west part of Iran, using the RTM-1688-2 radon meter. Also, the type and porosity of the underlying soil and the meteorological parameters such as temperature, humidity, atmospheric pressure, rainfall and wind speed were studied and the obtained results analyzed using STATA-Ver.8. In this study the obtained radon concentration was furthered in buildings which constructed on the soil with clayey gravel and sand feature than the soil with clay characteristic and little pasty with a significant difference ( P < 0.05). While the lower coefficient about 1.3 was obtained in measured the thoron concentration and a significant difference was not observed. So the soil porosity can extremely effect on the indoor radon amount. Among all studied meteorological parameters, temperature has been determined as the most important meteorological parameter, influence the indoor radon and thoron concentrations.

Hysteresis and uncertainty in soil water-retention curve parameters

USGS Publications Warehouse

Likos, William J.; Lu, Ning; Godt, Jonathan W.

2014-01-01

Accurate estimates of soil hydraulic parameters representing wetting and drying paths are required for predicting hydraulic and mechanical responses in a large number of applications. A comprehensive suite of laboratory experiments was conducted to measure hysteretic soil-water characteristic curves (SWCCs) representing a wide range of soil types. Results were used to quantitatively assess differences and uncertainty in three simplifications frequently adopted to estimate wetting-path SWCC parameters from more easily measured drying curves. They are the following: (1) αw=2αd, (2) nw=nd, and (3) θws=θds, where α, n, and θs are fitting parameters entering van Genuchten’s commonly adopted SWCC model, and the superscripts w and d indicate wetting and drying paths, respectively. The average ratio αw/αd for the data set was 2.24±1.25. Nominally cohesive soils had a lower αw/αd ratio (1.73±0.94) than nominally cohesionless soils (3.14±1.27). The average nw/nd ratio was 1.01±0.11 with no significant dependency on soil type, thus confirming the nw=nd simplification for a wider range of soil types than previously available. Water content at zero suction during wetting (θws) was consistently less than during drying (θds) owing to air entrapment. The θws/θds ratio averaged 0.85±0.10 and was comparable for nominally cohesive (0.87±0.11) and cohesionless (0.81±0.08) soils. Regression statistics are provided to quantitatively account for uncertainty in estimating hysteretic retention curves. Practical consequences are demonstrated for two case studies.

The influence of bioavailable heavy metals and microbial parameters of soil on the metal accumulation in rice grain.

PubMed

Xiao, Ling; Guan, Dongsheng; Peart, M R; Chen, Yujuan; Li, Qiqi; Dai, Jun

2017-10-01

A field-based study was undertaken to analyze the effects of soil bioavailable heavy metals determined by a sequential extraction procedure, and soil microbial parameters on the heavy metal accumulation in rice grain. The results showed that Cd, Cr, Cu, Ni, Pb and Zn concentrations in rice grain decreases by 65.9%, 78.9%, 32.6%, 80.5%, 61.0% and 15.7%, respectively in the sites 3 (far-away), compared with those in sites 1 (close-to). Redundancy analysis (RDA) indicated that soil catalase activity, the MBC/MBN ratio, along with bioavailable Cd, Cr and Ni could explain 68.9% of the total eigenvalue, indicating that these parameters have a great impact on the heavy metal accumulation in rice grain. The soil bioavailable heavy metals have a dominant impact on their accumulation in rice grain, with a variance contribution of 60.1%, while the MBC/MBN has a regulatory effect, with a variance contribution of 4.1%. Stepwise regression analysis showed that the MBC/MBN, urease and catalase activities are the key microbial parameters that affect the heavy metal accumulation in rice by influencing the soil bioavailable heavy metals or the translocation of heavy metals in rice. RDA showed an interactive effect between Cu, Pb and Zn in rice grain and the soil bioavailable Cd, Cr and Ni. The heavy metals in rice grain, with the exception of Pb, could be predicted by their respective soil bioavailable heavy metals. The results suggested that Pb accumulation in rice grain was mainly influenced by the multi-metal interactive effects, and less affected by soil bioavailable Pb. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling the soil water retention curves of soil-gravel mixtures with regression method on the Loess Plateau of China.

PubMed

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present.

Modeling the Soil Water Retention Curves of Soil-Gravel Mixtures with Regression Method on the Loess Plateau of China

PubMed Central

Wang, Huifang; Xiao, Bo; Wang, Mingyu; Shao, Ming'an

2013-01-01

Soil water retention parameters are critical to quantify flow and solute transport in vadose zone, while the presence of rock fragments remarkably increases their variability. Therefore a novel method for determining water retention parameters of soil-gravel mixtures is required. The procedure to generate such a model is based firstly on the determination of the quantitative relationship between the content of rock fragments and the effective saturation of soil-gravel mixtures, and then on the integration of this relationship with former analytical equations of water retention curves (WRCs). In order to find such relationships, laboratory experiments were conducted to determine WRCs of soil-gravel mixtures obtained with a clay loam soil mixed with shale clasts or pebbles in three size groups with various gravel contents. Data showed that the effective saturation of the soil-gravel mixtures with the same kind of gravels within one size group had a linear relation with gravel contents, and had a power relation with the bulk density of samples at any pressure head. Revised formulas for water retention properties of the soil-gravel mixtures are proposed to establish the water retention curved surface models of the power-linear functions and power functions. The analysis of the parameters obtained by regression and validation of the empirical models showed that they were acceptable by using either the measured data of separate gravel size group or those of all the three gravel size groups having a large size range. Furthermore, the regression parameters of the curved surfaces for the soil-gravel mixtures with a large range of gravel content could be determined from the water retention data of the soil-gravel mixtures with two representative gravel contents or bulk densities. Such revised water retention models are potentially applicable in regional or large scale field investigations of significantly heterogeneous media, where various gravel sizes and different gravel contents are present. PMID:23555040

Modeling the cadmium balance in Australian agricultural systems in view of potential impacts on food and water quality.

PubMed

de Vries, W; McLaughlin, M J

2013-09-01

The historical build up and future cadmium (Cd) concentrations in top soils and in crops of four Australian agricultural systems are predicted with a mass balance model, focusing on the period 1900-2100. The systems include a rotation of dryland cereals, a rotation of sugarcane and peanuts/soybean, intensive dairy production and intensive horticulture. The input of Cd to soil is calculated from fertilizer application and atmospheric deposition and also examines options including biosolid and animal manure application in the sugarcane rotation and dryland cereal production systems. Cadmium output from the soil is calculated from leaching to deeper horizons and removal with the harvested crop or with livestock products. Parameter values for all Cd fluxes were based on a number of measurements on Australian soil-plant systems. In the period 1900-2000, soil Cd concentrations were predicted to increase on average between 0.21 mg kg(-1) in dryland cereals, 0.42 mg kg(-1) in intensive agriculture and 0.68 mg kg(-1) in dairy production, which are within the range of measured increases in soils in these systems. Predicted soil concentrations exceed critical soil Cd concentrations, based on food quality criteria for Cd in crops during the simulation period in clay-rich soils under dairy production and intensive horticulture. Predicted dissolved Cd concentrations in soil pore water exceed a ground water quality criterion of 2 μg l(-1) in light textured soils, except for the sugarcane rotation due to large water leaching fluxes. Results suggest that the present fertilizer Cd inputs in Australia are in excess of the long-term critical loads in heavy-textured soils for dryland cereals and that all other systems are at low risk. Calculated critical Cd/P ratios in P fertilizers vary from <50 to >1000 mg Cd kg P(-1) for the different soil, crop and environmental conditions applied. Copyright © 2013 Elsevier B.V. All rights reserved.

Identifying desertification risk areas using fuzzy membership and geospatial technique - A case study, Kota District, Rajasthan

NASA Astrophysics Data System (ADS)

Dasgupta, Arunima; Sastry, K. L. N.; Dhinwa, P. S.; Rathore, V. S.; Nathawat, M. S.

2013-08-01

Desertification risk assessment is important in order to take proper measures for its prevention. Present research intends to identify the areas under risk of desertification along with their severity in terms of degradation in natural parameters. An integrated model with fuzzy membership analysis, fuzzy rule-based inference system and geospatial techniques was adopted, including five specific natural parameters namely slope, soil pH, soil depth, soil texture and NDVI. Individual parameters were classified according to their deviation from mean. Membership of each individual values to be in a certain class was derived using the normal probability density function of that class. Thus if a single class of a single parameter is with mean μ and standard deviation σ, the values falling beyond μ + 2 σ and μ - 2 σ are not representing that class, but a transitional zone between two subsequent classes. These are the most important areas in terms of degradation, as they have the lowest probability to be in a certain class, hence highest probability to be extended or narrowed down in next or previous class respectively. Eventually, these are the values which can be easily altered, under extrogenic influences, hence are identified as risk areas. The overall desertification risk is derived by incorporating the different risk severity of each parameter using fuzzy rule-based interference system in GIS environment. Multicriteria based geo-statistics are applied to locate the areas under different severity of desertification risk. The study revealed that in Kota, various anthropogenic pressures are accelerating land deterioration, coupled with natural erosive forces. Four major sources of desertification in Kota are, namely Gully and Ravine erosion, inappropriate mining practices, growing urbanization and random deforestation.

Profiling microbial community structures across six large oilfields in China and the potential role of dominant microorganisms in bioremediation.

PubMed

Sun, Weimin; Li, Jiwei; Jiang, Lei; Sun, Zhilei; Fu, Meiyan; Peng, Xiaotong

2015-10-01

Successful bioremediation of oil pollution is based on a comprehensive understanding of the in situ physicochemical conditions and indigenous microbial communities as well as the interaction between microorganisms and geochemical variables. Nineteen oil-contaminated soil samples and five uncontaminated controls were taken from six major oilfields across different geoclimatic regions in China to investigate the spatial distribution of the microbial ecosystem. Microbial community analysis revealed remarkable variation in microbial diversity between oil-contaminated soils taken from different oilfields. Canonical correspondence analysis (CCA) further demonstrated that a suite of in situ geochemical parameters, including soil moisture and sulfate concentrations, were among the factors that influenced the overall microbial community structure and composition. Phylogenetic analysis indicated that the vast majority of sequences were related to the genera Arthrobacter, Dietzia, Pseudomonas, Rhodococcus, and Marinobacter, many of which contain known oil-degrading or oil-emulsifying species. Remarkably, a number of archaeal genera including Halalkalicoccus, Natronomonas, Haloterrigena, and Natrinema were found in relatively high abundance in some of the oil-contaminated soil samples, indicating that these Euryarchaeota may play an important ecological role in some oil-contaminated soils. This study offers a direct and reliable reference of the diversity of the microbial community in various oil-contaminated soils and may influence strategies for in situ bioremediation of oil pollution.

Likelihood parameter estimation for calibrating a soil moisture using radar backscatter

USDA-ARS?s Scientific Manuscript database

Assimilating soil moisture information contained in synthetic aperture radar imagery into land surface model predictions can be done using a calibration, or parameter estimation, approach. The presence of speckle, however, necessitates aggregating backscatter measurements over large land areas in or...

Symbiosis of Arbuscular Mycorrhizal Fungi and Robinia pseudoacacia L. Improves Root Tensile Strength and Soil Aggregate Stability

PubMed Central

Zhang, Haoqiang; Liu, Zhenkun; Chen, Hui; Tang, Ming

2016-01-01

Robinia pseudoacacia L. (black locust) is a widely planted tree species on Loess Plateau for revegetation. Due to its symbiosis forming capability with arbuscular mycorrhizal (AM) fungi, we explored the influence of arbuscular mycorrhizal fungi on plant biomass, root morphology, root tensile strength and soil aggregate stability in a pot experiment. We inoculated R. pseudoacacia with/without AM fungus (Rhizophagus irregularis or Glomus versiforme), and measured root colonization, plant growth, root morphological characters, root tensile force and tensile strength, and parameters for soil aggregate stability at twelve weeks after inoculation. AM fungi colonized more than 70% plant root, significantly improved plant growth. Meanwhile, AM fungi elevated root morphological parameters, root tensile force, root tensile strength, Glomalin-related soil protein (GRSP) content in soil, and parameters for soil aggregate stability such as water stable aggregate (WSA), mean weight diameter (MWD) and geometric mean diameter (GMD). Root length was highly correlated with WSA, MWD and GMD, while hyphae length was highly correlated with GRSP content. The improved R. pseudoacacia growth, root tensile strength and soil aggregate stability indicated that AM fungi could accelerate soil fixation and stabilization with R. pseudoacacia, and its function in revegetation on Loess Plateau deserves more attention. PMID:27064570

[Parameters optimization and cleaning efficiency evaluation of attrition scrubbing remediation of Pb-contaminated soil].

PubMed

Yang, Wen; Huang, Jin-lou; Peng, Hui-qing; Li, Si-tuo

2013-09-01

Attrition scrubbing was used to remediate lead contaminated-site soil, and the main purpose was to remove fine particles and lead contaminants from the surface of sand. The optimal parameters of attrition scrubbing were determined by orthogonal experiment, and three soil samples with different lead concentration were subjected to attrition scrubbing experiments. The results showed that the optimal scrubbing parameters were: a solid ratio of 70% dry matter, a temperature of 25 degrees C, an attrition time of 30 min, and an attrition speed of 1200 r x min(-1). Before attrition scrubbing, the screening and analysis of soil showed that in all three soil samples, lead was mainly enriched on sand and fine particles, and the distribution of lead was highly correlated to the organic matter. After attrition scrubbing, the washing efficiency of the original state lead contaminated sand soil in triplicates was 67.61%, 31.71% and 41.01%, respectively, which indicates that attrition scrubbing can remove part of the fine soil and lead contaminants from the surface of sand, to accomplish the purpose of pollutants enrichment. Scanning electron microscopy (SEM) analysis showed that the sand surface became smooth after attrition scrubbing. The results above show that attrition scrubbing has a good washing effect for the remediation of lead contaminated sand soil.

Symbiosis of Arbuscular Mycorrhizal Fungi and Robinia pseudoacacia L. Improves Root Tensile Strength and Soil Aggregate Stability.

PubMed

Zhang, Haoqiang; Liu, Zhenkun; Chen, Hui; Tang, Ming

2016-01-01

Robinia pseudoacacia L. (black locust) is a widely planted tree species on Loess Plateau for revegetation. Due to its symbiosis forming capability with arbuscular mycorrhizal (AM) fungi, we explored the influence of arbuscular mycorrhizal fungi on plant biomass, root morphology, root tensile strength and soil aggregate stability in a pot experiment. We inoculated R. pseudoacacia with/without AM fungus (Rhizophagus irregularis or Glomus versiforme), and measured root colonization, plant growth, root morphological characters, root tensile force and tensile strength, and parameters for soil aggregate stability at twelve weeks after inoculation. AM fungi colonized more than 70% plant root, significantly improved plant growth. Meanwhile, AM fungi elevated root morphological parameters, root tensile force, root tensile strength, Glomalin-related soil protein (GRSP) content in soil, and parameters for soil aggregate stability such as water stable aggregate (WSA), mean weight diameter (MWD) and geometric mean diameter (GMD). Root length was highly correlated with WSA, MWD and GMD, while hyphae length was highly correlated with GRSP content. The improved R. pseudoacacia growth, root tensile strength and soil aggregate stability indicated that AM fungi could accelerate soil fixation and stabilization with R. pseudoacacia, and its function in revegetation on Loess Plateau deserves more attention.

The modelling influence of water content to mechanical parameter of soil in analysis of slope stability

NASA Astrophysics Data System (ADS)

Gusman, M.; Nazki, A.; Putra, R. R.

2018-04-01

One of the parameters in slope stability analysis is the shear strength of the soil. Changes in soil shear strength characteristics lead to a decrease in safety factors on the slopes. This study aims to see the effect of increased moisture content on soil mechanical parameters. The case study study was conducted on the slopes of Sitinjau Lauik Kota Padang. The research method was done by laboratory analysis and simple liniear regression analysis and multiple. Based on the test soil results show that the increase in soil water content causes a decrease in cohesion values and internal shear angle. The relationship of moisture content to cohesion is described in equation Y = 55.713-0,6X with R2 = 0.842. While the relationship of water content to shear angle in soil is described in the equation Y = 38.878-0.258X with R2 = 0.915. From several simulations of soil water level improvement, calculation of safety factor (SF) of slope. The calculation results show that the increase of groundwater content is very significant affect the safety factor (SF) slope. SF slope values are in safe condition when moisture content is 50% and when it reaches maximum water content 73.74% slope safety factor value potentially for landslide.

Denaturing gradient gel electrophoresis fingerprinting of soil bacteria in the vicinity of the Chinese Great Wall Station, King George Island, Antarctica.

PubMed

Pan, Qi; Wang, Feng; Zhang, Yang; Cai, Minghong; He, Jianfeng; Yang, Haizhen

2013-08-01

Bacterial diversity was investigated in soil samples collected from 13 sites around the Great Wall Station, Fildes Peninsula, King George Island, Antarctica, using denaturing gradient gel electrophoresis (DGGE) of 16S rRNA genes. The classes alpha-, beta-, and gamma-Proteobacteria, as well as the phylum Actinobacteria, were found to be the dominant bacteria in the soils around the Great Wall Station. Although the selected samples were not contaminated by oil, a relationship between soil parameters, microbial biodiversity, and human impact was still seen. Sample sites in human impacted areas showed lower bacterial biodiversity (average H' = 2.65) when compared to non-impacted sites (average H' = 3.05). There was no statistically significant correlation between soil bacterial diversity and total organic carbon (TOC), total nitrogen, or total phosphorus contents of the soil. Canonical correlation analysis showed that TOC content was the most important factor determining bacterial community profiles among the measured soil parameters. In conclusion, microbial biodiversity and community characteristics within relatively small scales (1.5 km) were determined as a function of local environment parameters and anthropogenic impact.

Soil process-oriented modelling of within-field variability based on high-resolution 3D soil type distribution maps.

NASA Astrophysics Data System (ADS)

Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe

2016-04-01

Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon (SOC), as essential input variable, was predicted by measured soil samples and associated to STD of the upper 30 cm. The comprehensive and high-resolution (4x4 m) soil profile information (up to 2 m soil depth) were then used to initialise a soil process model (Carbon and Nitrogen Dynamics - CANDY) for soil functional modelling (daily steps of matter fluxes, soil temperature and water balances). Our study was conducted on a practical field (~32,000 m²) of an agricultural farm in Central Germany with Chernozem soils under arid conditions (average rainfall < 550 mm). This soil region is known to have differences in soil structure mainly occurring within the subsoil, since topsoil conditions are described as homogenous. The modelled soil functions considered local climate information and practical farming activities. Results show, as expected, distinguished functional variability, both on spatial and temporal resolution for subsoil evident structures, e.g. visible differences for available water capacity within 0-100 cm but homogenous conditions for the topsoil.

Comparative analysis of tree classification models for detecting fusarium oxysporum f. sp cubense (TR4) based on multi soil sensor parameters

NASA Astrophysics Data System (ADS)

Estuar, Maria Regina Justina; Victorino, John Noel; Coronel, Andrei; Co, Jerelyn; Tiausas, Francis; Señires, Chiara Veronica

2017-09-01

Use of wireless sensor networks and smartphone integration design to monitor environmental parameters surrounding plantations is made possible because of readily available and affordable sensors. Providing low cost monitoring devices would be beneficial, especially to small farm owners, in a developing country like the Philippines, where agriculture covers a significant amount of the labor market. This study discusses the integration of wireless soil sensor devices and smartphones to create an application that will use multidimensional analysis to detect the presence or absence of plant disease. Specifically, soil sensors are designed to collect soil quality parameters in a sink node from which the smartphone collects data from via Bluetooth. Given these, there is a need to develop a classification model on the mobile phone that will report infection status of a soil. Though tree classification is the most appropriate approach for continuous parameter-based datasets, there is a need to determine whether tree models will result to coherent results or not. Soil sensor data that resides on the phone is modeled using several variations of decision tree, namely: decision tree (DT), best-fit (BF) decision tree, functional tree (FT), Naive Bayes (NB) decision tree, J48, J48graft and LAD tree, where decision tree approaches the problem by considering all sensor nodes as one. Results show that there are significant differences among soil sensor parameters indicating that there are variances in scores between the infected and uninfected sites. Furthermore, analysis of variance in accuracy, recall, precision and F1 measure scores from tree classification models homogeneity among NBTree, J48graft and J48 tree classification models.

User Requirements for the Application of Remote Sensing in the Planning and Management of Water Resource Systems

NASA Technical Reports Server (NTRS)

Burgy, R. H.

1972-01-01

Data relating to hydrologic and water resource systems and subsystems management are reported. Systems models, user application, and remote sensing technology are covered. Parameters governing water resources include evaportranspiration, vegetation, precipitation, streams and estuaries, reservoirs and lakes, and unsaturate and saturated soil zones.

C-SWAT: The Soil and Water Assessment Tool with consolidated input files in alleviating computational burden of recursive simulations

USDA-ARS?s Scientific Manuscript database

The temptation to include model parameters and high resolution input data together with the availability of powerful optimization and uncertainty analysis algorithms has significantly enhanced the complexity of hydrologic and water quality modeling. However, the ability to take advantage of sophist...

Application of the MAGIC model to the Glacier Lakes catchments

Treesearch

John O. Reuss

1994-01-01

The MAGIC model (Cosby et al. 1985, 1986) was calibrated for East and West Glacier Lakes, two adjacent high-altitude (3200 m- 3700 m) catchments in the Medicine Bow National Forest of southern Wyoming. This model uses catchment characteristics including weathering rates, soil chemical characteristics, hydrological parameters, and precipitation amounts and composition...

Evaluating the effect of tillage on soil structural properties using the pedostructure concept

USDA-ARS?s Scientific Manuscript database

The pedostructure (PS) concept is a physically-based method of soil characterization that defines a soil based on its structure and the relationship between structure and soil water behavior. There are fifteen unique pedostructure parameters that define the macropore and micropore soil water behavio...

Soil quality parameters for row-crop and grazed pasture systems with agroforestry buffers

USDA-ARS?s Scientific Manuscript database

Incorporation of trees and establishment of buffers are practices that can improve soil quality. Soil enzyme activities and water stable aggregates are sensitive indices for assessing soil quality by detecting early changes in soil management. However, studies comparing grazed pasture and row crop...

Average pollutant concentration in soil profile simulated with Convective-Dispersive Equation. Model and Manual

USDA-ARS?s Scientific Manuscript database

Different parts of soil solution move with different velocities, and therefore chemicals are leached gradually from soil with infiltrating water. Solute dispersivity is the soil parameter characterizing this phenomenon. To characterize the dispersivity of soil profile at field scale, it is desirable...

Use of a flux-based field capacity criterion to identify effective hydraulic parameters of layered soil profiles subjected to synthetic drainage experiments

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Romano, Nunzio

2016-01-01

This study explores the feasibility of identifying the effective soil hydraulic parameterization of a layered soil profile by using a conventional unsteady drainage experiment leading to field capacity. The flux-based field capacity criterion is attained by subjecting the soil profile to a synthetic drainage process implemented numerically in the Soil-Water-Atmosphere-Plant (SWAP) model. The effective hydraulic parameterization is associated to either aggregated or equivalent parameters, the former being determined by the geometrical scaling theory while the latter is obtained through the inverse modeling approach. Outcomes from both these methods depend on information that is sometimes difficult to retrieve at local scale and rather challenging or virtually impossible at larger scales. The only knowledge of topsoil hydraulic properties, for example, as retrieved by a near-surface field campaign or a data assimilation technique, is often exploited as a proxy to determine effective soil hydraulic parameterization at the largest spatial scales. Comparisons of the effective soil hydraulic characterization provided by these three methods are conducted by discussing the implications for their use and accounting for the trade-offs between required input information and model output reliability. To better highlight the epistemic errors associated to the different effective soil hydraulic properties and to provide some more practical guidance, the layered soil profiles are then grouped by using the FAO textural classes. For the moderately heterogeneous soil profiles available, all three approaches guarantee a general good predictability of the actual field capacity values and provide adequate identification of the effective hydraulic parameters. Conversely, worse performances are encountered for the highly variable vertical heterogeneity, especially when resorting to the "topsoil-only" information. In general, the best performances are guaranteed by the equivalent parameters, which might be considered a reference for comparisons with other techniques. As might be expected, the information content of the soil hydraulic properties pertaining only to the uppermost soil horizon is rather inefficient and also not capable to map out the hydrologic behavior of the real vertical soil heterogeneity since the drainage process is significantly affected by profile layering in almost all cases.

Modeling leaching of viruses by the Monte Carlo method.

PubMed

Faulkner, Barton R; Lyon, William G; Khan, Faruque A; Chattopadhyay, Sandip

2003-11-01

A predictive screening model was developed for fate and transport of viruses in the unsaturated zone by applying the final value theorem of Laplace transformation to previously developed governing equations. A database of input parameters allowed Monte Carlo analysis with the model. The resulting kernel densities of predicted attenuation during percolation indicated very small, but finite probabilities of failure for all homogeneous USDA classified soils to attenuate reovirus 3 by 99.99% in one-half meter of gravity drainage. The logarithm of saturated hydraulic conductivity and water to air-water interface mass transfer coefficient affected virus fate and transport about 3 times more than any other parameter, including the logarithm of inactivation rate of suspended viruses. Model results suggest extreme infiltration events may play a predominant role in leaching of viruses in soils, since such events could impact hydraulic conductivity. The air-water interface also appears to play a predominating role in virus transport and fate. Although predictive modeling may provide insight into actual attenuation of viruses, hydrogeologic sensitivity assessments for the unsaturated zone should include a sampling program.

Stabilization of Black Cotton Soil Using Micro-fine Slag

NASA Astrophysics Data System (ADS)

Shukla, Rajesh Prasad; Parihar, Niraj Singh

2016-09-01

This work presents the results of laboratory tests conducted on black cotton soil mixed with micro-fine slag. Different proportions of micro-fine slag, i.e., 3, 6, 9, 12 and 15 % were mixed with the black cotton soil to improve soil characteristics. The improvement in the characteristics of stabilized soil was assessed by evaluating the changes in the physical and strength parameters of the soil, namely, the Atterberg limits, free swell, the California Bearing Ratio (CBR), compaction parameters and Unconfined Compressive Strength (UCS). The mixing of micro-fine slag decreases the liquid limit, plasticity index and Optimum Moisture Contents (OMC) of the soil. Micro-fine slag significantly increases the plastic limit, UCS and CBR of the soil up to 6-7 % mixing, but mixing of more slag led to decrease in the UCS and CBR of the soil. The unsoaked CBR increased by a substantial amount unlike soaked CBR value. The swell potential of the soil is reduced from medium to very low. The optimum amount of micro-fine slag is found to be approximately 6-7 % by the weight of the soil.

Study on friction coefficient of soft soil based on particle flow code

NASA Astrophysics Data System (ADS)

Lei, Xiaohong; Zhang, Zhongwei

2017-04-01

There has no uniform method for determining the micro parameters in particle flow code, and the corresponding formulas obtained by each scholar can only be applied to similar situations. In this paper, the relationship between the micro parameters friction coefficient and macro parameters friction angle is established by using the two axis servo compression as the calibration experiment, and the corresponding formula is fitted to solve the difficulties of determining the PFC micro parameters which provide a reference for determination of the micro parameters of soft soil.

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yu; Hou, Zhangshuan; Huang, Maoyi

2013-12-10

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find thatmore » using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.« less

Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction

NASA Astrophysics Data System (ADS)

Baatz, Roland; Hendricks Franssen, Harrie-Jan; Han, Xujun; Hoar, Tim; Reemt Bogena, Heye; Vereecken, Harry

2017-05-01

In situ soil moisture sensors provide highly accurate but very local soil moisture measurements, while remotely sensed soil moisture is strongly affected by vegetation and surface roughness. In contrast, cosmic-ray neutron sensors (CRNSs) allow highly accurate soil moisture estimation on the field scale which could be valuable to improve land surface model predictions. In this study, the potential of a network of CRNSs installed in the 2354 km2 Rur catchment (Germany) for estimating soil hydraulic parameters and improving soil moisture states was tested. Data measured by the CRNSs were assimilated with the local ensemble transform Kalman filter in the Community Land Model version 4.5. Data of four, eight and nine CRNSs were assimilated for the years 2011 and 2012 (with and without soil hydraulic parameter estimation), followed by a verification year 2013 without data assimilation. This was done using (i) a regional high-resolution soil map, (ii) the FAO soil map and (iii) an erroneous, biased soil map as input information for the simulations. For the regional soil map, soil moisture characterization was only improved in the assimilation period but not in the verification period. For the FAO soil map and the biased soil map, soil moisture predictions improved strongly to a root mean square error of 0.03 cm3 cm-3 for the assimilation period and 0.05 cm3 cm-3 for the evaluation period. Improvements were limited by the measurement error of CRNSs (0.03 cm3 cm-3). The positive results obtained with data assimilation of nine CRNSs were confirmed by the jackknife experiments with four and eight CRNSs used for assimilation. The results demonstrate that assimilated data of a CRNS network can improve the characterization of soil moisture content on the catchment scale by updating spatially distributed soil hydraulic parameters of a land surface model.

Enzymatic activities in a semiarid soil amended with different soil treatment: Soil quality improvement

NASA Astrophysics Data System (ADS)

Hueso González, Paloma; Elbl, Jakub; Dvořáčková, Helena; Francisco Martinez Murillo, Juan; Damian Ruiz Sinoga, Jose

2017-04-01

The use of soil quality indicators may be an effective approach to assess the positive effect of the organic amendment as good restoration methods. Relying on the natural fertility of the soil, the most commonly chemical and physical parameters used to evaluate soil quality are depend to the soil biological parameters. The measurement of soil basal respiration and the mineralization of organic matter are commonly accepted as a key indicator for measuring changes to soil quality. Thus, the simultaneous measurement of various enzymes seems to be useful to evaluate soil biochemical activity and related processes. In this line, Dehydrogenase activity is widely used in evaluating the metabolic activity of soil microorganisms and to evaluate the effects caused by the addition of organic amendments. Variations in phosphatase activity, apart from indicating changes in the quantity and quality of soil phosphorated substrates, are also good indicators of soil biological status. This study assesses the effect of five soil amendments as restoration techniques for semiarid Mediterrenean ecosystems. The goal is to interpret the status of biological and chemical parameters in each treatment as soil quality indicators in degraded forests. The main objectives were to: i) analyze the effect of various organic amendments on the enzimatic activity of soil; ii) analyze the effect of the amendments on soil respiration; iii) assess the effect of these parameters on the soil chemical properties which are indicative of soil healthy; and iv) evaluated form the land management point of view which amendment could result a effective method to restore Mediterranean degraded areas. An experimental paired-plot layout was established in southern of Spain (homogeneous slope gradient: 7.5%; aspect: N170). Five amendments were applied in an experimental set of plots: straw mulching; mulch with chipped branches of Aleppo Pine (Pinus halepensis Mill.); TerraCotten hydroabsobent polymers; sewage sludge; sheep manure and; control (without amendment). Five years after the amendment addition, soil from the 12 plots was sampled. Three samples were collected from each plot (36 soil samples in total) from the soil surface, e.g. 0-10 cm, in which most soil transformations occur. Soil indicators analyzed were: i) EC; ii) pH; iii) soil organic C (SOC); iv)total Nitrogen (N); v) Carbon of microbial biomass; vi) Dehydrogenase activity; Phosphatase activity and; vii) basal respiration. According to our results, the straw mulch, pinus mulch and sewage sludge treatments helped to maintain the SOC and N at high levels, five years after the amendment addition and comparing to the control. A similar trend has been registered for the dehydrogenase activity, phosphatase activity and basal respiration. Conversely, regarding to control, when the soils were amended with polymers or manure, no significant differences in soil chemical and biological properties were found. In conclusion, from a land management standpoint, the use of pinus mulch, straw mulch and sewage sludge have been proved as a significant method to increase soil quality on Mediterranean semiarid degraded forests.

Predicting Soluble Nickel in Soils Using Soil Properties and Total Nickel

PubMed Central

Zhang, Xiaoqing; Li, Jumei; Wei, Dongpu; Li, Bo; Ma, Yibing

2015-01-01

Soil soluble nickel (Ni) concentration is very important for determining soil Ni toxicity. In the present study, the relationships between soil properties, total and soluble Ni concentrations in soils were developed in a wide range of soils with different properties and climate characteristics. The multiple regressions showed that soil pH and total soil Ni concentrations were the most significant parameters in predicting soluble Ni concentrations with the adjusted determination coefficients (Radj 2) values of 0.75 and 0.68 for soils spiked with soluble Ni salt and the spiked soils leached with artificial rainwater to mimic field conditions, respectively. However, when the soils were divided into three categories (pH < 7, 7–8 and > 8), they obtained better predictions with Radj 2 values of 0.78–0.90 and 0.79–0.94 for leached and unleached soils, respectively. Meanwhile, the other soil properties, such as amorphous Fe and Al oxides and clay, were also found to be important for determining soluble Ni concentrations, indicating that they were also presented as active adsorbent surfaces. Additionally, the whole soil speciation including bulk soil properties and total soils Ni concentrations were analyzed by mechanistic speciation models WHAM VI and Visual MINTEQ3.0. It was found that WHAM VI provided the best predictions for the soils with pH < 7, was relatively reasonable for pH 7 to 8, and gave an overestimation for pH > 8. The Visual MINTEQ3.0 could provide better estimation for pH < 8 and meanwhile quite reasonable results for pH > 8. These results indicated the possibility and applicability of these models to predict soil soluble Ni concentration by soil properties. PMID:26217951

Predicting Soluble Nickel in Soils Using Soil Properties and Total Nickel.

PubMed

Zhang, Xiaoqing; Li, Jumei; Wei, Dongpu; Li, Bo; Ma, Yibing

2015-01-01

Soil soluble nickel (Ni) concentration is very important for determining soil Ni toxicity. In the present study, the relationships between soil properties, total and soluble Ni concentrations in soils were developed in a wide range of soils with different properties and climate characteristics. The multiple regressions showed that soil pH and total soil Ni concentrations were the most significant parameters in predicting soluble Ni concentrations with the adjusted determination coefficients (Radj2) values of 0.75 and 0.68 for soils spiked with soluble Ni salt and the spiked soils leached with artificial rainwater to mimic field conditions, respectively. However, when the soils were divided into three categories (pH < 7, 7-8 and > 8), they obtained better predictions with Radj2 values of 0.78-0.90 and 0.79-0.94 for leached and unleached soils, respectively. Meanwhile, the other soil properties, such as amorphous Fe and Al oxides and clay, were also found to be important for determining soluble Ni concentrations, indicating that they were also presented as active adsorbent surfaces. Additionally, the whole soil speciation including bulk soil properties and total soils Ni concentrations were analyzed by mechanistic speciation models WHAM VI and Visual MINTEQ3.0. It was found that WHAM VI provided the best predictions for the soils with pH < 7, was relatively reasonable for pH 7 to 8, and gave an overestimation for pH > 8. The Visual MINTEQ3.0 could provide better estimation for pH < 8 and meanwhile quite reasonable results for pH > 8. These results indicated the possibility and applicability of these models to predict soil soluble Ni concentration by soil properties.

The Temporal Dynamics of Spatial Patterns of Observed Soil Moisture Interpreted Using the Hydrus 1-D Model

NASA Astrophysics Data System (ADS)

Chen, M.; Willgoose, G. R.; Saco, P. M.

2009-12-01

This paper investigates the soil moisture dynamics over two subcatchments (Stanley and Krui) in the Goulburn River in NSW during a three year period (2005-2007) using the Hydrus 1-D unsaturated soil water flow model. The model was calibrated to the seven Stanley microcatchment sites (1 sqkm site) using continuous time surface 30cm and full profile soil moisture measurements. Soil type, leaf area index and soil depth were found to be the key parameters changing model fit to the soil moisture time series. They either shifted the time series up or down, changed the steepness of dry-down recessions or determined the lowest point of soil moisture dry-down respectively. Good correlations were obtained between observed and simulated soil water storage (R=0.8-0.9) when calibrated parameters for one site were applied to the other sites. Soil type was also found to be the main determinant (after rainfall) of the mean of modelled soil moisture time series. Simulations of top 30cm were better than those of the whole soil profile. Within the Stanley microcatchment excellent soil moisture matches could be generated simply by adjusting the mean of soil moisture up or down slightly. Only minor modification of soil properties from site to site enable good fits for all of the Stanley sites. We extended the predictions of soil moisture to a larger spatial scale of the Krui catchment (sites up to 30km distant from Stanley) using soil and vegetation parameters from Stanley but the locally recorded rainfall at the soil moisture measurement site. The results were encouraging (R=0.7~0.8). These results show that it is possible to use a calibrated soil moisture model to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000km2. This paper demonstrates the potential usefulness of continuous time, point scale soil moisture (typical of that measured by permanently installed TDR probes) in predicting the soil wetness status over a catchment of significant size.

A Soil Temperature Model for Closed Canopied Forest Stands

Treesearch

James M. Vose; Wayne T. Swank

1991-01-01

A microcomputer-based soil temperature model was developed to predict temperature at the litter-soil interface and soil temperatures at three depths (0.10 m, 0.20 m, and 1.25 m) under closed forest canopies. Comparisons of predicted and measured soil temperatures indicated good model performance under most conditions. When generalized parameters describing soil...

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar

PubMed Central

Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco

2008-01-01

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. PMID:27879932

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

USGS Publications Warehouse

Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

2011-01-01

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

The analysis of soil cores polluted with certain metals using the Box-Cox transformation.

PubMed

Meloun, Milan; Sánka, Milan; Nemec, Pavel; Krítková, Sona; Kupka, Karel

2005-09-01

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples.

Detecting seasonal variations of soil parameters via field measurements and stochastic simulations in the hillslope

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; An, Hyunuk; Kim, Sanghyun

2015-04-01

Soil moisture, a critical factor in hydrologic systems, plays a key role in synthesizing interactions among soil, climate, hydrological response, solute transport and ecosystem dynamics. The spatial and temporal distribution of soil moisture at a hillslope scale is essential for understanding hillslope runoff generation processes. In this study, we implement Monte Carlo simulations in the hillslope scale using a three-dimensional surface-subsurface integrated model (3D model). Numerical simulations are compared with multiple soil moistures which had been measured using TDR(Mini_TRASE) for 22 locations in 2 or 3 depths during a whole year at a hillslope (area: 2100 square meters) located in Bongsunsa Watershed, South Korea. In stochastic simulations via Monte Carlo, uncertainty of the soil parameters and input forcing are considered and model ensembles showing good performance are selected separately for several seasonal periods. The presentation will be focused on the characterization of seasonal variations of model parameters based on simulations with field measurements. In addition, structural limitations of the contemporary modeling method will be discussed.

Contrasting influence of soil nutrients and microbial community on differently sized basal consumers

NASA Astrophysics Data System (ADS)

Vonk, J. Arie; Mulder, Christian

2013-07-01

There is increasing evidence of the coexistence of trophic and environmental constraints belowground. While too often ignored in current literature, the extent to which phosphorus is relevant for soil biota was demonstrated in this study by positive correlations of soil C/P and N/P ratios with all the measured microbial parameters (biomass, density and activity), with the numerical abundance of roundworms (Nematoda) and potworms (Enchytraeidae) from lower trophic levels and with the roundworm biomass. Total worm biomass seems dependent on land use, being in rangelands about twice as high as in croplands, although the relative contribution of potworms remains comparable for both land use types (49 ± 20 % SD versus 45 ± 27 % SD). Besides soil [P], soil type plays an important role in the relative biomass of potworms compared to roundworms. Soil parameters (here pH, C/P and N/P ratios) are better predictors for the abundance and biomass of roundworms than microbial parameters. We also propose a graphical way to visualize the major responses of basal consumers to their microbial drivers.

Observations of net soil exchange of CO2 in a dryland show experimental warming increases carbon losses in biocrust soils

USGS Publications Warehouse

Darrouzet-Nardi, Anthony N.; Reed, Sasha C.; Grote, Ed; Belnap, Jayne

2015-01-01

Many arid and semiarid ecosystems have soils covered with well-developed biological soil crust communities (biocrusts) made up of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface. These communities are a fundamental component of dryland ecosystems, and are critical to dryland carbon (C) cycling. To examine the effects of warming temperatures on soil C balance in a dryland ecosystem, we used infrared heaters to warm biocrust-dominated soils to 2 °C above control conditions at a field site on the Colorado Plateau, USA. We monitored net soil exchange (NSE) of CO2 every hour for 21 months using automated flux chambers (5 control and 5 warmed chambers), which included the CO2 fluxes of the biocrusts and the soil beneath them. We observed measurable photosynthesis in biocrust soils on 12 % of measurement days, which correlated well with precipitation events and soil wet-up. These days included several snow events, providing what we believe to be the first evidence of substantial photosynthesis underneath snow by biocrust organisms in drylands. Overall, biocrust soils in both control and warmed plots were net CO2 sources to the atmosphere, with control plots losing 62 ± 8 g C m−2 (mean ± SE) over the first year of measurement and warmed plots losing 74 ± 9 g C m−2. Between control and warmed plots, the difference in soil C loss was uncertain over the course of the entire year due to large and variable rates in spring, but on days during which soils were wet and crusts were actively photosynthesizing, biocrusts that were warmed by 2 °C had a substantially more negative C balance (i.e., biocrust soils took up less C and/or lost more C in warmed plots). Taken together, our data suggest a substantial risk of increased C loss from biocrust soils with higher future temperatures, and highlight a robust capacity to predict CO2 exchange in biocrust soils using easily measured environmental parameters.

Microclimatic modeling of the desert in the United Arab Emirates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalil, A.K.; Abdrabboh, M.A.; Kamel, K.A.

1996-10-01

The present study is concerned with the prediction of the weather parameters in the microclimate layer (less than 2 m above the ground surface) in the desert and sparsely vegetated areas in the United Arab Emirates. A survey was made of the weather data in these regions including solar radiation, wind speed, screen temperatures and relative humidity. Additionally, wind speed data were obtained at heights below two meters and surface albedo was recorded for various soil and vegetation conditions. A survey was also carried out for the different plant species in various areas of the U.A.E. Data on soil andmore » surface temperature were then analyzed. An energy balance model was formulated including incident short- and long-wave length radiation between earth and sky, convective heat transfer to/from earth surface, surface reflection of solar radiation and soil/plant evapotranspiration. An explicit one dimensional finite difference scheme was adapted to solve the resulting algebraic finite difference equations. The equation for surface nodes included thermal radiation as well as convection effects. The heat transfer coefficient was evaluated on the basis of wind speed and surface roughness at the site where the energy balance was set. Theoretical predictions of air and soil temperatures were accordingly compared to experimental measurements in selected sites, where reasonable agreements were observed.« less

Usefulness of Mehlich-3 test in the monitoring of phosphorus dispersion from Polish arable soils.

PubMed

Szara, Ewa; Sosulski, Tomasz; Szymańska, Magdalena; Szyszkowska, Katarzyna

2018-04-19

A considerable area of soils with low abundance of plant-available phosphorus and relatively low consumption of phosphorus fertilisers recorded in Poland over the last 20-25 years suggests that the dispersion of phosphates from arable soils in Poland can be low. The literature, however, provides reports on a considerable share of Polish agriculture in phosphorus pollution of Baltic Sea waters. The literature provides no data concerning phosphorus sorption parameters of arable soils in Poland. Due to this, the study involved the analysis of sorption properties: 1-point phosphorus sorption index (PSI) and degree of phosphorus saturation, based on molar ratio P, Al, and Fe determined by the Mehlich-3 method (DPS-1 M3  = P / (Al + Fe) and DPS-2 M3  = P / Al), 59 soils representing the main types of texture of soils in Poland, characterised by variable content of plant-available phosphorus by Egner-Riehm DL, organic carbon, and soil pH. The obtained results suggest that the soil texture has a lower effect on sorption properties (PSI) than the degree of acidification. Sorption parameters of soils increased with soil acidification as a result of an increase in the content of Al and Fe extracted by the Mehlich-3 extract in strongly acidified soils. An important finding of our study was evidencing that within the same class of abundance in plant-available phosphorus, the soils varied in the degree of phosphorus saturation and content of active phosphorus. This suggests the possibility of losses of phosphorus even from soils with low abundance of the component provided they are characterised by a high value of parameters DPS-1 M3 and DPS-2 M3 .

Isolation of plant-growth-promoting rhizobacteria from rhizospheric soil of halophytes and their impact on maize (Zea mays L.) under induced soil salinity.

PubMed

Ullah, Sami; Bano, Asghari

2015-04-01

The present investigation was aimed to scrutinize the salt tolerance potential of plant-growth-promoting rhizobacteria (PGPR) isolated from rhizospheric soil of selected halophytes (Atriplex leucoclada, Haloxylon salicornicum, Lespedeza bicolor, Suaeda fruticosa, and Salicornica virginica) collected from high-saline fields (electrical conductivity 4.3-5.5) of District Mardan, Pakistan. Five PGPR strains were identified using 16S rRNA amplification and sequence analysis. Bacillus sp., isolated from rhizospheric soil of Atriplex leucoclada, and Arthrobacter pascens, isolated from rhizospheric soil of Suaeda fruticosa, are active phosphate solubilizers and bacteriocin and siderophore producers; hence, their inoculation and co-inoculation on maize ('Rakaposhi') under induced salinity stress enhanced shoot and root length and shoot and root fresh and dry mass. The accumulation of osmolytes, including sugar and proline, and the elevation of antioxidant enzymes activity, including superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase, were enhanced in the maize variety when inoculated and co-inoculated with Bacillus sp. and Arthrobacter pascens. The PGPR (Bacillus sp. and A. pascens) isolated from the rhizosphere of the mentioned halophytes species showed reliability in growth promotion of maize crop in all the physiological parameters; hence, they can be used as bio-inoculants for the plants growing under salt stress.

Infiltration in soils with a saturated surface

NASA Astrophysics Data System (ADS)

Hogarth, W. L.; Lockington, D. A.; Barry, D. A.; Parlange, M. B.; Haverkamp, R.; Parlange, J.-Y.

2013-05-01

An earlier infiltration equation relied on curve fitting of infiltration data for the determination of one of the parameters, which limits its usefulness in practice. This handicap is removed here, and the parameter is now evaluated by linking it directly to soil-water properties. The new predictions of infiltration using this evaluation are quite accurate. Positions and shapes of soil-water profiles are also examined in detail and found to be predicted analytically with great precision.

A Method for Precision Closed-Loop Irrigation Using a Modified PID Control Algorithm

NASA Astrophysics Data System (ADS)

Goodchild, Martin; Kühn, Karl; Jenkins, Malcolm; Burek, Kazimierz; Dutton, Andrew

2016-04-01

The benefits of closed-loop irrigation control have been demonstrated in grower trials which show the potential for improved crop yields and resource usage. Managing water use by controlling irrigation in response to soil moisture changes to meet crop water demands is a popular approach but requires knowledge of closed-loop control practice. In theory, to obtain precise closed-loop control of a system it is necessary to characterise every component in the control loop to derive the appropriate controller parameters, i.e. proportional, integral & derivative (PID) parameters in a classic PID controller. In practice this is often difficult to achieve. Empirical methods are employed to estimate the PID parameters by observing how the system performs under open-loop conditions. In this paper we present a modified PID controller, with a constrained integral function, that delivers excellent regulation of soil moisture by supplying the appropriate amount of water to meet the needs of the plant during the diurnal cycle. Furthermore, the modified PID controller responds quickly to changes in environmental conditions, including rainfall events which can result in: controller windup, under-watering and plant stress conditions. The experimental work successfully demonstrates the functionality of a constrained integral PID controller that delivers robust and precise irrigation control. Coir substrate strawberry growing trial data is also presented illustrating soil moisture control and the ability to match water deliver to solar radiation.

Field Trial Assessment of Biological, Chemical, and Physical Responses of Soil to Tillage Intensity, Fertilization, and Grazing

NASA Astrophysics Data System (ADS)

Vargas Gil, Silvina; Becker, Analia; Oddino, Claudio; Zuza, Mónica; Marinelli, Adriana; March, Guillermo

2009-08-01

Soil microbial populations can fluctuate in response to environmental changes and, therefore, are often used as biological indicators of soil quality. Soil chemical and physical parameters can also be used as indicators because they can vary in response to different management strategies. A long-term field trial was conducted to study the effects of different tillage systems (NT: no tillage, DH: disc harrow, and MP: moldboard plough), P fertilization (diammonium phosphate), and cattle grazing (in terms of crop residue consumption) in maize ( Zea mays L.), sunflower ( Heliantus annuus L.), and soybean ( Glycine max L.) on soil biological, chemical, and physical parameters. The field trial was conducted for four crop years (2000/2001, 2001/2002, 2002/2003, and 2003/2004). Soil populations of Actinomycetes, Trichoderma spp., and Gliocladium spp. were 49% higher under conservation tillage systems, in soil amended with diammonium phosphate (DAP) and not previously grazed. Management practices also influenced soil chemical parameters, especially organic matter content and total N, which were 10% and 55% higher under NT than under MP. Aggregate stability was 61% higher in NT than in MP, 15% higher in P-fertilized soil, and also 9% higher in not grazed strips, bulk density being 12% lower in NT systems compared with MP. DAP application and the absence of grazing also reduced bulk density (3%). Using conservation tillage systems, fertilizing crops with DAP, and avoiding grazing contribute to soil health preservation and enhanced crop production.

Issues in the inverse modeling of a soil infiltration process

NASA Astrophysics Data System (ADS)

Kuraz, Michal; Jacka, Lukas; Leps, Matej

2017-04-01

This contribution addresses issues in evaluation of the soil hydraulic parameters (SHP) from the Richards equation based inverse model. The inverse model was representing single ring infiltration experiment on mountainous podzolic soil profile, and was searching for the SHP parameters of the top soil layer. Since the thickness of the top soil layer is often much lower than the depth required to embed the single ring or Guelph permeameter device, the SHPs for the top soil layer are very difficult to measure directly. The SHPs for the top soil layer were therefore identified here by inverse modeling of the single ring infiltration process, where, especially, the initial unsteady part of the experiment is expected to provide very useful data for evaluating the retention curve parameters (excluding the residual water content) and the saturated hydraulic conductivity. The main issue, which is addressed in this contribution, is the uniqueness of the Richards equation inverse model. We tried to answer the question whether is it possible to characterize the unsteady infiltration experiment with a unique set of SHPs values, and whether are all SHP parameters vulnerable with the non-uniqueness. Which is an important issue, since we could further conclude whether the popular gradient methods are appropriate here. Further the issues in assigning the initial and boundary condition setup, the influence of spatial and temporal discretization on the values of the identified SHPs, and the convergence issues with the Richards equation nonlinear operator during automatic calibration procedure are also covered here.

Environmental impacts of different crop rotations in terms of soil compaction.

PubMed

Götze, Philipp; Rücknagel, Jan; Jacobs, Anna; Märländer, Bernward; Koch, Heinz-Josef; Christen, Olaf

2016-10-01

Avoiding soil compaction caused by agricultural management is a key aim of sustainable land management, and the soil compaction risk should be considered when assessing the environmental impacts of land use systems. Therefore this project compares different crop rotations in terms of soil structure and the soil compaction risk. It is based on a field trial in Germany, in which the crop rotations (i) silage maize (SM) monoculture, (ii) catch crop mustard (Mu)_sugar beet (SB)-winter wheat (WW)-WW, (iii) Mu_SM-WW-WW and (iv) SB-WW-Mu_SM are established since 2010. Based on the cultivation dates, the operation specific soil compaction risks and the soil compaction risk of the entire crop rotations are modelled at two soil depths (20 and 35 cm). To this end, based on assumptions of the equipment currently used in practice by a model farm, two scenarios are modelled (100 and 50% hopper load for SB and WW harvest). In addition, after one complete rotation, in 2013 and in 2014, the physical soil parameters saturated hydraulic conductivity (kS) and air capacity (AC) were determined at soil depths 2-8, 12-18, 22-28 and 32-38 cm in order to quantify the soil structure. At both soil depths, the modelled soil compaction risks for the crop rotations including SB (Mu_SB-WW-WW, SB-WW-Mu_SM) are higher (20 cm: medium to very high risks; 35 cm: no to medium risks) than for those without SB (SM monoculture, Mu_SM-WW-WW; 20 cm: medium risks; 35 cm: no to low risks). This increased soil compaction risk is largely influenced by the SB harvest in years where soil water content is high. Halving the hopper load and adjusting the tyre inflation pressure reduces the soil compaction risk for the crop rotation as a whole. Under these conditions, there are no to low soil compaction risks for all variants in the subsoil (soil depth 35 cm). Soil structure is mainly influenced in the topsoil (2-8 cm) related to the cultivation of Mu as a catch crop and WW as a preceding crop. Concerning kS, Mu_SB-WW-WW (240 cm d(-1)) and Mu_SM-WW-WW (196 cm d(-1)) displayed significantly higher values than the SM monoculture (67 cm d(-1)), indicating better structural stability and infiltration capacity. At other soil depths, and for the parameter AC, there are no systematic differences in soil structure between the variants. Under the circumstances described, all crop rotations investigated are not associated with environmental impacts caused by soil compaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visible and near infrared spectroscopy coupled to random forest to quantify some soil quality parameters

NASA Astrophysics Data System (ADS)

de Santana, Felipe Bachion; de Souza, André Marcelo; Poppi, Ronei Jesus

2018-02-01

This study evaluates the use of visible and near infrared spectroscopy (Vis-NIRS) combined with multivariate regression based on random forest to quantify some quality soil parameters. The parameters analyzed were soil cation exchange capacity (CEC), sum of exchange bases (SB), organic matter (OM), clay and sand present in the soils of several regions of Brazil. Current methods for evaluating these parameters are laborious, timely and require various wet analytical methods that are not adequate for use in precision agriculture, where faster and automatic responses are required. The random forest regression models were statistically better than PLS regression models for CEC, OM, clay and sand, demonstrating resistance to overfitting, attenuating the effect of outlier samples and indicating the most important variables for the model. The methodology demonstrates the potential of the Vis-NIR as an alternative for determination of CEC, SB, OM, sand and clay, making possible to develop a fast and automatic analytical procedure.

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the impact of the VOD parameter on SM retrievals is more considerable than the effects of HR and ω. Overall, the inclusion of the VOD parameter in the SMAP SM retrieval algorithm was found to be a very interesting approach and showed the large potential benefit of the synergy between SMAP and SMOS.

Microbial Community Dynamics in Soil Depth Profiles Over 120,000 Years of Ecosystem Development

PubMed Central

Turner, Stephanie; Mikutta, Robert; Meyer-Stüve, Sandra; Guggenberger, Georg; Schaarschmidt, Frank; Lazar, Cassandre S.; Dohrmann, Reiner; Schippers, Axel

2017-01-01

Along a long-term ecosystem development gradient, soil nutrient contents and mineralogical properties change, therefore probably altering soil microbial communities. However, knowledge about the dynamics of soil microbial communities during long-term ecosystem development including progressive and retrogressive stages is limited, especially in mineral soils. Therefore, microbial abundances (quantitative PCR) and community composition (pyrosequencing) as well as their controlling soil properties were investigated in soil depth profiles along the 120,000 years old Franz Josef chronosequence (New Zealand). Additionally, in a microcosm incubation experiment the effects of particular soil properties, i.e., soil age, soil organic matter fraction (mineral-associated vs. particulate), O2 status, and carbon and phosphorus additions, on microbial abundances (quantitative PCR) and community patterns (T-RFLP) were analyzed. The archaeal to bacterial abundance ratio not only increased with soil depth but also with soil age along the chronosequence, coinciding with mineralogical changes and increasing phosphorus limitation. Results of the incubation experiment indicated that archaeal abundances were less impacted by the tested soil parameters compared to Bacteria suggesting that Archaea may better cope with mineral-induced substrate restrictions in subsoils and older soils. Instead, archaeal communities showed a soil age-related compositional shift with the Bathyarchaeota, that were frequently detected in nutrient-poor, low-energy environments, being dominant at the oldest site. However, bacterial communities remained stable with ongoing soil development. In contrast to the abundances, the archaeal compositional shift was associated with the mineralogical gradient. Our study revealed, that archaeal and bacterial communities in whole soil profiles are differently affected by long-term soil development with archaeal communities probably being better adapted to subsoil conditions, especially in nutrient-depleted old soils. PMID:28579976

Patterns of water infiltration and soil degradation over a 120-yr chronosequence from forest to agriculture in western Kenya

NASA Astrophysics Data System (ADS)

Nyberg, G.; Bargués Tobella, A.; Kinyangi, J.; Ilstedt, U.

2011-07-01

Soil degradation is commonly reported in the tropics where forest is converted to agriculture. Much of the native forest in the highlands of western Kenya has been converted to agricultural land in order to feed the growing population, and more land is being cleared. In tropical Africa, this land use change results in progressive soil degradation, as the period of cultivation increases. Sites that were converted to agriculture at different times can be evaluated as a chronosequence; this can aid in our understanding of the processes at work, particularly those in the soil. Both levels and variation of infiltration, soil carbon and other parameters are influenced by management within agricultural systems, but they have rarely been well documented in East Africa. We constructed a chronosequence for an area of western Kenya, using two native forest sites and six fields that had been converted to agriculture for varying lengths of time. We assessed changes in infiltrability (the steady-state infiltration rate), soil C and N, bulk density, δ13C, and the proportion of macro- and microaggregates in soil along a 119 yr chronosequence of conversion from natural forest to agriculture. Infiltration, soil C and N, decreased rapidly after conversion, while bulk density increased. Median infiltration rates fell to about 15 % of the initial values in the forest and C and N values dropped to around 60 %, whilst the bulk density increased by 50 %. Despite high spatial variability in infiltrability, these parameters correlated well with time since conversion and with each other. Our results indicate that landscape planners should include wooded elements in the landscape in sufficient quantity to ensure water infiltration at rates that prevent runoff and erosion. This should be the case for restoring degraded landscapes, as well as for the development of new agricultural areas.

Applicability of Different Hydraulic Parameters to Describe Soil Detachment in Eroding Rills

PubMed Central

Wirtz, Stefan; Seeger, Manuel; Zell, Andreas; Wagner, Christian; Wagner, Jean-Frank; Ries, Johannes B.

2013-01-01

This study presents the comparison of experimental results with assumptions used in numerical models. The aim of the field experiments is to test the linear relationship between different hydraulic parameters and soil detachment. For example correlations between shear stress, unit length shear force, stream power, unit stream power and effective stream power and the detachment rate does not reveal a single parameter which consistently displays the best correlation. More importantly, the best fit does not only vary from one experiment to another, but even between distinct measurement points. Different processes in rill erosion are responsible for the changing correlations. However, not all these procedures are considered in soil erosion models. Hence, hydraulic parameters alone are not sufficient to predict detachment rates. They predict the fluvial incising in the rill's bottom, but the main sediment sources are not considered sufficiently in its equations. The results of this study show that there is still a lack of understanding of the physical processes underlying soil erosion. Exerted forces, soil stability and its expression, the abstraction of the detachment and transport processes in shallow flowing water remain still subject of unclear description and dependence. PMID:23717669

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

[Migration in soil and accumulation in plants of peaceful nuclear explosion products in Perm region].

PubMed

Raskosha, N G; Shuktova, I I

2015-01-01

The data on the migration capacity in soil and accumulation of 238Pu, 239, 240Pu, 137Cs and 90Sr by plants in the area of a peaceful nuclear explosion located in the taiga zone are presented. The influence of the soil parameters on the distribution and transformation forms of the radionuclides in the podzolic soil profile was studied. The major amounts of man-made radionuclides were found in the matter of the ground lip. The accumulation parameters of pollutants by plants were the highest for the leaves, young branches and conifer of trees.

The Soil Microbiome Influences Grapevine-Associated Microbiota

PubMed Central

Zarraonaindia, Iratxe; Owens, Sarah M.; Weisenhorn, Pamela; West, Kristin; Hampton-Marcell, Jarrad; Lax, Simon; Bokulich, Nicholas A.; Mills, David A.; Martin, Gilles; Taghavi, Safiyh; van der Lelie, Daniel

2015-01-01

ABSTRACT Grapevine is a well-studied, economically relevant crop, whose associated bacteria could influence its organoleptic properties. In this study, the spatial and temporal dynamics of the bacterial communities associated with grapevine organs (leaves, flowers, grapes, and roots) and soils were characterized over two growing seasons to determine the influence of vine cultivar, edaphic parameters, vine developmental stage (dormancy, flowering, preharvest), and vineyard. Belowground bacterial communities differed significantly from those aboveground, and yet the communities associated with leaves, flowers, and grapes shared a greater proportion of taxa with soil communities than with each other, suggesting that soil may serve as a bacterial reservoir. A subset of soil microorganisms, including root colonizers significantly enriched in plant growth-promoting bacteria and related functional genes, were selected by the grapevine. In addition to plant selective pressure, the structure of soil and root microbiota was significantly influenced by soil pH and C:N ratio, and changes in leaf- and grape-associated microbiota were correlated with soil carbon and showed interannual variation even at small spatial scales. Diazotrophic bacteria, e.g., Rhizobiaceae and Bradyrhizobium spp., were significantly more abundant in soil samples and root samples of specific vineyards. Vine-associated microbial assemblages were influenced by myriad factors that shape their composition and structure, but the majority of organ-associated taxa originated in the soil, and their distribution reflected the influence of highly localized biogeographic factors and vineyard management. PMID:25805735

The soil microbiome influences grapevine-associated microbiota

DOE PAGES

Zarraonaindia, Iratxe; Owens, Sarah M.; Weisenhorn, Pamela; ...

2015-03-24

Grapevine is a well-studied, economically relevant crop, whose associated bacteria could influence its organoleptic properties. In this study, the spatial and temporal dynamics of the bacterial communities associated with grapevine organs (leaves, flowers, grapes, and roots) and soils were characterized over two growing seasons to determine the influence of vine cultivar, edaphic parameters, vine developmental stage (dormancy, flowering, preharvest), and vineyard. Belowground bacterial communities differed significantly from those aboveground, and yet the communities associated with leaves, flowers, and grapes shared a greater proportion of taxa with soil communities than with each other, suggesting that soil may serve as a bacterialmore » reservoir. A subset of soil microorganisms, including root colonizers significantly enriched in plant growth-promoting bacteria and related functional genes, were selected by the grapevine. In addition to plant selective pressure, the structure of soil and root microbiota was significantly influenced by soil pH and C:N ratio, and changes in leaf- and grape-associated microbiota were correlated with soil carbon and showed interannual variation even at small spatial scales. Diazotrophic bacteria, e.g., Rhizobiaceae and Bradyrhizobium spp., were significantly more abundant in soil samples and root samples of specific vineyards. Vine-associated microbial assemblages were influenced by myriad factors that shape their composition and structure, but the majority of organ-associated taxa originated in the soil, and their distribution reflected the influence of highly localized biogeographic factors and vineyard management.« less

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

NASA Astrophysics Data System (ADS)

Legates, David R.; Junghenn, Katherine T.

2018-04-01

Many local weather station networks that measure a number of meteorological variables (i.e. , mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.

Eco-geomorphic controls on slope stability

NASA Astrophysics Data System (ADS)

Hales, T.; Ford, C.; Hwang, T.; Vose, J.; Band, L.

2009-04-01

Vegetation controls soil-mantled landscape evolution primarily through growth of roots into soil and rock. Root-soil interactions affect the spatial distribution and rate of shallow landsliding and other hillslope processes. Yet the distribution and tensile strength of roots depends on a number of geomorphically-influenced parameters, including soil moisture. Our field-based study investigated the effects of topography on root distributions, tensile strengths, and cohesion. Systematic differences in plant species distribution and soil properties are found in the hollow-nose topography of soil-mantled landscapes; with hollows containing thick colluvial soils and mesic tree species and noses containing thinner, more differentiated soils and more xeric species. We investigated whether these topographic variations in geomorphic and ecologic properties affected the spatial distribution of root cohesion by measuring the distribution and tensile strength of roots from soil pits dug downslope of fifteen individual trees in the Coweeta Hydrologic Laboratory, North Carolina. Our soil pits were located to capture variance in plant species (10 species total), topographic positions (nose, hollow), and sizes (a range of DBH between 5 cm and 60 cm). Root tensile strengths showed little variance with different species, but showed strong differences as a function of topography, with nose roots stronger than hollow roots. Similarly, within species, root cellulose content was systematically greater in trees on nose positions compared to those in hollows. For all species, roots were concentrated close to the soil surface (at least 70% of biomass occurred within 50 cm of the surface) and variations in this pattern were primarily a function of topographic position. Hollow roots were more evenly distributed in the soil column than those on noses, yet trees located on noses had higher mean root cohesion than those in hollows because of a higher root tensile force. These data provide an empirical basis for the development of simple geomorphic transport laws that explicitly include vegetation.

The Soil Model Development and Intercomparison Panel (SoilMIP) of the International Soil Modeling Consortium (ISMC)

NASA Astrophysics Data System (ADS)

Vanderborght, Jan; Priesack, Eckart

2017-04-01

The Soil Model Development and Intercomparison Panel (SoilMIP) is an initiative of the International Soil Modeling Consortium. Its mission is to foster the further development of soil models that can predict soil functions and their changes (i) due to soil use and land management and (ii) due to external impacts of climate change and pollution. Since soil functions and soil threats are diverse but linked with each other, the overall aim is to develop holistic models that represent the key functions of the soil system and the links between them. These models should be scaled up and integrated in terrestrial system models that describe the feedbacks between processes in the soil and the other terrestrial compartments. We propose and illustrate a few steps that could be taken to achieve these goals. A first step is the development of scenarios that compare simulations by models that predict the same or different soil services. Scenarios can be considered at three different levels of comparisons: scenarios that compare the numerics (accuracy but also speed) of models, scenarios that compare the effect of differences in process descriptions, and scenarios that compare simulations with experimental data. A second step involves the derivation of metrics or summary statistics that effectively compare model simulations and disentangle parameterization from model concept differences. These metrics can be used to evaluate how more complex model simulations can be represented by simpler models using an appropriate parameterization. A third step relates to the parameterization of models. Application of simulation models implies that appropriate model parameters have to be defined for a range of environmental conditions and locations. Spatial modelling approaches are used to derive parameter distributions. Considering that soils and their properties emerge from the interaction between physical, chemical and biological processes, the combination of spatial models with process models would lead to consistent parameter distributions correlations and could potentially represent self-organizing processes in soils and landscapes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

M.A. Wasiolek

Inhalation exposure pathway modeling has recently been investigated as one of the tasks of the BIOPROTA Project (BIOPROTA 2005). BIOPROTA was set up to address the key uncertainties in long term assessments of contaminant releases into the environment arising from radioactive waste disposal. Participants of this international Project include national authorities and agencies, both regulators and operators, with responsibility for achieving safe and acceptable radioactive waste management. The objective of the inhalation task was to investigate the calculation of doses arising from inhalation of particles suspended from soils within which long-lived radionuclides, particularly alpha emitters, had accumulated. It was recognizedmore » that site-specific conditions influence the choice of conceptual model and input parameter values. Therefore, one of the goals of the task was to identify the circumstances in which different processes included in specific inhalation exposure pathway models were important. This paper discusses evaluation of processes and modeling assumptions specific to the proposed repository at Yucca Mountain as compared to the typical approaches and other models developed for different assessments and project specific contexts. Inhalation of suspended particulates that originate from contaminated soil is an important exposure pathway, particularly for exposure to actinides such as uranium, neptunium and plutonium. Radionuclide accumulation in surface soil arises from irrigation of soil with contaminated water over many years. The level of radionuclide concentration in surface soil depends on the assumed duration of irrigation. Irrigation duration is one of the parameters used on biosphere models and it depends on a specific assessment context. It is one of the parameters addressed in this paper from the point of view of assessment context for the proposed repository at Yucca Mountain. The preferred model for the assessment of inhalation exposure uses atmospheric mass loading approach, which is based on the mass of airborne particulates per unit volume of air that is inhaled by the receptor. This type of model was used by the majority of the BIOPROTA inhalation task participants and is also used in the Yucca Mountain model. Although the mass loading model is conceptually straightforward, there are some considerations that need to be included when using this model. Small particles have larger surface to volume ratio than large particles and this ratio increases in inverse proportion to the particle size. This is particularly important for elements such as plutonium, which have high sorption coefficients, and thus are preferentially attached to small particles of soil. Suspended particulates originating from soil are composed of particles smaller than average soil particles and thus, on average, have larger available surface area, and consequently activity, per unit mass than that of soil. The increase of radionuclide concentration of suspended particulates compared with that of underlying soil is quantified in terms of the enhancement factor, which is included in the inhalation model for the Yucca Mountain repository. In this paper, the use of the enhancement factor in the inhalation exposure models is discussed. Then, enhancement factor values used in the Yucca Mountain model are discussed from the perspective of site-specific conditions as well as the microenvironmental approach to modeling inhalation exposure of the receptor: The receptor can spend specified time in several environments, each of them characterized by an occupancy time, suspended particulate level, enhancement factor and breathing rate. The environment where inhalation exposure is the highest is associated with the receptor being active outdoors and involved in activities that generate high levels of dust by using farm equipment, walking, or conducting other outdoor activities. I n summary, it is important to recognize that site-specific conditions play an important role in constructing conceptual and mathematical models of inhalation exposure.« less

Approach To Development of Guidelines For Determination of Natural Attenuation Capacity and Resilience of Soils

NASA Astrophysics Data System (ADS)

Putters, B.

The natural attenuation capacity of the soil is often used to help remove contaminants from the soil and groundwater. However, the definition of natural attenuation capac- ity in terms of soil properties, and how it should be measured are still a matter of discussion. Moreover, due to the interaction between soil and pollutant during the attenuation processes, changes in soil properties may occur. The resilience of the soil determines the rate of recovery of the soil, and to what extent it regains its original capacity for attenuation. This resilience, too, is not yet defined or measureable. The objective of the research is to develop guidelines to determine the natural attenu- ation capacity and the resilience of soils. The approach comprises five steps: 1. Experimental data on degradation and adsorp- tion are collected from literature. Missing data are filled by means of regression tech- niques. 2. Based upon existing knowledge on fate and behaviour of pollutants in soil environment, data are analysed on expected relations between soil parameters: which parameters determine the processes. 3. The most important parameters are analysed in a sensitivity analysis, performed by means of a mechanistic model. The testing vari- ables in the sensitivity analysis are an expression of the natural attenuation capacity and the resilience, respectively, and will be related to time. 4. The sensitivity analy- sis is extended by development of an artificial neural network and by use of genetic algorithms. 5. Data from the realisations (model calculations with different input) are classified into guidelines.

Low-field NMR logging sensor for measuring hydraulic parameters of model soils

NASA Astrophysics Data System (ADS)

Sucre, Oscar; Pohlmeier, Andreas; Minière, Adrien; Blümich, Bernhard

2011-08-01

SummaryKnowing the exact hydraulic parameters of soils is very important for improving water management in agriculture and for the refinement of climate models. Up to now, however, the investigation of such parameters has required applying two techniques simultaneously which is time-consuming and invasive. Thus, the objective of this current study is to present only one technique, i.e., a new non-invasive method to measure hydraulic parameters of model soils by using low-field nuclear magnetic resonance (NMR). Hereby, two model clay or sandy soils were respectively filled in a 2 m-long acetate column having an integrated PVC tube. After the soils were completely saturated with water, a low-field NMR sensor was moved up and down in the PVC tube to quantitatively measure along the whole column the initial water content of each soil sample. Thereafter, both columns were allowed to drain. Meanwhile, the NMR sensor was set at a certain depth to measure the water content of that soil slice. Once the hydraulic equilibrium was reached in each of the two columns, a final moisture profile was taken along the whole column. Three curves were subsequently generated accordingly: (1) the initial moisture profile, (2) the evolution curve of the moisture depletion at that particular depth, and (3) the final moisture profile. All three curves were then inverse analyzed using a MATLAB code over numerical data produced with the van Genuchten-Mualem model. Hereby, a set of values ( α, n, θr and θs) was found for the hydraulic parameters for the soils under research. Additionally, the complete decaying NMR signal could be analyzed through Inverse Laplace Transformation and averaged on the 1/ T2 space. Through measurement of the decay in pure water, the effect on the relaxation caused by the sample could be estimated from the obtained spectra. The migration of the sample-related average <1/ T2, Sample> with decreasing saturation speaks for a enhancement of the surface relaxation as the soil dries, in concordance with results found by other authors. In conclusion, this low-field mobile NMR technique has proven itself to be a fast and a non-invasive mean to investigate the hydraulic behavior of soils and to explore microscopical aspect of the water retained in them. In the future, the sensor should allow easy soil moisture measurements on-field.

An Interactive Real-time Decision Support System for Leachate Irrigation on Evapotranspiration Landfill Covers

NASA Astrophysics Data System (ADS)

Wang, Y.

2015-12-01

Landfill disposal is still the most common and economical practice for municipal solid waste in most countries. However, heavily polluted leachate generated by excess rainwater percolating through the landfill waste is the major drawback of this practice. Evapotranspiration (ET) cover systems are increasingly being used as alternative cover systems to minimize percolation by evapotranspiration. Leachate recirculation is one of the least expensive options for leachate treatment. The combination of ET cover systems and leachate recirculation can be an economical and environment-friendly practice for landfill leachate management. An interactive real-time decision support system is being developed to better manage leachate irrigation using historical and forecasting weather data, and real time soil moisture data. The main frame of this system includes soil water modules, and plant-soil modules. An inverse simulation module is also included to calibrate certain parameters based on observed data when necessary. It would be an objectives-oriented irrigation management tool to minimize landfill operation costs and negative environmental impacts.

Microwave remote sensing and radar polarization signatures of natural fields

NASA Technical Reports Server (NTRS)

Mo, Tsan

1989-01-01

Theoretical models developed for simulation of microwave remote sensing of the Earth surface from airborne/spaceborne sensors are described. Theoretical model calculations were performed and the results were compared with data of field measurements. Data studied included polarimetric images at the frequencies of P band, L band, and C band, acquired with airborne polarimeters over a agricultural field test site. Radar polarization signatures from bare soil surfaces and from tree covered fields were obtained from the data. The models developed in this report include: (1) Small perturbation model of wave scatterings from randomly rough surfaces, (2) Physical optics model, (3) Geometrical optics model, and (4) Electromagnetic wave scattering from dielectric cylinders of finite lengths, which replace the trees and branches in the modeling of tree covered field. Additionally, a three-layer emissivity model for passive sensing of a vegetation covered soil surface is also developed. The effects of surface roughness, soil moisture contents, and tree parameters on the polarization signatures were investigated.

Subsurface Salts in Antarctic Dry Valley Soils

NASA Technical Reports Server (NTRS)

Englert, P.; Bishop, J. L.; Gibson, E. K.; Koeberl, C.

2013-01-01

The distribution of water-soluble ions, major and minor elements, and other parameters were examined to determine the extent and effects of chemical weathering on cold desert soils. Patterns at the study sites support theories of multiple salt forming processes, including marine aerosols and chemical weathering of mafic minerals. Periodic solar-mediated ionization of atmospheric nitrogen might also produce high nitrate concentrations found in older sediments. Chemical weathering, however, was the major contributor of salts in Antarctic Dry Valleys. The Antarctic Dry Valleys represent a unique analog for Mars, as they are extremely cold and dry desert environments. Similarities in the climate, surface geology, and chemical properties of the Dry Valleys to that of Mars imply the possible presence of these soil formation mechanisms on Mars, other planets and icy satellites.

A Simple and Accurate Rate-Driven Infiltration Model

NASA Astrophysics Data System (ADS)

Cui, G.; Zhu, J.

2017-12-01

In this study, we develop a novel Rate-Driven Infiltration Model (RDIMOD) for simulating infiltration into soils. Unlike traditional methods, RDIMOD avoids numerically solving the highly non-linear Richards equation or simply modeling with empirical parameters. RDIMOD employs infiltration rate as model input to simulate one-dimensional infiltration process by solving an ordinary differential equation. The model can simulate the evolutions of wetting front, infiltration rate, and cumulative infiltration on any surface slope including vertical and horizontal directions. Comparing to the results from the Richards equation for both vertical infiltration and horizontal infiltration, RDIMOD simply and accurately predicts infiltration processes for any type of soils and soil hydraulic models without numerical difficulty. Taking into account the accuracy, capability, and computational effectiveness and stability, RDIMOD can be used in large-scale hydrologic and land-atmosphere modeling.

Sampling Soil for Characterization and Site Description

NASA Technical Reports Server (NTRS)

Levine, Elissa

1999-01-01

The sampling scheme for soil characterization within the GLOBE program is uniquely different from the sampling methods of the other protocols. The strategy is based on an understanding of the 5 soil forming factors (parent material, climate, biota, topography, and time) at each study site, and how each of these interact to produce a soil profile with unique characteristics and unique input and control into the atmospheric, biological, and hydrological systems. Soil profile characteristics, as opposed to soil moisture and temperature, vegetative growth, and atmospheric and hydrologic conditions, change very slowly, depending on the parameter being measured, ranging from seasonally to many thousands of years. Thus, soil information, including profile description and lab analysis, is collected only one time for each profile at a site. These data serve two purposes: 1) to supplement existing spatial information about soil profile characteristics across the landscape at local, regional, and global scales, and 2) to provide specific information within a given area about the basic substrate to which elements within the other protocols are linked. Because of the intimate link between soil properties and these other environmental elements, the static soil properties at a given site are needed to accurately interpret and understand the continually changing dynamics of soil moisture and temperature, vegetation growth and phenology, atmospheric conditions, and chemistry and turbidity in surface waters. Both the spatial and specific soil information can be used for modeling purposes to assess and make predictions about global change.

Aerodynamic method for obtaining the soil water retention curve

NASA Astrophysics Data System (ADS)

Alekseev, V. V.; Maksimov, I. I.

2013-07-01

A new method for the rapid plotting of the soil water retention curve (SWRC) has been proposed that considers the soil water as an environment limited by the soil solid phase on one side and by the soil air on the other side. Both contact surfaces have surface energies, which play the main role in water retention. The use of an idealized soil model with consideration for the nonequilibrium thermodynamic laws and the aerodynamic similarity principles allows us to estimate the volumetric specific surface areas of soils and, using the proposed pedotransfer function (PTF), to plot the SWRC. The volumetric specific surface area of the solid phase, the porosity, and the specific free surface energy at the water-air interface are used as the SWRC parameters. Devices for measuring the parameters are briefly described. The differences between the proposed PTF and the experimental data have been analyzed using the statistical processing of the data.

Influence of xenobiotics on the microbiological and agrochemical parameters of soddy-podzolic soil

NASA Astrophysics Data System (ADS)

Vakkerov-Kouzova, N. D.

2010-08-01

We studied the influence of various chemical compounds, i.e., azobenzene (an insecticide and acaricide), nitrification inhibitors (DCD, dicyandiamide and DMPP, and 3,4-dimetylpyrazolphosphate), and inhibitors of urease activity (HQ-hydroquinone), on the agrochemical and microbiological parameters of a soddy-podzolic soil. It is proved that these xenobiotics are able to influence the agrochemical parameters (the pH and the content of NO{3/-} and NH{4/+}, the microbial activity (the basal respiration, the microbial mass carbon, and the microbial quotient), and the number of bacteria of different physiological groups in soddypodzolic soil. The influence of the xenobiotics was preserved for some time, which testified to their persistence in the soil. Upon cultivating the soil microorganisms in different media, the growth of the heterotrophic bacteria was inhibited, the radial growth velocity was slowed down, and the sporogenesis of the micromycetes was retarded. The toxic effect of the xenobiotics was higher with their increasing concentrations.

Modeling soil evaporation efficiency in a range of soil and atmospheric conditions using a meta-analysis approach

NASA Astrophysics Data System (ADS)

Merlin, O.; Stefan, V. G.; Amazirh, A.; Chanzy, A.; Ceschia, E.; Er-Raki, S.; Gentine, P.; Tallec, T.; Ezzahar, J.; Bircher, S.; Beringer, J.; Khabba, S.

2016-05-01

A meta-analysis data-driven approach is developed to represent the soil evaporative efficiency (SEE) defined as the ratio of actual to potential soil evaporation. The new model is tested across a bare soil database composed of more than 30 sites around the world, a clay fraction range of 0.02-0.56, a sand fraction range of 0.05-0.92, and about 30,000 acquisition times. SEE is modeled using a soil resistance (rss) formulation based on surface soil moisture (θ) and two resistance parameters rss,ref and θefolding. The data-driven approach aims to express both parameters as a function of observable data including meteorological forcing, cut-off soil moisture value θ1/2 at which SEE=0.5, and first derivative of SEE at θ1/2, named Δθ1/2-1. An analytical relationship between >(rss,ref;θefolding) and >(θ1/2;Δθ1/2-1>) is first built by running a soil energy balance model for two extreme conditions with rss = 0 and rss˜∞ using meteorological forcing solely, and by approaching the middle point from the two (wet and dry) reference points. Two different methods are then investigated to estimate the pair >(θ1/2;Δθ1/2-1>) either from the time series of SEE and θ observations for a given site, or using the soil texture information for all sites. The first method is based on an algorithm specifically designed to accomodate for strongly nonlinear SEE>(θ>) relationships and potentially large random deviations of observed SEE from the mean observed SEE>(θ>). The second method parameterizes θ1/2 as a multi-linear regression of clay and sand percentages, and sets Δθ1/2-1 to a constant mean value for all sites. The new model significantly outperformed the evaporation modules of ISBA (Interaction Sol-Biosphère-Atmosphère), H-TESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchange over Land), and CLM (Community Land Model). It has potential for integration in various land-surface schemes, and real calibration capabilities using combined thermal and microwave remote sensing data.

Thermodynamics of imidacloprid sorption in Croatian soils

NASA Astrophysics Data System (ADS)

Milin, Čedomila; Broznic, Dalibor

2015-04-01

Neonicotinoids are increasingly replacing the organophosphate and methylcarbamate acetylcholinesterase inhibitors which are losing their effectiveness because of selection for resistant pest populations. Imidacloprid is the most important neonicotinoid with low soil persistence, high insecticidal potency and relatively low mammalian toxicity. In Croatia, imidacloprid is most commonly used in olive growing areas, including Istria and Kvarner islands, as an effective means of olive fruit fly infestation control. Sorption-desorption behavior of imidacloprid in six soils collected from five coastal regions in Croatia at 20, 30 and 40°C was investigated using batch equilibrium technique. Isothermal data were applied to Freundlich, Langmuir and Temkin equation, and the thermodynamic parameters ΔH°, ΔG°, ΔS° were calculated. The sorption isotherm curves were of non-linear and may be classified as L-type suggesting a relatively high sorption capacity for imidacloprid. Our results showed that the KFsor values decreased for all the tested soils as the temperature increases, indicating that the temperature strongly influence the sorption. Values of ΔG° were negative (-4.65 to -2.00 kJ/mol) indicating that at all experimental temperatures the interactions of imidacloprid with soils were spontaneous process. The negative and small ΔH° values (-19.79 to -8.89 kJ/mol) were in the range of weak forces, such as H-bonds, consistent with interactions and par¬titioning of the imidacloprid molecules into soil organic matter. The ΔS° values followed the range of -57.12 to -14.51 J/molK, suggesting that imidacloprid molecules lose entropy during transition from the solution phase to soil surface. It was found that imidacloprid desorption from soil was concentration and temperature dependent, i.e. at lower imidacloprid concentrations and temperature, lower desorption percentage occurred. Desorption studies revealed that hysteretic behavior under different temperature treatments existed, and it was more pronounced at 20°C in the soils with higher organic carbon content. The study results emphasize the importance of thermodynamic parameters in controlling soil pesticide mobility in different geographical locations, seasons and greenhouses condition.

Rock-Eval analysis of French forest soils: the influence of depth, soil and vegetation types on SOC thermal stability and bulk chemistry

NASA Astrophysics Data System (ADS)

Soucemarianadin, Laure; Cécillon, Lauric; Baudin, François; Cecchini, Sébastien; Chenu, Claire; Mériguet, Jacques; Nicolas, Manuel; Savignac, Florence; Barré, Pierre

2017-04-01

Soil organic matter (SOM) is the largest terrestrial carbon pool and SOM degradation has multiple consequences on key ecosystem properties like nutrients cycling, soil emissions of greenhouse gases or carbon sequestration potential. With the strong feedbacks between SOM and climate change, it becomes particularly urgent to develop reliable routine methodologies capable of indicating the turnover time of soil organic carbon (SOC) stocks. Thermal analyses have been used to characterize SOM and among them, Rock-Eval 6 (RE6) analysis of soil has shown promising results in the determination of in-situ SOC biogeochemical stability. This technique combines a phase of pyrolysis followed by a phase of oxidation to provide information on both the SOC bulk chemistry and thermal stability. We analyzed with RE6 a set of 495 soils samples from 102 permanent forest sites of the French national network for the long-term monitoring of forest ecosystems (''RENECOFOR'' network). Along with covering pedoclimatic variability at a national level, these samples include a range of 5 depths up to 1 meter (0-10 cm, 10-20 cm, 20-40 cm, 40-80 cm and 80-100 cm). Using RE6 parameters that were previously shown to be correlated to short-term (hydrogen index, HI; T50 CH pyrolysis) or long-term (T50 CO2 oxidation and HI) SOC persistence, and that characterize SOM bulk chemical composition (oxygen index, OI and HI), we tested the influence of depth (n = 5), soil class (n = 6) and vegetation type (n = 3; deciduous, coniferous-fir, coniferous-pine) on SOM thermal stability and bulk chemistry. Results showed that depth was the dominant discriminating factor, affecting significantly all RE6 parameters. With depth, we observed a decrease of the thermally labile SOC pool and an increase of the thermally stable SOC pool, along with an oxidation and a depletion of hydrogen-rich moieties of the SOC. Soil class and vegetation type had contrasted effects on the RE6 parameters but both affected significantly T50 CO2 oxidation with, for instance, entic Podzols and dystric Cambisols containing relatively more thermally stable SOC in the deepest layer than hypereutric/calcaric Cambisols. Moreover, soils in deciduous plots contained a higher proportion of thermally stable SOC than soils in coniferous plots. This study shows that RE6 analysis constitutes a fast and cost effective way to qualitatively estimate SOM turnover and to discuss its ecosystem drivers. It offers promising prospects towards a quantitative estimation of SOC turnover and the development of RE6-based indicators related to the size of the different SOC kinetic pools.

Application of soil quality indices to assess the status of agricultural soils irrigated with treated wastewaters

NASA Astrophysics Data System (ADS)

Morugán-Coronado, A.; Arcenegui, V.; García-Orenes, F.; Mataix-Solera, J.; Mataix-Beneyto, J.

2012-12-01

The supply of water is limited in some parts of the Mediterranean region, such as southeastern Spain. The use of treated wastewater for the irrigation of agricultural soils is an alternative to using better-quality water, especially in semi-arid regions. On the other hand, this practice can modify some soil properties, change their relationships, the equilibrium reached and influence soil quality. In this work two soil quality indices were used to evaluate the effects of irrigation with treated wastewater in soils. The indices were developed studying different soil properties in undisturbed soils in SE Spain, and the relationships between soil parameters were established using multiple linear regressions. This study was carried out in three areas of Alicante Province (SE Spain) irrigated with wastewater, including four study sites. The results showed slight changes in some soil properties as a consequence of irrigation with wastewater, the obtained levels not being dangerous for agricultural soils, and in some cases they could be considered as positive from an agronomical point of view. In one of the study sites, and as a consequence of the low quality wastewater used, a relevant increase in soil organic matter content was observed, as well as modifications in most of the soil properties. The application of soil quality indices indicated that all the soils of study sites are in a state of disequilibrium regarding the relationships between properties independent of the type of water used. However, there were no relevant differences in the soil quality indices between soils irrigated with wastewater with respect to their control sites for all except one of the sites, which corresponds to the site where low quality wastewater was used.

Effects of the soil pore network architecture on the soil's physical functionalities

NASA Astrophysics Data System (ADS)

Smet, Sarah; Beckers, Eléonore; Léonard, Angélique; Degré, Aurore

2017-04-01

The soil fluid movement's prediction is of major interest within an agricultural or environmental scope because many processes depend ultimately on the soil fluids dynamic. It is common knowledge that the soil microscopic pore network structure governs the inner-soil convective fluids flow. There isn't, however, a general methodthat consider the pore network structure as a variable in the prediction of thecore scale soil's physical functionalities. There are various possible representations of the microscopic pore network: sample scale averaged structural parameters, extrapolation of theoretic pore network, or use of all the information available by modeling within the observed pore network. Different representations implydifferent analyzing methodologies. To our knowledge, few studies have compared the micro-and macroscopic soil's characteristics for the same soil core sample. The objective of our study is to explore the relationship between macroscopic physical properties and microscopic pore network structure. The saturated hydraulic conductivity, the air permeability, the retention curve, and others classical physical parameters were measured for ten soil samples from an agricultural field. The pore network characteristics were quantified through the analyses of X-ray micro-computed tomographic images(micro-CT system Skyscan-1172) with a voxel size of 22 µm3. Some of the first results confirmed what others studies had reported. Then, the comparison between macroscopic properties and microscopic parameters suggested that the air movements depended mostly on the pore connectivity and tortuosity than on the total porosity volume. We have also found that the fractal dimension calculated from the X-ray images and the fractal dimension calculated from the retention curve were significantly different. Our communication will detailthose results and discuss the methodology: would the results be similar with a different voxel size? What are the calculated and measured parameters uncertainties? Sarah Smet, as a research fellow, acknowledges the support of the National Fund for Scientific Research (Brussels, Belgium).

Process-based soil erodibility estimation for empirical water erosion models

USDA-ARS?s Scientific Manuscript database

A variety of modeling technologies exist for water erosion prediction each with specific parameters. It is of interest to scrutinize parameters of a particular model from the point of their compatibility with dataset of other models. In this research, functional relationships between soil erodibilit...

Data assimilation with soil water content sensors and pedotransfer functions in soil water flow modeling

USDA-ARS?s Scientific Manuscript database

Soil water flow models are based on a set of simplified assumptions about the mechanisms, processes, and parameters of water retention and flow. That causes errors in soil water flow model predictions. Soil water content monitoring data can be used to reduce the errors in models. Data assimilation (...