Modelling cadmium contamination in paddy soils under long-term remediation measures: Model development and stochastic simulations.

PubMed

Peng, Chi; Wang, Meie; Chen, Weiping

2016-09-01

A pollutant accumulation model (PAM) based on the mass balance theory was developed to simulate long-term changes of heavy metal concentrations in soil. When combined with Monte Carlo simulation, the model can predict the probability distributions of heavy metals in a soil-water-plant system with fluctuating environmental parameters and inputs from multiple pathways. The model was used for evaluating different remediation measures to deal with Cd contamination of paddy soils in Youxian county (Hunan province), China, under five scenarios, namely the default scenario (A), not returning paddy straw to the soil (B), reducing the deposition of Cd (C), liming (D), and integrating several remediation measures (E). The model predicted that the Cd contents of soil can lowered significantly by (B) and those of the plants by (D). However, in the long run, (D) will increase soil Cd. The concentrations of Cd in both soils and rice grains can be effectively reduced by (E), although it will take decades of effort. The history of Cd pollution and the major causes of Cd accumulation in soil were studied by means of sensitivity analysis and retrospective simulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

How well do we succeed in modeling the global soil carbon pools?

NASA Astrophysics Data System (ADS)

Viskari, T.; Liski, J.

2017-12-01

Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.

The Soil Carbon Paradigm Shift: Triangulating Theories, Measurements, and Models

NASA Astrophysics Data System (ADS)

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

2016-12-01

Predicting global responses of soil carbon (C) to environmental change remains confounded by a number of paradigms that have emerged from separate approaches. A prevailing paradigm in biogeochemistry interprets soil C as discrete pools based on estimated or measured turnover times (e.g., CENTURY model). An alternative is emerging that envisions the stabilization of soil C in tension between decomposition by microbial agents and protection by physical and chemical mechanisms. We propose an approach to bridge the gap between different paradigms, and to improve soil C forecasting by conceptualizing each paradigm as a triangle composed of three nodes: theory, analytical measurement, and numerical model. Paradigms tend to emerge from what can either be represented in models or measured using analytical instruments. But they gain power when all three elements are integrated in a balanced trinity. Our goal was to compare how theory, measurement, and model fit together in our understanding of soil C to learn from past successes, evaluate the strengths and weaknesses of current paradigms, and guide development of new understanding. We used a case-study approach to analyze each corner of the paradigm-triangle: i) paradigms that have strong theory but are constrained by weak linkages with measurements or models, ii) paradigms with robust models that have weak linkages with theory or measurements, and iii) paradigms with many measurements but little theoretical support or ability to be parameterized in numerical models. We conclude that established models like CENTURY dominate because theory and measurements that underlie the model form strong linkages that previously created a balanced triangle. Evolving paradigms based on physical protection and microbial agency are still struggling to gain traction because the theory is challenging to represent in models. The explicit examination of the strengths of emerging paradigms can, therefore, help refine and accelerate our ability to constrain projections of soil C dynamics.

Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

NASA Astrophysics Data System (ADS)

Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

2015-03-01

The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century

DOE PAGES

Abramoff, Rose; Xu, Xiaofeng; Hartman, Melannie; ...

2017-12-20

Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model—the Millennial model—that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation,more » and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. Finally, we review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. Here, we propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development.« less

The Millennial model: in search of measurable pools and transformations for modeling soil carbon in the new century

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

Abramoff, Rose; Xu, Xiaofeng; Hartman, Melannie

Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model—the Millennial model—that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation,more » and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. Finally, we review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. Here, we propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development.« less

Using the Rasch model as an objective and probabilistic technique to integrate different soil properties

NASA Astrophysics Data System (ADS)

Rebollo, Francisco J.; Jesús Moral García, Francisco

2016-04-01

Soil apparent electrical conductivity (ECa) is one of the simplest, least expensive soil measurements that integrates many soil properties affecting crop productivity, including, for instance, soil texture, water content, and cation exchange capacity. The ECa measurements obtained with a 3100 Veris sensor, operating in both shallow (0-30 cm), ECs, and deep (0-90 cm), ECd, mode, can be used as an additional and essential information to be included in a probabilistic model, the Rasch model, with the aim of quantifying the overall soil fertililty potential in an agricultural field. This quantification should integrate the main soil physical and chemical properties, with different units. In this work, the formulation of the Rasch model integrates 11 soil properties (clay, silt and sand content, organic matter -OM-, pH, total nitrogen -TN-, available phosphorus -AP- and potassium -AK-, cation exchange capacity -CEC-, ECd, and ECs) measured at 70 locations in a field. The main outputs of the model include a ranking of all soil samples according to their relative fertility potential and the unexpected behaviours of some soil samples and properties. In the case study, the considered soil variables fit the model reasonably, having an important influence on soil fertility, except pH, probably due to its homogeneity in the field. Moreover, ECd, ECs are the most influential properties on soil fertility and, on the other hand, AP and AK the less influential properties. The use of the Rasch model to estimate soil fertility potential (always in a relative way, taking into account the characteristics of the studied soil) constitutes a new application of great practical importance, enabling to rationally determine locations in a field where high soil fertility potential exists and establishing those soil samples or properties which have any anomaly; this information can be necessary to conduct site-specific treatments, leading to a more cost-effective and sustainable field management. Furthermore, from the measures of soil fertility potential at sampled locations, estimates can be computed using, for instance, a geostatistical algorithm, and these estimates can be utilized to map soil fertility potential and delineate with a rational basis the management zones in the field. Keywords: Rasch model; soil management; soil electrical conductivity; probabilistic algorithm.

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...

Evaluation of theoretical and empirical water vapor sorption isotherm models for soils

NASA Astrophysics Data System (ADS)

Arthur, Emmanuel; Tuller, Markus; Moldrup, Per; de Jonge, Lis W.

2016-01-01

The mathematical characterization of water vapor sorption isotherms of soils is crucial for modeling processes such as volatilization of pesticides and diffusive and convective water vapor transport. Although numerous physically based and empirical models were previously proposed to describe sorption isotherms of building materials, food, and other industrial products, knowledge about the applicability of these functions for soils is noticeably lacking. We present an evaluation of nine models for characterizing adsorption/desorption isotherms for a water activity range from 0.03 to 0.93 based on measured data of 207 soils with widely varying textures, organic carbon contents, and clay mineralogy. In addition, the potential applicability of the models for prediction of sorption isotherms from known clay content was investigated. While in general, all investigated models described measured adsorption and desorption isotherms reasonably well, distinct differences were observed between physical and empirical models and due to the different degrees of freedom of the model equations. There were also considerable differences in model performance for adsorption and desorption data. While regression analysis relating model parameters and clay content and subsequent model application for prediction of measured isotherms showed promise for the majority of investigated soils, for soils with distinct kaolinitic and smectitic clay mineralogy predicted isotherms did not closely match the measurements.

Modeling the Soil Water and Energy Balance of a Mixed Grass Rangeland and Evaluating a Soil Water Based Drought Index in Wyoming

NASA Astrophysics Data System (ADS)

Engda, T. A.; Kelleners, T. J.; Paige, G. B.

2013-12-01

Soil water content plays an important role in the complex interaction between terrestrial ecosystems and the atmosphere. Automated soil water content sensing is increasingly being used to assess agricultural drought conditions. A one-dimensional vertical model that calculates incoming solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow-soil heat exchange is applied to calculate water flow and heat transport in a Rangeland soil located near Lingel, Wyoming. The model is calibrated and validated using three years of measured soil water content data. Long-term average soil water content dynamics are calculated using a 30 year historical data record. The difference between long-term average soil water content and observed soil water content is compared with plant biomass to evaluate the usefulness of soil water content as a drought indicator. Strong correlation between soil moisture surplus/deficit and plant biomass may prove our hypothesis that soil water content is a good indicator of drought conditions. Soil moisture based drought index is calculated using modeled and measured soil water data input and is compared with measured plant biomass data. A drought index that captures local drought conditions proves the importance of a soil water monitoring network for Wyoming Rangelands to fill the gap between large scale drought indices, which are not detailed enough to assess conditions at local level, and local drought conditions. Results from a combined soil moisture monitoring and computer modeling, and soil water based drought index soil are presented to quantify vertical soil water flow, heat transport, historical soil water variations and drought conditions in the study area.

Relating soil solution Zn concentration to diffusive gradients in thin films measurements in contaminated soils.

PubMed

Degryse, Fien; Smolders, Erik; Oliver, Ian; Zhang, Hao

2003-09-01

The technique of diffusive gradients in thin films (DGT) has been suggested to sample an available fraction of metals in soil. The objectives of this study were to compare DGT measurements with commonly measured fractions of Zn in soil, viz, the soil solution concentration and the total Zn concentration. The DGT technique was used to measure fluxes and interfacial concentrations of Zn in three series of field-contaminated soils collected in transects toward galvanized electricity pylons and in 15 soils amended with ZnCl2 at six rates. The ratio of DGT-measured concentration to pore water concentration of Zn, R, varied between 0.02 and 1.52 (mean 0.29). This ratio decreased with decreasing distribution coefficient, Kd, of Zn in the soil, which is in agreement with the predictions of the DGT-induced fluxes in soils (DIFS) model. The R values predicted with the DIFS model were generally larger than the observed values in the ZnCl2-amended soils at the higher Zn rates. A modification of the DIFS model indicated that saturation of the resin gel was approached in these soils, despite the short deployment times used (2 h). The saturation of the resin with Zn did not occur in the control soils (no Zn salt added) or the field-contaminated soils. Pore water concentration of Zn in these soils was predicted from the DGT-measured concentration and the total Zn content. Predicted values and observations were generally in good agreement. The pore water concentration was more than 5 times underpredicted for the most acid soil (pH = 3) and for six other soils, for which the underprediction was attributed to the presence of colloidal Zn in the soil solution.

Variations of measured and simulated soil-loss amounts in a semiarid area in Turkey.

PubMed

Hacisalihoğlu, Sezgin

2010-06-01

The main goal of this research was soil-loss determination and comparison of the plot measurement results with simulation model (universal soil loss equation (USLE)) results in different land use and slope classes. The research took place in three different land-use types (Scotch pine forest, pasture land, and agricultural land) and in two different slope classes (15-20%, 35-40%). Within six measurement stations (for each land-use type and slope class-one station), totally 18 measurement plots have been constituted, and soil-loss amount measurements have been investigated during the research period (3 years along). USLE simulation model is used in these measurement plots for calculation the soil-loss amounts. The results pointed out that measured (in plots) and simulated (with USLE) soil-loss amounts differ significantly in each land-use type and slope class.

Prediction of soil stress-strain response incorporates mobilised shear strength envelope of granitic residual soil

NASA Astrophysics Data System (ADS)

Rahman, Abdul Samad Abdul; Noor, Mohd Jamaludin Md; Ahmad, Juhaizad Bin; Sidek, Norbaya

2017-10-01

The concept of effective stress has been the principal concept in characterizing soil volume change behavior in soil mechanics, the settlement models developed using this concept have been empirical in nature. However, there remain certain unexplained soil volume change behaviors that cannot be explained using the effective stress concept, one such behaviour is the inundation settlement. Studies have begun to indicate the inevitable role of shear strength as a critical element to be incorporated in models to unravel the unexplained soil behaviours. One soil volume change model that applies the concept of effective stress and the shear strength interaction is the Rotational Multiple Yield Surface Framework (RMYSF) model. This model has been developed from the soil-strain behavior under anisotropic stress condition. Hence, the RMYSF actually measure the soil actual elasto-plastic response to stress rather than assuming it to be fully elastic or plastic as normally perceived by the industry. The frameworks measures the increase in the mobilize shear strength when the soil undergo anisotropic settlement.

The international soil moisture network: A data hosting facility for global in situ soil moisture measurements

USDA-ARS?s Scientific Manuscript database

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, long-term time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land co...

Bare soil respiration in a temperate climate: multiyear evaluation of a coupled CO2 transport and carbon turnover model

NASA Astrophysics Data System (ADS)

Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.

2006-12-01

The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.

Metal Ion Speciation and Dissolved Organic Matter Composition in Soil Solutions

NASA Astrophysics Data System (ADS)

Benedetti, M. F.; Ren, Z. L.; Bravin, M.; Tella, M.; Dai, J.

2014-12-01

Knowledge of the speciation of heavy metals and the role of dissolved organic matter (DOM) in soil solution is a key to understand metal mobility and ecotoxicity. In this study, soil column-Donnan membrane technique (SC-DMT) was used to measure metal speciation of Cd, Cu, Ni, Pb, and Zn in eighteen soil solutions, covering a wide range of metal sources and concentrations. DOM composition in these soil solutions was also determined. Our results show that in soil solution Pb and Cu are dominant in complex form, whereas Cd, Ni and Zn mainly exist as free ions; for the whole range of soil solutions, only 26.2% of DOM is reactive and consists mainly of fulvic acid (FA). The metal speciation measured by SC-DMT was compared to the predicted ones obtained via the NICA-Donnan model using the measured FA concentrations. The free ion concentrations predicted by speciation modelling were in good agreement with the measurements. Diffusive gradients in thin-films gels (DGT) were also performed to quantify the labile metal species in the fluxes from solid phase to solution in fourteen soils. The concentrations of metal species detected by DGT were compared with the free ion concentrations measured by DMT and the maximum concentrations calculated based on the predicted metal speciation in SC-DMT soil solutions. It is concluded that both inorganic species and a fraction of FA bound species account for the amount of labile metals measured by DGT, consistent with the dynamic features of this technique. The comparisons between measurements using analytical techniques and mechanistic model predictions provided mutual validation in their performance. Moreover, we show that to make accurate modelling of metal speciation in soil solutions, the knowledge of DOM composition is the crucial information, especially for Cu; like in previous studies the modelling of Pb speciation is not optimal and an updated of Pb generic binding parameters is required to reduce model prediction uncertainties.

Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance

USGS Publications Warehouse

Yi, Shuhua; McGuire, A. David; Harden, Jennifer; Kasischke, Eric; Manies, Kristen L.; Hinzman, Larry; Liljedahl, Anna K.; Randerson, J.; Liu, Heping; Romanovsky, Vladimir E.; Marchenko, Sergey S.; Kim, Yongwon

2009-01-01

Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.

Infiltration and runoff generation processes in fire-affected soils

USGS Publications Warehouse

Moody, John A.; Ebel, Brian A.

2014-01-01

Post-wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire-affected soils to predict time-to-start of runoff and peak runoff rate at the plot scale (1 m2). Time series of soil-water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one-dimensional post-wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high-resolution (1 mm) estimates of the soil-water profile and water fluxes within the unsaturated zone.Field and model estimates of the wetting-front depth indicated that post-wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, Ks, near the soil surface ranged from 0.1 to 5.2 mm h−1. Because of the relatively small values of Ks, the time-to-start of runoff (measured from the start of rainfall),  tp, was found to depend only on the initial soil-water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of  tp, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that  tp in fire-affected soils (which often have low values of Ks) is probably controlled more by the storm profile and the initial soil-water saturation deficit than by soil hydraulic properties.

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.

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.

Latent heat sink in soil heat flux measurements

USDA-ARS?s Scientific Manuscript database

The surface energy balance includes a term for soil heat flux. Soil heat flux is difficult to measure because it includes conduction and convection heat transfer processes. Accurate representation of soil heat flux is an important consideration in many modeling and measurement applications. Yet, the...

Latent Heat in Soil Heat Flux Measurements

USDA-ARS?s Scientific Manuscript database

The surface energy balance includes a term for soil heat flux. Soil heat flux is difficult to measure because it includes conduction and convection heat transfer processes. Accurate representation of soil heat flux is an important consideration in many modeling and measurement applications. Yet, the...

Spatial Irrigation Management Using Remote Sensing Water Balance Modeling and Soil Water Content Monitoring

NASA Astrophysics Data System (ADS)

Barker, J. Burdette

Spatially informed irrigation management may improve the optimal use of water resources. Sub-field scale water balance modeling and measurement were studied in the context of irrigation management. A spatial remote-sensing-based evapotranspiration and soil water balance model was modified and validated for use in real-time irrigation management. The modeled ET compared well with eddy covariance data from eastern Nebraska. Placement and quantity of sub-field scale soil water content measurement locations was also studied. Variance reduction factor and temporal stability were used to analyze soil water content data from an eastern Nebraska field. No consistent predictor of soil water temporal stability patterns was identified. At least three monitoring locations were needed per irrigation management zone to adequately quantify the mean soil water content. The remote-sensing-based water balance model was used to manage irrigation in a field experiment. The research included an eastern Nebraska field in 2015 and 2016 and a western Nebraska field in 2016 for a total of 210 plot-years. The response of maize and soybean to irrigation using variations of the model were compared with responses from treatments using soil water content measurement and a rainfed treatment. The remote-sensing-based treatment prescribed more irrigation than the other treatments in all cases. Excessive modeled soil evaporation and insufficient drainage times were suspected causes of the model drift. Modifying evaporation and drainage reduced modeled soil water depletion error. None of the included response variables were significantly different between treatments in western Nebraska. In eastern Nebraska, treatment differences for maize and soybean included evapotranspiration and a combined variable including evapotranspiration and deep percolation. Both variables were greatest for the remote-sensing model when differences were found to be statistically significant. Differences in maize yield in 2015 were attributed to random error. Soybean yield was lowest for the remote-sensing-based treatment and greatest for rainfed, possibly because of overwatering and lodging. The model performed well considering that it did not include soil water content measurements during the season. Future work should improve the soil evaporation and drainage formulations, because of excessive precipitation and include aerial remote sensing imagery and soil water content measurement as model inputs.

Remotely monitoring evaporation rate and soil water status using thermal imaging and "three-temperatures model (3T Model)" under field-scale conditions.

PubMed

Qiu, Guo Yu; Zhao, Ming

2010-03-01

Remote monitoring of soil evaporation and soil water status is necessary for water resource and environment management. Ground based remote sensing can be the bridge between satellite remote sensing and ground-based point measurement. The primary object of this study is to provide an algorithm to estimate evaporation and soil water status by remote sensing and to verify its accuracy. Observations were carried out in a flat field with varied soil water content. High-resolution thermal images were taken with a thermal camera; soil evaporation was measured with a weighing lysimeter; weather data were recorded at a nearby meteorological station. Based on the thermal imaging and the three-temperatures model (3T model), we developed an algorithm to estimate soil evaporation and soil water status. The required parameters of the proposed method were soil surface temperature, air temperature, and solar radiation. By using the proposed method, daily variation in soil evaporation was estimated. Meanwhile, soil water status was remotely monitored by using the soil evaporation transfer coefficient. Results showed that the daily variation trends of measured and estimated evaporation agreed with each other, with a regression line of y = 0.92x and coefficient of determination R(2) = 0.69. The simplicity of the proposed method makes the 3T model a potentially valuable tool for remote sensing.

Soil Moisture Project Evaluation Workshop

NASA Technical Reports Server (NTRS)

Gilbert, R. H. (Editor)

1980-01-01

Approaches planned or being developed for measuring and modeling soil moisture parameters are discussed. Topics cover analysis of spatial variability of soil moisture as a function of terrain; the value of soil moisture information in developing stream flow data; energy/scene interactions; applications of satellite data; verifying soil water budget models; soil water profile/soil temperature profile models; soil moisture sensitivity analysis; combinations of the thermal model and microwave; determing planetary roughness and field roughness; how crust or a soil layer effects microwave return; truck radar; and truck/aircraft radar comparison.

Extrapolative capability of two models that estimating soil water retention curve between saturation and oven dryness.

PubMed

Lu, Sen; Ren, Tusheng; Lu, Yili; Meng, Ping; Sun, Shiyou

2014-01-01

Accurate estimation of soil water retention curve (SWRC) at the dry region is required to describe the relation between soil water content and matric suction from saturation to oven dryness. In this study, the extrapolative capability of two models for predicting the complete SWRC from limited ranges of soil water retention data was evaluated. When the model parameters were obtained from SWRC data in the 0-1500 kPa range, the FX model (Fredlund and Xing, 1994) estimations agreed well with measurements from saturation to oven dryness with RMSEs less than 0.01. The GG model (Groenevelt and Grant, 2004) produced larger errors at the dry region, with significantly larger RMSEs and MEs than the FX model. Further evaluations indicated that when SWRC measurements in the 0-100 kPa suction range was applied for model establishment, the FX model was capable of producing acceptable SWRCs across the entire water content range. For a higher accuracy, the FX model requires soil water retention data at least in the 0- to 300-kPa range to extend the SWRC to oven dryness. Comparing with the Khlosi et al. (2006) model, which requires measurements in the 0-500 kPa range to reproduce the complete SWRCs, the FX model has the advantage of requiring less SWRC measurements. Thus the FX modeling approach has the potential to eliminate the processes for measuring soil water retention in the dry range.

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.

Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

NASA Astrophysics Data System (ADS)

Wever, Nander; Comola, Francesco; Bavay, Mathias; Lehning, Michael

2017-08-01

The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

Modeling of technical soil-erosion control measures and its impact on soil erosion off-site effects within urban areas

NASA Astrophysics Data System (ADS)

Dostal, Tomas; Devaty, Jan

2013-04-01

The paper presents results of surface runoff, soil erosion and sediment transport modeling using Erosion 3D software - physically based mathematical simulation model, event oriented, fully distributed. Various methods to simulate technical soil-erosion conservation measures were tested, using alternative digital elevation models of different precision and resolution. Ditches and baulks were simulated by three different approaches, (i) by change of the land-cover parameters to increase infiltration and decrease flow velocity, (ii) by change of the land-cover parameters to completely infiltrate the surface runoff and (iii) by adjusting the height of the digital elevation model by "burning in" the channels of the ditches. Results show advantages and disadvantages of each approach and conclude suitable methods for combinations of particular digital elevation model and purpose of the simulations. Further on a set of simulations was carried out to model situations before and after technical soil-erosion conservation measures application within a small catchment of 4 km2. These simulations were focused on quantitative and qualitative assessment of technical soil-erosion control measures impact on soil erosion off-site effects within urban areas located downstream of intensively used agricultural fields. The scenarios were built upon a raster digital elevation model with spatial resolution of 3 meters derived from LiDAR 5G vector point elevation data. Use of this high-resolution elevation model allowed simulating the technical soil-erosion control measures by direct terrain elevation adjustment. Also the structures within the settlements were emulated by direct change in the elevation of the terrain model. The buildings were lifted up to simulate complicated flow behavior of the surface runoff within urban areas, using approach of Arévalo (Arévalo, 2011) but focusing on the use of commonly available data without extensive detailed editing. Application of the technical soil-erosion control measures induced strong change in overall amount of eroded/deposited material as well as spatial erosion/deposition patterns within the settlement areas. Validation of modeled scenarios and effects on measured data was not possible as no real runoff event was recorded in the target area so the conclusions were made by comparing the different modeled scenarios. Advantages and disadvantages of used approach to simulate technical soil-erosion conservation measures are evaluated and discussed as well as the impact of use of high-resolution elevation data on the intensity and spatial distribution of soil erosion and deposition. Model approved ability to show detailed distribution of damages over target urban area, which is very sensitive for off-site effects of surface runoff, soil erosion and sediment transport and also high sensitivity to input data, especially to DEM, which affects surface runoff pattern and therefore intensity of harmful effects. Acknowledgement: This paper has been supported by projects: Ministry of the interior of the CR VG 20122015092, and project NAZV QI91C008 TPEO.

Effect of soil moisture on seasonal variation in indoor radon concentration: modelling and measurements in 326 Finnish houses

PubMed Central

Arvela, H.; Holmgren, O.; Hänninen, P.

2016-01-01

The effect of soil moisture on seasonal variation in soil air and indoor radon is studied. A brief review of the theory of the effect of soil moisture on soil air radon has been presented. The theoretical estimates, together with soil moisture measurements over a period of 10 y, indicate that variation in soil moisture evidently is an important factor affecting the seasonal variation in soil air radon concentration. Partitioning of radon gas between the water and air fractions of soil pores is the main factor increasing soil air radon concentration. On two example test sites, the relative standard deviation of the calculated monthly average soil air radon concentration was 17 and 26 %. Increased soil moisture in autumn and spring, after the snowmelt, increases soil gas radon concentrations by 10–20 %. In February and March, the soil gas radon concentration is in its minimum. Soil temperature is also an important factor. High soil temperature in summer increased the calculated soil gas radon concentration by 14 %, compared with winter values. The monthly indoor radon measurements over period of 1 y in 326 Finnish houses are presented and compared with the modelling results. The model takes into account radon entry, climate and air exchange. The measured radon concentrations in autumn and spring were higher than expected and it can be explained by the seasonal variation in the soil moisture. The variation in soil moisture is a potential factor affecting markedly to the high year-to-year variation in the annual or seasonal average radon concentrations, observed in many radon studies. PMID:25899611

Estimating Infiltration Rates for a Loessal Silt Loam Using Soil Properties

Treesearch

M. Dean Knighton

1978-01-01

Soil properties were related to infiltration rates as measured by single-ringsteady-head infiltometers. The properties showing strong simple correlations were identified. Regression models were developed to estimate infiltration rate from several soil properties. The best model gave fair agreement to measured rates at another location.

Simulating soil-water movement through loess-veneered landscapes using nonconsilient saturated hydraulic conductivity measurements

USGS Publications Warehouse

Williamson, Tanja N.; Lee, Brad D.; Schoeneberger, Philip J.; McCauley, W. M.; Indorante, Samuel J.; Owens, Phillip R.

2014-01-01

Soil Survey Geographic Database (SSURGO) data are available for the entire United States, so are incorporated in many regional and national models of hydrology and environmental management. However, SSURGO does not provide an understanding of spatial variability and only includes saturated hydraulic conductivity (Ksat) values estimated from particle size analysis (PSA). This study showed model sensitivity to the substitution of SSURGO data with locally described soil properties or alternate methods of measuring Ksat. Incorporation of these different soil data sets significantly changed the results of hydrologic modeling as a consequence of the amount of space available to store soil water and how this soil water is moved downslope. Locally described soil profiles indicated a difference in Ksat when measured in the field vs. being estimated from PSA. This, in turn, caused a difference in which soil layers were incorporated in the hydrologic simulations using TOPMODEL, ultimately affecting how soil water storage was simulated. Simulations of free-flowing soil water, the amount of water traveling through pores too large to retain water against gravity, were compared with field observations of water in wells at five slope positions along a catena. Comparison of the simulated data with the observed data showed that the ability to model the range of conditions observed in the field varied as a function of three soil data sets (SSURGO and local field descriptions using PSA-derived Ksat or field-measured Ksat) and that comparison of absolute values of soil water storage are not valid if different characterizations of soil properties are used.

Relationship between soil erodibility and modeled infiltration rate in different soils

NASA Astrophysics Data System (ADS)

Wang, Guoqiang; Fang, Qingqing; Wu, Binbin; Yang, Huicai; Xu, Zongxue

2015-09-01

The relationship between soil erodibility, which is hard to measure, and modeled infiltration rate were rarely researched. Here, the soil erodibility factors (K and Ke in the USLE, Ki and K1 in the WEPP) were calculated and the infiltration rates were modeled based on the designed laboratory simulation experiments and proposed infiltration model, in order to build their relationship. The impacts of compost amendment on the soil erosion characteristics and relationship were also studied. Two contrasting agricultural soils (bare and cultivated fluvo-aquic soils) were used, and different poultry compost contents (control, low and high) were applied to both soils. The results indicated that the runoff rate, sediment yield rate and soil erodibility of the bare soil treatments were generally higher than those of the corresponding cultivated soil treatments. The application of composts generally decreased sediment yield and soil erodibility but did not always decrease runoff. The comparison of measured and modeled infiltration rates indicated that the model represented the infiltration processes well with an N-S coefficient of 0.84 for overall treatments. Significant negative logarithmic correlations have been found between final infiltration rate (FIR) and the four soil erodibility factors, and the relationship between USLE-K and FIR demonstrated the best correlation. The application of poultry composts would not influence the logarithmic relationship between FIR and soil erodibility. Our study provided a useful tool to estimate soil erodibility.

Soil moisture, dielectric permittivity and emissivity of soil: effective depth of emission measured by the L-band radiometer ELBARA

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Jerzy; Lipiec, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan

2014-05-01

Due to the large variation of soil moisture in space and in time, obtaining soil water balance with an aid of data acquired from the surface is still a challenge. Microwave remote sensing is widely used to determine the water content in soil. It is based on the fact that the dielectric constant of the soil is strongly dependent on its water content. This method provides the data in both local and global scales. Very important issue that is still not solved, is the soil depth at which radiometer "sees" the incoming radiation and how this "depth of view" depends on water content and physical properties of soil. The microwave emission comes from its entire profile, but much of this energy is absorbed by the upper layers of soil. As a result, the contribution of each layer to radiation visible for radiometer decreases with depth. The thickness of the surface layer, which significantly contributes to the energy measured by the radiometer is defined as the "penetration depth". In order to improve the physical base of the methodology of soil moisture measurements using microwave remote sensing and to determine the effective emission depth seen by the radiometer, a new algorithm was developed. This algorithm determines the reflectance coefficient from Fresnel equations, and, what is new, the complex dielectric constant of the soil, calculated from the Usowicz's statistical-physical model (S-PM) of dielectric permittivity and conductivity of soil. The model is expressed in terms of electrical resistance and capacity. The unit volume of soil in the model consists of solid, water and air, and is treated as a system made up of spheres, filling volume by overlapping layers. It was assumed that connections between layers and spheres in the layer are represented by serial and parallel connections of "resistors" and "capacitors". The emissivity of the soil surface is calculated from the ratio between the brightness temperature measured by the ELBARA radiometer (GAMMA Remote Sensing AG) and the physical temperature of the soil surface measured by infrared sensor. As the input data for S-PM: volumes of soil components, mineralogical composition, organic matter content, specific surface area and bulk density of the soil were used. Water contents in the model are iteratively changed, until emissivities calculated from the S-PM reach the best agreement with emissivities measured by the radiometer. Final water content will correspond to the soil moisture measured by the radiometer. Then, the examined soil profile will be virtually divided into thin slices where moisture, temperature and thermal properties will be measured and simultaneously modelled via S-PM. In the next step, the slices will be "added" starting from top (soil surface), until the effective soil moisture will be equal to the soil moisture measured by ELBARA. The thickness of obtained stack will be equal to desired "penetration depth". Moreover, it will be verified further by measuring the moisture content using thermal inertia. The work was partially funded by the Government of Poland through an ESA Contract under the PECS ELBARA_PD project No. 4000107897/13/NL/KML.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

Toth, B.; Weynants, M.; Pasztor, L.; Hengl, T.

2017-12-01

Reliable quantitative information on soil hydraulic properties is crucial for modelling hydrological, meteorological, ecological and biological processes of the Critical Zone. Most of the Earth system models need information on soil moisture retention capacity and hydraulic conductivity in the full matric potential range. These soil hydraulic properties can be quantified, but their measurement is expensive and time consuming, therefore measurement-based catchment scale mapping of these soil properties is not possible. The increasing availability of soil information and methods describing relationships between simple soil characteristics and soil hydraulic properties provide the possibility to derive soil hydraulic maps based on spatial soil datasets and pedotransfer functions (PTFs). Over the last decade there has been a significant development in preparation of soil hydraulic maps. Spatial datasets on model parameters describing the soil hydraulic processes have become available for countries, continents and even for the whole globe. Our aim is to present European soil hydraulic maps, show their performance, highlight their advantages and drawbacks, and propose possible ways to further improve the performance of those.

Microwave remote sensing of soil water content

NASA Technical Reports Server (NTRS)

Cihlar, J.; Ulaby, F. T.

1975-01-01

Microwave remote sensing of soils to determine water content was considered. A layered water balance model was developed for determining soil water content in the upper zone (top 30 cm), while soil moisture at greater depths and near the surface during the diurnal cycle was studied using experimental measurements. Soil temperature was investigated by means of a simulation model. Based on both models, moisture and temperature profiles of a hypothetical soil were generated and used to compute microwave soil parameters for a clear summer day. The results suggest that, (1) soil moisture in the upper zone can be predicted on a daily basis for 1 cm depth increments, (2) soil temperature presents no problem if surface temperature can be measured with infrared radiometers, and (3) the microwave response of a bare soil is determined primarily by the moisture at and near the surface. An algorithm is proposed for monitoring large areas which combines the water balance and microwave methods.

Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

NASA Technical Reports Server (NTRS)

Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

2013-01-01

Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

Field-scale soil moisture space-time geostatistical modeling for complex Palouse landscapes in the inland Pacific Northwest

NASA Astrophysics Data System (ADS)

Chahal, M. K.; Brown, D. J.; Brooks, E. S.; Campbell, C.; Cobos, D. R.; Vierling, L. A.

2012-12-01

Estimating soil moisture content continuously over space and time using geo-statistical techniques supports the refinement of process-based watershed hydrology models and the application of soil process models (e.g. biogeochemical models predicting greenhouse gas fluxes) to complex landscapes. In this study, we model soil profile volumetric moisture content for five agricultural fields with loess soils in the Palouse region of Eastern Washington and Northern Idaho. Using a combination of stratification and space-filling techniques, we selected 42 representative and distributed measurement locations in the Cook Agronomy Farm (Pullman, WA) and 12 locations each in four additional grower fields that span the precipitation gradient across the Palouse. At each measurement location, soil moisture was measured on an hourly basis at five different depths (30, 60, 90, 120, and 150 cm) using Decagon 5-TE/5-TM soil moisture sensors (Decagon Devices, Pullman, WA, USA). This data was collected over three years for the Cook Agronomy Farm and one year for each of the grower fields. In addition to ordinary kriging, we explored the correlation of volumetric water content with external, spatially exhaustive indices derived from terrain models, optical remote sensing imagery, and proximal soil sensing data (electromagnetic induction and VisNIR penetrometer)

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

NASA Astrophysics Data System (ADS)

Cai, Gaochao; Vanderborght, Jan; Langensiepen, Matthias; Schnepf, Andrea; Hüging, Hubert; Vereecken, Harry

2018-04-01

How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil-plant-atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes-Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use normalized root density functions.

Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

NASA Technical Reports Server (NTRS)

Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.

1997-01-01

A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.

AggModel: A soil organic matter model with measurable pools for use in incubation studies

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

Segoli, Moran; De Gryze, S.; Dou, Fugen

2013-01-01

Current soil organic matter (SOM) models are empirical in nature by employing few conceptual SOM pools that have a specific turnover time, but that are not measurable and have no direct relationship with soil structural properties. Most soil particles are held together in aggregates and the number, size and stability of these aggregates significantly affect the size and amount of organic matter contained in these aggregates, and its susceptibility to decomposition. While it has been shown that soil aggregates and their dynamics can be measured directly in the laboratory and in the field, the impact of soil aggregate dynamics onmore » SOM decomposition has not been explicitly incorporated in ecosystem models. Here, we present AggModel, a conceptual and simulation model that integrates soil aggregate and SOM dynamics. In AggModel, we consider unaggregated and microaggregated soil that can exist within or external to macroaggregated soil. Each of the four aggregate size classes contains particulate organic matter and mineral-associated organic matter fractions. We used published data from laboratory incubations to calibrate and validate the biological and environmental effects on the rate of formation and breakdown of macroaggregates and microaggregates, and the organic matter dynamics within these different aggregate fractions. After calibration, AggModel explained more than 70% of the variation in aggregate masses and over 90% of the variation in aggregate-associated carbon. The model estimated the turnover time of macroaggregates as 32 days and 166 days for microaggregates. Sensitivity analysis of AggModel parameterization supported the notion that macroaggregate turnover rate has a strong control over microaggregate masses and, hence, carbon sequestration. In addition to AggModel being a proof-of-concept, the advantage of a model that is based on measurable SOM fractions is that its internal structure and dynamics can be directly calibrated and validated by using experimental data. In conclusion, AggModel successfully incorporates the explicit representation for the turnover of soil aggregates and their influence on SOM dynamics and can form the basis for new SOM modules within existing ecosystem models.« less

Measured and simulated soil water evaporation from four Great Plains soils

USDA-ARS?s Scientific Manuscript database

The amount of soil water lost during stage one and stage two soil water evaporation is of interest to crop water use modelers. The ratio of measured soil surface temperature (Ts) to air temperature (Ta) was tested as a signal for the transition in soil water evaporation from stage one to stage two d...

A weighting lysimeter for a laboratory experiment on water and energy fluxes measurements and hydrological models verification

NASA Astrophysics Data System (ADS)

Corbari, Chiara; paleari, roberto; mantovani, federico; tarro, stefano; mancini, marco

2017-04-01

Weighting lysimeters allow a direct measurement of water loss from the soil, determining the soil water balance, and thus providing an interesting tool to validate hydrological models. Lysimeters, which world originates from the greek words "lysis" (movement) and "metron" (to measure) have been used to measure percolation of water through the soils for over 300 years. The aim of this study is twofold: 1) to perform water and energy flux measurements under different meteorological conditions, irrigation practice (surface flood, drip and groundwater capillary rise), and soil coverage (bare soil and basil crop), 2) to verify hydrological model FEST-EWB parameterization at the lysimeter scale. A weighting lysimeter has been constructed in the Hydraulic Laboratory of Politecnico di Milano. It consists of a steel box of 1.5 x 1.5 x 1 m containing reconstructed soil. The box is mounted on a scale with four load cells with a nominal weight of 6000 kg and a precision of 0,5 kg. The lysimeter is fully instrumented to measure all the main components of the hydrological cycle. Profiles of soil moisture and temperature are provided by 7 probes; ground heat flux is measured by a heat flux plate and two thermocouples; the drainage flux is measured by a tipping bucket rain gauge; the four components of radiation are provided by a net radiometer; air temperature and humidity are measured by a thermo-hygrometer. Data are collected every 10 minutes on a datalogger. A thermal camera is also installed to provide accurate maps of land surface temperature. The different instruments have been subjected to a rigorous calibration process. A low cost station is also installed based on an Arduino micro-controller measuring soil moisture and temperature, air humidity and temperature and solar radiation. The idea is to understand whether low cost instruments can be used to monitor the fundamental hydrological variables. The measured fluxes (e.g. evapotranspiration, soil moisture, land surface temperature) are then used to verify the correctness of the hydrological model FEST-EWB parameterization. A general good accuracy of 2-6 % between observed and modeled fluxes is obtained.

The soil water regime of stony soils in a mountain catchment

NASA Astrophysics Data System (ADS)

Hlaváčiková, Hana; Danko, Michal; Holko, Ladislav; Hlavčo, Jozef; Novák, Viliam

2016-04-01

Investigation of processes related to runoff generation is an important topic in catchment hydrology. Observations are usually carried out in small catchments or on hillslopes. Many of such catchments are located in mountain or forested areas. From many studies it is evident that soil conditions and soil characteristics are one of the crucial factors in runoff generation. Mountainous or forest soils have usually high rock fragments content. Nevertheless, the influence of soil stoniness on water flow was not sufficiently studied up to now at catchment and hillslope scales due to flow formation complexity or problems with stony soil properties measurement (installing measuring devices, interpretation of measured data). Results of this work can be divided in two groups: (1) hydrophysical properties of stony soils measurements, and (2) water flow dynamic modelling in stony soils. Properties of stony soils were measured in the Jalovecky creek catchment, the Western Tatra Mts., Slovakia. Altitude of particular study sites varies from 780 to1500 m a.s.l. We measured and analyzed the stoniness of reference soil profiles, as well as retention properties of stony soils (fine soil fraction and rock fragments separately) and hydraulic conductivities of surface and subsurface soil layers. The methodology for determination of the effective hydrophysical properties of a stony soil (later used in modelling) was proposed using results from measurements, calculation, and numerical Darcy experiments. Modelling results show that the presence of rock fragments with low water retention in a stony soil with moderate or high stoniness can cause the soil water storage decrease by 16-31% in compared to the soil without rock fragments. In addition, decreased stony soil retention capacity resulted in faster outflow increase at the bottom of the soil profile during non-ponding infiltration. Furthermore, the presence of rock fragments can increase maximum outflow value. It is not possible to simply extrapolate the results from a soil profile to larger catchment scale because spatial variability of soil properties and unknown bedrock properties. Moreover, water outflow from the soil profile is a complex problem in which several factors co-operate. However, this points out that the presence of rock fragments in moderate or highly stony soils can play a significant role in catchment runoff generation under certain circumstances.

Evaluation and inversion of a net ecosystem carbon exchange model for grasslands and croplands

NASA Astrophysics Data System (ADS)

Herbst, M.; Klosterhalfen, A.; Weihermueller, L.; Graf, A.; Schmidt, M.; Huisman, J. A.; Vereecken, H.

2017-12-01

A one-dimensional soil water, heat, and CO2 flux model (SOILCO2), a pool concept of soil carbon turnover (RothC), and a crop growth module (SUCROS) was coupled to predict the net ecosystem exchange (NEE) of carbon. This model, further referred to as AgroC, was extended with routines for managed grassland as well as for root exudation and root decay. In a first step, the coupled model was applied to two winter wheat sites and one upland grassland site in Germany. The model was calibrated based on soil water content, soil temperature, biometric, and soil respiration measurements for each site, and validated in terms of hourly NEE measured with the eddy covariance technique. The overall model performance of AgroC was acceptable with a model efficiency >0.78 for NEE. In a second step, AgroC was optimized with the eddy covariance NEE measurements to examine the effect of various objective functions, constraints, and data-transformations on estimated NEE, which showed a distinct sensitivity to the choice of objective function and the inclusion of soil respiration data in the optimization process. Both, day and nighttime fluxes, were found to be sensitive to the selected optimization strategy. Additional consideration of soil respiration measurements improved the simulation of small positive fluxes remarkably. Even though the model performance of the selected optimization strategies did not diverge substantially, the resulting annual NEE differed substantially. We conclude that data-transformation, definition of objective functions, and data sources have to be considered cautiously when using a terrestrial ecosystem model to determine carbon balances by means of eddy covariance measurements.

Simulating soil C stability with mechanistic systems models: a multisite comparison of measured fractions and modelled pools

NASA Astrophysics Data System (ADS)

Robertson, Andy; Schipanski, Meagan; Sherrod, Lucretia; Ma, Liwang; Ahuja, Lajpat; McNamara, Niall; Smith, Pete; Davies, Christian

2016-04-01

Agriculture, covering more than 30% of global land area, has an exciting opportunity to help combat climate change by effectively managing its soil to promote increased C sequestration. Further, newly sequestered soil carbon (C) through agriculture needs to be stored in more stable forms in order to have a lasting impact on reducing atmospheric CO2 concentrations. While land uses in different climates and soils require different management strategies, the fundamental mechanisms that regulate C sequestration and stabilisation remain the same. These mechanisms are used by a number of different systems models to simulate C dynamics, and thus assess the impacts of change in management or climate. To evaluate the accuracy of these model simulations, our research uses a multidirectional approach to compare C stocks of physicochemical soil fractions collected at two long-term agricultural sites. Carbon stocks for a number of soil fractions were measured at two sites (Lincoln, UK; Colorado, USA) over 8 and 12 years, respectively. Both sites represent managed agricultural land but have notably different climates and levels of disturbance. The measured soil fractions act as proxies for varying degrees of stability, with C contained within these fractions relatable to the C simulated within the soil pools of mechanistic systems models1. Using stable isotope techniques at the UK site, specific turnover times of C within the different fractions were determined and compared with those simulated in the pools of 3 different models of varying complexity (RothC, DayCent and RZWQM2). Further, C dynamics and N-mineralisation rates of the measured fractions at the US site were assessed and compared to results of the same three models. The UK site saw a significant increase in C stocks within the most stable fractions, with topsoil (0-30cm) sequestration rates of just over 0.3 tC ha-1 yr-1 after only 8 years. Further, the sum of all fractions reported C sequestration rates of nearly 1.0 tC ha-1 yr-1. At the US site, however, topsoil C sequestration was less consistent noting considerable variation over the 12 years of measured data. Both sites showed noteworthy discrepancies when model-simulated C was compared with measured C. While all three models were able to simulate the bulk C stocks within reasonable degrees of uncertainty, the accuracy broke down considerably when this bulk soil was split into fractions/pools. Using the data collected and accounting for the differences in model structure, we present potential next steps in model development as well as the variables that should be measured when aiming to reduce the uncertainties inherent in mechanistic systems models. References 1 - Zimmermann et al., 2007. Measured soil organic matter fractions can be related to pools in the RothC model. European Journal of Soil Science, 58:658-667.

Numerical Modeling of Coupled Water Flow and Heat Transport in Soil and Snow

NASA Astrophysics Data System (ADS)

Kelleners, T.

2015-12-01

A numerical model is developed to calculate coupled water flow and heat transport in seasonally frozen soil and snow. Both liquid water flow and water vapor flow are included. The effect of dissolved ions on soil water freezing point depression is included by combining an expression for osmotic head with the Clapeyron equation and the van Genuchten soil water retention function. The coupled water flow and heat transport equations are solved using the Thomas algorithm and Picard iteration. Ice pressure is always assumed zero and frost heave is neglected. The new model is tested using data from a high-elevation rangeland soil that is subject to significant soil freezing and a mountainous forest soil that is snow-covered for about 8 months of the year. Soil hydraulic parameters are mostly based on measurements and only vegetation parameters are fine-tuned to match measured and calculated soil water content, soil & snow temperature, and snow height. Modeling statistics for both systems show good performance for temperature, intermediate performance for snow height, and relatively low performance for soil water content, in accordance with earlier results with an older version of the model.

Testing Pearl Model In Three European Sites

NASA Astrophysics Data System (ADS)

Bouraoui, F.; Bidoglio, G.

The Plant Protection Product Directive (91/414/EEC) stresses the need of validated models to calculate predicted environmental concentrations. The use of models has become an unavoidable step before pesticide registration. In this context, European Commission, and in particular DGVI, set up a FOrum for the Co-ordination of pes- ticide fate models and their USe (FOCUS). In a complementary effort, DG research supported the APECOP project, with one of its objective being the validation and im- provement of existing pesticide fate models. The main topic of research presented here is the validation of the PEARL model for different sites in Europe. The PEARL model, actually used in the Dutch pesticide registration procedure, was validated in three well- instrumented sites: Vredepeel (the Netherlands), Brimstone (UK), and Lanna (Swe- den). A step-wise procedure was used for the validation of the PEARL model. First the water transport module was calibrated, and then the solute transport module, using tracer measurements keeping unchanged the water transport parameters. The Vrede- peel site is characterised by a sandy soil. Fourteen months of measurements were used for the calibration. Two pesticides were applied on the site: bentazone and etho- prophos. PEARL predictions were very satisfactory for both soil moisture content, and pesticide concentration in the soil profile. The Brimstone site is characterised by a cracking clay soil. The calibration was conducted on a time series measurement of 7 years. The validation consisted in comparing predictions and measurement of soil moisture at different soil depths, and in comparing the predicted and measured con- centration of isoproturon in the drainage water. The results, even if in good agreement with the measuremens, highlighted the limitation of the model when the preferential flow becomes a dominant process. PEARL did not reproduce well soil moisture pro- file during summer months, and also under-predicted the arrival of isoproturon to the drains. The Lanna site is characterised by s structured clay soil. PEARL was success- ful in predicting soil moisture profiles and the draining water. PEARL performed well in predicting the soil concentration of bentazone at different depth. However, since PEARL does not consider cracks in the soil, it did not predict well the peak concen- trations of bentazone in the drainage water. Along with the validation results for the three sites, a sensitivity analysis of the model is presented.

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.

Quantifying soil profile change caused by land use in central Missouri loess hillslopes

Treesearch

Samuel J. Indorante; John M. Kabrick; Brad D. Lee; Jon M. Maatta

2014-01-01

Three major challenges are present when studying anthropogenic impacts on soil profile properties: (i) site selection; (ii) sampling and modeling native and cultivated soil-landscape relationships; and (iii) graphically and statistically comparing native and cultivated sites to model soil profile changes. This study addressed those challenges by measuring and modeling...

Introducing a decomposition rate modifier in the Rothamsted Carbon Model to predict soil organic carbon stocks in saline soils.

PubMed

Setia, Raj; Smith, Pete; Marschner, Petra; Baldock, Jeff; Chittleborough, David; Smith, Jo

2011-08-01

Soil organic carbon (SOC) models such as the Rothamsted Carbon Model (RothC) have been used to estimate SOC dynamics in soils over different time scales but, until recently, their ability to accurately predict SOC stocks/carbon dioxide (CO(2)) emissions from salt-affected soils has not been assessed. Given the large extent of salt-affected soils (19% of the 20.8 billion ha of arable land on Earth), this may lead to miss-estimation of CO(2) release. Using soils from two salt-affected regions (one in Punjab, India and one in South Australia), an incubation study was carried out measuring CO(2) release over 120 days. The soils varied both in salinity (measured as electrical conductivity (EC) and calculated as osmotic potential using EC and water content) and sodicity (measured as sodium adsorption ratio, SAR). For soils from both regions, the osmotic potential had a significant positive relationship with CO(2)-C release, but no significant relationship was found between SAR and CO(2)-C release. The monthly cumulative CO(2)-C was simulated using RothC. RothC was modified to take into account reductions in plant inputs due to salinity. A subset of non-salt-affected soils was used to derive an equation for a "lab-effect" modifier to account for changes in decomposition under lab conditions and this modifier was significantly related with pH. Using a subset of salt-affected soils, a decomposition rate modifier (as a function of osmotic potential) was developed to match measured and modelled CO(2)-C release after correcting for the lab effect. Using this decomposition rate modifier, we found an agreement (R(2) = 0.92) between modelled and independently measured data for a set of soils from the incubation experiment. RothC, modified by including reduced plant inputs due to salinity and the salinity decomposition rate modifier, was used to predict SOC stocks of soils in a field in South Australia. The predictions clearly showed that SOC stocks are reduced in saline soils. Therefore both the decomposition rate modifier and plant input modifier should be taken into account when accounting for SOC turnover in saline soils. Since modeling has previously not accounted for the impact of salinity, our results suggest that previous predictions may have overestimated SOC stocks.

Constitutive Soil Properties for Mason Sand and Kennedy Space Center

NASA Technical Reports Server (NTRS)

Thomas, Michael A.; Chitty, Daniel E.

2011-01-01

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle (CEV). This report provides constitutive material models for two soil conditions at Kennedy Space Center (KSC) and four conditions of Mason Sand. The Mason Sand is the test sand for LaRC s drop tests and swing tests of the Orion. The soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LSDYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The soil models are intended to be specific to the soil conditions they were tested at. The two KSC models represent two conditions at KSC: low density dry sand and high density in-situ moisture sand. The Mason Sand model was tested at four conditions which encompass measured conditions at LaRC s drop test site.

Rapid Measurement of Soil Carbon in Rice Paddy Field of Lombok Island Indonesia Using Near Infrared Technology

NASA Astrophysics Data System (ADS)

Kusumo, B. H.; Sukartono, S.; Bustan, B.

2018-02-01

Measuring soil organic carbon (C) using conventional analysis is tedious procedure, time consuming and expensive. It is needed simple procedure which is cheap and saves time. Near infrared technology offers rapid procedure as it works based on the soil spectral reflectance and without any chemicals. The aim of this research is to test whether this technology able to rapidly measure soil organic C in rice paddy field. Soil samples were collected from rice paddy field of Lombok Island Indonesia, and the coordinates of the samples were recorded. Parts of the samples were analysed using conventional analysis (Walkley and Black) and some other parts were scanned using near infrared spectroscopy (NIRS) for soil spectral collection. Partial Least Square Regression (PLSR) Models were developed using data of soil C analysed using conventional analysis and data from soil spectral reflectance. The models were moderately successful to measure soil C in rice paddy field of Lombok Island. This shows that the NIR technology can be further used to monitor the C change in rice paddy soil.

Electrical Grounding - a Field for Geophysicists and Electrical Engineers Partnership

NASA Astrophysics Data System (ADS)

Freire, P. F.; Pane, E.; Guaraldo, N.

2012-12-01

Technology for designing ground electrodes for high-voltage direct current transmission systems (HVDC) has being using in the last years, deep soil models based on a wide range of geophysical methods. These models shall include detailed representation of shallow soil, down to 100 meters, in order to allow the evaluation of the soil conditions where the ground electrodes will be buried. Also deep soil models are needed, to be used for the interference studies, which shall represent a soil volume of about 15 km deep and a surface area of about 15 to 30 km radius. Large facilities for power plants (hydroelectric and wind farms, for example) and industrial complexes (such as petrochemical plants) has become usual at the current stage of Brazil industrialization. Grounding mats for these facilities are made of a buried cooper mesh, interconnected to a wide variety of metallic masses, such as steel reinforced concrete foundations, ducts in general etc. These grounding systems may present dimensions with the order of hundreds of meters, and, at least in Brazil, are usually calculated by using electrical resistivity soil models, based on short spacing Wenner measurements (with maximum spacing of about 64 m.). The soil model shall be the best possible representation of the environment in which the grounding electrodes are immersed, for the purpose of calculation of resistance or for digital simulation. The model to be obtained is limited by the amount and quality of soil resistivity measurements are available, and the resources to be used in the calculations and simulations. Geophysics uses a wide range of technologies for exploring subsoil, ranging from surface measurements to wells logging - seismic, gravimetric, magnetic, electrical, electromagnetic and radiometric. The electrical and electromagnetic methods includes various measurement techniques (Wenner, Schlumberger, TDEM, Magneto-telluric etc.), which together allow the development of complex resistivity soil models, layered stratified or showing lateral variations, ranging down to several tens of kilometers deep, reaching the crust-mantle interface (typically with the order of 30-40 km). This work aims to analyze the constraints of the current soil models being used for grounding electrodes design, and suggests the need of a soil modeling methodology compatible with large grounding systems. Concerning the aspects related to soil modeling, electrical engineers need to get aware of geophysics resources, such as: - geophysical techniques for soil electrical resistivity prospection (down to about 15 kilometers deep); and - techniques for converting field measured data, from many different geophysical techniques, into adequate soil models for grounding grid simulation. It is also important to equalize the basic knowledge for the professionals that are working together for the specific purpose of soil modeling for electrical grounding studies. The authors have experienced the situation of electrical engineers working with geophysicists, but it was not clear for the latter the effective need of the electrical engineers, and for the engineers it was unknown the available geophysical resources, and also, what to do convert the large amount of soil resistivity data into a reliable soil model.

Comparison of different models for predicting soil bulk density. Case study - Slovakian agricultural soils

NASA Astrophysics Data System (ADS)

Makovníková, Jarmila; Širáň, Miloš; Houšková, Beata; Pálka, Boris; Jones, Arwyn

2017-10-01

Soil bulk density is one of the main direct indicators of soil health, and is an important aspect of models for determining agroecosystem services potential. By way of applying multi-regression methods, we have created a distributed prediction of soil bulk density used subsequently for topsoil carbon stock estimation. The soil data used for this study were from the Slovakian partial monitoring system-soil database. In our work, two models of soil bulk density in an equilibrium state, with different combinations of input parameters (soil particle size distribution and soil organic carbon content in %), have been created, and subsequently validated using a data set from 15 principal sampling sites of Slovakian partial monitoring system-soil, that were different from those used to generate the bulk density equations. We have made a comparison of measured bulk density data and data calculated by the pedotransfer equations against soil bulk density calculated according to equations recommended by Joint Research Centre Sustainable Resources for Europe. The differences between measured soil bulk density and the model values vary from -0.144 to 0.135 g cm-3 in the verification data set. Furthermore, all models based on pedotransfer functions give moderately lower values. The soil bulk density model was then applied to generate a first approximation of soil bulk density map for Slovakia using texture information from 17 523 sampling sites, and was subsequently utilised for topsoil organic carbon estimation.

Comparing measured and modelled soil carbon: which site-specific variables are linked to high stability?

NASA Astrophysics Data System (ADS)

Robertson, Andy; Schipanski, Meagan; Ma, Liwang; Ahuja, Lajpat; McNamara, Niall; Smith, Pete; Davies, Christian

2016-04-01

Changes in soil carbon (C) stocks have been studied in depth over the last two decades, as net greenhouse gas (GHG) sinks are highlighted to be a partial solution to the causes of climate change. However, the stability of this soil C is often overlooked when measuring these changes. Ultimately a net sequestration in soils is far less beneficial if labile C is replacing more stable forms. To date there is no accepted framework for measuring soil C stability, and as a result there is considerable uncertainty associated with the simulated impacts of land management and land use change when using process-based systems models. However, a recent effort to equate measurable soil C fractions to model pools has generated data that help to assess the impacts of land management, and can ultimately help to reduce the uncertainty of model predictions. Our research compiles this existing fractionation data along with site metadata to create a simplistic statistical model able to quantify the relative importance of different site-specific conditions. Data was mined from 23 published studies and combined with original data to generate a dataset of 100+ land use change sites across Europe. For sites to be included they required soil C fractions isolated using the Zimmermann et al. (2007) method and specific site metadata (mean annual precipitation, MAP; mean annual temperature, MAT; soil pH; land use; altitude). Of the sites, 75% were used to develop a generalized linear mixed model (GLMM) to create coefficients where site parameters can be used to predict influence on the measured soil fraction C stocks. The remaining 25% of sites were used to evaluate uncertainty and validate this empirical model. Further, four of the aforementioned sites were used to simulate soil C dynamics using the RothC, DayCent and RZWQM2 models. A sensitivity analysis (4096 model runs for each variable applying Latin hypercube random sampling techniques) was then used to observe whether these models place as much weight on the same site parameters as the GLMM. Sites were spread across an extensive geographic area and encompassed a wide range of conditions (2% to 44% clay content; 0.9° C to 18° C MAT; 300mm to 1400mm MAP). Topsoil (30 cm) C stocks also varied considerably (29.0 to 115.9 t/ha) but the proportion deemed stable (mean residence time >10 years) was relatively consistent (72 ± 2 %). The GLMM approach suggested that an interaction of soil pH and historic land use explained the largest amount of variation seen in stable fraction C stocks, closely followed by MAT and MAP interactions. For all three systems models, the stable soil C pools were most sensitive to climatic variables and land use. However, RZWQM2 did indicate that soil characteristics (texture, pH) also had an influence on stable C pool dynamics. References 1 - Zimmermann et al., 2007. Measured soil organic matter fractions can be related to pools in the RothC model. European Journal of Soil Science, 58:658-667.

Modelling seasonal variations of natural radioactivity in soils: A case study in southern Italy

NASA Astrophysics Data System (ADS)

Guagliardi, Ilaria; Rovella, Natalia; Apollaro, Carmine; Bloise, Andrea; Rosa, Rosanna De; Scarciglia, Fabio; Buttafuoco, Gabriele

2016-12-01

The activity of natural radionuclides in soil has become an environmental concern for local public and national authorities because of the harmful effects of radiation exposure on human health. In this context, modelling and mapping the activity of natural radionuclides in soil is an important research topic. The study was aimed to model, in a spatial sense, the soil radioactivity in an urban and peri-urban soils area in southern Italy to analyse the seasonal influence on soil radioactivity. Measures of gamma radiation naturally emitted through the decay of radioactive isotopes (potassium, uranium and thorium) were analysed using a geostatistical approach to map the spatial distribution of soil radioactivity. The activity of three radionuclides was measured at 181 locations using a high-resolution ?-ray spectrometry. To take into account the influence of season, the measurements were carried out in summer and in winter. Activity data were analysed by using a geostatistical approach and zones of relatively high or low radioactivity were delineated. Among the main processes which influence natural radioactivity such as geology, geochemical, pedological, and ecological processes, results of this study showed a prominent control of radio-emission measurements by seasonal changes. Low natural radioactivity levels were measured in December associated with winter weather and moist soil conditions (due to high rainfall and low temperature), and higher activity values in July, when the soil was dry and no precipitations occurred.

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.

Simulations and field observations of root water uptake in plots with different soil water availability.

NASA Astrophysics Data System (ADS)

Cai, Gaochao; Vanderborght, Jan; Couvreur, Valentin; Javaux, Mathieu; Vereecken, Harry

2015-04-01

Root water uptake is a main process in the hydrological cycle and vital for water management in agronomy. In most models of root water uptake, the spatial and temporal soil water status and plant root distributions are required for water flow simulations. However, dynamic root growth and root distributions are not easy and time consuming to measure by normal approaches. Furthermore, root water uptake cannot be measured directly in the field. Therefore, it is necessary to incorporate monitoring data of soil water content and potential and root distributions within a modeling framework to explore the interaction between soil water availability and root water uptake. But, most models are lacking a physically based concept to describe water uptake from soil profiles with vertical variations in soil water availability. In this contribution, we present an experimental setup in which root development, soil water content and soil water potential are monitored non-invasively in two field plots with different soil texture and for three treatments with different soil water availability: natural rain, sheltered and irrigated treatment. Root development is monitored using 7-m long horizontally installed minirhizotubes at six depths with three replicates per treatment. The monitoring data are interpreted using a model that is a one-dimensional upscaled version of root water uptake model that describes flow in the coupled soil-root architecture considering water potential gradients in the system and hydraulic conductances of the soil and root system (Couvreur et al., 2012). This model approach links the total root water uptake to an effective soil water potential in the root zone. The local root water uptake is a function of the difference between the local soil water potential and effective root zone water potential so that compensatory uptake in heterogeneous soil water potential profiles is simulated. The root system conductance is derived from inverse modelling using measurements of soil water potentials, water contents, and root distributions. The results showed that this modelling approach reproduced soil water dynamics well in the different plots and treatments. Root water uptake reduced when the effective soil water potential decreased to around -70 to -100 kPa in the root zone. Couvreur, V., Vanderborght, J., and Javaux, M.: A simple three dimensional macroscopic root water uptake model based on the hydraulic architecture approach, Hydrol. Earth Syst. Sci., 16, 2957-2971, doi:10.5194/hess-16-2957-2012, 2012.

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.

Perturbations and gradients as fundamental tests for modeling the soil carbon cycle

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Bailey, V. L.; Becker, K.; Fansler, S.; Hinkle, C.; Liu, C.

2013-12-01

An important step in matching process-level knowledge to larger-scale measurements and model results is to challenge those models with site-specific perturbations and/or changing environmental conditions. Here we subject modified versions of an ecosystem process model to two stringent tests: replicating a long-term climate change dryland experiment (Rattlesnake Mountain) and partitioning the carbon fluxes of a soil drainage gradient in the northern Everglades (Disney Wilderness Preserve). For both sites, on-site measurements were supplemented by laboratory incubations of soil columns. We used a parameter-space search algorithm to optimize, within observational limits, the model's influential inputs, so that the spun-up carbon stocks and fluxes matched observed values. Modeled carbon fluxes (net primary production and net ecosystem exchange) agreed with measured values, within observational error limits, but the model's partitioning of soil fluxes (autotrophic versus heterotrophic), did not match laboratory measurements from either site. Accounting for site heterogeneity at DWP, modeled carbon exchange was reasonably consistent with values from eddy covariance. We discuss the implications of this work for ecosystem- to global scale modeling of ecosystems in a changing climate.

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.

The rapid measurement of soil carbon stock using near-infrared technology

NASA Astrophysics Data System (ADS)

Kusumo, B. H.; Sukartono; Bustan

2018-03-01

As a soil pool stores carbon (C) three times higher than an atmospheric pool, the depletion of C stock in the soil will significantly increase the concentration of CO2 in the atmosphere, causing global warming. However, the monitoring or measurement of soil C stock using conventional procedures is time-consuming and expensive. So it requires a rapid and non-destructive technique that is simple and does not need chemical substances. This research is aimed at testing whether near-infrared (NIR) technology is able to rapidly measure C stock in the soil. Soil samples were collected from an agricultural land at the sub-district of Kayangan, North Lombok, Indonesia. The coordinates of the samples were recorded. Parts of the samples were analyzed using conventional procedure (Walkley and Black) and some other parts were scanned using near-infrared spectroscopy (NIRS) for soil spectral collection. Partial Least Square Regression (PLSR) was used to develop models from soil C data measured by conventional analysis and from spectral data scanned by NIRS. The best model was moderately successful to measure soil C stock in the study area in North Lombok. This indicates that the NIR technology can be further used to monitor the change of soil C stock in the soil.

Measuring temperature dependence of soil respiration: importance of incubation time, soil type, moisture content and model fits

NASA Astrophysics Data System (ADS)

Schipper, L. A.; Robinson, J.; O'Neill, T.; Ryburn, J.; Arcus, V. L.

2015-12-01

Developing robust models of the temperature response and sensitivity of soil respiration is critical for determining changes carbon cycling in response to climate change and at daily to annual time scales. Currently, approaches for measuring temperature dependence of soil respiration generally use long incubation times (days to weeks and months) at a limited number of incubation temperatures. Long incubation times likely allow thermal adaptation by the microbial population so that results are poorly representative of in situ soil responses. Additionally, too few incubation temperatures allows for the fit and justification of many different predictive equations, which can lead to inaccuracies when used for carbon budgeting purposes. We have developed a method to rapidly determine the response of soil respiration rate to wide range of temperatures. An aluminium block with 44 sample slots is heated at one end and cooled at the other to give a temperature gradient from 0 to 55°C at about one degree increments. Soil respiration is measured within 5 hours to minimise the possibility of thermal adaptation. We have used this method to demonstrate the similarity of temperature sensitivity of respiration for different soils from the same location across seasons. We are currently testing whether long-term (weeks to months) incubation alter temperature response and sensitivity that occurs in situ responses. This method is also well suited for determining the most appropriate models of temperature dependence and sensitivity of soil respiration (including macromolecular rate theory MMRT). With additional testing, this method is expected to be a more reliable method of measuring soil respiration rate for soil quality and modelling of soil carbon processes.

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.

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.

[Detecting the moisture content of forest surface soil based on the microwave remote sensing technology.

PubMed

Li, Ming Ze; Gao, Yuan Ke; Di, Xue Ying; Fan, Wen Yi

2016-03-01

The moisture content of forest surface soil is an important parameter in forest ecosystems. It is practically significant for forest ecosystem related research to use microwave remote sensing technology for rapid and accurate estimation of the moisture content of forest surface soil. With the aid of TDR-300 soil moisture content measuring instrument, the moisture contents of forest surface soils of 120 sample plots at Tahe Forestry Bureau of Daxing'anling region in Heilongjiang Province were measured. Taking the moisture content of forest surface soil as the dependent variable and the polarization decomposition parameters of C band Quad-pol SAR data as independent variables, two types of quantitative estimation models (multilinear regression model and BP-neural network model) for predicting moisture content of forest surface soils were developed. The spatial distribution of moisture content of forest surface soil on the regional scale was then derived with model inversion. Results showed that the model precision was 86.0% and 89.4% with RMSE of 3.0% and 2.7% for the multilinear regression model and the BP-neural network model, respectively. It indicated that the BP-neural network model had a better performance than the multilinear regression model in quantitative estimation of the moisture content of forest surface soil. The spatial distribution of forest surface soil moisture content in the study area was then obtained by using the BP neural network model simulation with the Quad-pol SAR data.

Soil moisture sensitivity of autotrophic and heterotrophic forest floor respiration in boreal xeric pine and mesic spruce forests

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Heikkinen, Jukka; Lehtonen, Aleksi

2016-04-01

Litter decomposition rates of the most process based soil carbon models affected by environmental conditions are linked with soil heterotrophic CO2 emissions and serve for estimating soil carbon sequestration; thus due to the mass balance equation the variation in measured litter inputs and measured heterotrophic soil CO2 effluxes should indicate soil carbon stock changes, needed by soil carbon management for mitigation of anthropogenic CO2 emissions, if sensitivity functions of the applied model suit to the environmental conditions e.g. soil temperature and moisture. We evaluated the response forms of autotrophic and heterotrophic forest floor respiration to soil temperature and moisture in four boreal forest sites of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) by a soil trenching experiment during year 2015 in southern Finland. As expected both autotrophic and heterotrophic forest floor respiration components were primarily controlled by soil temperature and exponential regression models generally explained more than 90% of the variance. Soil moisture regression models on average explained less than 10% of the variance and the response forms varied between Gaussian for the autotrophic forest floor respiration component and linear for the heterotrophic forest floor respiration component. Although the percentage of explained variance of soil heterotrophic respiration by the soil moisture was small, the observed reduction of CO2 emissions with higher moisture levels suggested that soil moisture response of soil carbon models not accounting for the reduction due to excessive moisture should be re-evaluated in order to estimate right levels of soil carbon stock changes. Our further study will include evaluation of process based soil carbon models by the annual heterotrophic respiration and soil carbon stocks.

An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

NASA Technical Reports Server (NTRS)

Wang, J. R.

1992-01-01

Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.

Distributed Soil Moisture Estimation in a Mountainous Semiarid Basin: Constraining Soil Parameter Uncertainty through Field Studies

NASA Astrophysics Data System (ADS)

Yatheendradas, S.; Vivoni, E.

2007-12-01

A common practice in distributed hydrological modeling is to assign soil hydraulic properties based on coarse textural datasets. For semiarid regions with poor soil information, the performance of a model can be severely constrained due to the high model sensitivity to near-surface soil characteristics. Neglecting the uncertainty in soil hydraulic properties, their spatial variation and their naturally-occurring horizonation can potentially affect the modeled hydrological response. In this study, we investigate such effects using the TIN-based Real-time Integrated Basin Simulator (tRIBS) applied to the mid-sized (100 km2) Sierra Los Locos watershed in northern Sonora, Mexico. The Sierra Los Locos basin is characterized by complex mountainous terrain leading to topographic organization of soil characteristics and ecosystem distributions. We focus on simulations during the 2004 North American Monsoon Experiment (NAME) when intensive soil moisture measurements and aircraft- based soil moisture retrievals are available in the basin. Our experiments focus on soil moisture comparisons at the point, topographic transect and basin scales using a range of different soil characterizations. We compare the distributed soil moisture estimates obtained using (1) a deterministic simulation based on soil texture from coarse soil maps, (2) a set of ensemble simulations that capture soil parameter uncertainty and their spatial distribution, and (3) a set of simulations that conditions the ensemble on recent soil profile measurements. Uncertainties considered in near-surface soil characterization provide insights into their influence on the modeled uncertainty, into the value of soil profile observations, and into effective use of on-going field observations for constraining the soil moisture response uncertainty.

A simplified regional-scale electromagnetic induction - Salinity calibration model using ANOCOVA modeling techniques

USDA-ARS?s Scientific Manuscript database

Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (ECa) is a potential means of characterizing the spatial variability of any soil property that influences ECa including soil salinity, water content, texture, bulk density, organic matter, and cation exc...

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.

The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation

NASA Astrophysics Data System (ADS)

Shuttleworth, J.; Rosolem, R.; Zreda, M.; Franz, T.

2013-08-01

Soil moisture status in land surface models (LSMs) can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX) model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC), which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a) degradation of the incoming high-energy neutron flux with soil depth, (b) creation of fast neutrons at each depth in the soil, and (c) scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS), and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.

Diurnal hysteresis between soil CO2 and soil temperature is controlled by soil water content

Treesearch

Diego A. Riveros-Iregui; Ryan E. Emanuel; Daniel J. Muth; L. McGlynn Brian; Howard E. Epstein; Daniel L. Welsch; Vincent J. Pacific; Jon M. Wraith

2007-01-01

Recent years have seen a growing interest in measuring and modeling soil CO2 efflux, as this flux represents a large component of ecosystem respiration and is a key determinant of ecosystem carbon balance. Process-based models of soil CO2 production and efflux, commonly based on soil temperature, are limited by nonlinearities such as the observed diurnal hysteresis...

A multimedia fate and chemical transport modeling system for pesticides: II. Model evaluation

NASA Astrophysics Data System (ADS)

Li, Rong; Scholtz, M. Trevor; Yang, Fuquan; Sloan, James J.

2011-07-01

Pesticides have adverse health effects and can be transported over long distances to contaminate sensitive ecosystems. To address problems caused by environmental pesticides we developed a multimedia multi-pollutant modeling system, and here we present an evaluation of the model by comparing modeled results against measurements. The modeled toxaphene air concentrations for two sites, in Louisiana (LA) and Michigan (MI), are in good agreement with measurements (average concentrations agree to within a factor of 2). Because the residue inventory showed no soil residues at these two sites, resulting in no emissions, the concentrations must be caused by transport; the good agreement between the modeled and measured concentrations suggests that the model simulates atmospheric transport accurately. Compared to the LA and MI sites, the measured air concentrations at two other sites having toxaphene soil residues leading to emissions, in Indiana and Arkansas, showed more pronounced seasonal variability (higher in warmer months); this pattern was also captured by the model. The model-predicted toxaphene concentration fraction on particles (0.5-5%) agrees well with measurement-based estimates (3% or 6%). There is also good agreement between modeled and measured dry (1:1) and wet (within a factor of less than 2) depositions in Lake Ontario. Additionally this study identified erroneous soil residue data around a site in Texas in a published US toxaphene residue inventory, which led to very low modeled air concentrations at this site. Except for the erroneous soil residue data around this site, the good agreement between the modeled and observed results implies that both the US and Mexican toxaphene soil residue inventories are reasonably good. This agreement also suggests that the modeling system is capable of simulating the important physical and chemical processes in the multimedia compartments.

Predicting the Mineral Composition of Dust Aerosols. Part 2; Model Evaluation and Identification of Key Processes with Observations

NASA Technical Reports Server (NTRS)

Perlwitz, J. P.; Garcia-Pando, C. Perez; Miller, R. L.

2015-01-01

A global compilation of nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols in an Earth system model. Both methods are based upon a Mean Mineralogical Table (MMT) that relates the soil mineral fractions to a global atlas of arid soil type. The Soil Mineral Fraction (SMF) method assumes that the aerosol mineral fractions match the fractions of the soil. The MMT is based upon soil measurements after wet sieving, a process that destroys aggregates of soil particles that would have been emitted from the original, undisturbed soil. The second method approximately reconstructs the emitted aggregates. This model is referred to as the Aerosol Mineral Fraction (AMF) method because the mineral fractions of the aerosols differ from those of the wet-sieved parent soil, partly due to reaggregation. The AMF method remedies some of the deficiencies of the SMF method in comparison to observations. Only the AMF method exhibits phyllosilicate mass at silt sizes, where they are abundant according to observations. In addition, the AMF quartz fraction of silt particles is in better agreement with measured values, in contrast to the overestimated SMF fraction. Measurements at distinct clay and silt particle sizes are shown to be more useful for evaluation of the models, in contrast to the sum over all particles sizes that is susceptible to compensating errors, as illustrated by the SMF experiment. Model errors suggest that allocation of the emitted silt fraction of each mineral into the corresponding transported size categories is an important remaining source of uncertainty. Evaluation of both models and the MMT is hindered by the limited number of size-resolved measurements of mineral content that sparsely sample aerosols from the major dust sources. The importance of climate processes dependent upon aerosol mineral composition shows the need for global and routine mineral measurements.

Predicting the mineral composition of dust aerosols – Part 2: Model evaluation and identification of key processes with observations

DOE PAGES

Perlwitz, J. P.; Perez Garcia-Pando, C.; Miller, R. L.

2015-10-21

A global compilation of nearly sixty measurement studies is used to evaluate two methods of simulating the mineral composition of dust aerosols in an Earth system model. Both methods are based upon a Mean Mineralogical Table (MMT) that relates the soil mineral fractions to a global atlas of arid soil type. The Soil Mineral Fraction (SMF) method assumes that the aerosol mineral fractions match the fractions of the soil. The MMT is based upon soil measurements after wet sieving, a process that destroys aggregates of soil particles that would have been emitted from the original, undisturbed soil. The second methodmore » approximately reconstructs the emitted aggregates. This model is referred to as the Aerosol Mineral Fraction (AMF) method because the mineral fractions of the aerosols differ from those of the wet-sieved parent soil, partly due to reaggregation. The AMF method remedies some of the deficiencies of the SMF method in comparison to observations. Only the AMF method exhibits phyllosilicate mass at silt sizes, where they are abundant according to observations. In addition, the AMF quartz fraction of silt particles is in better agreement with measured values, in contrast to the overestimated SMF fraction. Measurements at distinct clay and silt particle sizes are shown to be more useful for evaluation of the models, in contrast to the sum over all particles sizes that is susceptible to compensating errors, as illustrated by the SMF experiment. Model errors suggest that allocation of the emitted silt fraction of each mineral into the corresponding transported size categories is an important remaining source of uncertainty. Evaluation of both models and the MMT is hindered by the limited number of size-resolved measurements of mineral content that sparsely sample aerosols from the major dust sources. In conclusion, the importance of climate processes dependent upon aerosol mineral composition shows the need for global and routine mineral measurements.« less

Rain water transport and storage in a model sandy soil with hydrogel particle additives.

PubMed

Wei, Y; Durian, D J

2014-10-01

We study rain water infiltration and drainage in a dry model sandy soil with superabsorbent hydrogel particle additives by measuring the mass of retained water for non-ponding rainfall using a self-built 3D laboratory set-up. In the pure model sandy soil, the retained water curve measurements indicate that instead of a stable horizontal wetting front that grows downward uniformly, a narrow fingered flow forms under the top layer of water-saturated soil. This rain water channelization phenomenon not only further reduces the available rain water in the plant root zone, but also affects the efficiency of soil additives, such as superabsorbent hydrogel particles. Our studies show that the shape of the retained water curve for a soil packing with hydrogel particle additives strongly depends on the location and the concentration of the hydrogel particles in the model sandy soil. By carefully choosing the particle size and distribution methods, we may use the swollen hydrogel particles to modify the soil pore structure, to clog or extend the water channels in sandy soils, or to build water reservoirs in the plant root zone.

Improving the spatial representation of soil properties and hydrology using topographically derived watershed model initialization processes

NASA Astrophysics Data System (ADS)

Easton, Z. M.; Fuka, D.; Collick, A.; Kleinman, P. J. A.; Auerbach, D.; Sommerlot, A.; Wagena, M. B.

2015-12-01

Topography exerts critical controls on many hydrologic, geomorphologic, and environmental biophysical processes. Unfortunately many watershed modeling systems use topography only to define basin boundaries and stream channels and do not explicitly account for the topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. We develop and demonstrate a method that uses topography to spatially adjust soil morphological and soil hydrological attributes [soil texture, depth to the C-horizon, saturated conductivity, bulk density, porosity, and the field capacities at 33kpa (~ field capacity) and 1500kpa (~ wilting point) tensions]. In order to test the performance of the method the topographical adjusted soils and standard SSURGO soil (available at 1:20,000 scale) were overlaid on soil pedon pit data in the Grasslands Soil and Water Research Lab in Resiel, TX. The topographically adjusted soils exhibited significant correlations with measurements from the soil pits, while the SSURGO soil data showed almost no correlation to measured data. We also applied the method to the Grasslands Soil and Water Research watershed using the Soil and Water Assessment Tool (SWAT) model to 15 separate fields as a proxy to propagate changes in soil properties into field scale hydrological responses. Results of this test showed that the topographically adjusted soils resulted better model predictions of field runoff in 50% of the field, with the SSURGO soils preforming better in the remainder of the fields. However, the topographically adjusted soils generally predicted baseflow response more accurately, reflecting the influence of these soil properties on non-storm responses. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases improve model performance.

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.

Soil redistribution model for undisturbed and cultivated sites based on Chernobyl-derived cesium-137 fallout.

PubMed

Hrachowitz, Markus; Maringer, Franz-Josef; Steineder, Christian; Gerzabek, Martin H

2005-01-01

Measurements of 137Cs fallout have been used in combination with a range of conversion models for the investigation of soil relocation mechanisms and sediment budgets in many countries for more than 20 yr. The objective of this paper is to develop a conversion model for quantifying soil redistribution, based on Chernobyl-derived 137Cs. The model is applicable on uncultivated as well as on cultivated sites, taking into account temporal changes in the 137Cs depth distribution pattern as well as tillage-induced 137Cs dilution effects. The main idea of the new model is the combination of a modified exponential model describing uncultivated soil with a Chapman distribution based model describing cultivated soil. The compound model subsequently allows a dynamic description of the Chernobyl derived 137Cs situation in the soil and its change, specifically migration and soil transport processes over the course of time. Using the suggested model at the sampling site in Pettenbach, in the Austrian province of Oberösterreich 137Cs depth distributions were simulated with a correlation coefficient of 0.97 compared with the measured 137Cs depth profile. The simulated rates of soil distribution at different positions at the sampling site were found to be between 27 and 60 Mg ha(-1) yr(-1). It was shown that the model can be used to describe the temporal changes of 137Cs depth distributions in cultivated as well as uncultivated soils. Additionally, the model allows to quantify soil redistribution in good correspondence with already existing models.

Probing soil nitrogen transformations using triple nitrate isotopes

NASA Astrophysics Data System (ADS)

Yu, Z.; Elliott, E. M.

2017-12-01

Models of soil nitrogen (N) transformations are essential for understanding biogeochemical N cycling and its environmental implications. While natural abundance stable N isotopes (δ15N) of the soil N pool are widely used to infer soil N dynamics, its quantitative use is limited by uncertainties in the relevant isotopic fractionations. Oxygen-17 isotope anomalies in nitrate (Δ17O-NO3-), originating from mass-independent fractionation during photochemical NO3- formation, are a conservative tracer of atmospherically deposited NO3- in terrestrial ecosystems. Therefore, measurement of soil Δ17O-NO3- may provide additional tracing power for δ15N-based process models, in that Δ17O-NO3- is not altered by mass-dependent isotopic fractionations. In this study, we conducted both laboratory and field experiments to assess the effectiveness of using triple NO3- isotopes (Δ17O, δ15N, δ18O) for modeling soil N transformations. Surface soil (0-7 cm) was sampled from an urban riparian area and temperate, upland forests in rural and urban settings for batch incubations and amendments with Δ17O-enriched NO3-. After amendment, the soils were extracted on six occasions over a 4-day period to measure concentrations and isotopic composition of NO3- and ammonium. A Δ17O-based numerical model was developed and used to derive gross N fluxes. In situ field soil and lysimeter sampling was also conducted at the rural forest site on five consecutive days immediately following snowmelt input of Δ17O-enriched NO3-. The results show that the temporal dynamics of Δ17O-NO3- can provide quantitative information on soil N turnover. In the laboratory incubations, modeled gross nitrification and denitrification rates were significantly higher for the urban forest and riparian soils, consistent with results from inhibitor-based potential measurements. Non-zero Δ17O-NO3- values, up to 4.3‰, were measured in the rural forest soil following the snowmelt event. A numerical model of the progressive decrease of soil Δ17O-NO3- indicates high NO3- production and consumption rates, revealing active post-snowmelt N cycling in soils. These preliminary results suggest that the triple NO3- isotopes are a powerful tracer for probing soil N transformations and future applications are expected to help disentangle soil N cycling complexity.

Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling

NASA Astrophysics Data System (ADS)

Tramblay, Yves; Bouvier, Christophe; Martin, Claude; Didon-Lescot, Jean-François; Todorovik, Dragana; Domergue, Jean-Marc

2010-06-01

Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture, modelled soil moisture through the Interaction-Sol-Biosphère-Atmosphère (ISBA) component of the SIM model (Météo-France), antecedent precipitation and base flow. A modelling approach based on the Soil Conservation Service-Curve Number method (SCS-CN) is used to simulate the flood events in a small headwater catchment in the Cevennes region (France). The model involves two parameters: one for the runoff production, S, and one for the routing component, K. The S parameter can be interpreted as the maximal water retention capacity, and acts as the initial condition of the model, depending on the antecedent moisture conditions. The model was calibrated from a 20-flood sample, and led to a median Nash value of 0.9. The local TDR measurements in the deepest layers of soil (80-140 cm) were found to be the best predictors for the S parameter. TDR measurements averaged over the whole soil profile, outputs of the SIM model, and the logarithm of base flow also proved to be good predictors, whereas antecedent precipitations were found to be less efficient. The good correlations observed between the TDR predictors and the S calibrated values indicate that monitoring soil moisture could help setting the initial conditions for simplified event-based models in small basins.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Coupling rainfall observations and satellite soil moisture for predicting event soil loss in Central Italy

NASA Astrophysics Data System (ADS)

Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang

2015-04-01

The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More specifically the analysis was focused on the evaluation of the effectiveness of coupling modeled or satellite-derived soil moisture with USLE-derived models in predicting event unit soil loss at the plot scale in a silty-clay soil in Central Italy. To this end was used the database of the Masse experimental station developed considering for a given erosive event (an event yielding a measurable soil loss) the simultaneous measures of the total runoff amount, Qe (mm), and soil loss per unit area, Ae (Mg-ha-1) at plot scale and of the rainfall data required to derive the erosivity factor Re according to Wischmeiser and Smith (1978), with a MIT=6 h (Bagarello et al., 2013; Todisco et al., 2012). To the purpose of this investigation only data collected on the λ = 22 m long plots were considered: 63 erosive events in the period 2008-2013, 18 occurred during the dry period (from June to September) and the other 45 in the complementary period (wet period). The models tested are the USLE/RUSLE and some USLE-derived formulations in which the event erosivity factor, Re, is corrected by the antecedent soil moisture, θ, and powered to an exponent α > 0 (α =1: linear model; α ≠ 1: power model). Both soil moisture data the satellite retrieved (θ = θsat) and the estimates (θ = θest) of Soil Water Balance model (Brocca et al., 2011) were tested. The results have been compared with those obtained by the USLE/RUSLE, USLE-M and USLE-MM models coupled with a parsimonious rainfall-runoff model, MILc, (Brocca et al. 2011) for the prediction of runoff volume (that in these models is the term used to correct the erosivity factor Re). The results showed that: including direct consideration of antecedent soil moisture and runoff in the event rainfall-runoff factor of the RUSLE/USLE enhanced the capacity of the model to account for variations in event soil loss when soil moisture and runoff volume are measured or predicted reasonably well; the accuracy of the original USLE/RUSLE model was always the lowest; the accuracy in estimating the event soil loss of a models with erosivity factor that includes the estimated runoff is always overcome by at least one model that uses the antecedent soil moisture θ in the erosivity index; the power models generally, at Masse, work better than the linear. The more accurate models are that with the estimated antecedent soil moisture, θest, when all the database is used and with the satellite retrieved soil moisture, θsat, when only the wet periods' events are considered. In fact it was also verified that much of the inaccuracy of the tested models is due to summer rainfall events, probably because of the particular characteristics that the soil assumes in the dry period (superficial crusts causing higher runoff): in this cases, high soil losses are observed in association to low values of soil moisture, while the simulated runoff assume low values too, since they are based on the antecedent wetness conditions. Thus, the analyses were repeated excluding the summer events. As expected, the performance of all the models increases, but still the use of θ provides the best results. The results of the analysis open interesting scenarios in the use of USLE-derived models for the unit event soil loss estimation at large scale. In particular the use of the soil moisture to correct the rainfall erosivity factor acquires a great practical importance, since it is a relatively simple measurable data and moreover because remote sensing soil moisture data are widely available and useful in large-scale erosion assessment. Bagarello, V., Di Piazza, G. V., Ferro, V., Giordano, G., 2008. Predicting unit soil loss in Sicily, south Italy. Hydrol. Process. 22, 586-595. Bagarello, V., Ferro, V., Giordano, G., Mannocchi, F., Todisco, F., Vergni, L., 2013. Predicting event soil loss form bare plots at two Italian sites. Catena 109, 96-102. Brocca, L., Melone, F., Moramarco, T., 2011. Distributed rainfall-runoff modeling for flood frequency estimation and flood forecasting. Hydrol. Process. 25, 2801-2813. Kinnell, P. I. A., Risse, L. M., 1998. USLE-M: empirical modeling rainfall erosion through runoff and sediment concentration. Soil Sci. Soc. Am. J. 62, 1667-1672. Todisco, F., Vergni, L., Mannocchi, F., Bomba, C., 2012. Calibration of the soil loss measurement at the Masse experimental station. Catena 91, 4-9. Wischmeier, W. H., Smith, D. D., 1978. Predicting rainfall-erosion losses - A guide to conservation planning. Agriculture Handbook 537, United Stated Department of Agriculture.

Evaluation of soil C-14 data for estimating inert organic matter in the RothC model

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

Rethemeyer, J.; Grootes, P.M.; Brodowski, S.

2007-07-01

Changes in soil organic carbon stocks were simulated with the Rothamsted carbon (RothC) model. We evaluated the calculation of a major input variable, the amount of inert organic matter (IOM), using measurable data. Three different approaches for quantifying IOM were applied to soils with mainly recent organic matter and with carbon contribution from fossil fuels: 1) IOM estimation via total soil organic carbon (SOC); 2) through bulk soil radiocarbon and a mass balance; and 3) by quantifying the portion of black carbon via a specific marker. The results were highly variable in the soil containing lignite-derived carbon and ranged frommore » 8% to 52% inert carbon of total SOC, while nearly similar amounts of 5% to 8% were determined in the soil with mainly recent organic matter. We simulated carbon dynamics in both soils using the 3 approaches for quantifying IOM in combination with carbon inputs derived from measured crop yields. In the soil with recent organic matter, all approaches gave a nearly similar good agreement between measured and modeled data, while in the soil with a fossil carbon admixture, only the C-14 approach was successful in matching the measured data. Although C-14 was useful for initializing RothC, care should be taken when interpreting SOC dynamics in soils containing carbon from fossil fuels, since these reflect the contribution from both natural and anthropogenic carbon sources.« less

Using passive capillary lysimeter water flux measurements to improve flow predictions in variably saturated soils.

USDA-ARS?s Scientific Manuscript database

Passive capillary lysimeters (PCLs) are uniquely suited for measuring water fluxes in variably-saturated soils. The objective of this work was to compare PCL flux measurements with simulated fluxes obtained with a calibrated unsaturated flow model. The Richards equation-based model was calibrated us...

Role of the interface between distributed fibre optic strain sensor and soil in ground deformation measurement

NASA Astrophysics Data System (ADS)

Zhang, Cheng-Cheng; Zhu, Hong-Hu; Shi, Bin

2016-11-01

Recently the distributed fibre optic strain sensing (DFOSS) technique has been applied to monitor deformations of various earth structures. However, the reliability of soil deformation measurements remains unclear. Here we present an integrated DFOSS- and photogrammetry-based test study on the deformation behaviour of a soil foundation model to highlight the role of strain sensing fibre-soil interface in DFOSS-based geotechnical monitoring. Then we investigate how the fibre-soil interfacial behaviour is influenced by environmental changes, and how the strain distribution along the fibre evolves during progressive interface failure. We observe that the fibre-soil interfacial bond is tightened and the measurement range of the fibre is extended under high densities or low water contents of soil. The plastic zone gradually occupies the whole fibre length when the soil deformation accumulates. Consequently, we derive a theoretical model to simulate the fibre-soil interfacial behaviour throughout the progressive failure process, which accords well with the experimental results. On this basis, we further propose that the reliability of measured strain can be determined by estimating the stress state of the fibre-soil interface. These findings may have important implications for interpreting and evaluating fibre optic strain measurements, and implementing reliable DFOSS-based geotechnical instrumentation.

Assessing five evolving microbial enzyme models against field measurements from a semiarid savannah—What are the mechanisms of soil respiration pulses?

NASA Astrophysics Data System (ADS)

Zhang, Xia; Niu, Guo-Yue; Elshall, Ahmed S.; Ye, Ming; Barron-Gafford, Greg A.; Pavao-Zuckerman, Mitch

2014-09-01

Soil microbial respiration pulses in response to episodic rainfall pulses (the "Birch effect") are poorly understood. We developed and assessed five evolving microbial enzyme models against field measurements from a semiarid savannah characterized by pulsed precipitation to understand the mechanisms to generate the Birch pulses. The five models evolve from an existing four-carbon (C) pool model to models with additional C pools and explicit representations of soil moisture controls on C degradation and microbial uptake rates. Assessing the models using techniques of model selection and model averaging suggests that models with additional C pools for accumulation of degraded C in the dry zone of the soil pore space result in a higher probability of reproducing the observed Birch pulses. Degraded C accumulated in dry soil pores during dry periods becomes immediately accessible to microbes in response to rainstorms, providing a major mechanism to generate respiration pulses. Explicitly representing the transition of degraded C and enzymes between dry and wet soil pores in response to soil moisture changes and soil moisture controls on C degradation and microbial uptake rates improve the models' efficiency and robustness in simulating the Birch effect. Assuming that enzymes in the dry soil pores facilitate degradation of complex C during dry periods (though at a lower rate) results in a greater accumulation of degraded C and thus further improves the models' performance. However, the actual mechanism inducing the greater accumulation of labile C needs further experimental studies.

Evaluation of fine soil moisture data from the IFloodS (NASA GPM) Ground Validation campaign using a fully-distributed ecohydrological model

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Arnone, E.; Bras, R. L.

2014-12-01

The spatial variability of soil, vegetation, topography, and precipitation controls hydrological processes, consequently resulting in high spatio-temporal variability of most of the hydrological variables, such as soil moisture. Limitation in existing measuring system to characterize this spatial variability, and its importance in various application have resulted in a need of reconciling spatially distributed soil moisture evolution model and corresponding measurements. Fully distributed ecohydrological model simulates soil moisture at high resolution soil moisture. This is relevant for range of environmental studies e.g., flood forecasting. They can also be used to evaluate the value of space born soil moisture data, by assimilating them into hydrological models. In this study, fine resolution soil moisture data simulated by a physically-based distributed hydrological model, tRIBS-VEGGIE, is compared with soil moisture data collected during the field campaign in Turkey river basin, Iowa. The soil moisture series at the 2 and 4 inch depth exhibited a more rapid response to rainfall as compared to bottom 8 and 20 inch ones. The spatial variability in two distinct land surfaces of Turkey River, IA, reflects the control of vegetation, topography and soil texture in the characterization of spatial variability. The comparison of observed and simulated soil moisture at various depth showed that model was able to capture the dynamics of soil moisture at a number of gauging stations. Discrepancies are large in some of the gauging stations, which are characterized by rugged terrain and represented, in the model, through large computational units.

SSDA code to apply data assimilation in soil water flow modeling: Documentation and user manual

USDA-ARS?s Scientific Manuscript database

Soil water flow models are based on simplified assumptions about the mechanisms, processes, and parameters of water retention and flow. That causes errors in soil water flow model predictions. Data assimilation (DA) with the ensemble Kalman filter (EnKF) corrects modeling results based on measured s...

Modelling the effect of low soil temperatures on transpiration by Scots pine

NASA Astrophysics Data System (ADS)

Mellander, Per-Erik; Stähli, Manfred; Gustafsson, David; Bishop, Kevin

2006-06-01

For ecosystem modelling of the Boreal forest it is important to include processes associated with low soil temperature during spring-early summer, as these affect the tree water uptake. The COUP model, a physically based SVAT model, was tested with 2 years of soil and snow physical measurements and sap flow measurements in a 70-year-old Scots pine stand in the boreal zone of northern Sweden. During the first year the extent and duration of soil frost was manipulated in the field. The model was successful in reproducing the timing of the soil warming after the snowmelt and frost thaw. A delayed soil warming, into the growing season, severely reduced the transpiration. We demonstrated the potential for considerable overestimation of transpiration by the model if the reduction of the trees' capacity to transpire due to low soil temperatures is not taken into account. We also demonstrated that the accumulated effect of aboveground conditions could be included when simulating the relationship between soil temperature and tree water uptake. This improved the estimated transpiration for the control plot and when soil warming was delayed into the growing season. The study illustrates the need of including antecedent conditions on root growth in the model in order to catch these effects on transpiration. The COUP model is a promising tool for predicting transpiration in high-latitude stands.

Modeling Recharge - can it be Done?

NASA Astrophysics Data System (ADS)

Verburg, K.; Bond, W. J.; Smith, C. J.; Dunin, F. X.

2001-12-01

In sub-humid areas where rainfall is relatively low and sporadic, recharge (defined as water movement beyond the active root zone) is the small difference between the much larger numbers rainfall and evapotranspiration. It is very difficult to measure and often modeling is resorted to instead. But is modeling this small number any less difficult than measurement? In Australia there is considerable debate over the magnitude of recharge under different agricultural systems because of its contribution to rising saline groundwater levels following the clearing of native vegetation in the last 100 years. Hence the adequacy of measured and modeled estimates of recharge is under close scrutiny. Results will be presented for the water balance of an intensively monitored 8 year sequence of crops and pastures. Measurements included meteorological inputs, evapotranspiration measured with a pair of weighing lysimeters, and soil water content was measured with TDR and neutron moisture meter. Recharge was estimated from the percolate removed from the lysimeters as well as, when conditions were suitable, from soil water measurements and combined soil water and evapotranspiration measurements. This data was simulated using a comprehensive soil-plant-atmosphere model (APSIM). Comparison with field measurements shows that the recharge can be simulated with an accuracy similar to that with which it can be measured. However, is either sufficiently accurate for the applications for which they are required?

Dual frequency microwave radiometer measurements of soil moisture for bare and vegetated rough surfaces

NASA Technical Reports Server (NTRS)

Lee, S. L.

1974-01-01

Controlled ground-based passive microwave radiometric measurements on soil moisture were conducted to determine the effects of terrain surface roughness and vegetation on microwave emission. Theoretical predictions were compared with the experimental results and with some recent airborne radiometric measurements. The relationship of soil moisture to the permittivity for the soil was obtained in the laboratory. A dual frequency radiometer, 1.41356 GHz and 10.69 GHz, took measurements at angles between 0 and 50 degrees from an altitude of about fifty feet. Distinct surface roughnesses were studied. With the roughness undisturbed, oats were later planted and vegetated and bare field measurements were compared. The 1.4 GHz radiometer was less affected than the 10.6 GHz radiometer, which under vegetated conditions was incapable of detecting soil moisture. The bare surface theoretical model was inadequate, although the vegetation model appeared to be valid. Moisture parameters to correlate apparent temperature with soil moisture were compared.

Remote measurement of soil moisture over vegetation using infrared temperature measurements

NASA Technical Reports Server (NTRS)

Carlson, Toby N.

1991-01-01

Better methods for remote sensing of surface evapotranspiration, soil moisture, and fractional vegetation cover were developed. The objectives were to: (1) further develop a model of water movement through the soil/plant/atmosphere system; (2) use this model, in conjunction with measurements of infrared surface temperature and vegetation fraction; (3) determine the magnitude of radiometric temperature response to water stress in vegetation; (4) show at what point one can detect that sensitivity to water stress; and (5) determine the practical limits of the methods. A hydrological model that can be used to calculate soil water content versus depth given conventional meteorological records and observations of vegetation cover was developed. An outline of the results of these initiatives is presented.

Modelling ammonia volatilization from animal slurry applied with trail hoses to cereals

NASA Astrophysics Data System (ADS)

Sommer, S. G.; Olesen, J. E.

In Europe ammonia (NH 3), volatilization from animal manure is the major source of NH 3 in the atmosphere. From March to July 1997, NH 3 volatilization from trail hose applied slurry was measured for seven days after application in six experiments. A statistical analysis of data showed that NH 3 volatilization rate during the first 4-5 h after slurry application increased significantly ( P<5%) with wind speed and soil slurry surface water content. NH 3 volatilization in the six measuring periods during the experiments increased significantly ( P<5%) with relative water content of the soil slurry surface, global radiation, pH, and decreased with increasing rainfall during each measuring period and rainfall accumulated from onset of each experiment. A mechanistic model of NH 3 volatilization was developed. Model inputs are climate variables, soil characteristics and total ammoniacal nitrogen (TAN=ammonium+ammonia) in the soil surface layer. A pH submodel for predicting pH at the surface of the soil slurry liquid was developed. The measured NH 3 volatilization was compared with model simulations. The simulated results explained 27% of the variation in measured NH 3 volatilization rates during all seven days, but 48% of measured volatilization rates during the first 24 h. Calculations with the model showed that applying slurry in the morning or in the afternoon reduced volatilization by 50% compared with a noon application. Spreading the slurry with trail hoses to a 60 cm high crop reduced losses by 75% compared with a spreading onto bare soil. Ammonia volatilization was 50% lower when the soil had dried out after slurry application compared with a wet slurry surface.

Phase Sensitiveness to Soil Moisture in Controlled Anechoic Chamber: Measurements and First Results

NASA Astrophysics Data System (ADS)

Ben Khadhra, K.; Nolan, M.; Hounam, D.; Boerner, T.

2005-12-01

To date many radar methods and models have been reported for the estimation of soil moisture, such as the Oh-model or the Dubois model. Those models, which use only the magnitude of the backscattered signal, show results with 5 to 10 % accuracy. In the last two decades SAR Interferometry (InSAR) and differential InSAR (DInSAR), which uses the phase of the backscattered signal, has been shown to be a useful tool for the creation of Digital Elevation Models (DEMs), and temporal changes due to earthquakes, subsidence, and other ground motions. Nolan (2003) also suggested the possibility to use DINSAR penetration depth as a proxy to estimate the soil moisture. The principal is based on the relationship between the penetration depth and the permittivity, which varies as a function of soil moisture. In this paper we will present new interferometric X-band laboratory measurements, which have been carried out in the Bistatic Measurement Facility at the DLR Oberpfaffenhofen, Microwaves and Radar Institute in Germany. The bistatic geometry enables us to have interferometric pairs with different baseline and different soil moistures controlled by a TDR (Time Domain Reflectivity) system. After calibration of the measuring system using a large metal plate, the sensitivity of phase and reflectivity with regard to moisture variation and therefore the penetration depth was evaluated. The effect of the surface roughness has been also reported. Current results demonstrate a non-linear relationship between the signal phase and the soil moisture, as expected, confirming the possibility of using DInSAR to measure variations in soil moisture.

Scaling methane oxidation: From laboratory incubation experiments to landfill cover field conditions

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

Abichou, Tarek, E-mail: abichou@eng.fsu.edu; Mahieu, Koenraad; Chanton, Jeff

2011-05-15

Evaluating field-scale methane oxidation in landfill cover soils using numerical models is gaining interest in the solid waste industry as research has made it clear that methane oxidation in the field is a complex function of climatic conditions, soil type, cover design, and incoming flux of landfill gas from the waste mass. Numerical models can account for these parameters as they change with time and space under field conditions. In this study, we developed temperature, and water content correction factors for methane oxidation parameters. We also introduced a possible correction to account for the different soil structure under field conditions.more » These parameters were defined in laboratory incubation experiments performed on homogenized soil specimens and were used to predict the actual methane oxidation rates to be expected under field conditions. Water content and temperature corrections factors were obtained for the methane oxidation rate parameter to be used when modeling methane oxidation in the field. To predict in situ measured rates of methane with the model it was necessary to set the half saturation constant of methane and oxygen, K{sub m}, to 5%, approximately five times larger than laboratory measured values. We hypothesize that this discrepancy reflects differences in soil structure between homogenized soil conditions in the lab and actual aggregated soil structure in the field. When all of these correction factors were re-introduced into the oxidation module of our model, it was able to reproduce surface emissions (as measured by static flux chambers) and percent oxidation (as measured by stable isotope techniques) within the range measured in the field.« less

Agricultural soil moisture experiment, Colby, Kansas 1978: Measured and predicted hydrological properties of the soil

NASA Technical Reports Server (NTRS)

Arya, L. M. (Principal Investigator)

1980-01-01

Predictive procedures for developing soil hydrologic properties (i.e., relationships of soil water pressure and hydraulic conductivity to soil water content) are presented. Three models of the soil water pressure-water content relationship and one model of the hydraulic conductivity-water content relationship are discussed. Input requirements for the models are indicated, and computational procedures are outlined. Computed hydrologic properties for Keith silt loam, a soil typer near Colby, Kansas, on which the 1978 Agricultural Soil Moisture Experiment was conducted, are presented. A comparison of computed results with experimental data in the dry range shows that analytical models utilizing a few basic hydrophysical parameters can produce satisfactory data for large-scale applications.

Upscaling of soil moisture measurements in NW Italy

NASA Astrophysics Data System (ADS)

Ferraris, Stefano; Canone, Davide; Previati, Maurizio; Brunod, Christian; Ratto, Sara; Cauduro, Marco

2015-04-01

There is large mismatch in spatial scale between the climate and meteorological model grid, and the scale of soil and vegetation measurements. Remote sensing data can help to fit the model scale, but they cannot provide rootzone data. In this work some soil moisture datasets are analysed for the sake of providing larger scale estimation of soil moisture and water and energy fluxes. The first dataset refers to a plain site near Torino, where measurements are taken since 1997 (Baudena et al., 2012), and a mountain site close to the town. The second one is a dataset in the mountains of Valle d'Aosta (Brocca et al., 2013), where 4 years of data are available. The use of digital elevation models and vegetation maps is shown in this work. Some soil processes (e.g. Whalley et al., 2012) are usually disregarded, but in this work their possible impact is considered. References L. Brocca, A. Tarpanelli, T. Moramarco, F. Melone, S.M. Ratto, M. Cauduro, S. Ferraris, N. Berni, F. Ponziani, W. Wagner, T. Melzer (2013). Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations VADOSE ZONE JOURNAL, vol. 8-2, p. 1-10, doi:10.2136/vzj2012.0102 M. Baudena, I. Bevilacqua, D. Canone, S. Ferraris, M. Previati, A. Provenzale (2012). Soil water dynamics at a midlatitude test site: Field measurements and box modeling approaches. JOURNAL OF HYDROLOGY, vol. 414-415, p. 329-340, ISSN: 0022-1694, doi: 10.1016/j.jhydrol.2011.11.009 W.R. Whalley, G.P. Matthews, S. Ferraris (2012). The effect of compaction and shear deformation of saturated soil on hydraulic conductivity. SOIL & TILLAGE RESEARCH, vol. 125, p. 23-29, ISSN: 0167-1987

Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

NASA Astrophysics Data System (ADS)

Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

2017-12-01

The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that need to be assessed against the risk. The modeling community can benefit from such analysis, however, error size and spatial distribution for global and regional predictions need to be assessed against the variability of other drivers and impact on management decisions.

An empirical model for the complex dielectric permittivity of soils as a function of water content

NASA Technical Reports Server (NTRS)

Wang, J. R.; Chmugge, T. J.

1978-01-01

The recent measurements on the dielectric properties of soils shows that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value of transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of ths soil-water mixtures. The relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

NASA Astrophysics Data System (ADS)

Meusburger, K.; Konz, N.; Schaub, M.; Alewell, C.

2010-06-01

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67 km 2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed "hotspots" of high erosion of up to 16 t ha -1 a -1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

Modelling increased soil cohesion by plant roots with EUROSEM

NASA Astrophysics Data System (ADS)

de Baets, S.; Poesen, J.; Torri, D.; Salvador, M. P.

2009-04-01

Soil cohesion is an important variable to model soil detachment by runoff (Morgan et al., 1998a). As soil particles are not loose, soil detachment by runoff will be limited by the cohesion of the soil material. It is generally recognized that plant roots contribute to the overall cohesion of the soil. Determination of this increased cohesion and soil roughness however is complicated and measurements of shear strength and soil reinforcement by plant roots are very time- and labour consuming. A model approach offers an alternative for the assessment of soil cohesion provided by plant roots However, few erosion models account for the effects of the below-ground biomass in their calculation of erosion rates. Therefore, the main objectives of this study is to develop an approach to improve an existing soil erosion model (EUROSEM) accounting for the erosion-reducing effects of roots. The approach for incorporating the root effects into this model is based on a comparison of measured soil detachment rates for bare and for root-permeated topsoil samples with predicted erosion rates under the same flow conditions using the erosion equation of EUROSEM. Through backwards calculation, transport capacity efficiencies and corresponding soil cohesion values can be assessed for bare and root-permeated topsoils respectively. The results are promising and show that grass roots provide a larger increase in soil cohesion as compared with tap-rooted species and that the increase in soil cohesion is not significantly different under wet and dry soil conditions, either for fibrous root systems or for tap root systems. Relationships are established between measured root density values and the corresponding calculated soil cohesion values, reflecting the effects of roots on the resistance of the topsoil to concentrated flow incision. These relationships enable one to incorporate the root effect into the soil erosion model EUROSEM, through adapting the soil cohesion input value. A scenario analysis performed with EUROSEM for different vegetation treatments, indicates that runoff and soil loss on root-permeated topsoils are slightly higher as compared to fully covered grass fields or harvested grass fields with some plant residue left, but much smaller as compared to bare topsoils. Moreover, when re-vegetating bare soils, roots are responsible for a large part of the reduction in soil loss and runoff by concentrated flow. Hence, this analysis shows that the contribution of roots to soil cohesion is very important for preventing soil loss and reducing runoff volume. The increase in soil shear strength due to the binding effect of roots on soil particles is two orders of magnitude lower as compared with soil reinforcement achieved when roots mobilize their tensile strength during soil shearing and root breakage.

Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition.

PubMed

Viscarra Rossel, Raphael A; Lobsey, Craig R; Sharman, Chris; Flick, Paul; McLachlan, Gordon

2017-05-16

Soil information is needed for environmental monitoring to address current concerns over food, water and energy securities, land degradation, and climate change. We developed the Soil Condition ANalysis System (SCANS) to help address these needs. It integrates an automated soil core sensing system (CSS) with statistical analytics and modeling to characterize soil at fine depth resolutions and across landscapes. The CSS's sensors include a γ-ray attenuation densitometer to measure bulk density, digital cameras to image the measured soil, and a visible-near-infrared (vis-NIR) spectrometer to measure iron oxides and clay mineralogy. The spectra are also modeled to estimate total soil organic carbon (C), particulate, humus, and resistant organic C (POC, HOC, and ROC, respectively), clay content, cation exchange capacity (CEC), pH, volumetric water content, available water capacity (AWC), and their uncertainties. Measurements of bulk density and organic C are combined to estimate C stocks. Kalman smoothing is used to derive complete soil property profiles with propagated uncertainties. The SCANS provides rapid, precise, quantitative, and spatially explicit information about the properties of soil profiles with a level of detail that is difficult to obtain with other approaches. The information gained effectively deepens our understanding of soil and calls attention to the central role soil plays in our environment.

Nitrogen deposition and soil carbon sequestration: enzymes, experiments, and model estimates (Invited)

NASA Astrophysics Data System (ADS)

Goodale, C. L.; Weiss, M.; Tonitto, C.; Stone, M.

2010-12-01

Atmospheric nitrogen has long been expected to increase forest carbon sequestration, by means of enhanced productivity and litter production. More recently, N deposition has received attention for its potential for inducing soil C sequestration by suppressing microbial decomposition. Here, we present a range of measurements and model projections of the effects of N additions on soil C dynamics in forest soils of the northeastern U.S. A review of field-scale measurements of soil C stocks suggests modest enhancements of soil C storage in long-term N addition studies. Measurements of forest floor material from six long-term N addition studies showed that N additions suppressed microbial biomass and oxidative enzyme activity across sites. Additional analyses on soils from two of these sites are exploring the interactive effects of temperature and N addition on the activity of a range of extracellular enzymes used for decomposition of a range of organic matter. Incubations of forest floor material from four of these sites showed inhibition of heterotrophic respiration by an average of 28% during the first week of incubation, although this inhibition disappeared after 2 to 11 months. Nitrogen additions had no significant effect on DOC loss or on the partitioning of soil C into light or heavy (mineral-associated) organic matter. Last, we have adapted a new model of soil organic matter decomposition for the PnET-CN model to assess the long-term impact of suppressed decomposition on C sequestration in various soil C pools.

Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; McGuire, A. David; Zhu, Qing; Liu, Yaling; Teskey, Robert O.

2014-01-01

Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long-term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one- and two-horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO2 efflux from trenched plots in a Dahurian larch (Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long-term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short-term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long-term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long-term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.

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.

An integrated soil-crop system model for water and nitrogen management in North China

PubMed Central

Liang, Hao; Hu, Kelin; Batchelor, William D.; Qi, Zhiming; Li, Baoguo

2016-01-01

An integrated model WHCNS (soil Water Heat Carbon Nitrogen Simulator) was developed to assess water and nitrogen (N) management in North China. It included five main modules: soil water, soil temperature, soil carbon (C), soil N, and crop growth. The model integrated some features of several widely used crop and soil models, and some modifications were made in order to apply the WHCNS model under the complex conditions of intensive cropping systems in North China. The WHCNS model was evaluated using an open access dataset from the European International Conference on Modeling Soil Water and N Dynamics. WHCNS gave better estimations of soil water and N dynamics, dry matter accumulation and N uptake than 14 other models. The model was tested against data from four experimental sites in North China under various soil, crop, climate, and management practices. Simulated soil water content, soil nitrate concentrations, crop dry matter, leaf area index and grain yields all agreed well with measured values. This study indicates that the WHCNS model can be used to analyze and evaluate the effects of various field management practices on crop yield, fate of N, and water and N use efficiencies in North China. PMID:27181364

Use of modeled and satelite soil moisture to estimate soil erosion in central and southern Italy.

NASA Astrophysics Data System (ADS)

Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang

2016-04-01

This study presents an accurate comparison between two different approaches aimed to enhance accuracy of the Universal Soil Loss Equation (USLE) in estimating the soil loss at the single event time scale. Indeed it is well known that including the observed event runoff in the USLE improves its soil loss estimation ability at the event scale. In particular, the USLE-M and USLE-MM models use the observed runoff coefficient to correct the rainfall erosivity factor. In the first case, the soil loss is linearly dependent on rainfall erosivity, in the second case soil loss and erosivity are related by a power law. However, the measurement of the event runoff is not straightforward or, in some cases, possible. For this reason, the first approach used in this study is the use of Soil Moisture For Erosion (SM4E), a recent USLE-derived model in which the event runoff is replaced by the antecedent soil moisture. Three kinds of soil moisture datasets have been separately used: the ERA-Interim/Land reanalysis data of the European Centre for Medium-range Weather Forecasts (ECMWF); satellite retrievals from the European Space Agency - Climate Change Initiative (ESA-CCI); modeled data using a Soil Water Balance Model (SWBM). The second approach is the use of an estimated runoff rather than the observed. Specifically, the Simplified Continuous Rainfall-Runoff Model (SCRRM) is used to derive the runoff estimates. SCRMM requires soil moisture data as input and at this aim the same three soil moisture datasets used for the SM4E have been separately used. All the examined models have been calibrated and tested at the plot scale, using data from the experimental stations for the monitoring of the erosive processes "Masse" (Central Italy) and "Sparacia" (Southern Italy). Climatic data and runoff and soil loss measures at the event time scale are available for the period 2008-2013 at Masse and for the period 2002-2013 at Sparacia. The results show that both the approaches can provide better results than the USLE. Specifically, the SM4E model has proven to be particularly effective at Masse, providing the best soil loss estimations, especially when the modeled soil moisture is used. In this case, the RSR index (ratio between the Root Mean Square Error and the Observed Standard deviation) is equal to 0.94. Instead, the SCRRM is able to better estimate the event runoff at Sparacia than at Masse, thus resulting in good performances of the USLE-derived models using the estimated runoff; however, even at Sparacia the SM4E with modeled soil moisture gives the better soil loss estimates, with RSR = 0.54. These results open an interesting scenario in the use of empirical models to determine soil loss at a large scale, since soil moisture is a not only a simple in situ measurement, but only a widely available information on a global scale from remote sensing.

Model-based surface soil moisture (SSM) retrieval algorithm using multi-temporal RISAT-1 C-band SAR data

NASA Astrophysics Data System (ADS)

Pandey, Dharmendra K.; Maity, Saroj; Bhattacharya, Bimal; Misra, Arundhati

2016-05-01

Accurate measurement of surface soil moisture of bare and vegetation covered soil over agricultural field and monitoring the changes in surface soil moisture is vital for estimation for managing and mitigating risk to agricultural crop, which requires information and knowledge to assess risk potential and implement risk reduction strategies and deliver essential responses. The empirical and semi-empirical model-based soil moisture inversion approach developed in the past are either sensor or region specific, vegetation type specific or have limited validity range, and have limited scope to explain physical scattering processes. Hence, there is need for more robust, physical polarimetric radar backscatter model-based retrieval methods, which are sensor and location independent and have wide range of validity over soil properties. In the present study, Integral Equation Model (IEM) and Vector Radiative Transfer (VRT) model were used to simulate averaged backscatter coefficients in various soil moisture (dry, moist and wet soil), soil roughness (smooth to very rough) and crop conditions (low to high vegetation water contents) over selected regions of Gujarat state of India and the results were compared with multi-temporal Radar Imaging Satellite-1 (RISAT-1) C-band Synthetic Aperture Radar (SAR) data in σ°HH and σ°HV polarizations, in sync with on field measured soil and crop conditions. High correlations were observed between RISAT-1 HH and HV with model simulated σ°HH & σ°HV based on field measured soil with the coefficient of determination R2 varying from 0.84 to 0.77 and RMSE varying from 0.94 dB to 2.1 dB for bare soil. Whereas in case of winter wheat crop, coefficient of determination R2 varying from 0.84 to 0.79 and RMSE varying from 0.87 dB to 1.34 dB, corresponding to with vegetation water content values up to 3.4 kg/m2. Artificial Neural Network (ANN) methods were adopted for model-based soil moisture inversion. The training datasets for the NNs were obtained from theoretical forward-scattering models with controlled parameters, thus allowing the control of wide range of soil and crop parameters with which the network was trained. A preliminary performance analysis showed good results with estimation of soil moisture with RMSE better than 6%.

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.

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.

Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

2011-01-01

The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

A Comparison of Land Surface Model Soil Hydraulic Properties Estimated by Inverse Modeling and Pedotransfer Functions

NASA Technical Reports Server (NTRS)

Gutmann, Ethan D.; Small, Eric E.

2007-01-01

Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.

Modeling preferential water flow and solute transport in unsaturated soil using the active region model

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

Sheng, F.; Wang, K.; Zhang, R.

2009-03-15

Preferential flow and solute transport are common processes in the unsaturated soil, in which distributions of soil water content and solute concentrations are often characterized as fractal patterns. An active region model (ARM) was recently proposed to describe the preferential flow and transport patterns. In this study, ARM governing equations were derived to model the preferential soil water flow and solute transport processes. To evaluate the ARM equations, dye infiltration experiments were conducted, in which distributions of soil water content and Cl{sup -} concentration were measured. Predicted results using the ARM and the mobile-immobile region model (MIM) were compared withmore » the measured distributions of soil water content and Cl{sup -} concentration. Although both the ARM and the MIM are two-region models, they are fundamental different in terms of treatments of the flow region. The models were evaluated based on the modeling efficiency (ME). The MIM provided relatively poor prediction results of the preferential flow and transport with negative ME values or positive ME values less than 0.4. On the contrary, predicted distributions of soil water content and Cl- concentration using the ARM agreed reasonably well with the experimental data with ME values higher than 0.8. The results indicated that the ARM successfully captured the macroscopic behavior of preferential flow and solute transport in the unsaturated soil.« less

Interpretation and estimation for dynamic mobility of chlorpyrifos in soils containing different organic matters.

PubMed

Hwang, Jeong-In; Lee, Sung-Eun; Kim, Jang-Eok

2015-12-01

The adsorption and removal behaviors of the organophosphate insecticide chlorpyrifos in two soils (AS and GW soils) with different organic matter contents were investigated to predict the dynamic residues in the soil environment. The adsorption test showed that the chlorpyrifos adsorptive power for the AS soil containing high organic matter content was greater than that for the GW soil. The extent of the time-dependent removal of chlorpyrifos in the tested soils was not significantly different except at 90 days after the treatment. The availability of a chemical-specific residue model developed in this study was statistically assessed to estimate the chlorpyrifos residue in soil solutions that could be absorbed into plants. The values modeled using the soil experimental data were satisfactory, having a mean deviation of 32% from the measured data. The correlation between the modeled and measured data was acceptable, with mean coefficients of correlation (R(2)) of 0.89. Furthermore, the average of the residual error was low at 0.43, which corresponded to a mean factor of -1.9. The developed model could be used as a critical tool to predict the subsequent plant uptake of chlorpyrifos.

NASA Soil Moisture Data Products and Their Incorporation in DREAM

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holland, Donald; Henderson, Vaneshette

2005-01-01

NASA provides soil moisture data products that include observations from the Advanced Microwave Scanning Radiometer on the Earth Observing System Aqua satellite, field measurements from the Soil Moisture Experiment campaigns, and model predictions from the Land Information System and the Goddard Earth Observing System Data Assimilation System. Incorporation of the NASA soil moisture products in the Dust Regional Atmospheric Model is possible through use of the satellite observations of soil moisture to set initial conditions for the dust simulations. An additional comparison of satellite soil moisture observations with mesoscale atmospheric dynamics modeling is recommended. Such a comparison would validate the use of NASA soil moisture data in applications and support acceptance of satellite soil moisture data assimilation in weather and climate modeling.

Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

NASA Technical Reports Server (NTRS)

Potter, Christopher; Malhi, Yadvinder

2004-01-01

Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

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.

Soil nitric oxide emissions from terrestrial ecosystems in China: a synthesis of modeling and measurements

PubMed Central

Huang, Yong; Li, Dejun

2014-01-01

Soils are among the major sources of atmospheric nitric oxide (NO), which play a crucial role in atmospheric chemistry. Here we systematically synthesized the modeling studies and field measurements and presented a novel soil NO emission inventory of terrestrial ecosystems in China. The previously modeled inventories ranged from 480 to 1375 and from 242.8 to 550 Gg N yr−1 for all lands and croplands, respectively. Nevertheless, all the previous modeling studies were conducted based on very few measurements from China. According to the current synthesis of field measurements, most soil NO emission measurements were conducted at croplands, while the measurements were only conducted at two sites for forest and grassland. The median NO flux was 3.2 ng N m−2 s−1 with a fertilizer induced emission factor (FIE) of 0.04% for rice fields, and was 7.1 ng N m−2 s−1 with an FIE of 0.67% for uplands. A novel NO emission inventory of 1226.33 (ranging from 588.24 to 2132.05) Gg N yr−1 was estimated for China's terrestrial ecosystems, which was about 18% of anthropogenic emissions. More field measurements should be conducted to cover more biomes and obtain more representative data in order to well constrain soil NO emission inventory of China. PMID:25490942

Anaerobic soil volume as a major controlling factor for soil denitrification and respiration

NASA Astrophysics Data System (ADS)

Reent Köster, Jan; Tong, Bingxin; Grosz, Balázs; Burkart, Stefan; Ruoss, Nicolas; Well, Reinhard

2017-04-01

Gas diffusion in soil is a key variable to control denitrification and its N2O to N2 product ratio since it affects two major proximal denitrification factors, i.e. the concentrations of O2 and of N2O. Gas diffusivity is governed by the structure and the state of water saturation of the pore system. At a given O2 consumption rate decreasing diffusivity causes an enhanced anaerobic soil volume where denitrification can occur. Gas diffusivity is generally quantified as bulk diffusion coefficients that represent the lineal diffusive gas flux through the soil matrix. However, the spatial distribution of respiratory O2 consumption and denitrification - and hence the local concentration of O2 and N2O - is highly non-homogeneous. Knowledge of the anaerobic soil volume fraction (ansvf) has been proposed as a key control on denitrification, and has subsequently been used in many denitrification models. The ansvf has previously been quantified by direct measurement of O2 distribution in individual soil aggregates using microsensors. The measured ansvf corresponded to modelled values based on measured aggregate diffusivity and respiration, but was not yet correlated with measured denitrification rates. In the present ongoing study, we are incubating soil cores amended with nitrate and organic litter in an automated mesocosm system under aerobic as well as anaerobic conditions. An N2 depleted incubation atmosphere and the 15N labeled soil nitrate pool facilitate quantification of the N2 production in the soil by IRMS, and fluxes of N2O and CO2 are monitored via gas chromatography. The ansvf and the measured denitrification and respiration rates will then be used for model validation. During the session we will present first results of this study.

Evaluation of dielectric mixing models for microwave soil moisture retrieval using data from the Combined Radar/Radiometer (ComRAD) ground-based SMAP simulator

USDA-ARS?s Scientific Manuscript database

Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

Simulating Soil Organic Carbon Stock Changes in Agro-ecosystems using CQESTR, DayCent, and IPCC Tier 1 Methods

USDA-ARS?s Scientific Manuscript database

Models are often used to quantify how land use change and management impact soil organic carbon (SOC) stocks because it is often not feasible to use direct measuring methods. Because models are simplifications of reality, it is essential to compare model outputs with measured values to evaluate mode...

Modeling global annual N2O and NO emissions from fertilized fields

NASA Astrophysics Data System (ADS)

Bouwman, A. F.; Boumans, L. J. M.; Batjes, N. H.

2002-12-01

Information from 846 N2O emission measurements in agricultural fields and 99 measurements for NO emissions was used to describe the influence of various factors regulating emissions from mineral soils in models for calculating global N2O and NO emissions. Only those factors having a significant influence on N2O and NO emissions were included in the models. For N2O these were (1) environmental factors (climate, soil organic C content, soil texture, drainage and soil pH); (2) management-related factors (N application rate per fertilizer type, type of crop, with major differences between grass, legumes and other annual crops); and (3) factors related to the measurements (length of measurement period and frequency of measurements). The most important controls on NO emission include the N application rate per fertilizer type, soil organic-C content and soil drainage. Calculated global annual N2O-N and NO-N emissions from fertilized agricultural fields amount to 2.8 and 1.6 Mtonne, respectively. The global mean fertilizer-induced emissions for N2O and NO amount to 0.9% and 0.7%, respectively, of the N applied. These overall results account for the spatial variability of the main N2O and NO emission controls on the landscape scale.

Survey of in-situ and remote sensing methods for soil moisture determination

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Jackson, T. J.; Mckim, H. L.

1981-01-01

General methods for determining the moisture content in the surface layers of the soil based on in situ or point measurements, soil water models and remote sensing observations are surveyed. In situ methods described include gravimetric techniques, nuclear techniques based on neutron scattering or gamma-ray attenuation, electromagnetic techniques, tensiometric techniques and hygrometric techniques. Soil water models based on column mass balance treat soil moisture contents as a result of meteorological inputs (precipitation, runoff, subsurface flow) and demands (evaporation, transpiration, percolation). The remote sensing approaches are based on measurements of the diurnal range of surface temperature and the crop canopy temperature in the thermal infrared, measurements of the radar backscattering coefficient in the microwave region, and measurements of microwave emission or brightness temperature. Advantages and disadvantages of the various methods are pointed out, and it is concluded that a successful monitoring system must incorporate all of the approaches considered.

Estimation of bare soil evaporation using multifrequency airborne SAR

NASA Technical Reports Server (NTRS)

Soares, Joao V.; Shi, Jiancheng; Van Zyl, Jakob; Engman, E. T.

1992-01-01

It is shown that for homogeneous areas soil moisture can be derived from synthetic aperture radar (SAR) measurements, so that the use of microwave remote sensing can given realistic estimates of energy fluxes if coupled to a simple two-layer model repesenting the soil. The model simulates volumetric water content (Wg) using classical meterological data, provided that some of the soil thermal and hydraulic properties are known. Only four parameters are necessary: mean water content, thermal conductivity and diffusitivity, and soil resistance to evaporation. They may be derived if a minimal number of measured values of Wg and surface layer temperature (Tg) are available together with independent measurements of energy flux to compare with the estimated values. The estimated evaporation is shown to be realistic and in good agreement with drying stage theory in which the transfer of water in the soil is in vapor form.

Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem

Treesearch

J.A. O' Donnell; J.W. Harden; A.D. McGuire; V.E. Romanovsky

2011-01-01

In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil...

Evaluation of Crop-Water Consumption Simulation to Support Agricultural Water Resource Management using Satellite-based Water Cycle Observations

NASA Astrophysics Data System (ADS)

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

2016-12-01

Water scarcity is one of the main factors limiting agricultural development. Numerical models integrated with remote sensing datasets are increasingly being used operationally as inputs for crop water balance models and agricultural forecasting due to increasing availability of high temporal and spatial resolution datasets. However, the model accuracy in simulating soil water content is affected by the accuracy of the soil hydraulic parameters used in the model, which are used in the governing equations. However, soil databases are known to have a high uncertainty across scales. Also, for agricultural sites, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally. The present study utilizes effective soil hydraulic parameters obtained using a 1-km downscaled microwave remote sensing soil moisture product based on the NASA Advanced Microwave Scanning Radiometer (AMSR-E) using the genetic algorithm inverse method within the Catchment Land Surface Model (CLSM). Secondly, to provide realistic irrigation estimates for agricultural sites, an irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches the threshold, 50% with respect to the maximum available water capacity obtained from the effective soil hydraulic parameters. An additional important criterion utilized is the estimation of crop water consumption based on dynamic root growth and uptake in root zone layer. Model performance is evaluated using MODIS land surface temperature (LST) product. The soil moisture estimates for the root zone are also validated with the in situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005).

Advances in soil erosion research: processes, measurement, and modeling

USDA-ARS?s Scientific Manuscript database

Soil erosion by the environmental agents of water and wind is a continuing global menace that threatens the agricultural base that sustains our civilization. Members of ASABE have been at the forefront of research to understand erosion processes, measure erosion and related processes, and model very...

Eco-hydrological Responses to Soil and Water Conservation in the Jinghe River Basin

NASA Astrophysics Data System (ADS)

Peng, H.; Jia, Y.; Qiu, Y.

2011-12-01

The Jinghe River Basin is one of the most serious soil erosion areas in the Loess Plateau. Many measures of soil and water conservation were applied in the basin. Terrestrial ecosystem model BIOME-BGC and distributed hydrological model WEP-L were used to build eco-hydrological model and verified by field observation and literature values. The model was applied in the Jinghe River Basin to analyze eco-hydrological responses under the scenarios of vegetation type change due to soil and water conservation polices. Four scenarios were set under the measures of conversion of cropland to forest, forestation on bare land, forestation on slope wasteland and planting grass on bare land. Analysis results show that the soil and water conservation has significant effects on runoff and the carbon cycle in the Jinghe River Basin: the average annual runoff would decrease and the average annual NPP and carbon storage would increase. Key words: soil and water conservation; conversion of cropland to forest; eco-hydrology response; the Jinghe River Basin

Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain.

PubMed

Fernández, Cristina; Vega, José A

2018-05-04

Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparing the performance of coupled soil-vegetation-atmosphere models at two contrasting field sites in South-West Germany

NASA Astrophysics Data System (ADS)

Gayler, S.; Wöhling, T.; Priesack, E.; Wizemann, H.-D.; Wulfmeyer, V.; Ingwersen, J.; Streck, T.

2012-04-01

The soil moisture, the energy balance at the land surface and the state of the lower atmosphere are closely linked by complex feedback processes. The vegetation acts as the interface between soil and atmosphere and plays an important role in this coupled system. Consequently, a consistent description of the fluxes of water, energy and carbon is a prerequisite for analyzing many problems in soil-, plant- and atmospheric research. To better understand the complex interplay of the involved processes, many numerical and physics-based soil-plant-atmosphere simulation models were developed during the last decades. As these models have been developed for different purposes, the degree of complexity in describing individual feedback processes can vary considerably. In models designed to predict soil moisture, for example, plants are often sufficiently represented by a simple sink term. If these models are calibrated, sometimes only one state variable and the corresponding calibration data type is used, e.g. soil water contents or pressure heads. In this case, vegetation properties and feedbacks between soil moisture, plant growth and stomatal conductivity are neglected to a large extent. Some crop models, in turn, pay little attention to modeling soil water transport. In a coupled soil-vegetation-atmosphere model, however, the interface between soil and atmosphere has to be consistent in all directions. As different data types such as soil moisture, leaf area development and evapotranspiration may contain contrasting information about the system under consideration, the fitting of such a model to a single data type may result in a poor agreement to another data type. The trade-off between the fittings to different data types can thereby be caused by structural inadequacies in the model or by errors in input and calibration data. In our study, we compare the Community Land Model CLM (version 3.5, offline mode) with different agricultural crop models to analyze the adequacy of their structural complexity on two winter wheat research fields under different climate in South-West Germany. We investigate the ability of the models to simultaneously fit measured soil water contents, leaf area development and actual evapotranspiration rates from eddy-covariance measurements. The calibration of the models is performed in a multi-criteria context using three objective functions, which describe the discrepancy between measurements and simulations of the three data types. We use the AMALGAM evolutionary search algorithm to simultaneously estimate the most important plant and soil hydraulic parameters. The results show that the trade-off in fitting soil moisture, leaf area development and evapotranspiration can be quite large for those models that represent plant processes by simple concepts. However, these trade-offs are smaller for the more mechanistic plant growth models, so that it can be expected that these optimized mechanistic models will provide the basis for improved simulations of land-surface-atmosphere feedback processes.

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

The WEPP Model Application in a Small Watershed in the Loess Plateau

PubMed Central

Han, Fengpeng; Ren, Lulu; Zhang, Xingchang; Li, Zhanbin

2016-01-01

In the Loess Plateau, soil erosion has not only caused serious ecological and environmental problems but has also impacted downstream areas. Therefore, a model is needed to guide the comprehensive control of soil erosion. In this study, we introduced the WEPP model to simulate soil erosion both at the slope and watershed scales. Our analyses showed that: the simulated values at the slope scale were very close to the measured. However, both the runoff and soil erosion simulated values at the watershed scale were higher than the measured. At the slope scale, under different coverage, the simulated erosion was slightly higher than the measured. When the coverage is 40%, the simulated results of both runoff and erosion are the best. At the watershed scale, the actual annual runoff of the Liudaogou watershed is 83m3; sediment content is 0.097 t/m3, annual erosion sediment 8.057t and erosion intensity 0.288 t ha-1 yr-1. Both the simulated values of soil erosion and runoff are higher than the measured, especially the runoff. But the simulated erosion trend is relatively accurate after the farmland is returned to grassland. We concluded that the WEPP model can be used to establish a reasonable vegetation restoration model and guide the vegetation restoration of the Loess Plateau. PMID:26963704

Measuring and understanding soil water repellency through novel interdisciplinary approaches

NASA Astrophysics Data System (ADS)

Balshaw, Helen; Douglas, Peter; Doerr, Stefan; Davies, Matthew

2017-04-01

Food security and production is one of the key global issues faced by society. It has become evermore essential to work the land efficiently, through better soil management and agronomy whilst protecting the environment from air and water pollution. The failure of soil to absorb water - soil water repellency - can lead to major environmental problems such as increased overland flow and soil erosion, poor uptake of agricultural chemicals and increased risk of groundwater pollution due to the rapid transfer of contaminants and nutrient leaching through uneven wetting and preferential flow pathways. Understanding the causes of soil hydrophobicity is essential for the development of effective methods for its amelioration, supporting environmental stability and food security. Organic compounds deposited on soil mineral or aggregate surfaces have long been recognised as a major factor in causing soil water repellency. It is widely accepted that the main groups of compounds responsible are long-chain acids, alkanes and other organic compounds with hydrophobic properties. However, when reapplied to sands and soils, the degree of water repellency induced by these compounds and mixtures varied widely with compound type, amount and mixture, in a seemingly unpredictable way. Our research to date involves two new approaches for studying soil wetting. 1) We challenge the theoretical basis of current ideas on the measured water/soil contact angle measurements. Much past and current discussion involves Wenzel and Cassie-Baxter models to explain anomalously high contact angles for organics on soils, however here we propose that these anomalously high measured contact angles are a consequence of the measurement of a water drop on an irregular non-planar surface rather than the thermodynamic factors of the Cassie-Baxter and Wenzel models. In our analysis we have successfully used a much simpler geometric approach for non-flat surfaces such as soil. 2) Fluorescent and phosphorescent probes are widely used in chemistry and biochemistry due to their sensitive response to their physical and chemical environment, such as polarity, and viscosity. However to date they have not been used to study soil water repellency. Here in collaboration with photochemistry groups in Swansea University and the University of Coimbra, we are examining the use of fluorescent probes to measure the polarity and viscosity of the soil/organic interface for both model and natural soils and how this changes in real time during wetting.

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Preliminary assessment of soil moisture over vegetation

NASA Technical Reports Server (NTRS)

Carlson, T. N.

1986-01-01

Modeling of surface energy fluxes was combined with in-situ measurement of surface parameters, specifically the surface sensible heat flux and the substrate soil moisture. A vegetation component was incorporated in the atmospheric/substrate model and subsequently showed that fluxes over vegetation can be very much different than those over bare soil for a given surface-air temperature difference. The temperature signatures measured by a satellite or airborne radiometer should be interpreted in conjunction with surface measurements of modeled parameters. Paradoxically, analyses of the large-scale distribution of soil moisture availability shows that there is a very high correlation between antecedent precipitation and inferred surface moisture availability, even when no specific vegetation parameterization is used in the boundary layer model. Preparatory work was begun in streamlining the present boundary layer model, developing better algorithms for relating surface temperatures to substrate moisture, preparing for participation in the French HAPEX experiment, and analyzing aircraft microwave and radiometric surface temperature data for the 1983 French Beauce experiments.

Lessons Learned from 2 Decades of Modelling Forest Dead Organic Matter and Soil Carbon at the National Scale

NASA Astrophysics Data System (ADS)

Shaw, C.; Kurz, W. A.; Metsaranta, J.; Bona, K. A.; Hararuk, O.; Smyth, C.

2017-12-01

The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a forest carbon budget model that operates on individual stands. It is applied from regional to national-scales in Canada for national and international reporting of GHG emissions and removals and in support of analyses of forest sector mitigation options and other scientific and policy questions. This presentation will review the history and continuous improvement process of representations of dead organic matter (DOM) and soil carbon modelling. Early model versions in which dead organic matter (DOM) pools only included litter, downed deadwood and soil, to the current version where these pools are estimated separately to better compare model estimates against field measurements, or new pools have been added. Uncertainty analyses consistently point at soil C pools as large sources of uncertainty. With the new ground plot measurements from the National Forest Inventory, and with a newly compiled forest soil carbon database, we have recently completed a model data assimilation exercise that helped reduce parameter uncertainties. Lessons learned from the continuous improvement process will be summarised and we will discuss how model modification have led to improved representation of DOM and soil carbon dynamics. We conclude by suggesting future research priorities that can advance DOM and soil carbon modelling in Canadian forest ecosystems.

Estimates of potential childhood lead exposure from contaminated soil using the US EPA IEUBK Model in Sydney, Australia.

PubMed

Laidlaw, Mark A S; Mohmmad, Shaike M; Gulson, Brian L; Taylor, Mark P; Kristensen, Louise J; Birch, Gavin

2017-07-01

Surface soils in portions of the Sydney (New South Wales, Australia) urban area are contaminated with lead (Pb) primarily from past use of Pb in gasoline, the deterioration of exterior lead-based paints, and industrial activities. Surface soil samples (n=341) were collected from a depth of 0-2.5cm at a density of approximately one sample per square kilometre within the Sydney estuary catchment and analysed for lead. The bioaccessibility of soil Pb was analysed in 18 samples. The blood lead level (BLL) of a hypothetical 24 month old child was predicted at soil sampling sites in residential and open land use using the United States Environmental Protection Agency (US EPA) Integrated Exposure Uptake and Biokinetic (IEUBK) model. Other environmental exposures used the Australian National Environmental Protection Measure (NEPM) default values. The IEUBK model predicted a geometric mean BLL of 2.0±2.1µg/dL using measured soil lead bioavailability measurements (bioavailability =34%) and 2.4±2.8µg/dL using the Australian NEPM default assumption (bioavailability =50%). Assuming children were present and residing at the sampling locations, the IEUBK model incorporating soil Pb bioavailability predicted that 5.6% of the children at the sampling locations could potentially have BLLs exceeding 5µg/dL and 2.1% potentially could have BLLs exceeding 10µg/dL. These estimations are consistent with BLLs previously measured in children in Sydney. Copyright © 2017 Elsevier Inc. All rights reserved.

Inversion algorithms for the microwave remote sensing of soil moisture. Experiments with swept frequency microwaves

NASA Technical Reports Server (NTRS)

Hancock, G. D.; Waite, W. P.

1984-01-01

Two experiments were performed employing swept frequency microwaves for the purpose of investigating the reflectivity from soil volumes containing both discontinuous and continuous changes in subsurface soil moisture content. Discontinuous moisture profiles were artificially created in the laboratory while continuous moisture profiles were induced into the soil of test plots by the environment of an agricultural field. The reflectivity for both the laboratory and field experiments was measured using bi-static reflectometers operated over the frequency ranges of 1.0 to 2.0 GHz and 4.0 to 8.0 GHz. Reflectivity models that considered the discontinuous and continuous moisture profiles within the soil volume were developed and compared with the results of the experiments. This comparison shows good agreement between the smooth surface models and the measurements. In particular the comparison of the smooth surface multi-layer model for continuous moisture profiles and the yield experiment measurements points out the sensitivity of the specular component of the scattered electromagnetic energy to the movement of moisture in the soil.

Variability of Total Below Ground Carbon Allocation amongst Common Agricultural Land Management Practices: a Case Study

NASA Astrophysics Data System (ADS)

Wacha, K. M.; Papanicolaou, T.; Wilson, C. G.

2010-12-01

Field measurements and numerical models are currently being used to estimate quantities of Total Belowground Carbon Allocation (TBCA) for three representative land uses, viz. corn, soybeans, and prairie bromegrass for CRP (Conservation Reserve Program) of an agricultural Iowa sub-watershed, located within the Clear Creek Watershed (CCW). Since it is difficult to measure TBCA directly, a mass balance approach has been implemented to estimate TBCA as follows: TBCA = FS + FE+ Δ(CS + CR + CL) - FA , where the term Fs denotes soil respiration; FE is the carbon content of the eroded/deposited soil; ΔCS, ΔCR, ΔCL denote the changes in carbon content of the mineral soil, plant roots, and litter layer, respectively; and FA is the above ground litter fall of dead plant material to the soil. The terms are hypothesized to have a huge impact on TBCA within agricultural settings due to intensive tillage practices, water-driven soil erosion/deposition, and high usage of fertilizer. To test our hypothesis, field measurements are being performed at the plot scale, replicating common agricultural land management practices. Soil respiration (FS) is being measured with an EGM-4 CO2 Gas Analyzer and SRC-1 Soil Respiration Chamber (PP Systems), soil moisture and temperature are recorded in the top 20 cm for each respective soil respiration measurement, and litter fall rates (FA) are acquired by collecting the residue in a calibrated pan. The change in carbon content of the soil (ΔCS), roots (ΔCR) and litter layer (ΔCL) are being analyzed by collecting soil samples throughout the life cycle of the plant. To determine the term FE for the three representative land management practices, a funnel collection system located at the plot outlet was used for collecting the eroded material after natural rainfall events. Field measurements of TBCA at the plot scale via the mass balance approach are used to calibrate the numerical agronomic process model DAYCENT, which simulates the daily fluxes of carbon (CS) and soil respiration (FS) and incorporates a plant-growth model that allows the determination of the terms FA, CR, and CL. Once calibrated, DAYCENT can be used in conjunction with the Watershed Erosion Prediction Project (WEPP) model, which calculates erosion/deposition rates, to provide estimates of TBCA at a larger global scale.

Simulation of water flow and nitrogen transport for a Bulgarian experimental plot using SWAP and ANIMO models.

PubMed

Marinov, Dimitar; Querner, Erik; Roelsma, Jan

2005-04-01

Unsaturated zone models are useful tools in predicting effects of measures and can be used to optimise agricultural practice aiming to minimise the impact on the environment. However, current soil models have a varying degree of abstraction level referring to simulated processes in time and space. In the framework of an EU funded project the SWAP (Soil-Water-Atmosphere-Plant) and ANIMO (Agricultural-Nutrient-Model) models were tested for an experimental arable plot in Bulgaria. SWAP was used to simulate water flow in the soil while ANIMO describes nitrogen movement and transformations. The objectives of this study are: (i) to show results of the combined application of water and nitrogen dynamics of originally Dutch models SWAP and ANIMO for specific Bulgarian soil and hydrological conditions; (ii) to calibrate and evaluate SWAP and ANIMO models by comparing numerical results with field measurements collected for an arable field in western Bulgaria and (iii) to analyse possible contamination of groundwater due to agricultural practice in the considered region. Further a short description of the experimental plot, as well as information about parameters of the investigated soil profiles, is provided. The obtained SWAP results evidenced that the model gives sufficient adaptation for soil water dynamics. The simulations of ANIMO for nitrogen cycle show greater divergence with observations but are satisfactory precise for the purposes of assessing land use impact on groundwater quality. In general, differences between model results and field measurements do not exceed 10-15%. For the experimental plot predictions indicate nitrate-N concentrations less then 5 mg/l in deeper soil compartments and low downward annual flux containing 0.133 kg N/ha. These results indicate that there is no serious pollution of the shallow groundwater table by nitrogen resulting from land use and agricultural activities.

Constitutive Soil Properties for Cuddeback Lake, California and Carson Sink, Nevada

NASA Technical Reports Server (NTRS)

Thomas, Michael A.; Chitty, Daniel E.; Gildea, Martin L.; T'Kindt, Casey M.

2008-01-01

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle. This report provides constitutive material modeling properties for four soil models from two dry lakebeds in the western United States. The four soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples from the lakebeds. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LS-DYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The four soil models are intended to be specific only to the two lakebeds discussed in the report. The Cuddeback A and B models represent the softest and hardest soils at Cuddeback Lake. The Carson Sink Wet and Dry models represent different seasonal conditions. It is possible to approximate other clay soils with these models, but the results would be unverified without geotechnical tests to confirm similar soil behavior.

Validation of the Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval in an Arctic tundra environment

NASA Astrophysics Data System (ADS)

Wrona, Elizabeth; Rowlandson, Tracy L.; Nambiar, Manoj; Berg, Aaron A.; Colliander, Andreas; Marsh, Philip

2017-05-01

This study examines the Soil Moisture Active Passive soil moisture product on the Equal Area Scalable Earth-2 (EASE-2) 36 km Global cylindrical and North Polar azimuthal grids relative to two in situ soil moisture monitoring networks that were installed in 2015 and 2016. Results indicate that there is no relationship between the Soil Moisture Active Passive (SMAP) Level-2 passive soil moisture product and the upscaled in situ measurements. Additionally, there is very low correlation between modeled brightness temperature using the Community Microwave Emission Model and the Level-1 C SMAP brightness temperature interpolated to the EASE-2 Global grid; however, there is a much stronger relationship to the brightness temperature measurements interpolated to the North Polar grid, suggesting that the soil moisture product could be improved with interpolation on the North Polar grid.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

NASA Technical Reports Server (NTRS)

Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

1998-01-01

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

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.

The advanced qualtiy control techniques planned for the Internation Soil Moisture Network

NASA Astrophysics Data System (ADS)

Xaver, A.; Gruber, A.; Hegiova, A.; Sanchis-Dufau, A. D.; Dorigo, W. A.

2012-04-01

In situ soil moisture observations are essential to evaluate and calibrate modeled and remotely sensed soil moisture products. Although a number of meteorological networks and field campaigns measuring soil moisture exist on a global and long-term scale, their observations are not easily accessible and lack standardization of both technique and protocol. Thus, handling and especially comparing these datasets with satellite products or land surface models is a demanding issue. To overcome these limitations the International Soil Moisture Network (ISMN; http://www.ipf.tuwien.ac.at/insitu/) has been initiated to act as a centralized data hosting facility. One advantage of the ISMN is that users are able to access the harmonized datasets easily through a web portal. Another advantage is the fully automated processing chain including the data harmonization in terms of units and sampling interval, but even more important is the advanced quality control system each measurement has to run through. The quality of in situ soil moisture measurements is crucial for the validation of satellite- and model-based soil moisture retrievals; therefore a sophisticated quality control system was developed. After a check for plausibility and geophysical limits a quality flag is added to each measurement. An enhanced flagging mechanism was recently defined using a spectrum based approach to detect spurious spikes, jumps and plateaus. The International Soil Moisture Network has already evolved to one of the most important distribution platforms for in situ soil moisture observations and is still growing. Currently, data from 27 networks in total covering more than 800 stations in Europe, North America, Australia, Asia and Africa is hosted by the ISMN. Available datasets also include historical datasets as well as near real-time measurements. The improved quality control system will provide important information for satellite-based as well as land surface model-based validation studies.

Developing a New Thermophysical Model for Lunar Regolith Soil at Low Temperatures

NASA Astrophysics Data System (ADS)

Woods-Robinson, R.; Siegler, M. A.; Paige, D. A.

2016-12-01

The thermophysical properties of the lunar regolith soil have been thoroughly investigated within the temperature range of 100 - 400 K. Extensive laboratory measurements of temperature-dependent thermal conductivity and specific heat have been performed on lunar samples collected from the Apollo and Luna missions. However, recent thermal emission measurements from the Lunar Reconnaissance Orbiter Diviner Lunar Radiometer Experiment have revealed temperatures near the poles as low 20 K, far below where existing thermophysical models begin to break down. In the absence of comprehensive laboratory measurements of lunar soil thermal properties at these low temperatures (20 - 100 K), we investigate solid state theory and lunar simulant materials to derive a physically-based theoretical model of specific heat and thermal conductivity in lunar soils in the full range 20 - 400 K. The primary distinctions between this model and its predecessors are: The focus on soil bulk density as a master variable The temperature dependence of the solid conduction component of thermal conductivity at low temperatures, and The concept that the composition and modal petrology of grains - both amorphous and crystalline components - could significantly influence thermal properties of the bulk soil. The simplest version of this model, which assumes that the soil behaves predominantly as a homogeneous particulate material composed of amorphous grains, shows that at low temperatures (20 - 100 K), specific heat is likely higher than expected from current models ( 0.027 J/gK at 20 K) and that thermal conductivity is almost an order of magnitude lower than has generally been assumed in the literature.Any higher-order approximation is difficult at this stage; the thermal conductivity at low temperature could vary drastically depending on the constituent grain materials, their degree of crystallinity, and contributions from phonon scattering modes, among other factors. We use a one-dimensional thermal model to illustrate the effects of our model on diurnal surface temperature variations in permanently shadowed regions on the moon. We aim to lay the theoretical foundation for a new approach to model thermal properties of regolith materials, and to justify the importance of new laboratory measurements of lunar soil below 100 K.

Using NEON Data to Test and Refine Conceptual and Numerical Models of Soil Biogeochemical and Microbial Dynamics

NASA Astrophysics Data System (ADS)

Weintraub, S. R.; Stanish, L.; Ayers, E.

2017-12-01

Recent conceptual and numerical models have proposed new mechanisms that underpin key biogeochemical phenomena, including soil organic matter storage and ecosystem response to nitrogen deposition. These models seek to explicitly capture the ecological links among biota, especially microbes, and their physical and chemical environment to represent belowground pools and fluxes and how they respond to perturbation. While these models put forth exciting new concepts, their broad predictive abilities are unclear as some have been developed and tested against only small or regional datasets. The National Ecological Observatory Network (NEON) presents new opportunities to test and validate these models with multi-site data that span wide climatic, edaphic, and ecological gradients. NEON is measuring surface soil biogeochemical pools and fluxes along with diversity, abundance, and functional potential of soil microbiota at 47 sites distributed across the United States. This includes co-located measurements of soil carbon and nitrogen concentrations and stable isotopes, net nitrogen mineralization and nitrification rates, soil moisture, pH, microbial biomass, and community composition via 16S and ITS rRNA sequencing and shotgun metagenomic analyses. Early NEON data demonstrates that these wide edaphic and climatic gradients are related to changes in microbial community structure and functional potential, as well as element pools and process rates. Going forward, NEON's suite of standardized soil data has the potential to advance our understanding of soil communities and processes by allowing us to test the predictions of new soil biogeochemical frameworks and models. Here, we highlight several recently developed models that are ripe for this kind of data validation, and discuss key insights that may result. Further, we explore synergies with other networks, such as (i)LTER and (i)CZO, which may increase our ability to advance the frontiers of soil biogeochemical modeling.

A new approach to predict soil temperature under vegetated surfaces.

PubMed

Dolschak, Klaus; Gartner, Karl; Berger, Torsten W

2015-12-01

In this article, the setup and the application of an empirical model, based on Newton's law of cooling, capable to predict daily mean soil temperature ( T soil ) under vegetated surfaces, is described. The only input variable, necessary to run the model, is a time series of daily mean air temperature. The simulator employs 9 empirical parameters, which were estimated by inverse modeling. The model, which primarily addresses forested sites, incorporates the effect of snow cover and soil freezing on soil temperature. The model was applied to several temperate forest sites, managing the split between Central Europe (Austria) and the United States (Harvard Forest, Massachusetts; Hubbard Brook, New Hampshire), aiming to cover a broad range of site characteristics. Investigated stands differ fundamentally in stand composition, elevation, exposition, annual mean temperature, precipitation regime, as well as in the duration of winter snow cover. At last, to explore the limits of the formulation, the simulator was applied to non-forest sites (Illinois), where soil temperature was recorded under short cut grass. The model was parameterized, specifically to site and measurement depth. After calibration of the model, an evaluation was performed, using ~50 % of the available data. In each case, the simulator was capable to deliver a feasible prediction of soil temperature in the validation time interval. To evaluate the practical suitability of the simulator, the minimum amount of soil temperature point measurements, necessary to yield expedient model performance was determined. In the investigated case 13-20 point observations, uniformly distributed within an 11-year timeframe, have been proven sufficient to yield sound model performance (root mean square error <0.9 °C, Nash-Sutcliffe efficiency >0.97). This makes the model suitable for the application on sites, where the information on soil temperature is discontinuous or scarce.

Hydrologic controls on equilibrium soil depths

NASA Astrophysics Data System (ADS)

Nicótina, L.; Tarboton, D. G.; Tesfa, T. K.; Rinaldo, A.

2011-04-01

This paper deals with modeling the mutual feedbacks between runoff production and geomorphological processes and attributes that lead to patterns of equilibrium soil depth. Our primary goal is an attempt to describe spatial patterns of soil depth resulting from long-term interactions between hydrologic forcings and soil production, erosion, and sediment transport processes under the framework of landscape dynamic equilibrium. Another goal is to set the premises for exploiting the role of soil depths in shaping the hydrologic response of a catchment. The relevance of the study stems from the massive improvement in hydrologic predictions for ungauged basins that would be achieved by using directly soil depths derived from geomorphic features remotely measured and objectively manipulated. Hydrological processes are here described by explicitly accounting for local soil depths and detailed catchment topography. Geomorphological processes are described by means of well-studied geomorphic transport laws. The modeling approach is applied to the semiarid Dry Creek Experimental Watershed, located near Boise, Idaho. Modeled soil depths are compared with field data obtained from an extensive survey of the catchment. Our results show the ability of the model to describe properly the mean soil depth and the broad features of the distribution of measured data. However, local comparisons show significant scatter whose origins are discussed.

Electromagnetic Power Attenuation in Soils

DTIC Science & Technology

2005-08-01

based on field measurements of effective conductivity. Previous Soil Property Models Clearly, the problem of predicting EM attenuation in soils...Curtis, J. O. (2001a). “Moisture effects on the dielectric properties of soils,” IEEE Transactions on Geoscience and Remote Sensing 39(1), 125-128... properties of materials by time-domain techniques,” IEEE Transactions on Instrumentation and Measurement IM-19(4), 377-382. Portland Cement Association

Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhao, Hong; Zeng, Yijian; Lv, Shaoning; Su, Zhongbo

2018-06-01

Soil information (e.g., soil texture and porosity) from existing soil datasets over the Tibetan Plateau (TP) is claimed to be inadequate and even inaccurate for determining soil hydraulic properties (SHP) and soil thermal properties (STP), hampering the understanding of the land surface process over TP. As the soil varies across three dominant climate zones (i.e., arid, semi-arid and subhumid) over the TP, the associated SHP and STP are expected to vary correspondingly. To obtain an explicit insight into the soil hydrothermal properties over the TP, in situ and laboratory measurements of over 30 soil property profiles were obtained across the climate zones. Results show that porosity and SHP and STP differ across the climate zones and strongly depend on soil texture. In particular, it is proposed that gravel impact on porosity and SHP and STP are both considered in the arid zone and in deep layers of the semi-arid zone. Parameterization schemes for porosity, SHP and STP are investigated and compared with measurements taken. To determine the SHP, including soil water retention curves (SWRCs) and hydraulic conductivities, the pedotransfer functions (PTFs) developed by Cosby et al. (1984) (for the Clapp-Hornberger model) and the continuous PTFs given by Wösten et al. (1999) (for the Van Genuchten-Mualem model) are recommended. The STP parameterization scheme proposed by Farouki (1981) based on the model of De Vries (1963) performed better across the TP than other schemes. Using the parameterization schemes mentioned above, the uncertainties of five existing regional and global soil datasets and their derived SHP and STP over the TP are quantified through comparison with in situ and laboratory measurements. The measured soil physical properties dataset is available at https://data.4tu.nl/repository/uuid:c712717c-6ac0-47ff-9d58-97f88082ddc0.

Soil Water and Temperature System (SWATS) Instrument Handbook

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

Cook, David R.

2016-04-01

The soil water and temperature system (SWATS) provides vertical profiles of soil temperature, soil-water potential, and soil moisture as a function of depth below the ground surface at hourly intervals. The temperature profiles are measured directly by in situ sensors at the Central Facility and many of the extended facilities of the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site. The soil-water potential and soil moisture profiles are derived from measurements of soil temperature rise in response to small inputs of heat. Atmospheric scientists use the data in climate models tomore » determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil.« less

Assessing the influence of the rhizosphere on soil hydraulic properties using X-ray computed tomography and numerical modelling

PubMed Central

Daly, Keith R.; Mooney, Sacha J.; Bennett, Malcolm J.; Crout, Neil M. J.; Roose, Tiina; Tracy, Saoirse R.

2015-01-01

Understanding the dynamics of water distribution in soil is crucial for enhancing our knowledge of managing soil and water resources. The application of X-ray computed tomography (CT) to the plant and soil sciences is now well established. However, few studies have utilized the technique for visualizing water in soil pore spaces. Here this method is utilized to visualize the water in soil in situ and in three-dimensions at successive reductive matric potentials in bulk and rhizosphere soil. The measurements are combined with numerical modelling to determine the unsaturated hydraulic conductivity, providing a complete picture of the hydraulic properties of the soil. The technique was performed on soil cores that were sampled adjacent to established roots (rhizosphere soil) and from soil that had not been influenced by roots (bulk soil). A water release curve was obtained for the different soil types using measurements of their pore geometries derived from CT imaging and verified using conventional methods, such as pressure plates. The water, soil, and air phases from the images were segmented and quantified using image analysis. The water release characteristics obtained for the contrasting soils showed clear differences in hydraulic properties between rhizosphere and bulk soil, especially in clay soil. The data suggest that soils influenced by roots (rhizosphere soil) are less porous due to increased aggregation when compared with bulk soil. The information and insights obtained on the hydraulic properties of rhizosphere and bulk soil will enhance our understanding of rhizosphere biophysics and improve current water uptake models. PMID:25740922

Relationship between specific surface area and the dry end of the water retention curve for soils with varying clay and organic carbon contents

NASA Astrophysics Data System (ADS)

Resurreccion, Augustus C.; Moldrup, Per; Tuller, Markus; Ferré, T. P. A.; Kawamoto, Ken; Komatsu, Toshiko; de Jonge, Lis Wollesen

2011-06-01

Accurate description of the soil water retention curve (SWRC) at low water contents is important for simulating water dynamics and biochemical vadose zone processes in arid environments. Soil water retention data corresponding to matric potentials of less than -10 MPa, where adsorptive forces dominate over capillary forces, have also been used to estimate soil specific surface area (SA). In the present study, the dry end of the SWRC was measured with a chilled-mirror dew point psychrometer for 41 Danish soils covering a wide range of clay (CL) and organic carbon (OC) contents. The 41 soils were classified into four groups on the basis of the Dexter number (n = CL/OC), and the Tuller-Or (TO) general scaling model describing water film thickness at a given matric potential (<-10 MPa) was evaluated. The SA estimated from the dry end of the SWRC (SA_SWRC) was in good agreement with the SA measured with ethylene glycol monoethyl ether (SA_EGME) only for organic soils with n > 10. A strong correlation between the ratio of the two surface area estimates and the Dexter number was observed and applied as an additional scaling function in the TO model to rescale the soil water retention curve at low water contents. However, the TO model still overestimated water film thickness at potentials approaching ovendry condition (about -800 MPa). The semi-log linear Campbell-Shiozawa-Rossi-Nimmo (CSRN) model showed better fits for all investigated soils from -10 to -800 MPa and yielded high correlations with CL and SA. It is therefore recommended to apply the empirical CSRN model for predicting the dry part of the water retention curve (-10 to -800 MPa) from measured soil texture or surface area. Further research should aim to modify the more physically based TO model to obtain better descriptions of the SWRC in the very dry range (-300 to -800 MPa).

Modeling Central Carbon Metabolic Processes in Soil Microbial Communities: Comparing Measured With Modeled

NASA Astrophysics Data System (ADS)

Dijkstra, P.; Fairbanks, D.; Miller, E.; Salpas, E.; Hagerty, S.

2013-12-01

Understanding the mechanisms regulating C cycling is hindered by our inability to directly observe and measure the biochemical processes of glycolysis, pentose phosphate pathway, and TCA cycle in intact and complex microbial communities. Position-specific 13C labeled metabolic tracer probing is proposed as a new way to study microbial community energy production, biosynthesis, C use efficiency (the proportion of substrate incorporated into microbial biomass), and enables the quantification of C fluxes through the central C metabolic network processes (Dijkstra et al 2011a,b). We determined the 13CO2 production from U-13C, 1-13C, 2-13C, 3-13C, 4-13C, 5-13C, and 6-13C labeled glucose and 1-13C and 2,3-13C pyruvate in parallel incubations in three soils along an elevation gradient. Qualitative and quantitative interpretation of the results indicate a high pentose phosphate pathway activity in soils. Agreement between modeled and measured CO2 production rates for the six C-atoms of 13C-labeled glucose indicate that the metabolic model used is appropriate for soil community processes, but that improvements can be made. These labeling and modeling techniques may improve our ability to analyze the biochemistry and (eco)physiology of intact microbial communities. Dijkstra, P., Blankinship, J.C., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011a. Probing C flux patterns of soil microbial metabolic networks using parallel position-specific tracer labeling. Soil Biology & Biochemistry 43, 126-132. Dijkstra, P., Dalder, J.J., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011b. Modeling soil metabolic processes using isotopologue pairs of position-specific 13C-labeled glucose and pyruvate. Soil Biology & Biochemistry 43, 1848-1857.

Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

NASA Astrophysics Data System (ADS)

Citakoglu, Hatice

2017-10-01

Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

Analysis of the Dielectric constant of saline-alkali soils and the effect on radar backscattering coefficient: a case study of soda alkaline saline soils in Western Jilin Province using RADARSAT-2 data.

PubMed

Li, Yang-yang; Zhao, Kai; Ren, Jian-hua; Ding, Yan-ling; Wu, Li-li

2014-01-01

Soil salinity is a global problem, especially in developing countries, which affects the environment and productivity of agriculture areas. Salt has a significant effect on the complex dielectric constant of wet soil. However, there is no suitable model to describe the variation in the backscattering coefficient due to changes in soil salinity content. The purpose of this paper is to use backscattering models to understand behaviors of the backscattering coefficient in saline soils based on the analysis of its dielectric constant. The effects of moisture and salinity on the dielectric constant by combined Dobson mixing model and seawater dielectric constant model are analyzed, and the backscattering coefficient is then simulated using the AIEM. Simultaneously, laboratory measurements were performed on ground samples. The frequency effect of the laboratory results was not the same as the simulated results. The frequency dependence of the ionic conductivity of an electrolyte solution is influenced by the ion's components. Finally, the simulated backscattering coefficients measured from the dielectric constant with the AIEM were analyzed using the extracted backscattering coefficient from the RADARSAT-2 image. The results show that RADARSAT-2 is potentially able to measure soil salinity; however, the mixed pixel problem needs to be more thoroughly considered.

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

NASA Astrophysics Data System (ADS)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

Quantifying the impacts of land use change on soil organic carbon losses in tropical peatlands

NASA Astrophysics Data System (ADS)

Farmer, J.; Smith, J.; Smith, P.; Matthews, R.

2012-04-01

The challenge of collecting field measurements of soil carbon dioxide (CO2) efflux and soil carbon (C) in tropical peatlands creates an opportunity for the use of SOC models for predicting local and regional impacts of land use and climate change on these soils, offering a way of translating this limited data into tangible results. Previously, no soil C model existed for use in non-steady state sites such as those found on tropical peats- in particular peat swamp forests which accumulate C, and oil palm plantations which are grown for 20-25 years between re-plantings. A simple, user friendly model has been created for use by scientists, policy makers and plantation managers. This model uses only limited inputs to predict the changes to soil C from land use and climate change. The model runs on the assumption that plant inputs can be related to yield, and that this can be used to derive the decomposition of SOM. It uses a simple decomposition response to determine the changes to the soil C. The model can run in a basic form if data is very limited, or a more complex form with modifiers for temperature, pH, salinity and soil moisture if this data is available. Using measured CO2 efflux and soil C values from peat cores, combined with literature values, we demonstrate the efficacy of the model, showing how we have identified and addressed some of the issues related to modelling soil C losses from tropical peat soils under land use change. Key challenges addressed included quantifying the effects of drainage when peat swamp forests are converted to oil palm plantations, and comparing field results between sites because in oil palm plantations the original soil conditions prior to conversion from peat swamp forest were largely unknown.

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.

Microwave soil moisture measurements and analysis

NASA Technical Reports Server (NTRS)

Newton, R. W.; Howell, T. A.; Nieber, J. L.; Vanbavel, C. H. M. (Principal Investigator)

1980-01-01

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

Modelling Furrow Irrigation-Induced Erosion on a Sandy Loam Soil in Samaru, Northern Nigeria

PubMed Central

Dibal, Jibrin M.; Igbadun, H. E.; Ramalan, A. A.; Mudiare, O. J.

2014-01-01

Assessment of soil erosion and sediment yield in furrow irrigation is limited in Samaru-Zaria. Data was collected in 2009 and 2010 and was used to develop a dimensionless model for predicting furrow irrigation-induced erosion (FIIE) using the dimensional analyses approach considering stream size, furrow length, furrow width, soil infiltration rate, hydraulic shear stress, soil erodibility, and time flow of water in the furrows as the building components. One liter of water-sediment samples was collected from the furrows during irrigations from which sediment concentrations and soil erosion per furrow were calculated. Stream sizes Q (2.5, 1.5, and 0.5 l/s), furrow lengths X (90 and 45 m), and furrow widths W (0.75 and 0.9 m) constituted the experimental factors randomized in a split plot design with four replications. Water flow into and out of the furrows was measured using cutthroat flumes. The model produced reasonable predictions relative to field measurements with coefficient of determination R 2 in the neighborhood of 0.8, model prediction efficiency NSE (0.7000), high index of agreement (0.9408), and low coefficient of variability (0.4121). The model is most sensitive to water stream size. The variables in the model are easily measurable; this makes it better and easily adoptable. PMID:27471748

Modeling thermal dynamics of active layer soils and near-surface permafrost using a fully coupled water and heat transport model

USGS Publications Warehouse

Jiang, Yueyang; Zhuang, Qianlai; O'Donnell, Jonathan A.

2012-01-01

Thawing and freezing processes are key components in permafrost dynamics, and these processes play an important role in regulating the hydrological and carbon cycles in the northern high latitudes. In the present study, we apply a well-developed soil thermal model that fully couples heat and water transport, to simulate the thawing and freezing processes at daily time steps across multiple sites that vary with vegetation cover, disturbance history, and climate. The model performance was evaluated by comparing modeled and measured soil temperatures at different depths. We use the model to explore the influence of climate, fire disturbance, and topography (north- and south-facing slopes) on soil thermal dynamics. Modeled soil temperatures agree well with measured values for both boreal forest and tundra ecosystems at the site level. Combustion of organic-soil horizons during wildfire alters the surface energy balance and increases the downward heat flux through the soil profile, resulting in the warming and thawing of near-surface permafrost. A projection of 21st century permafrost dynamics indicates that as the climate warms, active layer thickness will likely increase to more than 3 meters in the boreal forest site and deeper than one meter in the tundra site. Results from this coupled heat-water modeling approach represent faster thaw rates than previously simulated in other studies. We conclude that the discussed soil thermal model is able to well simulate the permafrost dynamics and could be used as a tool to analyze the influence of climate change and wildfire disturbance on permafrost thawing.

Estimating surface soil moisture from SMAP observations using a Neural Network technique.

PubMed

Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

2018-01-01

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Microbial Priming and Protected Carbon Responses to Elevated CO2 at Local to Global Scales: a New Modeling Approach

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Oishi, C.; Shevliakova, E.; Pacala, S. W.

2013-12-01

The soil carbon formulations commonly used in global carbon cycle models and Earth System models (ESMs) are based on first-order decomposition equations, where turnover of carbon is determined only by the size of the carbon pool and empirical functions of responses to temperature and moisture. These models do not include microbial dynamics or protection of carbon in microaggregates and mineral complexes, making them incapable of simulating important soil processes like priming and the influence of soil physical structure on carbon turnover. We present a new soil carbon dynamics model - Carbon, Organisms, Respiration, and Protection in the Soil Environment (CORPSE) - that explicitly represents microbial biomass and protected carbon pools. The model includes multiple types of carbon with different chemically determined turnover rates that interact with a single dynamic microbial biomass pool, allowing the model to simulate priming effects. The model also includes the formation and turnover of protected carbon that is inaccessible to microbial decomposers. The rate of protected carbon formation increases with microbial biomass. CORPSE has been implemented both as a stand-alone model and as a component of the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) ESM. We calibrated the model against measured soil carbon stocks from the Duke FACE experiment. The model successfully simulated the seasonal pattern of heterotrophic CO2 production. We investigated the roles of priming and protection in soil carbon accumulation by running the model using measured inputs of leaf litter, fine roots, and root exudates from the ambient and elevated CO2 plots at the Duke FACE experiment. Measurements from the experiment showed that elevated CO2 caused enhanced root exudation, increasing soil carbon turnover in the rhizosphere due to priming effects. We tested the impact of increased root exudation on soil carbon accumulation by comparing model simulations of carbon accumulation under elevated CO2 with and without increased root exudation. Increased root exudation stimulated microbial activity in the model, resulting in reduced accumulation of chemically recalcitrant carbon, but increasing the formation of protected carbon. This indicates that elevated CO2 could cause decreases in soil carbon storage despite increases in productivity in ecosystems where protection of soil carbon is limited. These effects have important implications for simulations of soil carbon response to elevated CO2 in current terrestrial carbon cycle models. The CORPSE model has been implemented in LM3, the terrestrial component of the GFDL ESM. In addition to the functionality described above, this model adds vertically resolved carbon pools and vertical transfers of carbon, leading to a decrease in carbon turnover rates with depth due to leaching of priming agents from the surface. We present preliminary global simulations using this model, including the variation of microbial activity and protected carbon with latitude and the resulting impacts on the sensitivity of soil carbon to climatic warming.

Horizon Partitioning of Soil CO2 Sources and their Isotopic Composition (13C) in a Pinus Sylvestris Stand

NASA Astrophysics Data System (ADS)

Goffin, S.; Parent, F.; Plain, C.; Maier, M.; Schack-Kirchner, H.; Aubinet, M.; Longdoz, B.

2012-12-01

The overall aim of this study is to contribute to a better understanding of mechanisms behind soil CO2 efflux using carbon stable isotopes. The approach combines a soil multilayer analysis and the isotopic tool in an in situ study. The specific goal of this work is to quantify the origin and the determinism of 13CO2 and 12CO2 production processes in the different soil layers using the gradient-efflux approach. To meet this, the work includes an experimental setup and a modeling approach. The experimental set up (see also communication of Parent et al., session B008) comprised a combination of different systems, which were installed in a Scot Pine temperate forest at the Hartheim site (Southwestern Germany). Measurements include (i) half hourly vertical profiles of soil CO2 concentration (using soil CO2 probes), soil water content and temperature; (ii) half hourly soil surface CO2 effluxes (automatic chambers); (iii) half hourly isotopic composition of surface CO2 efflux and soil CO2 concentration profile and (iv) estimation of soil diffusivity through laboratory measurements conducted on soil samples taken at several depths. Using the data collected in the experimental part, we developed and used a diffusive transport model to simulate CO2 (13CO2 and 12CO2) flows inside and out of the soil based on Fick's first law. Given the horizontal homogeneity of soil physical parameters in Hartheim, we treated the soil as a structure consisting of distinctive layers of 5 cm thick and expressed the Fick's first law in a discrete formalism. The diffusion coefficient used in each layer was derived from (i) horizon specific relationships, obtained from laboratory measurements, between soil relative diffusivity and its water content and (ii) the soil water content values measured in situ. The concentration profile was obtained from in situ measurements. So, the main model inputs are the profiles of (i) CO2 (13CO2 and 12CO2) concentration, (ii) soil diffusion coefficient and (iii) soil water content. Once the diffusive fluxes deduced at each layer interface, the CO2 (13CO2 and 12CO2) production profile was calculated using the (discretized) mass balance equation in each layer. The results of the Hartheim measurement campaign will be presented. The CO2 source vertical profile and its link with the root and the Carbon organic content distribution will be showed. The dynamic of CO2 sources and their isotopic signature will be linked to climatic variables such soil temperature and soil water content. For example, we will show that the dynamics of CO2 sources was mainly related to temperature while changing of isotopic signature was more correlated to soil moisture.

A microwave systems approach to measuring root zone soil moisture

NASA Technical Reports Server (NTRS)

Newton, R. W.; Paris, J. F.; Clark, B. V.

1983-01-01

Computer microwave satellite simulation models were developed and the program was used to test the ability of a coarse resolution passive microwave sensor to measure soil moisture over large areas, and to evaluate the effect of heterogeneous ground covers with the resolution cell on the accuracy of the soil moisture estimate. The use of realistic scenes containing only 10% to 15% bare soil and significant vegetation made it possible to observe a 60% K decrease in brightness temperature from a 5% soil moisture to a 35% soil moisture at a 21 cm microwave wavelength, providing a 1.5 K to 2 K per percent soil moisture sensitivity to soil moisture. It was shown that resolution does not affect the basic ability to measure soil moisture with a microwave radiometer system. Experimental microwave and ground field data were acquired for developing and testing a root zone soil moisture prediction algorithm. The experimental measurements demonstrated that the depth of penetration at a 21 cm microwave wavelength is not greater than 5 cm.

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

Modeling pulsed soil respiration in an African savanna ecosystem

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

Fan, Zhaosheng; Neff, Jason C.; Hanan, Niall P.

2015-01-01

Savannas cover 60% of the African continent and play an important role in the global carbon (C) emissions from fire and land use. To better characterize the biophysical controls over soil respiration in these settings, half-hourly observations of volumetric soil-water content, temperature, and the concentration of carbon dioxide (CO2) at different soil depths were continually measured from 2005 to 2007 under trees ("sub-canopy") and between trees ("inter-canopy") in a savanna vegetation near Skukuza, Kruger National Park, South Africa. The measured soil climate and CO2 concentration data were assimilated into a process-based model that estimates the CO2 production and flux withmore » coupled dynamics of dissolved organic C (DOC) and microbial biomass C. Our results show that temporal and spatial variations in CO2 flux were strongly influenced by precipitation and vegetation cover, with two times greater CO2 flux in the subcanopy plots (similar to 2421 g CO2 m(-2) yr(-1)) than in the inter-canopy plots (similar to 1290 g CO2 m(-2) yr(-1)). Precipitation influenced soil respiration by changing soil temperature and moisture; however, our modeling analysis suggests that the pulsed response of soil respiration to precipitation events (known as "Birch effect") is a key control on soil fluxes at this site. At this site, "Birch effect" contributed to approximately 50% and 65% of heterotrophic respiration or 20% and 39% of soil respiration in the sub-canopy and inter-canopy plots, respectively. These results suggest that pulsed response of respiration to precipitation events is an important component of the C cycle of savannas and should be considered in both measurement and modeling studies of carbon exchange in similar ecosystems. (C) 2014 Elsevier B.V. All rights reserved.« less

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Difficulties in the evaluation and measuring of soil water infiltration

NASA Astrophysics Data System (ADS)

Pla-Sentís, Ildefonso

2013-04-01

Soil water infiltration is the most important hydrological parameter for the evaluation and diagnosis of the soil water balance and soil moisture regime. Those balances and regimes are the main regulating factors of the on site water supply to plants and other soil organisms and of other important processes like runoff, surface and mass erosion, drainage, etc, affecting sedimentation, flooding, soil and water pollution, water supply for different purposes (population, agriculture, industries, hydroelectricity), etc. Therefore the evaluation and measurement of water infiltration rates has become indispensable for the evaluation and modeling of the previously mentioned processes. Infiltration is one of the most difficult hydrological parameters to evaluate or measure accurately. Although the theoretical aspects of the process of soil water infiltration are well known since the middle of the past century, when several methods and models were already proposed for the evaluation of infiltration, still nowadays such evaluation is not frequently enough accurate for the purposes being used. This is partially due to deficiencies in the methodology being used for measuring infiltration, including some newly proposed methods and equipments, and in the use of non appropriate empirical models and approaches. In this contribution we present an analysis and discussion about the main difficulties found in the evaluation and measurement of soil water infiltration rates, and the more commonly committed errors, based on the past experiences of the author in the evaluation of soil water infiltration in many different soils and land conditions, and in their use for deducing soil water balances under variable and changing climates. It is concluded that there are not models or methods universally applicable to any soil and land condition, and that in many cases the results are significantly influenced by the way we use a particular method or instrument, and by the alterations in the soil conditions by the land management, but also due to the manipulation of the soil before and during the measurement. Direct "in situ" field evaluations have to be preferred in any case to indirect deductions from other soil characteristics measured under laboratory conditions in the same soils, or in other soils, through the so called "pedo-transfer" functions, or through the use of stochastic models such as the SCS Curve Number Method, or of other models using empirical or physical approaches, which have demonstrated to be of limited value in most of the cases. References Philip, J. R., 1954., An infiltration equation with physical significance: Soil Sci..,v. 77, p. 153-157. Philip, J. R., 1958. The theory of infiltration, pt. 7: Soil Sci., v. 85, no. 6, p. 333-337. Pla, I.1981. Simuladores de lluvia para el estudio de relaciones suelo-agua bajo agricultura de secano en los trópicos. Rev. Fac. Agron. XII(1-2):81-93.Maracay (Venezuela) Pla, I. 1986. A routine laboratory index to predict the effects of soil sealing on soil and water conservation. En "Assesment of Soil Surface Sealing and Crusting". 154-162.State Univ. of Ghent.Gante (Bélgica Pla, I., 1997. A soil water balance model for monitoring soil erosion processes and effects on steep lands in the tropics. Soil Technology. 11(1):17-30. Elsevier Pla, I., M.C. Ramos, S. Nacci, F. Fonseca y X. Abreu. 2005. Soil moisture regime in dryland vineyards of Catalunya (Spain) as influenced by climate, soil and land management. "Integrated Soil and Water Management for Orchard Development". FAO Land and Water Bulletin 10. 41-49. Roma (Italia). Pla, I., 2006. Hydrological approach for assessing desertification processes in the Mediterranean region. In W.G. Kepner et al. (Editors), Desertification in the Mediterranean Region. A Security Issue. 579-600 Springer. Heidelberg (Germany) Pla, I. 2011. Evaluación y Modelización Hidrológica para el Diagnóstico y Prevención de "Desastres Naturales". Gestión y Ambiente 14 (3): 17-22. UN-Medellín (Colombia). ISSN 0124.177X Pla, I. 2011. Medición y evaluación de propiedades físicas de los suelos: dificultades y errores más frecuentes. II-Propiedades hidrológicas. Suelos Ecuatoriales 40 (2): 94-127 Reynolds W.D., B.T. Bowman, R.R. Brunke, C.F. Drury and C.S. Tan. 2000. Comparison of Tension Infiltrometer, Pressure Infiltrometer, and Soil Core Estimates of Saturated Hydraulic Conductivity . Soil Science Society of America Journal 64:478-484 Richards, L. A., 1952. Report of the Subcommittee on Permeability and Infiltration, Committee on Terminology, Soil Science Society of America: Soil Sci. Soc.America Proc., v. 16, p. 85-88. Segal, E., S.A.Bradford, P. Shouse; N. Lazarovich, and D. Corwin. 2008. Integration of Hard and Soft Data to Characterize Field-Scale Hydraulic Properties for Flow and Transport Studies. Vadose Zone J 7:878-889 Young, E. 1991. Infiltration measurements, a review. Hydrological processes 5: 309-320

Evaluation of a Compartmental Model for Prediction of Nitrate Leaching Losses,

DTIC Science & Technology

1981-12-01

model results limit their utility, the calculated total dissolved solids (TDS) of the soil solution (7146 mg L-1) and the measured TDS of tile...measured values of plant uptake, residual inorganic N and average annual In eq 1, the term on the left-hand side represents soil solution N concentrations...Research Applied to National the soil solution below which the uptake efficiency Needs, decreases sharply. 11 Table 3. Summary of water input data (cm of H2

Lead exposure in young children over a 5-year period from urban environments using alternative exposure measures with the US EPA IEUBK model - A trial.

PubMed

Gulson, Brian; Taylor, Alan; Stifelman, Marc

2018-02-01

The US Environmental Protection Agency (EPA) Integrated Exposure Uptake Biokinetic (IEUBK) model has been widely used to predict blood lead (PbB) levels in children especially around industrial sites. Exposure variables have strongly focussed on the major contribution of lead (Pb) in soil and interior dust to total intake and, in many studies, site-specific data for air, water, diet and measured PbB were not available. We have applied the IEUBK model to a comprehensive data set, including measured PbB, for 108 children monitored over a 5-year period in Sydney, New South Wales, Australia. To use this data set, we have substituted available data (with or without modification) for standard inputs as needed. For example, as an alternative measure for soil Pb concentration (μg/g), we have substituted exterior dust sweepings Pb concentration (μg/g). As alternative measures for interior dust Pb concentration (μg/g) we have used 1) 30-day cumulative petri dish deposition data (PDD) (as µg Pb/m 2 /30days), or 2) hand wipe data (as μg Pb/hand). For comparison, simulations were also undertaken with estimates of dust Pb concentration derived from a prior regression of dust Pb concentration (μg/g) on dust Pb loading (μg/ft 2 ) as concentration is the unit specified for the Model. Simulations for each subject using observed data aggregated over the 5-year interval of the study, the most usual application of the IEUBK model, showed using Wilcoxon tests that there was a significant difference between the observed values and the values predicted by the Model containing soil with hand wipes (p < 0.001), and soil and PDD (p = 0.026) but not those for the other two sets of predictors, based on sweepings and PDD or sweepings and wipes. Overall, simulations of the Model using alternative exposure measures of petri dish dust (and possibly hand wipes) instead of vacuum cleaner dust and dust sweepings instead of soil provide predicted PbB which are generally consistent with each other and observed values. The predicted geometric mean PbBs were 2.17 ( ± 1.24) μg/dL for soil with PDD, 1.95 ( ± 1.17) μg/dL for soil with hand wipes, 2.36 ( ± 1.75) μg/dL for sweepings with PDD, and 2.15 ( ± 1.69) for sweepings with hand wipes. These results are in good agreement with the observed geometric mean PbB of 2.46 ( ± 0.99) μg/dL. In contrast to all other IEUBK model studies to our knowledge, we have stratified the data over the age ranges from 1 to 5 years. The median of the predicted values was lower than that for the observed values for every combination of age and set of measures; in some cases, the difference was statistically significant. The differences between observed and predicted PbB tended to be greatest for the soil plus wipes measure and for the oldest age group. Use of 'default dust' values calculated from the site-specific soil values, a common application of the IEUBK model, results in predicted PbB about 22% (range 0 to 52%) higher than those from soil with PDD data sets. Geometric mean contributions estimated from the Model to total Pb intake for a child aged 1-2 years was 0.09% for air, 42% for diet, 5.3% for water and 42% for soil and dust. Our results indicate that it is feasible to use alternative measures of soil and dust exposure to provide reliable predictions of PbB in urban environments. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of SWAT and GeoWEPP model in predicting the impact of stone bunds on runoff and erosion processes in the Northern Ethiopian Highlands

NASA Astrophysics Data System (ADS)

Demelash, Nigus; Flagler, Jared; Renschler, Chris; Strohmeier, Stefan; Holzmann, Hubert; Feras, Ziadat; Addis, Hailu; Zucca, Claudio; Bayu, Wondimu; Klik, Andreas

2017-04-01

Soil degradation is a major issue in the Ethiopian highlands which are most suitable for agriculture and, therefore, support a major part of human population and livestock. Heavy rainstorms during the rainy season in summer create soil erosion and runoff processes which affect soil fertility and food security. In the last years programs for soil conservation and afforestation were initiated by the Ethiopian government to reduce erosion risk, retain water in the landscape and improve crop yields. The study was done in two adjacent watersheds in the Northwestern highlands of Ethiopia. One of the watersheds is developed by soil and water conservation structures (stone bunds) in 2011 and the other one is without soil and water conservation structures. Spatial distribution of soil textures and other soil properties were determined in the field and in the laboratory and a soil map was derived. A land use map was evaluated based on satellite images and ground truth data. A Digital Elevation Model of the watershed was developed based on conventional terrestrial surveying using a total station. At the outlet of the watersheds weirs with cameras were installed to measure surface runoff. During each event runoff samples were collected and sediment concentration was analyzed. The objective of this study is 1) to assess the impact of stone bunds on runoff and erosion processes by using simulation models, and 2) to compare the performance of two soil erosion models in predicting the measurements. The selected erosion models were the Soil and Water Assessment Tool (SWAT) and the Geospatial Interface to the Water Erosion Prediction Project (GeoWEPP). The simulation models were calibrated/verified for the 2011-2013 periods and validated with 2014-2015 data. Results of this comparison will be presented.

Bidirectional reflectance modeling of non-homogeneous plant canopies

NASA Technical Reports Server (NTRS)

Norman, John M.

1986-01-01

The objective of this research is to develop a 3-dimensional radiative transfer model for predicting the bidirectional reflectance distribution function (BRDF) for heterogeneous vegetation canopies. Leaf bidirectional reflectance and transmittance distribution functions were measured for corn and soybean leaves. The measurements clearly show that leaves are complex scatterers and considerable specular reflectance is possible. Because of the character of leaf reflectance, true leaf reflectance is larger than the nadir reflectances that are normally used to represent leaves. A 3-dimensional reflectance model, named BIGAR (Bidirectional General Array Model), was developed and compared with measurements from corn and soybean. The model is based on the concept that heterogeneous canopies can be described by a combination of many subcanopies, which contain all the foliage, and these subcanopy envelopes can be characterized by ellipsoids of various sizes and shapes. The model/measurement comparison results indicate that this relatively simple model captures the essential character of row crop BRDF's. Finally, two soil BDRF models were developed: one represents soil particles as rectangular blocks and the other represents soil particles as spheres. The sphere model was found to be superior.

Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland

NASA Astrophysics Data System (ADS)

Swain, Michael; Swain, Matthew; Lohmann, Melinda; Swain, Eric

2012-02-01

SummaryTwo physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32 m diameter by 0.99 m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat-sand-soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed. Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1 cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9 cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6 cm of water and 55.9 cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat-sand-soil mix lags behind maximum solar radiation by approximately 2 h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil.

Experimental determination of soil heat storage for the simulation of heat transport in a coastal wetland

USGS Publications Warehouse

Swain, Michael; Swain, Matthew; Lohmann, Melinda; Swain, Eric

2012-01-01

Two physical experiments were developed to better define the thermal interaction of wetland water and the underlying soil layer. This information is important to numerical models of flow and heat transport that have been developed to support biological studies in the South Florida coastal wetland areas. The experimental apparatus consists of two 1.32. m diameter by 0.99. m tall, trailer-mounted, well-insulated tanks filled with soil and water. A peat-sand-soil mixture was used to represent the wetland soil, and artificial plants were used as a surrogate for emergent wetland vegetation based on size and density observed in the field. The tanks are instrumented with thermocouples to measure vertical and horizontal temperature variations and were placed in an outdoor environment subject to solar radiation, wind, and other factors affecting the heat transfer. Instruments also measure solar radiation, relative humidity, and wind speed.Tests indicate that heat transfer through the sides and bottoms of the tanks is negligible, so the experiments represent vertical heat transfer effects only. The temperature fluctuations measured in the vertical profile through the soil and water are used to calibrate a one-dimensional heat-transport model. The model was used to calculate the thermal conductivity of the soil. Additionally, the model was used to calculate the total heat stored in the soil. This information was then used in a lumped parameter model to calculate an effective depth of soil which provides the appropriate heat storage to be combined with the heat storage in the water column. An effective depth, in the model, of 5.1. cm of wetland soil represents the heat storage needed to match the data taken in the tank containing 55.9. cm of peat/sand/soil mix. The artificial low-density laboratory sawgrass reduced the solar energy absorbed by the 35.6. cm of water and 55.9. cm of soil at midday by less than 5%. The maximum heat transfer into the underlying peat-sand-soil mix lags behind maximum solar radiation by approximately 2. h. A slightly longer temperature lag was observed between the maximum solar radiation and maximum water temperature both with and without soil. ?? 2012 Elsevier B.V.

Modelling and interpreting biologically crusted dryland soil sub-surface structure using automated micropenetrometry

NASA Astrophysics Data System (ADS)

Hoon, Stephen R.; Felde, Vincent J. M. N. L.; Drahorad, Sylvie L.; Felix-Henningsen, Peter

2015-04-01

Soil penetrometers are used routinely to determine the shear strength of soils and deformable sediments both at the surface and throughout a depth profile in disciplines as diverse as soil science, agriculture, geoengineering and alpine avalanche-safety (e.g. Grunwald et al. 2001, Van Herwijnen et al. 2009). Generically, penetrometers comprise two principal components: An advancing probe, and a transducer; the latter to measure the pressure or force required to cause the probe to penetrate or advance through the soil or sediment. The force transducer employed to determine the pressure can range, for example, from a simple mechanical spring gauge to an automatically data-logged electronic transducer. Automated computer control of the penetrometer step size and probe advance rate enables precise measurements to be made down to a resolution of 10's of microns, (e.g. the automated electronic micropenetrometer (EMP) described by Drahorad 2012). Here we discuss the determination, modelling and interpretation of biologically crusted dryland soil sub-surface structures using automated micropenetrometry. We outline a model enabling the interpretation of depth dependent penetration resistance (PR) profiles and their spatial differentials using the model equations, σ {}(z) ={}σ c0{}+Σ 1n[σ n{}(z){}+anz + bnz2] and dσ /dz = Σ 1n[dσ n(z) /dz{} {}+{}Frn(z)] where σ c0 and σ n are the plastic deformation stresses for the surface and nth soil structure (e.g. soil crust, layer, horizon or void) respectively, and Frn(z)dz is the frictional work done per unit volume by sliding the penetrometer rod an incremental distance, dz, through the nth layer. Both σ n(z) and Frn(z) are related to soil structure. They determine the form of σ {}(z){} measured by the EMP transducer. The model enables pores (regions of zero deformation stress) to be distinguished from changes in layer structure or probe friction. We have applied this method to both artificial calibration soils in the laboratory, and in-situ field studies. In particular, we discuss the nature and detection of surface and buried (fossil) subsurface Biological Soil Crusts (BSCs), voids, macroscopic particles and compositional layers. The strength of surface BSCs and the occurrence of buried BSCs and layers has been detected at sub millimetre scales to depths of 40mm. Our measurements and field observations of PR show the importance of morphological layering to overall BSC functions (Felde et al. 2015). We also discuss the effect of penetrometer shaft and probe-tip profiles upon the theoretical and experimental curves, EMP resolution and reproducibility, demonstrating how the model enables voids, buried biological soil crusts, exotic particles, soil horizons and layers to be distinguished one from another. This represents a potentially important contribution to advancing understanding of the relationship between BSCs and dryland soil structure. References: Drahorad SL, Felix-Henningsen P. (2012) An electronic micropenetrometer (EMP) for field measurements of biological soil crust stability, J. Plant Nutr. Soil Sci., 175, 519-520 Felde V.J.M.N.L., Drahorad S.L., Felix-Henningsen P., Hoon S.R. (2015) Ongoing oversanding induces biological soil crust layering - a new approach for BSC structure elucidation determined from high resolution penetration resistance data (submitted) Grunwald, S., Rooney D.J., McSweeney K., Lowery B. (2001) Development of pedotransfer functions for a profile cone penetrometer, Geoderma, 100, 25-47 Van Herwijnen A., Bellaire S., Schweizer J. (2009) Comparison of micro-structural snowpack parameters derived from penetration resistance measurements with fracture character observations from compression tests, Cold Regions Sci. {& Technol.}, 59, 193-201

Modelling phytoremediation by the hyperaccumulating fern, Pteris vittata, of soils historically contaminated with arsenic.

PubMed

Shelmerdine, Paula A; Black, Colin R; McGrath, Steve P; Young, Scott D

2009-05-01

Pteris vittata plants were grown on twenty-one UK soils contaminated with arsenic (As) from a wide range of natural and anthropogenic sources. Arsenic concentration was measured in fern fronds, soil and soil pore water collected with Rhizon samplers. Isotopically exchangeable soil arsenate was determined by equilibration with (73)As(V). Removal of As from the 21 soils by three sequential crops of P. vittata ranged between 0.1 and 13% of total soil As. Ferns grown on a soil subjected to long-term sewage sludge application showed reduced uptake of As because of high available phosphate concentrations. A combined solubility-uptake model was parameterised to enable prediction of phytoremediation success from estimates of soil As, 'As-lability' and soil pH. The model was used to demonstrate the remediation potential of P. vittata under different soil conditions and with contrasting assumptions regarding re-supply of the labile As pool from unavailable forms.

Modeling the effects of tree species and incubation temperature on soil's extracellular enzyme activity in 78-year-old tree plantations

NASA Astrophysics Data System (ADS)

Zhou, Xiaoqi; Wang, Shen S. J.; Chen, Chengrong

2017-12-01

Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C/N model to investigate how temperature and tree species influence soil C/N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and kauri pine (Agathis robusta C. Moore). Our results will be helpful for understanding the mechanisms of soil C and N cycling by different tree species, which will have implications for forest management.

Spatiotemporal Variability of Soil Hydraulic Properties from Field Data and Remote Sensing in the Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Becker, R.; Gebremichael, M.; Marker, M.

2015-12-01

Soil moisture is one of the main input variables for hydrological models. However due to the high spatial and temporal variability of soil properties it is often difficult to obtain accurate soil information at the required resolution. The new satellite SMAP promises to deliver soil moisture information at higher resolutions and could therefore improve the results of hydrological models. Nevertheless it still has to be investigated how precisely the SMAP soil moisture data can be used to delineate rainfall-runoff generation processes and if SMAP imagery can significantly improve the results of surface runoff models. Important parameters to understand the spatiotemporal distribution of soil humidity are infiltration and hydraulic conductivities apart from soil texture and macrostructure. During the SMAPVEX15-field campaign data on hydraulic conductivity and infiltration rates is collected in the Walnut Gulch Experimental Watershed (WGEW) in Southeastern Arizona in order to analyze the spatiotemporal variability of soil hydraulic properties. A Compact Constant Head Permeameter is used for in situ measurements of saturated hydraulic conductivity within the soil layers and a Hood Infiltrometer is used to determine infiltration rates at the undisturbed soil surface. Sampling sites were adjacent to the USDA-ARS meteorological and soil moisture measuring sites in the WGEW to take advantage of the long-term database of soil and climate data. Furthermore a sample plot of 3x3km was selected, where the spatial variability of soil hydraulic properties within a SMAP footprint was investigated. The results of the ground measurement based analysis are then compared with the remote sensing data derived from SMAP and aircraft-based microwave data to determine how well these spatiotemporal variations are captured by the remotely sensed data with the final goal of evaluating the use of future satellite soil moisture products for the improvement of rainfall runoff models. The results reveal several interesting features on the spatiotemporal variability of soil moisture at multiple scales, and the capabilities and limitations of remote sensing derived products in reproducing them.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 2; Aggregation

NASA Technical Reports Server (NTRS)

Schamschula, Marius; Crosson, William L.; Inguva, Ramarao; Yates, Thomas; Laymen, Charles A.; Caulfield, John

1998-01-01

This is a follow up on the preceding presentation by Crosson. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to aggregate the hydrological model outputs for soil moisture to allow comparison with measurements. Weighted neighborhood averaging methods are proposed to facilitate the comparison. We will also discuss such complications as misalignment, rotation and other distortions introduced by a generalized sensor image.

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

Application of a coupled ecosystem-chemical equilibrium model, DayCent-Chem, to stream and soil chemistry in a Rocky Mountain watershed

USGS Publications Warehouse

Hartman, M.D.; Baron, Jill S.; Ojima, D.S.

2007-01-01

Atmospheric deposition of sulfur and nitrogen species have the potential to acidify terrestrial and aquatic ecosystems, but nitrate and ammonium are also critical nutrients for plant and microbial productivity. Both the ecological response and the hydrochemical response to atmospheric deposition are of interest to regulatory and land management agencies. We developed a non-spatial biogeochemical model to simulate soil and surface water chemistry by linking the daily version of the CENTURY ecosystem model (DayCent) with a low temperature aqueous geochemical model, PHREEQC. The coupled model, DayCent-Chem, simulates the daily dynamics of plant production, soil organic matter, cation exchange, mineral weathering, elution, stream discharge, and solute concentrations in soil water and stream flow. By aerially weighting the contributions of separate bedrock/talus and tundra simulations, the model was able to replicate the measured seasonal and annual stream chemistry for most solutes for Andrews Creek in Loch Vale watershed, Rocky Mountain National Park. Simulated soil chemistry, net primary production, live biomass, and soil organic matter for forest and tundra matched well with measurements. This model is appropriate for accurately describing ecosystem and surface water chemical response to atmospheric deposition and climate change. ?? 2006 Elsevier B.V. All rights reserved.

Influence of Temperature, Relative Humidity, and Soil Properties on the Soil-Air Partitioning of Semivolatile Pesticides: Laboratory Measurements and Predictive Models.

PubMed

Davie-Martin, Cleo L; Hageman, Kimberly J; Chin, Yu-Ping; Rougé, Valentin; Fujita, Yuki

2015-09-01

Soil-air partition coefficient (Ksoil-air) values are often employed to investigate the fate of organic contaminants in soils; however, these values have not been measured for many compounds of interest, including semivolatile current-use pesticides. Moreover, predictive equations for estimating Ksoil-air values for pesticides (other than the organochlorine pesticides) have not been robustly developed, due to a lack of measured data. In this work, a solid-phase fugacity meter was used to measure the Ksoil-air values of 22 semivolatile current- and historic-use pesticides and their degradation products. Ksoil-air values were determined for two soils (semiarid and volcanic) under a range of environmentally relevant temperature (10-30 °C) and relative humidity (30-100%) conditions, such that 943 Ksoil-air measurements were made. Measured values were used to derive a predictive equation for pesticide Ksoil-air values based on temperature, relative humidity, soil organic carbon content, and pesticide-specific octanol-air partition coefficients. Pesticide volatilization losses from soil, calculated with the newly derived Ksoil-air predictive equation and a previously described pesticide volatilization model, were compared to previous results and showed that the choice of Ksoil-air predictive equation mainly affected the more-volatile pesticides and that the way in which relative humidity was accounted for was the most critical difference.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

Evapotranspiration measurement and modeling without fitting parameters in high-altitude grasslands

NASA Astrophysics Data System (ADS)

Ferraris, Stefano; Previati, Maurizio; Canone, Davide; Dematteis, Niccolò; Boetti, Marco; Balocco, Jacopo; Bechis, Stefano

2016-04-01

Mountain grasslands are important, also because one sixth of the world population lives inside watershed dominated by snowmelt. Also, grasslands provide food to both domestic and selvatic animals. The global warming will probably accelerate the hydrological cycle and increase the drought risk. The combination of measurements, modeling and remote sensing can furnish knowledge in such faraway areas (e.g.: Brocca et al., 2013). A better knowledge of water balance can also allow to optimize the irrigation (e.g.: Canone et al., 2015). This work is meant to build a model of water balance in mountain grasslands, ranging between 1500 and 2300 meters asl. The main input is the Digital Terrain Model, which is more reliable in grasslands than both in the woods and in the built environment. It drives the spatial variability of shortwave solar radiation. The other atmospheric forcings are more problematic to estimate, namely air temperature, wind and longwave radiation. Ad hoc routines have been written, in order to interpolate in space the meteorological hourly time variability. The soil hydraulic properties are less variable than in the plains, but the soil depth estimation is still an open issue. The soil vertical variability has been modeled taking into account the main processes: soil evaporation, root uptake, and fractured bedrock percolation. The time variability latent heat flux and soil moisture results have been compared with the data measured in an eddy covariance station. The results are very good, given the fact that the model has no fitting parameters. The space variability results have been compared with the results of a model based on Landsat 7 and 8 data, applied over an area of about 200 square kilometers. The spatial correlation is quite in agreement between the two models. Brocca et al. (2013). "Soil moisture estimation in alpine catchments through modelling and satellite observations". Vadose Zone Journal, 12(3), 10 pp. Canone et al. (2015). "Field measurements based model for surface irrigation efficiency assessment". Agric. Water Manag., 156(1) pp. 30-42

Prediction of Soil pH Hyperspectral Spectrum in Guanzhong Area of Shaanxi Province Based on PLS

NASA Astrophysics Data System (ADS)

Liu, Jinbao; Zhang, Yang; Wang, Huanyuan; Cheng, Jie; Tong, Wei; Wei, Jing

2017-12-01

The soil pH of Fufeng County, Yangling County and Wugong County in Shaanxi Province was studied. The spectral reflectance was measured by ASD Field Spec HR portable terrain spectrum, and its spectral characteristics were analyzed. The first deviation of the original spectral reflectance of the soil, the second deviation, the logarithm of the reciprocal logarithm, the first order differential of the reciprocal logarithm and the second order differential of the reciprocal logarithm were used to establish the soil pH Spectral prediction model. The results showed that the correlation between the reflectance spectra after SNV pre-treatment and the soil pH was significantly improved. The optimal prediction model of soil pH established by partial least squares method was a prediction model based on the first order differential of the reciprocal logarithm of spectral reflectance. The principal component factor was 10, the decision coefficient Rc2 = 0.9959, the model root means square error RMSEC = 0.0076, the correction deviation SEC = 0.0077; the verification decision coefficient Rv2 = 0.9893, the predicted root mean square error RMSEP = 0.0157, The deviation of SEP = 0.0160, the model was stable, the fitting ability and the prediction ability were high, and the soil pH can be measured quickly.

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.

Aging of nickel added to soils as predicted by soil pH and time.

PubMed

Ma, Yibing; Lombi, Enzo; McLaughlin, Mike J; Oliver, Ian W; Nolan, Annette L; Oorts, Koen; Smolders, Erik

2013-08-01

Although aging processes are important in risk assessment for metals in soils, the aging of Ni added to soils has not been studied in detail. In this study, after addition of water soluble Ni to soils, the changes over time in isotopic exchangeability, total concentrations and free Ni(2+) activity in soil pore water, were investigated in 16 European soils incubated outdoors for 18 months. The results showed that after Ni addition, concentrations of Ni in soil pore water and isotopic exchangeability of Ni in soils initially decreased rapidly. This phase was followed by further decreases in the parameters measured but these occurred at slower rates. Increasing soil pH increased the rate and extent of aging reactions. Semi-mechanistic models, based on Ni precipitation/nucleation on soil surfaces and micropore diffusion, were developed and calibrated. The initial fast processes, which were attributed to precipitation/nucleation, occurred over a short time (e.g. 1h), afterwards the slow processes were most likely controlled by micropore diffusion processes. The models were validated by comparing predicted and measured Ni aging in three additional, widely differing soils aged outdoors for periods up to 15 months in different conditions. These models could be used to scale ecotoxicological data generated in short-term studies to longer aging times. Copyright © 2013 Elsevier Ltd. All rights reserved.

Soil moisture needs in earth sciences

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1992-01-01

The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas.

Soil erosion by snow gliding - a first quantification attempt in a sub-alpine area, Switzerland

NASA Astrophysics Data System (ADS)

Meusburger, K.; Leitinger, G.; Mabit, L.; Mueller, M. H.; Walter, A.; Alewell, C.

2014-03-01

Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as soil erosion agent for four different land use/land cover types in a sub-alpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide deposits, the fallout radionuclide 137Cs, and modelling with the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model is suitable to estimate soil loss by water erosion, while the 137Cs method integrates soil loss due to all erosion agents involved. Thus, we hypothesise that the soil erosion rates determined with the 137Cs method are higher and that the observed discrepancy between the soil erosion rate of RUSLE and the 137Cs method is related to snow gliding and sediment concentrations in the snow glide deposits. Cumulative snow glide distance was measured for the sites in the winter 2009/10 and modelled for the surrounding area with the Spatial Snow Glide Model (SSGM). Measured snow glide distance ranged from 2 to 189 cm, with lower values at the north facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is important information with respect to conservation planning and expected land use changes in the Alps. Our hypothesis was confirmed: the difference of RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2= 0.64; p < 0.005) and snow sediment yields (R2 = 0.39; p = 0.13). A high difference (lower proportion of water erosion compared to total net erosion) was observed for high snow glide rates and vice versa. The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding is a key process impacting soil erosion pattern and magnitude in sub-alpine areas with similar topographic and climatic conditions.

Simulation of soil organic carbon in different soil size fractions using 13Carbon measurement data

NASA Astrophysics Data System (ADS)

Gottschalk, P.; Bellarby, J.; Chenu, C.; Foereid, B.; Wattenbach, M.; Zingore, S.; Smith, J.

2009-04-01

We simulate the soil organic carbon (SOC) dynamics at a chronoseqeunce site in France, using the Rothamsted Carbon model. The site exhibits a transition from C3 plants, dominated by pine forest, to a conventional C4 maize rotation. The different 13C signatures of the forest plants and maize are used to distinguish between the woodland derived carbon (C) and the maize derived C. The model is evaluated against total SOC and C derived from forest and maize, respectively. The SOC dynamics of the five SOC pools of the model, decomposable plant material (DPM), resistant plant material (RPM), biomass, humus and inert C, are also compared to the SOC dynamics measured in different soil size fractions. These fractions are > 50 μm (particulate organic matter), 2-50 μm (silt associated SOC) and <2 μm (clay associated SOC). Other authors had shown that the RPM pool of the model corresponds well to SOC measured in the soil size fraction > 50 μm and the sum of the other pools corresponds well to the SOC measured in the soil size fraction < 50 μm. Default model applications show that the model underestimates the fast drop in forest C stocks in the first 20 years after land-use change and overestimates the C accumulation of maize C. Several hypotheses were tested to evaluate the simulations. Input data and internal model parameter uncertainties had minor effects on the simulations results. Accounting for erosion and implementing a simple tillage routine did not improve the simulation fit to the data. We therefore hypothesize that a generic process that is not yet explicitly accounted for in the ROTHC model could explain the loss in soil C after land use change. Such a process could be the loss of the physical protection of soil organic matter as would be observed following cultivation of a previously uncultivated soil. Under native conditions a fraction of organic matter is protected in stable soil aggregates. These aggregates are physically disrupted by continuous and repeated cultivation of the soil. The underestimation of SOC loss by the model can be mainly attributed to the slow turnover of the humus pool. This pool was shown to represent mainly the SOC associated with the silt and clay soil fraction. Here, the clay associated SOC shows as similar turnover time as the humus pool in the model. We split the humus pool into a clay and a silt associated pool. The clay pool now corresponds to the clay associated SOC with the turnover time of the humus pool. The silt pool now corresponds to the silt associated SOC. From the measurements, the latter has a turnover time similar to the turnover time of the particulate organic matter. We therefore use the turnover time of the RPM pool for the silt pool. These modifications improve the simulations of the forest derived C significantly and improve the simulations of the maize derived C. Future work will further evaluate and refine this approach to eventually capture the SOC dynamics associated with physical protection, including the effect of tillage/no-tillage, in a simple approach.

Assessing the influence of the rhizosphere on soil hydraulic properties using X-ray computed tomography and numerical modelling.

PubMed

Daly, Keith R; Mooney, Sacha J; Bennett, Malcolm J; Crout, Neil M J; Roose, Tiina; Tracy, Saoirse R

2015-04-01

Understanding the dynamics of water distribution in soil is crucial for enhancing our knowledge of managing soil and water resources. The application of X-ray computed tomography (CT) to the plant and soil sciences is now well established. However, few studies have utilized the technique for visualizing water in soil pore spaces. Here this method is utilized to visualize the water in soil in situ and in three-dimensions at successive reductive matric potentials in bulk and rhizosphere soil. The measurements are combined with numerical modelling to determine the unsaturated hydraulic conductivity, providing a complete picture of the hydraulic properties of the soil. The technique was performed on soil cores that were sampled adjacent to established roots (rhizosphere soil) and from soil that had not been influenced by roots (bulk soil). A water release curve was obtained for the different soil types using measurements of their pore geometries derived from CT imaging and verified using conventional methods, such as pressure plates. The water, soil, and air phases from the images were segmented and quantified using image analysis. The water release characteristics obtained for the contrasting soils showed clear differences in hydraulic properties between rhizosphere and bulk soil, especially in clay soil. The data suggest that soils influenced by roots (rhizosphere soil) are less porous due to increased aggregation when compared with bulk soil. The information and insights obtained on the hydraulic properties of rhizosphere and bulk soil will enhance our understanding of rhizosphere biophysics and improve current water uptake models. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Effect of soil temperature on optical frequency transfer through unidirectional dense-wavelength-division-multiplexing fiber-optic links.

PubMed

Pinkert, T J; Böll, O; Willmann, L; Jansen, G S M; Dijck, E A; Groeneveld, B G H M; Smets, R; Bosveld, F C; Ubachs, W; Jungmann, K; Eikema, K S E; Koelemeij, J C J

2015-02-01

Results of optical frequency transfer over a carrier-grade dense-wavelength-division-multiplexing (DWDM) optical fiber network are presented. The relation between soil temperature changes on a buried optical fiber and frequency changes of an optical carrier through the fiber is modeled. Soil temperatures, measured at various depths by the Royal Netherlands Meteorology Institute (KNMI) are compared with observed frequency variations through this model. A comparison of a nine-day record of optical frequency measurements through the 2×298  km fiber link with soil temperature data shows qualitative agreement. A soil temperature model is used to predict the link stability over longer periods (days-months-years). We show that optical frequency dissemination is sufficiently stable to distribute and compare, e.g., rubidium frequency standards over standard DWDM optical fiber networks using unidirectional fibers.

Estimate carbon emissions from degraded permafrost with InSAR and a soil thermal model

NASA Astrophysics Data System (ADS)

Zhou, Z.; Liu, L.

2016-12-01

Climate warming, tundra fire over past decades has caused degradation in permafrost widely and quickly. Recent studies indicate that an increase in degradation could switch permafrost from a carbon sink to a source, with the potential of creating a positive feedback to anthropogenic climate warming. Unfortunately, Soil Organic Carbon (SOC) emissions from degraded permafrost unquantified, and limit our ability to understand SOC losses in arctic environments. This work will investigate recent 10 years of data already collected at the Anaktuvuk River fire (both ground and remote sensed), and will employ a soil thermal model to estimate SOC emission in this region. The model converts the increases in Active Layer Thickness (ALT), as measured by InSAR, to changes in Organic Layer Thickness (OLT), and SOC. ALOS-1/2 L-band SAR dataset will be used to produce the ATL changes over the study area. Soil prosperities (e.g. temperature at different depth, bulk density) will be used in the soil thermal model to estimate OLT changes and SOC losses. Ground measurement will validate the InSAR results and the soil thermal model. A final estimation of SOC emission will be produced in Anaktuvuk River region.

CONSERVB: A numerical method to compute soil water content and temperature profiles under a bare surface

NASA Technical Reports Server (NTRS)

Vanbavel, C. H. M.; Lascano, R. J.

1982-01-01

A comprehensive, yet fairly simple model of water disposition in a bare soil profile under the sequential impact of rain storms and other atmospheric influences, as they occur from hour to hour is presented. This model is intended mostly to support field studies of soil moisture dynamics by our current team, to serve as a background for the microwave measurements, and, eventually, to serve as a point of departure for soil moisture predictions for estimates based in part upon airborne measurements. The main distinction of the current model is that it accounts not only for the moisture flow in the soil-atmosphere system, but also for the energy flow and, hence, calculates system temperatures. Also, the model is of a dynamic nature, capable of supporting any required degree of resolution in time and space. Much critical testing of the sample is needed before the complexities of the hydrology of a vegetated surface can be related meaningfully to microwave observations.

Radar for Measuring Soil Moisture Under Vegetation

NASA Technical Reports Server (NTRS)

Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya

2004-01-01

A two-frequency, polarimetric, spaceborne synthetic-aperture radar (SAR) system has been proposed for measuring the moisture content of soil as a function of depth, even in the presence of overlying vegetation. These measurements are needed because data on soil moisture under vegetation canopies are not available now and are necessary for completing mathematical models of global energy and water balance with major implications for global variations in weather and climate.

Factors and processes governing the C-14 content of carbonate in desert soils

NASA Technical Reports Server (NTRS)

Amundson, Ronald; Wang, Yang; Chadwick, Oliver; Trumbore, Susan; Mcfadden, Leslie; Mcdonald, Eric; Wells, Steven; Deniro, Michael

1994-01-01

A model is presented describing the factors and processes which determine the measured C-14 ages of soil calcium carbonate. Pedogenic carbonate forms in isotopic equilium with soil CO2. Carbon dioxide in soils is a mixture of CO2 derived from two biological sources: respiration by living plant roots and respiration of microorganisms decomposing soil humus. The relative proportion of these two CO2 sources can greatly affect the initial C-14 content of pedogenic carbonate: the greater the contribution of humus-derived CO2, the greater the initial C-14 age of the carbonate mineral. For any given mixture of CO2 sources, the steady-state (14)CO2 distribution vs. soil depth can be described by a production/diffusion model. As a soil ages, the C-14 age of soil humus increases, as does the steady-state C-14 age of soil CO2 and the initial C-14 age of any pedogenic carbonate which forms. The mean C-14 age of a complete pedogenic carbonate coating or nodule will underestimate the true age of the soil carbonate. This discrepancy increases the older a soil becomes. Partial removal of outer (and younger) carbonate coatings greatly improves the relationship between measured C-14 age and true age. Although the production/diffusion model qualitatively explains the C-14 age of pedogenic carbonate vs. soil depth in many soils, other factors, such as climate change, may contribute to the observed trends, particularily in soils older than the Holocene.

Maximum Entropy Production Modeling of Evapotranspiration Partitioning on Heterogeneous Terrain and Canopy Cover: advantages and limitations.

NASA Astrophysics Data System (ADS)

Gutierrez-Jurado, H. A.; Guan, H.; Wang, J.; Wang, H.; Bras, R. L.; Simmons, C. T.

2015-12-01

Quantification of evapotranspiration (ET) and its partition over regions of heterogeneous topography and canopy poses a challenge using traditional approaches. In this study, we report the results of a novel field experiment design guided by the Maximum Entropy Production model of ET (MEP-ET), formulated for estimating evaporation and transpiration from homogeneous soil and canopy. A catchment with complex terrain and patchy vegetation in South Australia was instrumented to measure temperature, humidity and net radiation at soil and canopy surfaces. Performance of the MEP-ET model to quantify transpiration and soil evaporation was evaluated during wet and dry conditions with independently and directly measured transpiration from sapflow and soil evaporation using the Bowen Ratio Energy Balance (BREB). MEP-ET transpiration shows remarkable agreement with that obtained through sapflow measurements during wet conditions, but consistently overestimates the flux during dry periods. However, an additional term introduced to the original MEP-ET model accounting for higher stomatal regulation during dry spells, based on differences between leaf and air vapor pressure deficits and temperatures, significantly improves the model performance. On the other hand, MEP-ET soil evaporation is in good agreement with that from BREB regardless of moisture conditions. The experimental design allows a plot and tree scale quantification of evaporation and transpiration respectively. This study confirms for the first time that the MEP-ET originally developed for homogeneous open bare soil and closed canopy can be used for modeling ET over heterogeneous land surfaces. Furthermore, we show that with the addition of an empirical function simulating the plants ability to regulate transpiration, and based on the same measurements of temperature and humidity, the method can produce reliable estimates of ET during both wet and dry conditions without compromising its parsimony.

Constitutive Soil Properties for Unwashed Sand and Kennedy Space Center

NASA Technical Reports Server (NTRS)

Thomas, Michael A.; Chitty, Daniel E.; Gildea, Martin L.; T'Kindt, Casey M.

2008-01-01

Accurate soil models are required for numerical simulations of land landings for the Orion Crew Exploration Vehicle. This report provides constitutive material models for one soil, unwashed sand, from NASA Langley's gantry drop test facility and three soils from Kennedy Space Center (KSC). The four soil models are based on mechanical and compressive behavior observed during geotechnical laboratory testing of remolded soil samples. The test specimens were reconstituted to measured in situ density and moisture content. Tests included: triaxial compression, hydrostatic compression, and uniaxial strain. A fit to the triaxial test results defines the strength envelope. Hydrostatic and uniaxial tests define the compressibility. The constitutive properties are presented in the format of LS-DYNA Material Model 5: Soil and Foam. However, the laboratory test data provided can be used to construct other material models. The four soil models are intended to be specific to the soil conditions discussed in the report. The unwashed sand model represents clayey sand at high density. The KSC models represent three distinct coastal sand conditions: low density dry sand, high density in-situ moisture sand, and high density flooded sand. It is possible to approximate other sands with these models, but the results would be unverified without geotechnical tests to confirm similar soil behavior.

Input-decomposition balance of heterotrophic processes in a warm-temperate mixed forest in Japan

NASA Astrophysics Data System (ADS)

Jomura, M.; Kominami, Y.; Ataka, M.; Makita, N.; Dannoura, M.; Miyama, T.; Tamai, K.; Goto, Y.; Sakurai, S.

2010-12-01

Carbon accumulation in forest ecosystem has been evaluated using three approaches. One is net ecosystem exchange (NEE) estimated by tower flux measurement. The second is net ecosystem production (NEP) estimated by biometric measurements. NEP can be expressed as the difference between net primary production and heterotrophic respiration. NEP can also be expressed as the annual increment in the plant biomass (ΔW) plus soil (ΔS) carbon pools defined as follows; NEP = ΔW+ΔS The third approach needs to evaluate annual carbon increment in soil compartment. Soil carbon accumulation rate could not be measured directly in a short term because of the small amount of annual accumulation. Soil carbon accumulation rate can be estimated by a model calculation. Rothamsted carbon model is a soil organic carbon turnover model and a useful tool to estimate the rate of soil carbon accumulation. However, the model has not sufficiently included variations in decomposition processes of organic matters in forest ecosystems. Organic matter in forest ecosystems have a different turnover rate that creates temporal variations in input-decomposition balance and also have a large variation in spatial distribution. Thus, in order to estimate the rate of soil carbon accumulation, temporal and spatial variation in input-decomposition balance of heterotrophic processes should be incorporated in the model. In this study, we estimated input-decomposition balance and the rate of soil carbon accumulation using the modified Roth-C model. We measured respiration rate of many types of organic matters, such as leaf litter, fine root litter, twigs and coarse woody debris using a chamber method. We can illustrate the relation of respiration rate to diameter of organic matters. Leaf and fine root litters have no diameter, so assumed to be zero in diameter. Organic matters in small size, such as leaf and fine root litter, have high decomposition respiration. It could be caused by the difference in structure of organic matter. Because coarse woody debris has shape of cylinder, microbes decompose from the surface of it. Thus, respiration rate of coarse woody debris is lower than that of leaf and fine root litter. Based on this result, we modified Roth-C model and estimate soil carbon accumulation rate in recent years. Based on the results from a soil survey, the forest soil stored 30tC ha-1 in O and A horizon. We can evaluate the modified model using this result. NEP can be expressed as the annual increment in the plant biomass plus soil carbon pools. So if we can estimate NEP using this approach, then we can evaluate NEP estimated by micrometeorological and ecological approaches and reduce uncertainty of NEP estimation.

Application of the two-source energy balance model to partition evapotranspiration in an arid wine vineyard

NASA Astrophysics Data System (ADS)

Kool, Dilia; Kustas, William P.; Agam, Nurit

2016-04-01

The partitioning of evapotranspiration (ET) into transpiration (T), a productive water use, and soil water evaporation (E), which is generally considered a water loss, is highly relevant to agriculture in the light of increasing desertification and water scarcity. This task is challenged by the complexity of soil and plant interactions, coupled with changes in atmospheric and soil water content conditions. Many of the processes controlling water/energy exchange are not adequately modeled. The two-source energy balance model (TSEB) was evaluated and adapted for independent E and T estimations in an isolated drip-irrigated wine vineyard in the arid Negev desert. The TSEB model estimates ET by computing vegetation and soil energy fluxes using remotely sensed composite surface temperature, local weather data (solar radiation, air temperature and humidity, and wind speed), and vegetation metrics (row spacing, canopy height and width, and leaf area). The soil and vegetation energy fluxes are computed numerically using a system of temperature gradient and resistance equations; where soil and canopy temperatures are derived from the composite surface temperature. For estimation of ET, the TSEB model has been shown to perform well for various agricultural crops under a wide range of environmental conditions, but validation of T and E fluxes is limited to one study in a well-watered cotton crop. Extending the TSEB approach to water-limited vineyards demands careful consideration regarding how the complex canopy structure of vineyards will influence the accuracy of the partitioning between E and T. Data for evaluation of the TSEB model were collected over a season (bud break till harvest). Composite, canopy, and soil surface temperatures were measured using infrared thermometers. The composite vegetation and soil surface energy fluxes were assessed using independent measurements of net radiation, and soil, sensible and latent heat flux. The below canopy energy balance was assessed at the dry midrow position as well as the wet irrigated position directly underneath the vine row, where net radiation and soil heat flux were measured, sensible heat flux was computed indirectly, and E was calculated as the residual. While the below canopy energy balance approach used in this study allowed continuous assessment of E at daily intervals, instantaneous E fluxes could not be assessed due to vertical variability in shading below the canopy. Seasonal partitioning indicated that total E amounted to 9-11% of ET. Initial evaluation of the TSEB model indicated that discrepancies between modeled and measured fluxes can largely be attributed to net radiation partitioning. In addition, large diurnal variation at the soil surface requires adaptation of the soil heat flux formulations. Improved estimation of energy fluxes by accounting for the relatively complex canopy structure of vineyards will be highlighted.

Numerical Modeling of Water Fluxes in the Root Zone of Irrigated Pecan

NASA Astrophysics Data System (ADS)

Shukla, M. K.; Deb, S.

2010-12-01

Information is still limited on the coupled liquid water, water vapor, heat transport and root water uptake for irrigated pecan. Field experiments were conducted in a sandy loam mature pecan field in Las Cruces, New Mexico. Three pecan trees were chosen to monitor diurnal soil water content under the canopy (approximately half way between trunk and the drip line) and outside the drip line (bare spot) along a transect at the depths of 5, 10, 20, 40, and 60 cm using TDR sensors. Soil temperature sensors were installed at an under-canopy locations and bare spot to monitor soil temperature data at depths of 5, 10, 20, and 40 cm. Simulations of the coupled transport of liquid water, water vapor, and heat with and without root water uptake were carried out using the HYDRUS-1D code. Measured soil hydraulic and thermal properties, continuous meteorological data, and pecan characteristics, e.g. rooting depth, leaf area index, were used in the model simulations. Model calibration was performed for a 26-day period from DOY 204 through DOY 230, 2009 based on measured soil water content and soil temperature data at different soil depths, while the model was validated for a 90-day period from DOY 231 through DOY 320, 2009 at bare spot. Calibrated parameters were also used to apply the model at under-canopy locations for a 116-day period from DOY 204 to 320. HYDRUS-1D simulated water contents and soil temperatures correlated well with the measured data at each depth. Numerical assessment of various transport mechanisms and quantitative estimates of isothermal and thermal water fluxes with and without root water uptake in the unsaturated zone within canopy and bare spot is in progress and will be presented in the conference.

Estimation of soil cation exchange capacity using Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS)

NASA Astrophysics Data System (ADS)

Emamgolizadeh, S.; Bateni, S. M.; Shahsavani, D.; Ashrafi, T.; Ghorbani, H.

2015-10-01

The soil cation exchange capacity (CEC) is one of the main soil chemical properties, which is required in various fields such as environmental and agricultural engineering as well as soil science. In situ measurement of CEC is time consuming and costly. Hence, numerous studies have used traditional regression-based techniques to estimate CEC from more easily measurable soil parameters (e.g., soil texture, organic matter (OM), and pH). However, these models may not be able to adequately capture the complex and highly nonlinear relationship between CEC and its influential soil variables. In this study, Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) were employed to estimate CEC from more readily measurable soil physical and chemical variables (e.g., OM, clay, and pH) by developing functional relations. The GEP- and MARS-based functional relations were tested at two field sites in Iran. Results showed that GEP and MARS can provide reliable estimates of CEC. Also, it was found that the MARS model (with root-mean-square-error (RMSE) of 0.318 Cmol+ kg-1 and correlation coefficient (R2) of 0.864) generated slightly better results than the GEP model (with RMSE of 0.270 Cmol+ kg-1 and R2 of 0.807). The performance of GEP and MARS models was compared with two existing approaches, namely artificial neural network (ANN) and multiple linear regression (MLR). The comparison indicated that MARS and GEP outperformed the MLP model, but they did not perform as good as ANN. Finally, a sensitivity analysis was conducted to determine the most and the least influential variables affecting CEC. It was found that OM and pH have the most and least significant effect on CEC, respectively.

Estimating Lead (Pb) Bioavailability In A Mouse Model

EPA Science Inventory

Children are exposed to Pb through ingestion of Pb-contaminated soil. Soil Pb bioavailability is estimated using animal models or with chemically defined in vitro assays that measure bioaccessibility. However, bioavailability estimates in a large animal model (e.g., swine) can be...

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.

Meteorological measurements. Chapter 3

Treesearch

David Y. Hollinger

2008-01-01

Environmental measurements are useful for detecting climatic trends, understanding how the environment influences biological processes, and as input to ecosystem models. Landscape-scale monitoring requires a suite of environmental measures for all of these purposes, including air and soil temperature, humidity, wind speed, precipitation and soil moisture, and different...

Measurement of air and VOC vapor fluxes during gas-driven soil remediation: bench-scale experiments.

PubMed

Kim, Heonki; Kim, Taeyun; Shin, Seungyeop; Annable, Michael D

2012-09-04

In this laboratory study, an experimental method was developed for the quantitative analyses of gas fluxes in soil during advective air flow. One-dimensional column and two- and three-dimensional flow chamber models were used in this study. For the air flux measurement, n-octane vapor was used as a tracer, and it was introduced in the air flow entering the physical models. The tracer (n-octane) in the gas effluent from the models was captured for a finite period of time using a pack of activated carbon, which then was analyzed for the mass of n-octane. The air flux was calculated based on the mass of n-octane captured by the activated carbon and the inflow concentration. The measured air fluxes are in good agreement with the actual values for one- and two-dimensional model experiments. Using both the two- and three-dimensional models, the distribution of the air flux at the soil surface was measured. The distribution of the air flux was found to be affected by the depth of the saturated zone. The flux and flux distribution of a volatile contaminant (perchloroethene) was also measured by using the two-dimensional model. Quantitative information of both air and contaminant flux may be very beneficial for analyzing the performance of gas-driven subsurface remediation processes including soil vapor extraction and air sparging.

Inducing in situ, nonlinear soil response applying an active source

USGS Publications Warehouse

Johnson, P.A.; Bodin, P.; Gomberg, J.; Pearce, F.; Lawrence, Z.; Menq, F.-Y.

2009-01-01

[1] It is well known that soil sites have a profound effect on ground motion during large earthquakes. The complex structure of soil deposits and the highly nonlinear constitutive behavior of soils largely control nonlinear site response at soil sites. Measurements of nonlinear soil response under natural conditions are critical to advancing our understanding of soil behavior during earthquakes. Many factors limit the use of earthquake observations to estimate nonlinear site response such that quantitative characterization of nonlinear behavior relies almost exclusively on laboratory experiments and modeling of wave propagation. Here we introduce a new method for in situ characterization of the nonlinear behavior of a natural soil formation using measurements obtained immediately adjacent to a large vibrator source. To our knowledge, we are the first group to propose and test such an approach. Employing a large, surface vibrator as a source, we measure the nonlinear behavior of the soil by incrementally increasing the source amplitude over a range of frequencies and monitoring changes in the output spectra. We apply a homodyne algorithm for measuring spectral amplitudes, which provides robust signal-to-noise ratios at the frequencies of interest. Spectral ratios are computed between the receivers and the source as well as receiver pairs located in an array adjacent to the source, providing the means to separate source and near-source nonlinearity from pervasive nonlinearity in the soil column. We find clear evidence of nonlinearity in significant decreases in the frequency of peak spectral ratios, corresponding to material softening with amplitude, observed across the array as the source amplitude is increased. The observed peak shifts are consistent with laboratory measurements of soil nonlinearity. Our results provide constraints for future numerical modeling studies of strong ground motion during earthquakes.

Measuring soil moisture with imaging radars

NASA Technical Reports Server (NTRS)

Dubois, Pascale C.; Vanzyl, Jakob; Engman, Ted

1995-01-01

An empirical model was developed to infer soil moisture and surface roughness from radar data. The accuracy of the inversion technique is assessed by comparing soil moisture obtained with the inversion technique to in situ measurements. The effect of vegetation on the inversion is studied and a method to eliminate the areas where vegetation impairs the algorithm is described.

Modelling of the long-term fate of pesticide residues in agricultural soils and their surface exchange with the atmosphere: Part II. Projected long-term fate of pesticide residues.

PubMed

Scholtz, M T; Bidleman, T F

2007-05-01

In the first part of this paper, a simple coupled dynamic soil-atmosphere model for studying the gaseous exchange of pesticide soil residues with the atmosphere is described and evaluated by comparing model results with published measurements of pesticide concentrations in air and soil. In Part II, the model is used to study the concentration profiles of pesticide residues in both undisturbed and annually tilled agricultural soils. Future trends are estimated for the measured air and soil concentrations of lindane and six highly persistent pesticides (toxaphene, p,p'-DDE, dieldrin, cis- and trans-chlordane and trans-nonachlor) over a twenty-year period due to volatilization and leaching into the deeper soil. Wet deposition and particle associated pesticide deposition (that increase soil residue concentrations) and soil erosion, degradation in the soil (other than for lindane) and run-off in precipitation are not considered in this study. Estimates of the rain deposition fluxes are reported that show that, other than for lindane, net volatilization fluxes greatly exceed rain deposition fluxes. The model shows that the persistent pesticides studied are highly immobile in soil and that loss of these highly persistent residues from the soil is by volatilization rather than leaching into the deeper soil. The soil residue levels of these six pesticides are currently sources of net volatilization to the atmosphere and will remain so for many years. The maximum rate of volatilization from the soil was simulated by setting the atmospheric background concentration to zero; these simulations show that the rates of volatilization will not be significantly increased since soil resistance rather than the atmospheric concentration controls the volatilization rates. Annual tilling of the soils increases the volatilization loss to the atmosphere. Nonetheless, the model predicts that, if only air-soil exchange is considered, more than 76% of current persistent pesticide residues will remain after 20 years in the top 7 cm of annually tilled soils. In contrast, lindane is relatively mobile in soil due to weaker binding to soil carbon and leaching of lindane into soil is the main removal route for current lindane residues near the soil surface. The model predicts that the soil is a sink for lindane in the atmosphere and that soil residue levels of lindane in the surface soil are determined by a balance between dry gaseous deposition to the soil from the atmosphere and leaching from the surface soil into the deeper soil where degradation is the dominant loss route. The model suggests that deposition of lindane from the atmosphere will sustain residues in the soil and, in the absence of fresh applications of lindane to the soil, eliminating lindane from the atmosphere would lead to a rapid decline of lindane residues in agricultural soils of the southern U.S.

Limitations of experiments performed in artificially made OECD standard soils for predicting cadmium, lead and zinc toxicity towards organisms living in natural soils.

PubMed

Sydow, Mateusz; Chrzanowski, Łukasz; Cedergreen, Nina; Owsianiak, Mikołaj

2017-08-01

Development of comparative toxicity potentials of cationic metals in soils for applications in hazard ranking and toxic impact assessment is currently jeopardized by the availability of experimental effect data. To compensate for this deficiency, data retrieved from experiments carried out in standardized artificial soils, like OECD soils, could potentially be tapped as a source of effect data. It is, however, unknown whether such data are applicable to natural soils where the variability in pore water concentrations of dissolved base cations is large, and where mass transfer limitations of metal uptake can occur. Here, free ion activity models (FIAM) and empirical regression models (ERM, with pH as a predictor) were derived from total metal EC50 values (concentration with effects in 50% of individuals) using speciation for experiments performed in artificial OECD soils measuring ecotoxicological endpoints for terrestrial earthworms, potworms, and springtails. The models were validated by predicting total metal based EC50 values using backward speciation employing an independent set of natural soils with missing information about ionic composition of pore water, as retrieved from a literature review. ERMs performed better than FIAMs. Pearson's r for log 10 -transformed total metal based EC50s values (ERM) ranged from 0.25 to 0.74, suggesting a general correlation between predicted and measured values. Yet, root-mean-square-error (RMSE) ranged from 0.16 to 0.87 and was either smaller or comparable with the variability of measured EC50 values, suggesting modest performance. This modest performance was mainly due to the omission of pore water concentrations of base cations during model development and their validation, as verified by comparisons with predictions of published terrestrial biotic ligand models. Thus, the usefulness of data from artificial OECD soils for global-scale assessment of terrestrial ecotoxic impacts of Cd, Pb and Zn in soils is limited due to relatively small variability of pore water concentrations of dissolved base cations in OECD soils, preventing their inclusion in development of predictive models. Our findings stress the importance of considering differences in ionic composition of soil pore water when characterizing terrestrial ecotoxicity of cationic metals in natural soils. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling orange tree root water uptake active area by minimally invasive ERT data and transpiration measurements

NASA Astrophysics Data System (ADS)

Vanella, Daniela; Boaga, Jacopo; Perri, Maria Teresa; Consoli, Simona; Cassiani, Giorgio

2015-04-01

The comprehension of the hydrological processes involving plant root dynamics is crucial for implementing water saving measures in agriculture. This is particular urgent in areas, like those Mediterranean, characterized by scarce water availability. The study of root water dynamics should not be separated from a more general analysis of the mass and energy fluxes transferred in the soil-plant-atmosphere continuum. In our study, in order to carry this inclusive approach, minimal invasive 3D time-lapse electrical resistivity tomography (ERT) for soil moisture estimation was combined with plant transpiration fluxes directly measured with Sap Flow (SF) techniques and Eddy Covariance methods, and volumetric soil moisture measurements by TDR probes. The main objective of this inclusive approach was to accurately define root-zone water dynamics and individuate the root-area effectively active for water and nutrient uptake process. The monitoring was carried out in Eastern Sicily (south Italy) in summers 2013 and 2014, within an experimental orange orchard farm. During the first year of experiment (October 2013), ERT measurements were carried out around the pertinent volume of one fully irrigated tree, characterized by a vegetation ground cover of 70%; in the second year (June 2014), ERT monitoring was conducted considering a cutting plant, thus to evaluate soil water dynamics without the significant plant transpiration contribution. In order to explore the hydrological dynamics of the root zone volume surrounded by the monitored tree, the resistivity data acquired during the ERT monitoring were converted into soil moisture content distribution by a laboratory calibration based on the soil electrical properties as a function of moisture content and pore water electrical conductivity. By using ERT data in conjunction with the agro-meteorological information (i.e. irrigation rates, rainfall, evapotranspiration by Eddy Covariance, transpiration by Sap Flow and soil moisture content by TRD) of the test area, a spatially distributed one-dimensional (1D) model that solves the Richards' equation was applied; in the model the van Genuchten parameters were obtained by laboratory analysis of soil water retention and soil permeability at saturation. Results of the 1D model were successfully compared with both ERT-based soil moisture dynamics and TDR measurements of soil moisture. The modelling allows to defining the soil volume interested by root water uptake process and its extent. In particular, this volume results significantly smaller (i.e. surface area of 1.75 m2, with 0.4 m cm thickness) than expected, considering the design of the drip irrigation scheme adopted in the farm. The obtained results confirm that ERT is a technique that (i) can provide a lot of information on small scale and vegetation related processes; (ii) the integration with physical modelling is essential to capture the meaning of space-time signal changes; (iii) in the case of the orange orchard, this approach shows that about half of the irrigated water is wasted.

Measuring and Modeling Root Distribution and Root Reinforcement in Forested Slopes for Slope Stability Calculations

NASA Astrophysics Data System (ADS)

Cohen, D.; Giadrossich, F.; Schwarz, M.; Vergani, C.

2016-12-01

Roots provide mechanical anchorage and reinforcement of soils on slopes. Roots also modify soil hydrological properties (soil moisture content, pore-water pressure, preferential flow paths) via subsurface flow path associated with root architecture, root density, and root-size distribution. Interactions of root-soil mechanical and hydrological processes are an important control of shallow landslide initiation during rainfall events and slope stability. Knowledge of root-distribution and root strength are key components to estimate slope stability in vegetated slopes and for the management of protection forest in steep mountainous area. We present data that show the importance of measuring root strength directly in the field and present methods for these measurements. These data indicate that the tensile force mobilized in roots depends on root elongation (a function of soil displacement), root size, and on whether roots break in tension of slip out of the soil. Measurements indicate that large lateral roots that cross tension cracks at the scarp are important for slope stability calculations owing to their large tensional resistance. These roots are often overlooked and when included, their strength is overestimated because extrapolated from measurements on small roots. We present planned field experiments that will measure directly the force held by roots of different sizes during the triggering of a shallow landslide by rainfall. These field data are then used in a model of root reinforcement based on fiber-bundle concepts that span different spacial scales, from a single root to the stand scale, and different time scales, from timber harvest to root decay. This model computes the strength of root bundles in tension and in compression and their effect on soil strength. Up-scaled to the stand the model yields the distribution of root reinforcement as a function of tree density, distance from tree, tree species and age with the objective of providing quantitative estimates of tree root reinforcement for best management practice of protection forests.

Application of a modeling approach to designate soil and soil organic carbon loss to wind erosion on long-term monitoring sites (BDF) in Northern Germany

NASA Astrophysics Data System (ADS)

Nerger, Rainer; Funk, Roger; Cordsen, Eckhard; Fohrer, Nicola

2017-04-01

Soil organic carbon (SOC) loss is a serious problem in maize monoculture areas of Northern Germany. Sites of the soil monitoring network (SMN) "Boden-Dauerbeobachtung" show long-term soil and SOC losses, which cannot be explained by conventional SOC balances nor by other non-Aeolian causes. Using a process-based model, the main objective was to determine whether these losses can be explained by wind erosion. In the long-term context of 10 years, wind erosion was not measured directly but often observed. A suitable estimation approach linked high-quality soil/farming monitoring data with wind erosion modeling results. The model SWEEP, validated for German sandy soils, was selected using 10-minute wind speed data. Two similar local SMN study sites were compared, however, site A was characterized by high SOC loss and often affected by wind erosion, while the reference site B was not. At site A soil mass and SOC stock decreased by 49.4 and 2.44 kg m-2 from 1999 to 2009. Using SWEEP, a total soil loss of 48.9 kg m-2 resulted for 16 erosion events (max. single event 12.6 kg m-2). A share of 78% was transported by suspension with a SOC enrichment ratio (ER) of 2.96 (saltation ER 0.98), comparable to the literature. At the reference site measured and modeled topsoil losses were minimal. The good agreement between monitoring and modeling results suggested that wind erosion caused significant long-term soil and SOC losses. The approach uses results of prior studies and is applicable to similar well-studied sites without other noteworthy SOC losses.

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)

Estimation of Soil Moisture Profile using a Simple Hydrology Model and Passive Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Soman, Vishwas V.; Crosson, William L.; Laymon, Charles; Tsegaye, Teferi

1998-01-01

Soil moisture is an important component of analysis in many Earth science disciplines. Soil moisture information can be obtained either by using microwave remote sensing or by using a hydrologic model. In this study, we combined these two approaches to increase the accuracy of profile soil moisture estimation. A hydrologic model was used to analyze the errors in the estimation of soil moisture using the data collected during Huntsville '96 microwave remote sensing experiment in Huntsville, Alabama. Root mean square errors (RMSE) in soil moisture estimation increase by 22% with increase in the model input interval from 6 hr to 12 hr for the grass-covered plot. RMSEs were reduced for given model time step by 20-50% when model soil moisture estimates were updated using remotely-sensed data. This methodology has a potential to be employed in soil moisture estimation using rainfall data collected by a space-borne sensor, such as the Tropical Rainfall Measuring Mission (TRMM) satellite, if remotely-sensed data are available to update the model estimates.

Prediction of terrestrial gamma dose rate based on geological formations and soil types in the Johor State, Malaysia.

PubMed

Saleh, Muneer Aziz; Ramli, Ahmad Termizi; bin Hamzah, Khaidzir; Alajerami, Yasser; Moharib, Mohammed; Saeed, Ismael

2015-10-01

This study aims to predict and estimate unmeasured terrestrial gamma dose rate (TGDR) using statistical analysis methods to derive a model from the actual measurement based on geological formation and soil type. The measurements of TGDR were conducted in the state of Johor with a total of 3873 measured points which covered all geological formations, soil types and districts. The measurements were taken 1 m above the soil surface using NaI [Ti] detector. The measured gamma dose rates ranged from 9 nGy h(-1) to 1237 nGy h(-1) with a mean value of 151 nGy h(-1). The data have been normalized to fit a normal distribution. Tests of significance were conducted among all geological formations and soil types, using the unbalanced one way ANOVA. The results indicated strong significant differences due to the different geological formations and soil types present in Johor State. Pearson Correlation was used to measure the relations between gamma dose rate based on geological formation and soil type (D(G,S)) with the gamma dose rate based on geological formation (D(G)) or soil type (D(s)). A very good correlation was found between D(G,S) and D(G) or D(G,S) and D(s). A total of 118 pairs of geological formations and soil types were used to derive the statistical contribution of geological formations and soil types to gamma dose rates. The contribution of the gamma dose rate from geological formation and soil type were found to be 0.594 and 0.399, respectively. The null hypotheses were accepted for 83% of examined data, therefore, the model could be used to predict gamma dose rates based on geological formation and soil type information. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

An update on remote measurement of soil moisture over vegetation using infrared temperature measurements: A FIFE perspective

NASA Technical Reports Server (NTRS)

Carlson, Toby N.

1988-01-01

Using model development, image analysis and micrometeorological measurements, the object is to push beyond the present limitations of using the infrared temperature method for remotely determining surface energy fluxes and soil moisture over vegetation. Model development consists of three aspects: (1) a more complex vegetation formulation which is more flexible and realistic; (2) a method for modeling the fluxes over patchy vegetation cover; and (3) a method for inferring a two-layer soil vertical moisture gradient from analyses of horizontal variations in surface temperatures. HAPEX and FIFE satellite data will be used along with aircraft thermal infrared and solar images as input for the models. To test the models, moisture availability and bulk canopy resistances will be calculated from data collected locally at the Rock Springs experimental field site and, eventually, from the FIFE project.

Tropical forest response to a drier future: Measurement and modeling of soil organic matter stocks and turnover

NASA Astrophysics Data System (ADS)

Finstad, K. M.; Campbell, A.; Pett-Ridge, J.; Zhang, N.; McFarlane, K. J.

2017-12-01

Tropical forests account for over 50% of the global terrestrial carbon sink and 29% of global soil carbon, but the stability of carbon in these ecosystems under a changing climate is unknown. Recent work suggests moisture may be more important than temperature in driving soil carbon storage and emissions in the tropics. However, data on belowground carbon cycling in the tropics is sparse, and the role of moisture on soil carbon dynamics is underrepresented in current land surface models limiting our ability to extrapolate from field experiments to the entire region. We measured radiocarbon (14C) and calculated turnover rates of organic matter from 37 soil profiles from the Neotropics including sites in Mexico, Brazil, Costa Rica, Puerto Rico, and Peru. Our sites represent a large range of moisture, spanning 710 to 4200 mm of mean annual precipitation, and include Andisols, Oxisols, Inceptisols, and Ultisols. We found a large range in soil 14C profiles between sites, and in some locations, we also found a large spatial variation within a site. We compared measured soil C stocks and 14C profiles to data generated from the Community Land Model (CLM) v.4.5 and have begun to generate data from the ACME Land Model (ALM) v.1. We found that the CLM consistently overestimated carbon stocks and the mean age of soil carbon at the surface (upper 50 cm), and underestimated the mean age of deep soil carbon. Additionally, the CLM did not capture the variation in 14C and C stock profiles that exists between and within the sites across the Neotropics. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-736060.

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.

Magnetic soil mapping and modelling for sustainable land use management in Ukraine

NASA Astrophysics Data System (ADS)

Menshov, Oleksandr; Kruglov, Oleksandr; Pereira, Paulo; Sukhorada, Anatoliy

2015-04-01

The agricultural activities need to be monitored in order to observe if they respect the sustainability principles. During the last 15 years we have been using the magnetic susceptibility measurements for the identification of soil properties and degradation risks. This method can be used to measure soil fertility. We observed a decrease of soil magnetic susceptibility values in the areas with high erosion risk. Magnetic susceptibility can be used as an indicator in identifying rates and depths of soil erosion. Compared to other conventional methods, this one, have a low cost and is time saving. This opens new possibilities to have a better cover of the studied area, collect more samples, hence, a better spatial and temporal resolution. Another field of the soil magnetic properties study is the land use change a result of the urban sprawl and technogenic pollution. The increased risk of the soil degradation is connected to soil pollution and the high concentrations of heavy metals and other dangerous chemical elements and compounds to the environment. The main sources of the anthropogenic pollution are the vehicle circulation, power plants, cement and chemical industry. The components released by these sources contain magnetic properties, which can be identified in soils. In this way we can identify the negative impacts of these activities on the ecosystems sustainability and services and promote measures to recover it. We obtained new results on an example of the urban and industry developed sites of Ukraine. The interpretation of soil magnetic parameter measurements depends on knowledge of a reference value. It is influenced by the type of soils and landscape topography. Magnetic methods are an effective method for temporal and spatial soil mapping and modeling. The results of the soils magnetic studies are valuable to sustainable land use management.

A heat and water transfer model for seasonally frozen soils with application to a precipitation-runoff model

USGS Publications Warehouse

Emerson, Douglas G.

1994-01-01

A model that simulates heat and water transfer in soils during freezing and thawing periods was developed and incorporated into the U.S. Geological Survey's Precipitation-Runoff Modeling System. The model's transfer of heat is based on an equation developed from Fourier's equation for heat flux. The model's transfer of water within the soil profile is based on the concept of capillary forces. Field capacity and infiltration rate can vary throughout the freezing and thawing period, depending on soil conditions and rate and timing of snowmelt. The model can be used to determine the effects of seasonally frozen soils on ground-water recharge and surface-water runoff. Data collected for two winters, 1985-86 and 1986-87, on three runoff plots were used to calibrate and verify the model. The winter of 1985-86 was colder than normal, and snow cover was continuous throughout the winter. The winter of 1986-87 was warmer than normal, and snow accumulated for only short periods of several days. as the criteria for determining the degree of agreement between simulated and measured data. The model was calibrated using the 1985-86 data for plot 2. The calibration simulation agreed closely with the measured data. The verification simulations for plots 1 and 3 using the 1985-86 data and for plots 1 and 2 using the 1986-87 data agreed closely with the measured data. The verification simulation for plot 3 using the 1986-87 data did not agree closely. The recalibration simulations for plots 1 and 3 using the 1985-86 data indicated little improvement because the verification simulations for plots 1 and 3 already agreed closely with the measured data.

Predicting the diurnal blue-sky albedo of soils using their laboratory reflectance spectra and roughness indices

NASA Astrophysics Data System (ADS)

Cierniewski, Jerzy; Ceglarek, Jakub; Karnieli, Arnon; Królewicz, Sławomir; Kaźmierowski, Cezary; Zagajewski, Bogdan

2017-10-01

The objective of this study was to assess the relationship between the hyperspectral reflectance of soils and their albedo, measured under various roughness conditions. 108 soil surface measurements were conducted in Poland and Israel. Each surface was characterised by its diurnal albedo variation in the field as well as by its reflectance spectra obtained in the laboratory. The best fit to the model was achieved by post-processing manipulation of the spectra, namely second derivate transformation. Using a stepwise elimination process, four spectral wavelengths and the roughness index were selected for modelling. The resulting models allowed the albedo of a soil to be predicted for its different roughness states and any solar zenith angle, provided that hyperspectral reflectance data is available.

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

Understanding controls of hydrologic processes across two monolithological catchments using model-data integration

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Li, L.

2016-12-01

Field measurements are important to understand the fluxes of water, energy, sediment, and solute in the Critical Zone however are expensive in time, money, and labor. This study aims to assess the model predictability of hydrological processes in a watershed using information from another intensively-measured watershed. We compare two watersheds of different lithology using national datasets, field measurements, and physics-based model, Flux-PIHM. We focus on two monolithological, forested watersheds under the same climate in the Shale Hills Susquehanna CZO in central Pennsylvania: the Shale-based Shale Hills (SSH, 0.08 km2) and the sandstone-based Garner Run (GR, 1.34 km2). We firstly tested the transferability of calibration coefficients from SSH to GR. We found that without any calibration the model can successfully predict seasonal average soil moisture and discharge which shows the advantage of a physics-based model, however, cannot precisely capture some peaks or the runoff in summer. The model reproduces the GR field data better after calibrating the soil hydrology parameters. In particular, the percentage of sand turns out to be a critical parameter in reproducing data. With sandstone being the dominant lithology, GR has much higher sand percentage than SSH (48.02% vs. 29.01%), leading to higher hydraulic conductivity, lower overall water storage capacity, and in general lower soil moisture. This is consistent with area averaged soil moisture observations using the cosmic-ray soil moisture observing system (COSMOS) at the two sites. This work indicates that some parameters, including evapotranspiration parameters, are transferrable due to similar climatic and land cover conditions. However, the key parameters that control soil moisture, including the sand percentage, need to be recalibrated, reflecting the key role of soil hydrological properties.

Modelling soil-water dynamics in the rootzone of structured and water-repellent soils

NASA Astrophysics Data System (ADS)

Brown, Hamish; Carrick, Sam; Müller, Karin; Thomas, Steve; Sharp, Joanna; Cichota, Rogerio; Holzworth, Dean; Clothier, Brent

2018-04-01

In modelling the hydrology of Earth's critical zone, there are two major challenges. The first is to understand and model the processes of infiltration, runoff, redistribution and root-water uptake in structured soils that exhibit preferential flows through macropore networks. The other challenge is to parametrise and model the impact of ephemeral hydrophobicity of water-repellent soils. Here we have developed a soil-water model, which is based on physical principles, yet possesses simple functionality to enable easier parameterisation, so as to predict soil-water dynamics in structured soils displaying time-varying degrees of hydrophobicity. Our model, WEIRDO (Water Evapotranspiration Infiltration Redistribution Drainage runOff), has been developed in the APSIM Next Generation platform (Agricultural Production Systems sIMulation). The model operates on an hourly time-step. The repository for this open-source code is https://github.com/APSIMInitiative/ApsimX. We have carried out sensitivity tests to show how WEIRDO predicts infiltration, drainage, redistribution, transpiration and soil-water evaporation for three distinctly different soil textures displaying differing hydraulic properties. These three soils were drawn from the UNSODA (Unsaturated SOil hydraulic Database) soils database of the United States Department of Agriculture (USDA). We show how preferential flow process and hydrophobicity determine the spatio-temporal pattern of soil-water dynamics. Finally, we have validated WEIRDO by comparing its predictions against three years of soil-water content measurements made under an irrigated alfalfa (Medicago sativa L.) trial. The results provide validation of the model's ability to simulate soil-water dynamics in structured soils.

Measures of Microbial Biomass for Soil Carbon Decomposition Models

NASA Astrophysics Data System (ADS)

Mayes, M. A.; Dabbs, J.; Steinweg, J. M.; Schadt, C. W.; Kluber, L. A.; Wang, G.; Jagadamma, S.

2014-12-01

Explicit parameterization of the decomposition of plant inputs and soil organic matter by microbes is becoming more widely accepted in models of various complexity, ranging from detailed process models to global-scale earth system models. While there are multiple ways to measure microbial biomass, chloroform fumigation-extraction (CFE) is commonly used to parameterize models.. However CFE is labor- and time-intensive, requires toxic chemicals, and it provides no specific information about the composition or function of the microbial community. We investigated correlations between measures of: CFE; DNA extraction yield; QPCR base-gene copy numbers for Bacteria, Fungi and Archaea; phospholipid fatty acid analysis; and direct cell counts to determine the potential for use as proxies for microbial biomass. As our ultimate goal is to develop a reliable, more informative, and faster methods to predict microbial biomass for use in models, we also examined basic soil physiochemical characteristics including texture, organic matter content, pH, etc. to identify multi-factor predictive correlations with one or more measures of the microbial community. Our work will have application to both microbial ecology studies and the next generation of process and earth system models.

Stochastic estimation of plant-available soil water under fluctuating water table depths

NASA Astrophysics Data System (ADS)

Or, Dani; Groeneveld, David P.

1994-12-01

Preservation of native valley-floor phreatophytes while pumping groundwater for export from Owens Valley, California, requires reliable predictions of plant water use. These predictions are compared with stored soil water within well field regions and serve as a basis for managing groundwater resources. Soil water measurement errors, variable recharge, unpredictable climatic conditions affecting plant water use, and modeling errors make soil water predictions uncertain and error-prone. We developed and tested a scheme based on soil water balance coupled with implementation of Kalman filtering (KF) for (1) providing physically based soil water storage predictions with prediction errors projected from the statistics of the various inputs, and (2) reducing the overall uncertainty in both estimates and predictions. The proposed KF-based scheme was tested using experimental data collected at a location on the Owens Valley floor where the water table was artificially lowered by groundwater pumping and later allowed to recover. Vegetation composition and per cent cover, climatic data, and soil water information were collected and used for developing a soil water balance. Predictions and updates of soil water storage under different types of vegetation were obtained for a period of 5 years. The main results show that: (1) the proposed predictive model provides reliable and resilient soil water estimates under a wide range of external conditions; (2) the predicted soil water storage and the error bounds provided by the model offer a realistic and rational basis for decisions such as when to curtail well field operation to ensure plant survival. The predictive model offers a practical means for accommodating simple aspects of spatial variability by considering the additional source of uncertainty as part of modeling or measurement uncertainty.

Soil-atmosphere exchange of ammonia in a non-fertilized grassland: measured emission potentials and inferred fluxes

NASA Astrophysics Data System (ADS)

Wentworth, G. R.; Murphy, J. G.; Gregoire, P. K.; Cheyne, C. A. L.; Tevlin, A. G.; Hems, R.

2014-10-01

A 50-day field study was carried out in a semi-natural, non-fertilized grassland in south-western Ontario, Canada during the late summer and early autumn of 2012. The purpose was to explore surface-atmosphere exchange processes of ammonia (NH3) with a focus on bi-directional fluxes between the soil and atmosphere. Measurements of soil pH and ammonium concentration ([NH4+]) yielded the first direct quantification of soil emission potential (Γsoil = [NH4+]/[H+]) for this land type, with values ranging from 35 to 1850 (an average of 290). The soil compensation point, the atmospheric NH3 mixing ratio below which net emission from the soil will occur, exhibited both a seasonal trend and diurnal trend. Higher daytime and August compensation points were attributed to higher soil temperature. Soil-atmosphere fluxes were estimated using NH3 measurements from the Ambient Ion Monitor Ion Chromatograph (AIM-IC) and a simple resistance model. Vegetative effects were ignored due to the short canopy height and significant Γsoil. Inferred fluxes were, on average, 2.6 ± 4.5 ng m-2 s-1 in August (i.e. net emission) and -5.8 ± 3.0 ng m-2 s-1 in September (i.e. net deposition). These results are in good agreement with the only other bi-directional exchange study in a semi-natural, non-fertilized grassland. A Lagrangian dispersion model (Hybrid Single-Particle Lagrangian Integrated Trajectory - HYSPLIT) was used to calculate air parcel back-trajectories throughout the campaign and revealed that NH3 mixing ratios had no directional bias throughout the campaign, unlike the other atmospheric constituents measured. This implies that soil-atmosphere exchange over a non-fertilized grassland can significantly moderate near-surface NH3 concentrations. In addition, we provide indirect evidence that dew and fog evaporation can cause a morning increase of [NH3]g. Implications of our findings on current NH3 bi-directional exchange modelling efforts are also discussed.

Changes in soil erosion and sediment transport based on the RUSLE model in Zhifanggou watershed, China

NASA Astrophysics Data System (ADS)

Wang, Lei; Qian, Ju; Qi, Wen-Yan; Li, Sheng-Shuang; Chen, Jian-Long

2018-04-01

In this paper, changes of sediment yield and sediment transport were assessed using the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information Systems (GIS). This model was based on the integrated use of precipitation data, Landsat images in 2000, 2005 and 2010, terrain parameters (slope gradient and slope length) and soil composition in Zhifanggou watershed, Gansu Province, Northwestern China. The obtained results were basically consistent with the measured values. The results showed that the mean modulus of soil erosion is 1224, 1118 and 875 t km-2 yr-1 and annual soil loss is 23 130, 21 130 and 16 536 in 2000, 2005 and 2010 respectively. The measured mean erosion modulus were 1581 and 1377 t km-2 yr-1, and the measured annual soil loss were 29 872 and 26 022 t in 2000 and 2005. From 2000 to 2010, the amount of soil erosion was reduced yearly. Very low erosion and low erosion dominated the soil loss status in the three periods, and moderate erosion followed. The zones classified as very low erosion were increasing, whereas the zones with low or moderate erosion were decreasing. In 2010, no zones were classified as high or very high soil erosion.

The perceptual trap: Experimental and modelling examples of soil moisture, hydraulic conductivity and response units in complex subsurface settings.

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Demand, Dominic; Allroggen, Niklas; Loritz, Ralf; Zehe, Erwin

2017-04-01

In order to discuss hypothesis testing in hydrology, the question of the solid foundation of such tests has to be answered. But how certain are we about our measurements of the components of the water balance and the states and dynamics of the complex systems? What implicit assumptions or bias are already embedded in our perception of the processes? How can we find light in the darkness of heterogeneity? We will contribute examples from experimental findings, modelling approaches and landscape analysis to the discussion. Example soil moisture and the soil continuum: The definition of soil moisture as fraction of water in the porous medium assumes locally well-mixed conditions. Moreover, a unique relation of soil water retention presumes instant local thermodynamic equilibrium in the pore water arrangement. We will show findings from soil moisture responses to precipitation events, from irrigation experiments, and from a model study of initial infiltration velocities. The results highlight, that the implicit assumption relating soil moisture state dynamics with actual soil water flow is biased towards the slow end of the actual velocity distribution and rather blind for preferential flow acting in a very small proportion of the pore space. Moreover, we highlight the assumption of a well-defined continuum during the extrapolation of point-scale measurements and why spatially and temporally continuous observation techniques of soil water states are essential for advancing our understanding and development of subsurface process theories. Example hydraulic conductivity: Hydraulic conductivity lies at the heart of hydrological research and modelling. Its values can range across several orders of magnitude at a single site alone. Yet, we often consider it a crisp, effective parameter. We have conducted measurements of soil hydraulic conductivity in the lab and in the field. Moreover, we assessed infiltration capacity and conducted plot-scale irrigation experiments to analyse the apparent vertical soil water velocity for different soils and different measurement techniques. The results give rise to questions about the universality of the Darcy-scale assumptions and a scale-invariant assessment of hydraulic conductivity. Example surface characteristics and subsurface processes: Hydrological models require the identification of some sort of response units based on available data. For this purpose many approaches relating surface properties to hydrological function have been developed. To test the coherence of surface characteristics and subsurface processes we contrasted in situ measurements, pedo-physical analyses of soil samples, an examination of the flow regimes and an investigation of GIS and remote sensing data. Our results show that landscape features and process characteristics do not necessarily align. Landscape classes and pedo-physical property means are not sufficient to define hydrologically functional units.

Measurement of soil lead bioavailability and influence of soil types and properties: A review.

PubMed

Yan, Kaihong; Dong, Zhaomin; Wijayawardena, M A Ayanka; Liu, Yanju; Naidu, Ravi; Semple, Kirk

2017-10-01

Lead (Pb) is a widespread heavy metal which is harmful to human health, especially to young children. To provide a human health risk assessment that is more relevant to real conditions, Pb bioavailability in soils is increasingly employed in the assessment procedure. Both in vivo and in vitro measurements for lead bioavailability are available. In vivo models are time- consuming and expensive, while in vitro models are rapid, economic, reproducible, and reliable while involving more uncertainties. Uncertainties in various measurements create difficulties in accurately predicting Pb bioavailability, resulting in the unnecessary remediation of sites. In this critical review, we utilised available data from in vivo and in vitro studies to identify the key parameters influencing the in vitro measurements, and presented uncertainties existing in Pb bioavailability measurements. Soil type, properties and metal content are reported to influence lead bioavailability; however, the differences in methods for assessing bioavailability and the differences in Pb source limit one's ability to conduct statistical analyses on influences of soil factors on Pb bioavailability. The information provided in the review is fundamentally useful for the measurement of bioavailability and risk assessment practices. Copyright © 2017 Elsevier Ltd. All rights reserved.

A preliminary assessment of the impact of landslide, earthflow, and gully erosion on soil carbon stocks in New Zealand

NASA Astrophysics Data System (ADS)

Basher, Les; Betts, Harley; Lynn, Ian; Marden, Mike; McNeill, Stephen; Page, Mike; Rosser, Brenda

2018-04-01

In geomorphically active landscapes such as New Zealand, quantitative data on the relationship between erosion and soil carbon (C) are needed to establish the effect of erosion on past soil C stocks and future stock changes. The soil C model currently used in New Zealand for soil C stock reporting does not account for erosion. This study developed an approach to characterise the effect of erosion suitable for soil C stock reporting and provides an initial assessment of the magnitude of the effect of erosion. A series of case studies were used to establish the local effect of landslide, earthflow, and gully erosion on soil C stocks and to compare field measurements of soil C stocks with model estimates. Multitemporal erosion mapping from orthophotographs was used to characterise erosion history, identify soil sampling plot locations, and allow soil C stocks to be calculated accounting for erosion. All eroded plots had lower soil C stocks than uneroded (by mass movement and gully erosion) plots sampled at the same sites. Landsliding reduces soil C stocks at plot and landscape scale, largely as a result of individual large storms. After about 70 years, soil C stocks were still well below the value measured for uneroded plots (by 40% for scars and 20-30% for debris tails) indicating that the effect of erosion is very persistent. Earthflows have a small effect on estimates of baseline (1990) soil C stocks and reduce soil C stocks at landscape scale. Gullies have local influence on soil C stocks but because they cover a small proportion of the landscape have little influence at landscape scale. At many of the sites, the soil C model overestimates landscape-scale soil C stocks.

Gravity changes, soil moisture and data assimilation

NASA Astrophysics Data System (ADS)

Walker, J.; Grayson, R.; Rodell, M.; Ellet, K.

2003-04-01

Remote sensing holds promise for near-surface soil moisture and snow mapping, but current techniques do not directly resolve the deeper soil moisture or groundwater. The benefits that would arise from improved monitoring of variations in terrestrial water storage are numerous. The year 2002 saw the launch of NASA's Gravity Recovery And Climate Experiment (GRACE) satellites, which are mapping the Earth's gravity field at such a high level of precision that we expect to be able to infer changes in terrestrial water storage (soil moisture, groundwater, snow, ice, lake, river and vegetation). The project described here has three distinct yet inter-linked components that all leverage off the same ground-based monitoring and land surface modelling framework. These components are: (i) field validation of a relationship between soil moisture and changes in the Earth's gravity field, from ground- and satellite-based measurements of changes in gravity; (ii) development of a modelling framework for the assimilation of gravity data to constrain land surface model predictions of soil moisture content (such a framework enables the downscaling and disaggregation of low spatial (500 km) and temporal (monthly) resolution measurements of gravity change to finer spatial and temporal resolutions); and (iii) further refining the downscaling and disaggregation of space-borne gravity measurements by making use of other remotely sensed information, such as the higher spatial (25 km) and temporal (daily) resolution remotely sensed near-surface soil moisture measurements from the Advanced Microwave Scanning Radiometer (AMSR) instruments on Aqua and ADEOS II. The important field work required by this project will be in the Murrumbidgee Catchment, Australia, where an extensive soil moisture monitoring program by the University of Melbourne is already in place. We will further enhance the current monitoring network by the addition of groundwater wells and additional soil moisture sites. Ground-based gravity measurements will also be made on a monthly basis at each monitoring site. There will be two levels of modelling and monitoring; regional across the entire Murrumbidgee Catchment (100,000 km2), and local across a small sub-catchment (150 km2).

Quantification of seasonal biomass effects on cosmic-ray soil water content determination

NASA Astrophysics Data System (ADS)

Baatz, R.; Bogena, H. R.; Hendricks Franssen, H.; Huisman, J. A.; Qu, W.; Montzka, C.; Korres, W.; Vereecken, H.

2013-12-01

The novel cosmic-ray soil moisture probes (CRPs) measure neutron flux density close to the earth surface. High energy cosmic-rays penetrate the Earth's atmosphere from the cosmos and become moderated by terrestrial nuclei. Hydrogen is the most effective neutron moderator out of all chemical elements. Therefore, neutron flux density measured with a CRP at the earth surface correlates inversely with the hydrogen content in the CRP's footprint. A major contributor to the amount of hydrogen in the sensor's footprint is soil water content. The ability to measure changes in soil water content within the CRP footprint at a larger-than-point scale (~30 ha) and at high temporal resolution (hourly) make these sensors an appealing measurement instrument for hydrologic modeling purposes. Recent developments focus on the identification and quantification of major uncertainties inherent in CRP soil moisture measurements. In this study, a cosmic-ray soil moisture network for the Rur catchment in Western Germany is presented. It is proposed to correct the measured neutron flux density for above ground biomass yielding vegetation corrected soil water content from cosmic-ray measurements. The correction for above ground water equivalents aims to remove biases in soil water content measurements on sites with high seasonal vegetation dynamics such as agricultural fields. Above ground biomass is estimated as function of indices like NDVI and NDWI using regression equations. The regression equations were obtained with help of literature information, ground-based control measurements, a crop growth model and globally available data from the Moderate Resolution Imaging Spectrometer (MODIS). The results show that above ground biomass could be well estimated during the first half of the year. Seasonal changes in vegetation water content yielded biases in soil water content of ~0.05 cm3/cm3 that could be corrected for with the vegetation correction. The vegetation correction has particularly high potential when applied at long term cosmic-ray monitoring sites and the cosmic-ray rover.

Application of geotechnical and geophysical field measurements in an active alpine environment

NASA Astrophysics Data System (ADS)

Lucas, D. R.; Fankhauser, K.; Springman, S. M.

2015-09-01

Rainfall can trigger landslides, rockfalls and debris flow events. When rainfall infiltrates into the soil, the suction (if there is any) is reduced, until positive water pressure can be developed, decreasing the effective stresses and leading to a potential failure. A challenging site for the study of mass movement is the Meretschibach catchment, a location in the Swiss Alps in the vicinity of Agarn, Canton of Valais. To study the effect of rainfall on slope stabilities, the soil characterization provides valuable insight on soil properties, necessary to establish a realistic ground model. This model, together with an effective long term-field monitoring, deliver the essential information and boundary conditions for predicting and validating rainfall- induced slope instabilities using numerical and physical modelling. Geotechnical monitoring, including soil temperature and volumetric water content measurements, has been performed on the study site together with geophysical measurements (ERT) to study the effect of rainfall on the (potential) triggering of landslides on a scree slope composed of a surficial layer of gravelly soil. These techniques were combined to provide information on the soil characteristics and depth to the bedrock. Seasonal changes of precipitation and temperature were reflected in corresponding trends in all measurements. A comparison of volumetric water content records was obtained from decagons, time domain reflectometry (TDR) and electrical resistivity tomography (ERT) conducted throughout the spring and summer months of 2014, yielding a reasonable agreement.

Sediment and solute transport in a mountainous watershed in Valle del Cauca, Colombia

NASA Astrophysics Data System (ADS)

Guzman, C. D.; Castro, A.; Morales, A.; Hoyos, F.; Moreno, P.; Steenhuis, T. S.

2014-12-01

A main goal of this study was to improve prediction of sediment and solute transport using soil surface and soil nutrient changes, based on field measurements, within small watersheds receiving conservation measures. Sediment samples and solute concentrations were measured from two streams in the southwestern region of the Colombian Andes. Two modeling approaches for stream discharge and sediment transport predicted were used with one of these being used for nutrient transport prediction. These streams are a part of a recent initiative from a water fund established by Asobolo, Asocaña, and Cenicaña in collaboration with the Natural Capital Project to improve conservation efforts and monitor their effects. On-site soil depth changes, groundwater depth measurements, and soil nutrient concentrations were also monitored to provide more information about changes within this mountainous watershed during one part of the yearly rainy season. This information is being coupled closely with the outlet sediment concentration and solute concentration patterns to discern correlations. Lateral transects in the upper, middle, and lower part of the hillsides in the Aguaclara watershed of the Rio Bolo watershed network showed differences in soil nutrient status and soil surface depth changes. The model based on semi-distributed hydrology was able to reproduce discharge and sediment transport rates as well as the initially used model indicating available options for comparison of conservation changes in the future.

Electrodynamic soil plate oscillator: Modeling nonlinear mesoscopic elastic behavior and hysteresis in nonlinear acoustic landmine detection

NASA Astrophysics Data System (ADS)

Korman, M. S.; Duong, D. V.; Kalsbeck, A. E.

2015-10-01

An apparatus (SPO), designed to study flexural vibrations of a soil loaded plate, consists of a thin circular elastic clamped plate (and cylindrical wall) supporting a vertical soil column. A small magnet attached to the center of the plate is driven by a rigid AC coil (located coaxially below the plate) to complete the electrodynamic soil plate oscillator SPO design. The frequency dependent mechanical impedance Zmech (force / particle velocity, at the plate's center) is inversely proportional to the electrical motional impedance Zmot. Measurements of Zmot are made using the complex output to input response of a Wheatstone bridge that has an identical coil element in one of its legs. Near resonance, measurements of Zmot (with no soil) before and after a slight point mass loading at the center help determine effective mass, spring, damping and coupling constant parameters of the system. "Tuning curve" behavior of real{ Zmot } and imaginary{ Zmot } at successively higher vibration amplitudes of dry sifted masonry sand are measured. They exhibit a decrease "softening" in resonance frequency along with a decrease in the quality Q factor. In soil surface vibration measurements a bilinear hysteresis model predicts the tuning curve shape for this nonlinear mesoscopic elastic SPO behavior - which also models the soil vibration over an actual plastic "inert" VS 1.6 buried landmine. Experiments are performed where a buried 1m cube concrete block supports a 12 inch deep by 30 inch by 30 inch concrete soil box for burying a VS 1.6 in dry sifted masonry sand for on-the-mine and off-the-mine soil vibration experiments. The backbone curve (a plot of the peak amplitude vs. corresponding resonant frequency from a family of tuning curves) exhibits mostly linear behavior for "on target" soil surface vibration measurements of the buried VS 1.6 or drum-like mine simulants for relatively low particle velocities of the soil. Backbone curves for "on target" measurements exhibit significant curvature when the soil particle velocity is relatively higher. An oscillator with hysteresis modeled by a distribution of parallel spring elements each with a different threshold slip condition seems to describe fairly linear backbone curve behavior [W. D. Iwan, Transactions of the ASME, J. of Applied Mech., 33,(1966), 893-900], while a single bilinear hysteresis element describes the backbone curvature results in the experiments reported here [T. K. Caughey, Transactions of the ASME, J. of Applied Mech., 27, (1960), 640-643]. When "off target" resonances have a different backbone curvature than "on the mine" backbone curves, then false alarms may be eliminated due to resonances from the natural soil layering. See [R. A. Guyer, J. TenCate, and P. Johnson, "Hysteresis and the Dynamic Elasticity of Consolidated Granular Materials," Phys. Rev. Lett., 82, 16 (1999), 3280-3283] for recent models of nonlinear mesoscopic behavior.

Production and transport of gases in the soil: from 1-D soil gas profiles towards 2- and 3-D representations of soil gas processes

NASA Astrophysics Data System (ADS)

Maier, Martin; Lang, Friederike; Schack-Kirchner, Helmer

2017-04-01

Most studies implicitly use a 1 dimensional simplification of soil processes with a dominating vertical profile, e.g in soil physical and chemical properties. In many cases, this is a useful and sufficient representation of the realty which helps to answer research questions in an efficient way. Yet, in some cases, a 2 D or 3 D analysis of the processes is necessary to avoid misinterpretation of experimental results, e.g. modeling the impact of chamber deployment time during the measurement of gas fluxes (von Fischer et al. 2009) or trenching experiments (Jassal et al. 2006). We developed a new method to determine the 2 D patterns of the soil gas diffusion coefficient DS/D0 in situ, using simultaneously several inert tracer gases. Soil gas transport was modelled inversely using the Finite Element Modeling program COMSOL. In combination with measurements of target gases such as CO2, CH4 and N2O, this allowed us for modelling the 2-D patterns of transport and production of CO2, CH4 and N2O in the soil. We observed how methane oxidation and soil respiration zones shifted within the soil profile while the gas fluxes at the surface remain rather stable during a 3 week campaign. The soil was a net sink for N2O, yet, in the subsoil local (weak) source of N2O lead to horizontal fluxes of N2O. We are testing the 3 D approach in the lab on defined substrates and objects to quantify the spatial resolution and reliability of the method. In a next step, we want to test the method in the field and study the ventilation and soil gas fluxes of an ant nest in 3D. References: von Fischer, J. C., G. Butters, P. C. Duchateau, R. J. Thelwell, and R. Siller (2009), In situ measures of methanotroph activity in upland soils: A reaction-diffusion model and field observation of water stress, J. Geophys. Res., 114, G01015, Jassal RS, Black TA (2006) Estimating heterotrophic and autotrophic soil respiration using small-area trenched plot technique: theory and practice. Agric. For. Meteorol. 140:193-202

Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

2013-04-01

Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

Assessment of Soil Erosion in a Cultivated Landscape Using Repeated Measurements of 137Cs

USDA-ARS?s Scientific Manuscript database

Soil erosion is a major environmental concern with the potential to severely impact soil and water quality. Assessments of soil erosion are normally carried out using model predictions. Cesium-137 can be used to provide estimates of soil erosion at a landscape scale, and it remains the best tool to ...

Pipelines subject to slow landslide movements: Structural modeling vs field measurement

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

Bruschi, R.; Glavina, S.; Spinazze, M.

1996-12-01

In recent years finite element techniques have been increasingly used to investigate the behavior of buried pipelines subject to soil movements. The use of these tools provides a rational basis for the definition of minimum wall thickness requirements in landslide crossings. Furthermore the design of mitigation measures or monitoring systems which control the development of undesirable strains in the pipe wall over time, requires a detailed structural modeling. The scope of this paper is to discuss the use of dedicated structural modeling with relevant calibration to field measurements. The strain measurements used were regularly gathered from pipe sections, in twomore » different sites over a period of time long enough to record changes of axial strain due to soil movement. Detailed structural modeling of pipeline layout in both sites and for operating conditions, is applied. Numerical simulations show the influence of the distribution of soil movement acting on the pipeline with regards to the state of strain which can be developed in certain locations. The role of soil nature and direction of relative movements in the definition of loads transferred to the pipeline, is also discussed.« less

A geospatial analysis of soil lead concentrations around regional Oklahoma airports.

PubMed

McCumber, Alexander; Strevett, K A

2017-01-01

Lead has been banned from automobile gasoline since 1995; however, lead is still used as an additive to aviation gasoline (avgas). Airports are now one of the greatest sources of lead air emission in the US. The objectives of this study were (1) to evaluate soil lead levels radially from three regional airports; (2) collect historical meteorological data; (3) examine the soil organic matter content and (4) develop correlation coefficients to evaluate correlations among variables. Soil samples were collected from 3 different airports in Oklahoma and the soil lead concentration was measured using x-ray fluorescence (XRF). The measured soil lead concentrations were plotted with the corresponding GPS location in ArcGIS and Inverse Distance Weight spatial analysis was used to create modeled isopleths of soil lead concentrations. One of the three airports was found to have soil lead concentrations that correlate with soil organic matter with one other showing correlation between soil lead concentration and distance from the airport. The spatial modeled isopleths showed elevated soil lead concentrations in the direction of prevailing winds with "hot spots" near the avgas fueling stations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental evaluation of four infiltration models for calcareous soil irrigated with treated untreated grey water and fresh water

NASA Astrophysics Data System (ADS)

Gharaibeh, M. A.; Eltaif, N. I.; Alrababah, M. A.; Alhamad, M. N.

2009-04-01

Infiltration is vital for both irrigated and rainfed agriculture. The knowledge of infiltration characteristics of a soil is the basic information required for designing an efficient irrigation system. The objective of the present study was to model soil infiltration using four models: Green and Ampt, Horton, Kostaikov and modified Kostiakov. Infiltration tests were conducted on field plot irrigated with treated, untreated greywater and fresh water. The field water infiltration data used in these models were based on double ring infiltrometer tests conducted for 4 h. The algebraic parameters of the infiltration models and nonlinear least squares regression were fitted using measured infiltration time [I (t)] data. Among process-based infiltration models, the Horton model performed best and matched the measured I (t) data with lower sum of squares (SS).

Investigation of Soil Erosion and Phosphorus Transport within an Agricultural Watershed

NASA Astrophysics Data System (ADS)

Klik, A.; Jester, W.; Muhar, A.; Peinsitt, A.; Rampazzo, N.; Mentler, A.; Staudinger, B.; Eder, M.

2003-04-01

In a 40 ha agricultural used watershed in Austria, surface runoff, soil erosion and nutrient losses are measured spatially distributed with 12 small erosion plots. Crops during growing season 2002 are canola, corn, sunflower, winter wheat, winter barley, rye, sugar beets, and pasture. Canopy height and canopy cover are observed in 14-day intervals. Four times per year soil water content, shear stress and random roughness of the surface are measured in a 25 x 25 m grid (140 points). The same raster is sampled for soil texture analyses and content of different phosphorus fractions in the 0-10 cm soil depth. Spatially distributed data are used for geostatistical analysis. Along three transects hydrologic conditions of the hillslope position (top, middle, foot) are investigated by measuring soil water content and soil matrix potential. After erosive events erosion features (rills, deposition, ...) are mapped using GPS. All measured data will be used as input parameters for the Limburg Soil Erosion Model (LISEM).

Linking annual N2O emission in organic soils to mineral nitrogen input as estimated by heterotrophic respiration and soil C/N ratio.

PubMed

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted.

The Integrated Soil Erosion Risk Management Model of Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Setiawan, M. A.; Stoetter, J.; Sartohadi, J.; Christanto, N.

2009-04-01

Many types of soil erosion modeling have been developed worldwide; each of models has its own advantage and assumption based on the originated area. Ironically, in the tropical countries where the rainfall intensity is higher than other area, the soil erosion problem gain less attention. As in Indonesia, due the inadequate supporting data and method to dealing with, the soil erosion management appears to be least prior in the policy decision. Hence, there is increasing necessity towards the initiation and integration of risk management model in the soil erosion, to prevent further land degradation problem in Indonesia. The main research objective is to generate a model which can analyze the dynamic system of soil erosion problem. This model will comprehensively consider four main aspects within the dynamic system analysis, i.e.: soil erosion rate modeling, the tolerable soil erosion rate, total soil erosion cost, and soil erosion management measures. The generating model will involve some sub-software i.e. the PC Raster to maintain the soil erosion modeling, Powersim Constructor Ver. 2.5 as the tool to analyze the dynamic system and Python Ver. 2.6.1 to build the main Graphical User Interface model. The first step addressed in this research is figuring the most appropriate soil erosion model to be applied in Indonesia based on landscape, climate, and data availability condition. This appropriate model must have the simplicity aspect in input data but still deal with the process based analysis. By using the soil erosion model result, the total soil erosion cost will be calculated both on-site and off-site effect. The total soil erosion cost will be stated in Rupiah (Indonesian currency) and Dollar. That total result is then used as one of input parameters for the tolerable soil erosion rate. Subsequently, the tolerable soil erosion rate decides whether the soil erosion rate has exceeded the allowed value or not. If the soil erosion rate has bigger value than the tolerable soil erosion rate, the soil erosion management will be applied base on cost and benefit analysis. The soil erosion management measures will conduct as decision maker of defining the best alternative soil conservation method in a certain area. Besides the engineering and theoretical methods, the local wisdom also will be taken into account in defining the alternative manners of soil erosion management. As a prototype, this integrated model will be generated and simulated in Serayu Watershed, Central Java, since this area has a serious issue in soil erosion problem mainly in the upper stream area (Dieng area). The extraordinary monoculture plantation (potatoes) and very intensive soil tillage without proper soil conservation method has accelerated the soil erosion and depleted the soil fertility. Based on the potatoes productivity data (kg/ha) from 1997-2007 showed that there was a declining trend line, approximately minus 8,2% every year. On the other hand the fertilizer and pesticide consumption in agricultural land are significantly increasing every year. In the same time, the high erosion rate causes serious sedimentation problem in lower stream. Those conditions can be used as study case in determining the element at risk of soil erosion and calculation method for the total soil erosion cost (on-site and off-site effect). Moreover, The Serayu Watershed consists of complex landforms which might have variation of soil erosion tolerable rate. In the future, this integrated model can obtain valuable basis data of the soil erosion hazard in spatial and temporal information including its total cost, the sustainability time of certain land or agriculture area, also the consequences price of applying certain agriculture or soil management. Since this model give result explicitly in spatial and temporal, this model can be used by the local authority to run the land use scenario in term of soil erosion impact before applied them in the real condition. In practice, such integrated model could give more understanding knowledge to the local people about the soil erosion, its processes, impacts, and how to manage that. Keywords: Risk assessment, soil erosion, dynamic system, environmental valuation

Watershed sediment measurement and sediment transport modeling techniques: Case study to quantify the impact of converting cropland to forested stream buffers on soil loss and water quality at the watershed scale

USDA-ARS?s Scientific Manuscript database

Watershed models such as the Soil and Water Assessment Tool (SWAT) have been widely used to simulate watershed hydrologic processes and the effect of management, such as agroforestry, on soil and water resources. In order to use model outputs for tasks ranging from aiding policy decision making to r...

Simulation with models of increasing complexity of CO2 emissions and nitrogen mineralisation, after soil application of labelled pig slurry and maize stalks

NASA Astrophysics Data System (ADS)

Bechini, Luca; Marino Gallina, Pietro; Geromel, Gabriele; Corti, Martina; Cavalli, Daniele

2015-04-01

High amounts of nitrogen are available per unit area in regions with intensive livestock operations. In swine farms, pig slurries are frequently incorporated in the soil together with maize stalks. Simulation models may help to understand nitrogen dynamics associated with animal manure and crop residue decomposition in the soil, and to support the definition of best management practices. The objective of this work was to test the ability of different models to simulate CO2 emissions and nitrogen mineralisation during a laboratory incubation (under optimal soil water content and constant temperature) of maize stalks (ST) and pig slurry (PS). A loam soil was amended with labelled (15N) or unlabelled maize stalks and pig slurries, in the presence of ammonium sulphate (AS). These treatments were established: unfertilised soil; ST15 + AS + PS; ST + AS15 + PS; and ST + AS + PS15. During 180 days, we measured CO2 emissions; microbial biomass C, N, and 15N; and soil mineral N (SMN and SM-15N). Three models of increasing complexity were calibrated using measured data. The models were two modifications of ICBM 2B/N (Kätterer and Andrén, 2001) and CN-SIM (Petersen et al., 2005). The three models simulated rather accurately the emissions of CO2 throughout the incubation period (Relative Root Mean Squared Error, RRMSE = 8-25). The simplest model (with one pool for ST and one for PS) strongly overestimated SMN immobilisation from day 3 to day 21, both in the treatments with AS15 and PS15 (RRMSE = 27-30%). The other two models represented rather well the dynamics of SMN in the soil (RRMSE = 21-25%), simulating a fast increase of nitrate concentration in the first days, and slower rates of nitrification thereafter. Worse performances were obtained with all models for the simulation of SM-15N in the treatment with ST15 (RRMSE = 64-104%): experimental data showed positive mineralization of stalk-derived N from the beginning of the incubation, while models strongly underestimated ST15 mineralisation until day 7. Due to model structure, trade-offs exist between a good simulation of CO2 emissions and a good simulation of SMN. Therefore, simulation performances of the three models are a compromise between the errors in the simulation of C and N dynamics. Thus, some models (especially the simplest one), overestimated or underestimated SMN to match CO2 measurements. This preliminary work emphasised the importance of testing models with both C and N measurements. This reduced the risk of obtaining model parameters suitable for the simulation of N (or opposite C) dynamics that lead to unrealistic simulation of C (or N) decomposition. The use of 15N-labelled materials will help to improve models for the simulation of added organic matter decomposition. Kätterer, T., Andrén, O., 2001. The ICBM family of analytically solved models of soil carbon, nitrogen and microbial biomass dynamics'descriptions and application examples. Ecol. Model. 136, 191-207. doi:10.1016/S0304-3800(00)00420-8. Petersen, B.M., Jensen, L.S., Hansen, S., Pedersen, A., Henriksen, T.M., Sørensen, P., Trinsoutrot-Gattin, I., Berntsen, J., 2005. CN-SIM: a model for the turnover of soil organic matter. II. Short-term carbon and nitrogen development. Soil Biol. Biochem. 37, 375-393. doi:10.1016/j.soilbio.2004.08.007.

Development and application of a soil organic matter-based soil quality index in mineralized terrane of the Western US

USGS Publications Warehouse

Blecker, S.W.; Stillings, Lisa L.; Amacher, M.C.; Ippolito, J.A.; DeCrappeo, N.M.

2013-01-01

Soil quality indices provide a means of distilling large amounts of data into a single metric that evaluates the soil’s ability to carry out key ecosystem functions. Primarily developed in agroecosytems, then forested ecosystems, an index using the relation between soil organic matter and other key soil properties in more semi-arid systems of the Western US impacted by different geologic mineralization was developed. Three different sites in two different mineralization types, acid sulfate and Cu/Mo porphyry in California and Nevada, were studied. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized terrane as well as waste rock and tailings. Eight different microbial parameters (carbon substrate utilization, microbial biomass-C, mineralized-C, mineralized-N and enzyme activities of acid phosphatase, alkaline phosphatase, arylsulfatase, and fluorescein diacetate) along with a number of physicochemical parameters were measured. Multiple linear regression models between these parameters and both total organic carbon and total nitrogen were developed, using the ratio of predicted to measured values as the soil quality index. In most instances, pooling unmineralized and mineralized soil data within a given study site resulted in lower model correlations. Enzyme activity was a consistent explanatory variable in the models across the study sites. Though similar indicators were significant in models across different mineralization types, pooling data across sites inhibited model differentiation of undisturbed and disturbed sites. This procedure could be used to monitor recovery of disturbed systems in mineralized terrane and help link scientific and management disciplines.

Improved soil water deficit estimation through the integration of canopy temperature measurements into a soil water balance model

USDA-ARS?s Scientific Manuscript database

Correct prediction of the dynamics of total available water in the root zone (TAWr) is critical for irrigation management as shown in the soil water balance model presented in FAO paper 56 (Allen et al., 1998). In this study, we propose a framework to improve TAWr estimation by incorporating the cro...

Wildfire impacts on soil-water retention in the Colorado Front Range, United States

USGS Publications Warehouse

Ebel, Brian A.

2012-01-01

This work examined the plot-scale differences in soil-water retention caused by wildfire in the area of the 2010 Fourmile Canyon Fire in the Colorado Front Range, United States. We measured soil-water retention curves on intact cores and repacked samples, soil particle-size distributions, and organic matter content. Estimates were also made of plant-available water based on the soil-water retention curves. Parameters for use in soil-hydraulic property models were estimated; these parameters can be used in unsaturated flow modeling for comparing burned and unburned watersheds. The primary driver for measured differences in soil-water retention in burned and unburned soils was organic matter content and not soil-particle size distribution. The tendency for unburned south-facing soils to have greater organic matter content than unburned north-facing soils in this field area may explain why unburned south-facing soils had greater soil-water retention than unburned north-facing soils. Our results suggest that high-severity wildfire can “homogenize” soil-water retention across the landscape by erasing soil-water retention differences resulting from organic matter content, which for this site may be affected by slope aspect. This homogenization could have important implications for ecohydrology and plant succession/recovery in burned areas, which could be a factor in dictating the window of vulnerability of the landscape to flash floods and erosion that are a common consequence of wildfire.

Wildfire impacts on soil-water retention in the Colorado Front Range, United States

NASA Astrophysics Data System (ADS)

Ebel, Brian A.

2012-12-01

This work examined the plot-scale differences in soil-water retention caused by wildfire in the area of the 2010 Fourmile Canyon Fire in the Colorado Front Range, United States. We measured soil-water retention curves on intact cores and repacked samples, soil particle-size distributions, and organic matter content. Estimates were also made of plant-available water based on the soil-water retention curves. Parameters for use in soil-hydraulic property models were estimated; these parameters can be used in unsaturated flow modeling for comparing burned and unburned watersheds. The primary driver for measured differences in soil-water retention in burned and unburned soils was organic matter content and not soil-particle size distribution. The tendency for unburned south-facing soils to have greater organic matter content than unburned north-facing soils in this field area may explain why unburned south-facing soils had greater soil-water retention than unburned north-facing soils. Our results suggest that high-severity wildfire can "homogenize" soil-water retention across the landscape by erasing soil-water retention differences resulting from organic matter content, which for this site may be affected by slope aspect. This homogenization could have important implications for ecohydrology and plant succession/recovery in burned areas, which could be a factor in dictating the window of vulnerability of the landscape to flash floods and erosion that are a common consequence of wildfire.

Hysteretic sediment fluxes in rainfall-driven soil erosion

NASA Astrophysics Data System (ADS)

Cheraghi, Mohsen; Jomaa, Seifeddine; Sander, Graham C.; Barry, D. Andrew

2017-04-01

Hysteresis patterns of different sediment particle sizes were studied via a detailed laboratory study and modelling. Seven continuous rainfall events with stepwise- varying rainfall intensities (30, 37.5, 45, 60, 45, 37.5 and 30 mm h-1, each 20 min duration) were conducted using a 5-m × 2-m erosion flume. Flow rates and sediment concentration data were measured using flume discharge samples, and interpreted using the Hairsine and Rose (HR) soil erosion model. The total sediment concentration and concentrations of seven particle size classes (< 2, 2-20, 20-50, 50-100, 100-315, 315-1000 and > 1000 μm) were measured. For the total eroded soil and the finer particle sizes (< 2, 2-20 and 20-50 μm), there was a clockwise pattern in the sediment concentration versus discharge curves. However, as the particle size increased, concentrations tended to vary linearly with discharge. The HR model predictions for the total eroded soil and the finer particle size classes (up to 100 μm) were in good agreement with the experimental results. For the larger particles, the model provided qualitative agreement with the measurements but concentration values were different. In agreement with previous investigations using the HR model, these differences were attributed to the HR model's assumption of suspended sediment flow, which does not account for saltation and rolling motions. Keywords: Hysteresis effects, Sediment transport, Flume experiment, Splash soil erosion, Hairsine and Rose model, Particle Swarm Optimization.

Models Robustness for Simulating Drainage and NO3-N Fluxes

NASA Astrophysics Data System (ADS)

Jabro, Jay; Jabro, Ann

2013-04-01

Computer models simulate and forecast appropriate agricultural practices to reduce environmental impact. The objectives of this study were to assess and compare robustness and performance of three models -- LEACHM, NCSWAP, and SOIL-SOILN--for simulating drainage and NO3-N leaching fluxes in an intense pasture system without recalibration. A 3-yr study was conducted on a Hagerstown silt loam to measure drainage and NO3-N fluxes below 1 m depth from N-fertilized orchardgrass using intact core lysimeters. Five N-fertilizer treatments were replicated five times in a randomized complete block experimental design. The models were validated under orchardgrass using soil, water and N transformation rate parameters and C pools fractionation derived from a previous study conducted on similar soils under corn. The model efficiency (MEF) of drainage and NO3-N fluxes were 0.53, 0.69 for LEACHM; 0.75, 0.39 for NCSWAP; and 0.94, 0.91for SOIL-SOILN. The models failed to produce reasonable simulations of drainage and NO3-N fluxes in January, February and March due to limited water movement associated with frozen soil and snow accumulation and melt. The differences between simulated and measured NO3-N leaching and among models' performances may also be related to soil N and C transformation processes embedded in the models These results are a monumental progression in the validation of computer models which will lead to continued diffusion across diverse stakeholders.

A comparison of radiative transfer models for predicting the microwave emission from soils

NASA Technical Reports Server (NTRS)

Schmugge, T. J.; Choudhury, B. J.

1981-01-01

Noncoherent and coherent numerical models for predicting emission from soils are compared. Coherent models use the boundary conditions on the electric fields across the layer boundaries to calculate the radiation intensity, and noncoherent models consider radiation intensities directly. Interference may cause different results in the two approaches when coupling between soil layers in coherent models causes greater soil moisture sampling depths. Calculations performed at frequencies of 1.4 and 19.4 GHz show little difference between the models at 19.4 GHz, although differences are apparent at the lower frequency. A definition for an effective emissivity is also given for when a nonuniform temperature profile is present, and measurements made from a tower show good agreement with calculations from the coherent model.

Modeling soil processes - are we lost in diversity?

NASA Astrophysics Data System (ADS)

Vogel, Hans-Joerg; Schlüter, Steffen

2015-04-01

Soils are among the most complex environmental systems. Soil functions - e.g. production of biomass, habitat for organisms, reactor for and storage of organic matter, filter for ground water - emerge from a multitude of processes interacting at different scales. It still remains a challenge to model and predict these functions including their stability and resilience towards external perturbations. As an inherent property of complex systems it is prohibitive to unravel all the relevant process in all detail to derive soil functions and their dynamics from first principles. Hence, when modeling soil processes and their interactions one is close to be lost in the overwhelming diversity and spatial heterogeneity of soil properties. In this contribution we suggest to look for characteristic similarities within the hyperdimensional state space of soil properties. The underlying hypothesis is that this state space is not evenly and/or randomly populated but that processes of self organization produce attractors of physical, chemical and biological properties which can be identified. (The formation of characteristic soil horizons is an obvious example). To render such a concept operational a suitable and limited set of indicators is required. Ideally, such indicators are i) related to soil functions, ii) are measurable and iii) are integral measures of the relevant physical, chemical and biological soil properties. This would allow for identifying suitable attractors. We will discuss possible indicators and will focus on soil structure as an especially promising candidate. It governs the availability of water and gas, it effects the spatial distribution of organic matter and, moreover, it forms the habitat of soil organisms and it is formed by soil biota. Quantification of soil structural properties became possible only recently with the development of more powerful tools for non-invasive imaging. Future research need to demonstrate in how far these tools can be used to identify functional soil types (i.e. attractors) allowing for modeling soil processes at an integral level. We provide an example from the 100-years fertilization experiment in Bad-Lauchstädt.

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters, and the single scattering albedo. After this climatological calibration, the modeling system can provide L-band brightness temperatures with a global mean absolute bias of less than 10K against SMOS observations, across multiple incidence angles and for horizontal and vertical polarization. Third, seasonal and regional variations in the residual biases are addressed by estimating the vegetation optical depth through state augmentation during the assimilation of the L-band brightness temperatures. This strategy, tested here with SMOS data, is part of the baseline approach for the Level 4 Surface and Root Zone Soil Moisture data product from the planned Soil Moisture Active Passive (SMAP) satellite mission.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

New DEMs may stimulate significant advancements in remote sensing of soil moisture

NASA Astrophysics Data System (ADS)

Nolan, Matt; Fatland, Dennis R.

From Napoleon's defeat at Waterloo to increasing corn yields in Kansas to greenhouse gas flux in the Arctic, the importance of soil moisture is endemic to world affairs and merits the considerable attention it receives from the scientific community. This importance can hardly be overstated, though it often goes unstated.Soil moisture is one of the key variables in a variety of broad areas critical to the conduct of societies' economic and political affairs and their well-being; these include the health of agricultural crops, global climate dynamics, military trafficability planning, and hazards such as flooding and forest fires. Unfortunately the in situ measurement of the spatial distribution of soil moisture on a watershed-scale is practically impossible. And despite decades of international effort, a satellite remote sensing technique that can reliably measure soil moisture with a spatial resolution of meters has not yet been identified or implemented. Due to the lack of suitable measurement techniques and, until recently digital elevation models (DEMs), our ability to understand and predict soil moisture dynamics through modeling has largely remained crippled from birth [Grayson and Bloschl, 200l].

Soil mixing of stratified contaminated sands.

PubMed

Al-Tabba, A; Ayotamuno, M J; Martin, R J

2000-02-01

Validation of soil mixing for the treatment of contaminated ground is needed in a wide range of site conditions to widen the application of the technology and to understand the mechanisms involved. Since very limited work has been carried out in heterogeneous ground conditions, this paper investigates the effectiveness of soil mixing in stratified sands using laboratory-scale augers. This enabled a low cost investigation of factors such as grout type and form, auger design, installation procedure, mixing mode, curing period, thickness of soil layers and natural moisture content on the unconfined compressive strength, leachability and leachate pH of the soil-grout mixes. The results showed that the auger design plays a very important part in the mixing process in heterogeneous sands. The variability of the properties measured in the stratified soils and the measurable variations caused by the various factors considered, highlighted the importance of duplicating appropriate in situ conditions, the usefulness of laboratory-scale modelling of in situ conditions and the importance of modelling soil and contaminant heterogeneities at the treatability study stage.

A new perspective on soil erosion: exploring a thermodynamic approach in a small area of the River Inn catchment

NASA Astrophysics Data System (ADS)

Reid, Lucas; Scherer, Ulrike; Zehe, Erwin

2016-04-01

Soil erosion modeling has always struggled with compensating for the difference in time and spatial scale between model, data and the actual processes involved. This is especially the case with non-event based long-term models based on the Universal Soil Loss Equation (USLE), yet USLE based soil erosion models are among the most common and widely used for they have rather low data requirements and can be applied to large areas. But the majority of mass from soil erosion is eroded within short periods of times during heavy rain events, often within minutes or hours. Advancements of the USLE (eg. the Modified Universal Soil Loss Equation, MUSLE) allow for a daily time step, but still apply the same empirical methods derived from the USLE. And to improve the actual quantification of sediment input into rivers soil erosion models are often combined with a Sediment Delivery Ratio (SDR) to get results within the range of measurements. This is still a viable approach for many applications, yet it leaves much to be desired in terms of understanding and reproducing the processes behind soil erosion and sediment input into rivers. That's why, instead of refining and retuning the existing methods, we explore a more comprehensive, physically consistent description on soil erosion. The idea is to describe soil erosion as a dissipative process (Kleidon et al., 2013) and test it in a small sub-basin of the River Inn catchment area in the pre-Alpine foothills. We then compare the results to sediment load measurements from the sub-basin and discuss the advantages and issues with the application of such an approach.

Quasi 3D modelling of water flow in the sandy soil

NASA Astrophysics Data System (ADS)

Rezaei, Meisam; Seuntjens, Piet; Joris, Ingeborg; Boënne, Wesley; De Pue, Jan; Cornelis, Wim

2016-04-01

Monitoring and modeling tools may improve irrigation strategies in precision agriculture. Spatial interpolation is required for analyzing the effects of soil hydraulic parameters, soil layer thickness and groundwater level on irrigation management using hydrological models at field scale. We used non-invasive soil sensor, a crop growth (LINGRA-N) and a soil hydrological model (Hydrus-1D) to predict soil-water content fluctuations and crop yield in a heterogeneous sandy grassland soil under supplementary irrigation. In the first step, the sensitivity of the soil hydrological model to hydraulic parameters, water stress, crop yield and lower boundary conditions was assessed after integrating models at one soil column. Free drainage and incremental constant head conditions were implemented in a lower boundary sensitivity analysis. In the second step, to predict Ks over the whole field, the spatial distributions of Ks and its relationship between co-located soil ECa measured by a DUALEM-21S sensor were investigated. Measured groundwater levels and soil layer thickness were interpolated using ordinary point kriging (OK) to a 0.5 by 0.5 m in aim of digital elevation maps. In the third step, a quasi 3D modelling approach was conducted using interpolated data as input hydraulic parameter, geometric information and boundary conditions in the integrated model. In addition, three different irrigation scenarios namely current, no irrigation and optimized irrigations were carried out to find out the most efficient irrigation regime. In this approach, detailed field scale maps of soil water stress, water storage and crop yield were produced at each specific time interval to evaluate the best and most efficient distribution of water using standard gun sprinkler irrigation. The results show that the effect of the position of the groundwater level was dominant in soil-water content prediction and associated water stress. A time-dependent sensitivity analysis of the hydraulic parameters showed that changes in soil water content are mainly affected by the soil saturated hydraulic conductivity Ks in a two-layered soil. Results demonstrated the large spatial variability of Ks (CV = 86.21%). A significant negative correlation was found between ln Ks and ECa (r = 0.83; P≤0.01). This site-specific relation between ln Ks and ECa was used to predict Ks for the whole field after validation using an independent dataset of measured Ks. Result showed that this approach can accurately determine the field scale irrigation requirements, taking into account variations in boundary conditions and spatial variations of model parameters across the field. We found that uniform distribution of water using standard gun sprinkler irrigation is not an efficient approach since at locations with shallow groundwater, the amount of water applied will be excessive as compared to the crop requirements, while in locations with a deeper groundwater table, the crop irrigation requirements will not be met during crop water stress. Numerical results showed that optimal irrigation scheduling using the aforementioned water stress calculations can save up to ~25% irrigation water as compared to the current irrigation regime. This resulted in a yield increase of ~7%, simulated by the crop growth model.

Process-based modeling of temperature and water profiles in the seedling recruitment zone: Part I. Model validation

USDA-ARS?s Scientific Manuscript database

Process-based modeling provides detailed spatial and temporal information of the soil environment in the shallow seedling recruitment zone across field topography where measurements of soil temperature and water may not sufficiently describe the zone. Hourly temperature and water profiles within the...

The Use of Mixed Effects Models for Obtaining Low-Cost Ecosystem Carbon Stock Estimates in Mangroves of the Asia-Pacific

NASA Astrophysics Data System (ADS)

Bukoski, J. J.; Broadhead, J. S.; Donato, D.; Murdiyarso, D.; Gregoire, T. G.

2016-12-01

Mangroves provide extensive ecosystem services that support both local livelihoods and international environmental goals, including coastal protection, water filtration, biodiversity conservation and the sequestration of carbon (C). While voluntary C market projects that seek to preserve and enhance forest C stocks offer a potential means of generating finance for mangrove conservation, their implementation faces barriers due to the high costs of quantifying C stocks through measurement, reporting and verification (MRV) activities. To streamline MRV activities in mangrove C forestry projects, we develop predictive models for (i) biomass-based C stocks, and (ii) soil-based C stocks for the mangroves of the Asia-Pacific. We use linear mixed effect models to account for spatial correlation in modeling the expected C as a function of stand attributes. The most parsimonious biomass model predicts total biomass C stocks as a function of both basal area and the interaction between latitude and basal area, whereas the most parsimonious soil C model predicts soil C stocks as a function of the logarithmic transformations of both latitude and basal area. Random effects are specified by site for both models, and are found to explain a substantial proportion of variance within the estimation datasets. The root mean square error (RMSE) of the biomass C model is approximated at 24.6 Mg/ha (18.4% of mean biomass C in the dataset), whereas the RMSE of the soil C model is estimated at 4.9 mg C/cm 3 (14.1% of mean soil C). A substantial proportion of the variation in soil C, however, is explained by the random effects and thus the use of the SOC model may be most valuable for sites in which field measurements of soil C exist.

Multifractal Model of Soil Water Erosion

NASA Astrophysics Data System (ADS)

Oleshko, Klaudia

2017-04-01

Breaking of solid surface symmetry during the interaction between the rainfall of high erosivity index and internally unstable volcanic soil/vegetation systems, results in roughness increasing as well as fertile horizon loosing. In these areas, the sustainability of management practices depends on the ability to select and implement the precise indicators of soil erodibility and vegetation capacity to protect the system against the extreme damaging precipitation events. Notwithstanding, the complex, non-linear and scaling nature of the phenomena involved in the interaction among the soil, vegetation and precipitation is still not taken into account by the numerous commonly used empirical, mathematical and computer simulation models: for instance, by the universal soil loss equation (USLE). The soil erodibility factor (K-factor) is still measuring by a set of empirical, dimensionless parameters and indexes, without taking into account the scaling (frequently multifractal) origin of a broad range of heterogeneous, anisotropic and dynamical phenomena involved in hydric erosion. Their mapping is not representative of this complex system spatial variability. In our research, we propose to use the toolbox of fractals and multifractals techniques in vista of its ability to measure the scale invariance and type/degree of soil, vegetation and precipitation symmetry breaking. The hydraulic units are chosen as the precise measure of soil/vegetation stability. These units are measured and modeled for soils with contrasting architecture, based on their porosity/permeability (Poroperm) as well as retention capacity relations. The simple Catalog of the most common Poroperm relations is proposed and the main power law relations among the elements of studied system are established and compared for some representative agricultural and natural Biogeosystems of Mexico. All resulted are related with the Mandelbrot' Baby Theorem in order to construct the universal Phase Diagram which graphically represents the critical points of the dynamics of soil erodibility as function of the vegetation cover and precipitation parameters.

Modelling in situ enzyme potential of soils: a tool to predict soil respiration from agricultural fields

NASA Astrophysics Data System (ADS)

Shahbaz Ali, Rana; Poll, Christian; Demyan, Scott; Nkwain Funkuin, Yvonne; Ingwersen, Joachim; Wizemann, Hans-Dieter; Kandeler, Ellen

2014-05-01

The fate of soil organic carbon (SOC) is one of the largest uncertainties in predicting future climate and terrestrial ecosystem functions. Extra-cellular enzymes, produced by microorganisms, perform the very first step in SOC degradation and serve as key components in global carbon cycling. Very little information is available about the seasonal variation in the temperature sensitivity of soil enzymes. Here we aim to model in situ enzyme potentials involved in the degradation of either labile or recalcitrant organic compounds to understand the temporal variability of degradation processes. To identify the similarities in seasonal patterns of soil respiration and in situ enzyme potentials, we compared the modelled in situ enzyme activities with weekly measured soil CO2 emissions. Arable soil samples from two different treatments (4 years fallow and currently vegetated plots; treatments represent range of carbon input into soil) were collected every month from April, 2012 to April, 2013, from two different study regions (Kraichgau and Swabian Alb) in Southwest Germany. The vegetation plots were under crop rotation in both study areas. We measured activities of three enzymes including β-glucosidase, xylanase and phenoloxidase at five different temperatures. We also measured soil microbial biomass in form of microbial carbon (Cmic). Land-use and area had significant effects (P < 0.001) on the microbial biomass; fallow plots having less Cmic than vegetation plots. Potential activities of β-glucosidase (P < 0.001) and xylanase (P < 0.01) were significantly higher in the vegetation plots of the Swabian Alb region than in the Kraichgau region. In both study areas, enzyme activities were higher during vegetation period and lower during winter which points to the importance of carbon input and/or temperature and soil moisture. We calculated the temperature sensitivity (Q10) of enzyme activities based on laboratory measurements of enzyme activities at a range of incubation temperatures. Q10 of β-glucosidase activity changed significantly across the year (Q10 values ranges from 1.5 to 2.0 in Kraichgau and 1.6 to 2.1 in Swabian Alb), while for xylanase activity, no significant effects were found (Q10 values ranges from 1.2 to 3.0 in Kraichgau and 1.3 to 3.3 in Swabian Alb) in both study regions. By using laboratory based enzyme activities, calculated Q10 values, and daily soil temperature data, we modelled in situ enzyme potentials in soils for labile and recalcitrant carbon pools for both study regions. We observed an increase in modelled in situ enzyme activities during the summer period and a substantial decrease during winter indicating temperature as a strong controlling factor. A significant higher positive correlation of soil surface CO2 flux with modelled in situ β-glucosidase activity was found in both study regions compared to modelled in situ xylanase activity. These results demonstrate that (1) Q10 values are site and season specific and should be added into carbon models and (2) the indication of the relevance of greater contribution of labile carbon pool to soil CO2 emissions.

Improving Representations of Near-Surface Permafrost and Soil Temperature Profiles in the Regional Arctic System Model (RASM)

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Hamman, J.; Nijssen, B.

2017-12-01

Permafrost and seasonally frozen soils are a key characteristic of the terrestrial Arctic, and the fate of near-surface permafrost as a result of climate change is projected to have strong impacts on terrestrial biogeochemistry. The active layer thickness (ALT) is the layer of soil that freezes and thaws annually, and shifts in the depth of the ALT are projected to occur over large areas of the Arctic that are characterized by discontinuous permafrost. Faithful representation of permafrost in land models in climate models is a product of both soil dynamics and the coupling of air and soil temperatures. A common problem is a large bias in simulated ALT due to a model depth that is too shallow. Similarly, soil temperatures often show systematic biases, which lead to biases in air temperature due to poorly modeled air-soil temperature feedbacks in a coupled environment. In this study, we use the Regional Arctic System Model (RASM), a fully-coupled regional earth system model that is run at a 50-km land/atmosphere resolution over a pan-Arctic domain and uses the Variable Infiltration Capacity (VIC) model as its land model. To understand what modeling decisions are necessary to accurately represent near-surface permafrost and soil temperature profiles, we perform a large number of RASM simulations with prescribed atmospheric forcings (e.g. VIC in standalone mode in RASM) while varying the model soil depth, thickness of soil moisture layers, number of soil layers and the distribution of soil nodes. We compare modeled soil temperatures and ALT to observations from the Circumpolar Active Layer Monitoring (CALM) network. CALM observations include annual ALT observations as well as daily soil temperature measurements at three soil depths for three sites in Alaska. In the future, we will use our results to inform our modeling of permafrost dynamics in fully-coupled RASM simulations.

Wave-current induced erosion of cohesive riverbanks in northern Manitoba, Canada

NASA Astrophysics Data System (ADS)

Kimiaghalam, N.; Clark, S.; Ahmari, H.; Hunt, J.

2015-03-01

The field of cohesive soil erosion is still not fully understood, in large part due to the many soil parameters that affect cohesive soil erodibility. This study is focused on two channels, 2-Mile and 8-Mile channels in northern Manitoba, Canada, that were built to connect Lake Winnipeg with Playgreen Lake and Playgreen Lake with Kiskikittogisu Lake, respectively. The banks of the channels consist of clay rich soils and alluvial deposits of layered clay, silts and sands. The study of erosion at the sites is further complicated because the flow-induced erosion is combined with the effects of significant wave action due to the large fetch length on the adjacent lakes, particularly Lake Winnipeg that is the seventh largest lake in North America. The study included three main components: field measurements, laboratory experiments and numerical modelling. Field measurements consisted of soil sampling from the banks and bed of the channels, current measurements and water sampling. Grab soil samples were used to measure the essential physical and electrochemical properties of the riverbanks, and standard ASTM Shelby tube samples were used to estimate the critical shear stress and erodibility of the soil samples using an erosion measurement device (EMD). Water samples were taken to estimate the sediment concentration profile and also to monitor changes in sediment concentration along the channels over time. An Acoustic Doppler Current Profiler (ADCP) was used to collect bathymetry and current data, and two water level gauges have been installed to record water levels at the entrance and outlet of the channels. The MIKE 21 NSW model was used to simulate waves using historical winds and measured bathymetry of the channels and lakes. Finally, results from the wave numerical model, laboratory tests and current measurement were used to estimate the effect of each component on erodibility of the cohesive banks.

Linking Belowground Plant Traits With Ecosystem Processes: A Multi-Biome Perspective

NASA Astrophysics Data System (ADS)

Iversen, C. M.; Norby, R. J.; Childs, J.; McCormack, M. L.; Walker, A. P.; Hanson, P. J.; Warren, J.; Sloan, V. L.; Sullivan, P. F.; Wullschleger, S.; Powell, A. S.

2015-12-01

Fine plant roots are short-lived, narrow-diameter roots that play an important role in ecosystem carbon, water, and nutrient cycling in biomes ranging from the tundra to the tropics. Root ecologists make measurements at a millimeter scale to answer a question with global implications: In response to a changing climate, how do fine roots modulate the exchange of carbon between soils and the atmosphere and how will this response affect our future climate? In a Free-Air CO2 Enrichment experiment in Oak Ridge, TN, elevated [CO2] caused fine roots to dive deeper into the soil profile in search of limiting nitrogen, which led to increased soil C storage in deep soils. In contrast, the fine roots of trees and shrubs in an ombrotrophic bog are constrained to nutrient-poor, oxic soils above the average summer water table depth, though this may change with warmer, drier conditions. Tundra plant species are similarly constrained to surface organic soils by permafrost or waterlogged soils, but have many adaptations that alter ecosystem C fluxes, including aerenchyma that oxygenate the rhizosphere but also allow direct methane flux to the atmosphere. FRED, a global root trait database, will allow terrestrial biosphere models to represent the complexity of root traits across the globe, informing both model representation of ecosystem C and nutrient fluxes, but also the gaps where measurements are needed on plant-soil interactions (for example, in the tropical biome). While the complexity of mm-scale measurements may never have a place in large-scale global models, close collaboration between empiricists and modelers can help to guide the scaling of important, yet small-scale, processes to quantify their important roles in larger-scale ecosystem fluxes.

Soil as a Sustainable Resource for the Bioeconomy - BonaRes

NASA Astrophysics Data System (ADS)

Wollschläger, Ute; Amelung, Wulf; Brüggemann, Nicolas; Brunotte, Joachim; Gebbers, Robin; Grosch, Rita; Heinrich, Uwe; Helming, Katharina; Kiese, Ralf; Leinweber, Peter; Reinhold-Hurek, Barbara; Veldkamp, Edzo; Vogel, Hans-Jörg; Winkelmann, Traud

2017-04-01

Fertile soils are a fundamental resource for the production of biomass and provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for bio-based products which require preserving and - ideally - improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained: filter for clean water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these soil functions result from the interaction of a multitude of physical, chemical and biological processes which are insufficiently understood. In addition, we lack understanding about the interplay between the socio-economic system and the soil system and how soil functions benefit human wellbeing, including SDGs. However, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management. To make soil management sustainable, we need to establish a scientific knowledge base of complex soil system processes that allows for developing models and tools to quantitatively predict the impact of a multitude of management measures on soil functions. This will finally allow for the provision of options for a site-specific, sustainable soil management. To face this challenge, the German Federal Ministry of Education and Research (BMBF) recently launched the funding program "Soil as a Sustainable Resource for the Bioeconomy - BonaRes". In a joint effort, ten collaborative projects and the coordinating BonaRes Centre are engaged to close existing knowledge gaps for a profound and systemic assessment and understanding of soil functions and their sensitivity to soil management. In BonaRes, the complete process chain of sustainable soil use in the context of a sustainable bio-economy is being addressed: from understanding of soil processes using state-of the art and novel measurement and modelling techniques towards soil functions and ecosystem services driving the development of assessment and decision support tools for a sustainable soil management. To this end, soil scientists and researchers from several other disciplines including social sciences are collaborating closely. Besides a better understanding of fundamental soil processes from each of the collaborative projects and the development of novel measurement techniques and models, the outcome of the joint BonaRes programme will be a web-based portal (www.bonares.de) providing information, knowledge, models, a data repository with doi-referenced, internationally available, open soil data from the BonaRes funding initiative and beyond, as well as decision support options for a sustainable soil management. This presentation will provide an overview about the BonaRes funding initiative and the research conducted therein.

Soil property effects on wind erosion of organic soils

NASA Astrophysics Data System (ADS)

Zobeck, Ted M.; Baddock, Matthew; Scott Van Pelt, R.; Tatarko, John; Acosta-Martinez, Veronica

2013-09-01

Histosols (also known as organic soils, mucks, or peats) are soils that are dominated by organic matter (OM > 20%) in half or more of the upper 80 cm. Forty two states have a total of 21 million ha of Histosols in the United States. These soils, when intensively cropped, are subject to wind erosion resulting in loss of crop productivity and degradation of soil, air, and water quality. Estimating wind erosion on Histosols has been determined by USDA-Natural Resources Conservation Service (NRCS) as a critical need for the Wind Erosion Prediction System (WEPS) model. WEPS has been developed to simulate wind erosion on agricultural land in the US, including soils with organic soil material surfaces. However, additional field measurements are needed to understand how soil properties vary among organic soils and to calibrate and validate estimates of wind erosion of organic soils using WEPS. Soil properties and sediment flux were measured in six soils with high organic contents located in Michigan and Florida, USA. Soil properties observed included organic matter content, particle density, dry mechanical stability, dry clod stability, wind erodible material, and geometric mean diameter of the surface aggregate distribution. A field portable wind tunnel was used to generate suspended sediment and dust from agricultural surfaces for soils ranging from 17% to 67% organic matter. The soils were tilled and rolled to provide a consolidated, friable surface. Dust emissions and saltation were measured using an isokinetic vertical slot sampler aspirated by a regulated suction source. Suspended dust was sampled using a Grimm optical particle size analyzer. Particle density of the saltation-sized material (>106 μm) was inversely related to OM content and varied from 2.41 g cm-3 for the soil with the lowest OM content to 1.61 g cm-3 for the soil with highest OM content. Wind erodible material and the geometric mean diameter of the surface soil were inversely related to dry clod stability. The effect of soil properties on sediment flux varied among flux types. Saltation flux was adequately predicted with simple linear regression models. Dry mechanical stability was the best single soil property linearly related to saltation flux. Simple linear models with soil properties as independent variables were not well correlated with PM10E values (mass flux). A second order polynomial equation with OM as the independent variable was found to be most highly correlated with PM10E values. These results demonstrate that variations in sediment and dust emissions can be linked to soil properties using simple models based on one or more soil properties to estimate saltation mass flux and PM10E values from organic and organic-rich soils.

Using Historical Precipitation, Temperature, and Runoff Observations to Evaluate Evaporation Formulations in Land Surface Models

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Mahanama, P. P.

2012-01-01

Key to translating soil moisture memory into subseasonal precipitation and air temperature forecast skill is a realistic treatment of evaporation in the forecast system used - in particular, a realistic treatment of how evaporation responds to variations in soil moisture. The inherent soil moisture-evaporation relationships used in today's land surface models (LSMs), however, arguably reflect little more than guesswork given the lack of evaporation and soil moisture data at the spatial scales represented by regional and global models. Here we present a new approach for evaluating this critical aspect of LSMs. Seasonally averaged precipitation is used as a proxy for seasonally-averaged soil moisture, and seasonally-averaged air temperature is used as a proxy for seasonally-averaged evaporation (e.g., more evaporative cooling leads to cooler temperatures) the relationship between historical precipitation and temperature measurements accordingly mimics in certain important ways nature's relationship between soil moisture and evaporation. Additional information on the relationship is gleaned from joint analysis of precipitation and streamflow measurements. An experimental framework that utilizes these ideas to guide the development of an improved soil moisture-evaporation relationship is described and demonstrated.

Statistical Modelling of the Soil Dielectric Constant

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Marczewski, Wojciech; Bogdan Usowicz, Jerzy; Lipiec, Jerzy

2010-05-01

The dielectric constant of soil is the physical property being very sensitive on water content. It funds several electrical measurement techniques for determining the water content by means of direct (TDR, FDR, and others related to effects of electrical conductance and/or capacitance) and indirect RS (Remote Sensing) methods. The work is devoted to a particular statistical manner of modelling the dielectric constant as the property accounting a wide range of specific soil composition, porosity, and mass density, within the unsaturated water content. Usually, similar models are determined for few particular soil types, and changing the soil type one needs switching the model on another type or to adjust it by parametrization of soil compounds. Therefore, it is difficult comparing and referring results between models. The presented model was developed for a generic representation of soil being a hypothetical mixture of spheres, each representing a soil fraction, in its proper phase state. The model generates a serial-parallel mesh of conductive and capacitive paths, which is analysed for a total conductive or capacitive property. The model was firstly developed to determine the thermal conductivity property, and now it is extended on the dielectric constant by analysing the capacitive mesh. The analysis is provided by statistical means obeying physical laws related to the serial-parallel branching of the representative electrical mesh. Physical relevance of the analysis is established electrically, but the definition of the electrical mesh is controlled statistically by parametrization of compound fractions, by determining the number of representative spheres per unitary volume per fraction, and by determining the number of fractions. That way the model is capable covering properties of nearly all possible soil types, all phase states within recognition of the Lorenz and Knudsen conditions. In effect the model allows on generating a hypothetical representative of the soil type, and that way it enables clear comparing to results from other soil type dependent models. The paper is focused on proper representing possible range of porosity in commonly existing soils. This work is done with aim of implementing the statistical-physical model of the dielectric constant to a use in the model CMEM (Community Microwave Emission Model), applicable to SMOS (Soil Moisture and Ocean Salinity ESA Mission) data. The input data to the model clearly accepts definition of soil fractions in common physical measures, and in opposition to other empirical models, does not need calibrating. It is not dependent on recognition of the soil by type, but instead it offers the control of accuracy by proper determination of the soil compound fractions. SMOS employs CMEM being funded only by the sand-clay-silt composition. Common use of the soil data, is split on tens or even hundreds soil types depending on the region. We hope that only by determining three element compounds of sand-clay-silt, in few fractions may help resolving the question of relevance of soil data to the input of CMEM, for SMOS. Now, traditionally employed soil types are converted on sand-clay-silt compounds, but hardly cover effects of other specific properties like the porosity. It should bring advantageous effects in validating SMOS observation data, and is taken for the aim in the Cal/Val project 3275, in the campaigns for SVRT (SMOS Validation and Retrieval Team). Acknowledgements. This work was funded in part by the PECS - Programme for European Cooperating States, No. 98084 "SWEX/R - Soil Water and Energy Exchange/Research".

Coupled isotopic and simulation modeling of gaseous nitrogen losses from tropical rainforests

NASA Astrophysics Data System (ADS)

Bai, E.; Houlton, B.

2008-12-01

Gaseous nitrogen (N) losses remove fixed N from the biosphere and play an important role in regulating Earth's climate system. Current techniques for directly measuring gaseous N fluxes are still limited, however, and many uncertainties remain. We combined natural isotopic and simulation modeling (DAYCENT; daily version of CENTURY) to examine the extent to which N isotopes offer meaningful constraint to estimates of large-scale gaseous N emissions from terrestrial ecosystems. The isotope model considers two scenarios: in the first, soil δ15N is a linear function of fraction of gaseous N losses; in the second, underexpression of the isotope effect of denitrification is considered and soil 15N/14N is determined by both the fraction of gaseous losses and the proportion of nitrate consumed locally by denitrification. We examined the coupled simulation and isotope-based model along two Hawaiian rainforest gradients which span a range of tropical rainfall climates, soil biogeochemical ages and ecosystem 15N/14N. Under most conditions (MAP < 4050 mm and age > 2100 yr), modeled soil 15N/14N ratios agreed reasonably well with measurements (r2 = 0.53), consistent with full expression of a field-calibrated isotope effect (scenario 1). In very wet sites (MAP > 4050 mm), locally complete consumption of nitrate appears to lower the effective isotope effect of denitrification at ecosystem levels, resulting in soil 15N/14N ratios that approach those of the N inputs (i.e., scenario 2). Replacing DAYCENT simulation results with field-based measures of N gas fluxes (NOx + N2O) yielded consistently lower estimates of soil 15N/14N ratios across the forests, pointing to a missing gas N loss term (i.e., N2), inadequate coverage of spatial and temporal heterogeneity by empirical measures or both. These results demonstrate the potential for soil N isotopes to constrain N gas fluxes at large geographic scales, implying a quantitative tracer for gaseous N losses from terrestrial ecosystems.

Validating HYLARSMET: a Hydrologically Consistent Land Surface Model for Soil Moisture and Evapotranspiration Modelling over Southern Africa using Remote Sensing and Meteorological Data

NASA Astrophysics Data System (ADS)

Sinclair, Scott; Pegram, Geoff; Mengitsu, Michael; Everson, Colin

2015-04-01

Timeous knowledge of the spatial distribution of soil moisture and evapotranspiration over a large region in fine detail has great value for coping with two weather extremes: flash floods and droughts, since the state of the wetness of the land surface has a major impact on runoff response. Also, the ability to monitor the wetness of the soil and the actual evapotranspiration over large regions, without having to laboriously take expensive samples, is a bonus for agricultural managers who need to predict crop yields. We present samples of the daily national Soil Moisture and Evapotranspiration estimates on a grid of 7300 locations centred in 12 km squares, then move on to the results of a validation study for soil moisture and evapotranspiration estimated using the PyTOPKAPI hydrological model in Land Surface Modelling mode, a system called HYLARSMET. The HYLARSMET estimates are compared with detailed evapotranspiration and soil moisture measurements made at the Baynesfield experimental farm in the KwaZulu-Natal province of South Africa, run by the University of KZN. The HYLARSMET evapotranspiration estimates compared very well with the measured estimates for the two chosen crop types, in spite of the fact that the HYLARSMET estimates were not designed to explicitly account for the crop types at each site. The same seasonality effects were evident in all 3 estimates, and there was a stronger ET relationship between HYLARSMET and the Soybean site (Pearson r = 0.81) than for Maize, (r = 0.59). The soil moisture relationship was stronger between the two in situ measured estimates (r = 0.98 at 0.5 m depth) than it was between HYLARSMET and the field estimates (r about 0.52 in both cases). Overall there was a reasonably good relationship between HYLARSMET and the in situ measurements of ET and SM at each site, indicating the value of the modelling procedure.

Soil Temperature and Moisture Profile (STAMP) System Handbook

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

Cook, David R.

The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are alsomore » useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.« less

Extending the timescale for using beryllium 7 measurements to document soil redistribution by erosion

NASA Astrophysics Data System (ADS)

Walling, D. E.; Schuller, P.; Zhang, Y.; Iroumé, A.

2009-02-01

The need for spatially distributed information on soil mobilization, transfer, and deposition within the landscape by erosion has focused attention on the potential for using fallout radionuclides (i.e., 137Cs, excess 210Pb, and 7Be) to document soil redistribution rates. Whereas 137Cs and excess 210Pb are used to estimate medium- and longer-term erosion rates (i.e., approximately 45 years and 100 years, respectively), 7Be, by virtue of its short half-life (53 days), provides potential for estimating short-term soil redistribution on bare soils. However, the approach commonly used with this radionuclide means that it can only be applied to individual events or short periods of heavy rain. In addition, it is also frequently difficult to ensure that the requirement for spatially uniform 7Be inventories across the study area immediately prior to the study period is met. If the existing approach is applied to longer periods with several rainfall events (e.g., several weeks or more) soil redistribution is likely to be substantially underestimated. These problems limit the potential for using the 7Be approach, particularly in investigations where there is a need to assemble representative information on soil redistribution occurring during the entire wet season. This paper reports the development of a new or refined model for converting radionuclide measurements to estimates of soil redistribution (conversion model) for use with 7Be measurements, which permits much longer periods to be studied. This refined model aims to retain much of the simplicity of the existing approach, but takes account of the temporal distribution of both 7Be fallout and erosion during the study period and of the evolution of the 7Be depth distribution during this period. The approach was successfully tested using 7Be measurements from a study of short-term soil redistribution undertaken within an area of recently harvested forest located near Valdivia in Southern Chile. The study period extended over about 3 months and included the main part of the winter wet season of 2006. The estimates of soil redistribution obtained using the new conversion model were consistent with those obtained from erosion pins deployed within the same study area and were two to three times greater than those obtained using the approach and conversion model employed in existing studies.

Documentation of a heat and water transfer model for seasonally frozen soils with application to a precipitation-runoff model

USGS Publications Warehouse

Emerson, Douglas G.

1991-01-01

A model that simulates heat and water transfer in soils during freezing and thawing periods was developed and incorporated into the U.S. Geological Survey's Precipitation-Runoff Modeling System. The transfer of heat 1s based on an equation developed from Fourier's equation for heat flux. Field capacity and infiltration rate can vary throughout the freezing and thawing period, depending on soil conditions and rate and timing of snowmelt. The transfer of water within the soil profile is based on the concept of capillary forces. The model can be used to determine the effects of seasonally frozen soils on ground-water recharge and surface-water runoff. Data collected for two winters, 1985-86 and 1986-87, on three runoff plots were used to calibrate and verify the model. The winter of 1985-86 was colder than normal and snow cover was continuous throughout the winter. The winter of 1986-87 was wanner than normal and snow accumulated for only short periods of several days.Runoff, snowmelt, and frost depths were used as the criteria for determining the degree of agreement between simulated and measured data. The model was calibrated using the 1985-86 data for plot 2. The calibration simulation agreed closely with the measured data. The verification simulations for plots 1 and 3 using the 1985-86 data and for plots 1 and 2 using the 1986-87 data agreed closely with the measured data. The verification simulation for plot 3 using the 1986-87 data did not agree closely. The recalibratlon simulations for plots 1 and 3 using the 1985-86 data Indicated small improvement because the verification simulations for plots 1 and 3 already agreed closely with the measured data.

Fingerprinting breakthrough curves in soils

NASA Astrophysics Data System (ADS)

Koestel, J. K.

2017-12-01

Conservative solute transport through soil is predominantly modeled using a few standard solute transport models like the convection dispersion equation or the mobile-immobile model. The adequacy of these models is seldom investigated in detail as it would require knowledge on the 3-D spatio-temporal evolution of the solute plume that is normally not available. Instead, shape-measures of breakthrough curves (BTCs) such as the apparent dispersivity and the relative 5%-arrival time may be used to fingerprint breakthrough curves as well as forward solutions of solute transport models. In this fashion the similarity of features from measured and modeled BTC data becomes quantifiable. In this study I am presenting a new set of shape-measures that characterize the log-log tailings of BTC. I am using the new shape measures alongside with more established ones to map the features of BTCs obtained forward models of the convective dispersive equation, log-normal and Gamma transfer functions, the mobile-immobile model and the continuous time random walk model with respect to their input parameters. In a second step, I am comparing corresponding shape-measures for 206 measured BTCs extracted from peer-reviewed literature. Preliminary results show that power-law tailings are very common in BTCs from soil samples and that BTC features that are exclusive to a mobile-immobile type solute transport process are very rarely found.

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Comparing Noah-MP simulations of energy and water fluxes in the soil-vegetation-atmosphere continuum with plot scale measurements

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Högy, Petra; Ingwersen, Joachim; Wizemann, Hans-Dieter; Wulfmeyer, Volker; Streck, Thilo

2013-04-01

During the last years, land-surface models have proven to perform well in several studies that compared simulated fluxes of water and energy from the land surface to the atmosphere against measured fluxes at the plot-scale. In contrast, considerable deficits of land-surface models have been identified to simulate soil water fluxes and vertical soil moisture distribution. For example, Gayler et al. (2013) showed that simplifications in the representation of root water uptake can result in insufficient simulations of the vertical distribution of soil moisture and its dynamics. However, in coupled simulations of the terrestrial water cycle, both sub-systems, the atmosphere and the subsurface hydrogeo-system, must fit together and models are needed, which are able to adequately simulate soil moisture, latent heat flux, and their interrelationship. Consequently, land-surface models must be further improved, e.g. by incorporation of advanced biogeophysics models. To improve the conceptual realism in biophysical and hydrological processes in the community land surface model Noah, this model was recently enhanced to Noah-MP by a multi-options framework to parameterize individual processes (Niu et al., 2011). Thus, in Noah-MP the user can choose from several alternative models for vegetation and hydrology processes that can be applied in different combinations. In this study, we evaluate the performance of different Noah-MP model settings to simulate water and energy fluxes across the land surface at two contrasting field sites in South-West Germany. The evaluation is done in 1D offline-mode, i.e. without coupling to an atmospheric model. The atmospheric forcing is provided by measured time series of the relevant variables. Simulation results are compared with eddy covariance measurements of turbulent fluxes and measured time series of soil moisture at different depths. The aims of the study are i) to carve out the most appropriate combination of process parameterizations in Noah-MP to simultaneously match the different components of the water and energy cycle at the field sites under consideration, and ii) to estimate the uncertainty in model structure. We further investigate the potential to improve simulation results by incorporating concepts of more advanced root water uptake models from agricultural field scale models into the land-surface-scheme. Gayler S, Ingwersen J, Priesack E, Wöhling T, Wulfmeyer V, Streck T (2013): Assessing the relevance of sub surface processes for the simulation of evapotranspiration and soil moisture dynamics with CLM3.5: Comparison with field data and crop model simulations. Environ. Earth Sci., 69(2), under revision. Niu G-Y, Yang Z-L, Mitchell KE, Chen F, Ek MB, Barlage M, Kumar A, Manning K, Niyogi D, Rosero E, Tewari M and Xia Y (2011): The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research 116(D12109).

Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

2016-06-01

Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data assimilation on the evaporation fields is very mild, and difficult to assess due to the limited availability of eddy-covariance data. Nonetheless, our continental-scale simulations indicate that the assimilation of soil moisture can have a substantial impact on the estimated dynamics of evaporation in water-limited regimes. Progressing towards our goal of using satellite soil moisture to increase understanding of global land evaporation, future research will focus on the global application of this methodology and the consideration of multiple evaporation models.

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment.

PubMed

Saygın, Selen Deviren; Basaran, Mustafa; Ozcan, Ali Ugur; Dolarslan, Melda; Timur, Ozgur Burhan; Yilman, F Ebru; Erpul, Gunay

2011-09-01

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10 cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

Model development for prediction of soil water dynamics in plant production.

PubMed

Hu, Zhengfeng; Jin, Huixia; Zhang, Kefeng

2015-09-01

Optimizing water use in agriculture and medicinal plants is crucially important worldwide. Soil sensor-controlled irrigation systems are increasingly becoming available. However it is questionable whether irrigation scheduling based on soil measurements in the top soil could make best use of water for deep-rooted crops. In this study a mechanistic model was employed to investigate water extraction by a deep-rooted cabbage crop from the soil profile throughout crop growth. The model accounts all key processes governing water dynamics in the soil-plant-atmosphere system. Results show that the subsoil provides a significant proportion of the seasonal transpiration, about a third of water transpired over the whole growing season. This suggests that soil water in the entire root zone should be taken into consideration in irrigation scheduling, and for sensor-controlled irrigation systems sensors in the subsoil are essential for detecting soil water status for deep-rooted crops.

Soil Carbon Response to Soil Warming and Nitrogen Deposition in a Temperate Deciduous Forest

NASA Astrophysics Data System (ADS)

Parton, W. J.; Savage, K. E.; Davidson, E. A.; Trumbore, S.; Frey, S. D.

2011-12-01

While estimates of global soil C stocks vary widely, it is clear that soils store several times more C than is present in the atmosphere as CO2, and a significant fraction of soil C stocks are potentially subject to faster rates of decomposition in a warmer world. We address, through field based studies and modeling efforts, whether manipulations of soil temperature and nitrogen supply affect the magnitude and relative age of soil C substrates that are respired from a temperate deciduous forest located at Harvard Forest, MA. A soil warming and nitrogen addition experiment was initiated at the Harvard Forest in 2006. The experiment consists of six replicates of four treatments, control, heated, nitrogen, and heat+nitrogen addition. Soil temperatures in the heated plots are continuously elevated 5 oC above ambient and for the fertilized plots an aqueous solution of NH4NO3 is applied at a rate of 5 g m-2 yr-1. Soil C efflux from these plots was measured (n=24, 6 per treatment) biweekly throughout the year, while 14CO2 was measured (3 samples per treatment) several times during the summer months from 2006-2010. Following treatment, observed rates of annual C efflux increased under heating and nitrogen additions with heating treatments showing the greatest increase in respired C. The difference between control and treatments was greatest during the initial year following treatment; however this difference decreased in the subsequent 3 years of measurement. The plots designated for heating had a higher 14C signature from CO2 efflux prior to the heating (presumably due to spatial heterogeneity). However, because of the high spatial heterogeneity in measured 14C among treatments, no significant difference among treatments was observed from 2006 through 2010. Long term datasets (1995 through 2010) of soil C stocks, radiocarbon content, and CO2 efflux were used to parameterize the ForCent model for Harvard forest. The model was then run with the same treatment parameters as the field experiment for comparison of soil C efflux and 14C. Model results show increased annual C efflux for heated, nitrogen and nitrogen+heat plots with the largest increase in respired C from heated treatments. However there was little difference in simulated 14C respired from any treatment plots. While heating speeds up decomposition of all soil C pools in the model, the absolute amount of increased decomposition from the older pools (with higher 14C) was not large enough to make a difference in 14C composition of respired C, even as the more labile pool with lower 14C was gradually depleted. These results demonstrate that experiments conducted over several years do not provide great insight into the dynamics of slowly cycling soil C.

Assessing Vulnerability of Lake Erie Landscapes to Soil Erosion: Modelled and Measured Approaches

NASA Astrophysics Data System (ADS)

Joosse, P.; Laamrani, A.; Feisthauer, N.; Li, S.

2017-12-01

Loss of soil from agricultural landscapes to Lake Erie via water erosion is a key transport mechanism for phosphorus bound to soil particles. Agriculture is the dominant land use in the Canadian side of the Lake Erie basin with approximately 75% of the 2.3 million hectares under crop or livestock production. The variable geography and diversity of agricultural production systems and management practices makes estimating risk of soil erosion from agricultural landscapes in the Canadian Lake Erie basin challenging. Risk of soil erosion depends on a combination of factors including the extent to which soil remains bare, which differs with crop type and management. Two different approaches of estimating the vulnerability of landscapes to soil erosion will be compared among Soil Landscapes of Canada in the Lake Erie basin: a modelling approach incorporating farm census and soil survey data, represented by the 2011 Agriculture and Agri-Food Canada Agri-Environmental Indicator for Soil Erosion Risk; and, a measured approach using remotely sensed data that quantifies the magnitude of bare and covered soil across the basin. Results from both approaches will be compared by scaling the national level (1:1 million) Soil Erosion Risk Indicator and the remotely sensed data (30x30 m resolution) to the quaternary watershed level.

Evaluating experimental design for soil-plant model selection using a Bootstrap Filter and Bayesian model averaging

NASA Astrophysics Data System (ADS)

Wöhling, T.; Schöniger, A.; Geiges, A.; Nowak, W.; Gayler, S.

2013-12-01

The objective selection of appropriate models for realistic simulations of coupled soil-plant processes is a challenging task since the processes are complex, not fully understood at larger scales, and highly non-linear. Also, comprehensive data sets are scarce, and measurements are uncertain. In the past decades, a variety of different models have been developed that exhibit a wide range of complexity regarding their approximation of processes in the coupled model compartments. We present a method for evaluating experimental design for maximum confidence in the model selection task. The method considers uncertainty in parameters, measurements and model structures. Advancing the ideas behind Bayesian Model Averaging (BMA), we analyze the changes in posterior model weights and posterior model choice uncertainty when more data are made available. This allows assessing the power of different data types, data densities and data locations in identifying the best model structure from among a suite of plausible models. The models considered in this study are the crop models CERES, SUCROS, GECROS and SPASS, which are coupled to identical routines for simulating soil processes within the modelling framework Expert-N. The four models considerably differ in the degree of detail at which crop growth and root water uptake are represented. Monte-Carlo simulations were conducted for each of these models considering their uncertainty in soil hydraulic properties and selected crop model parameters. Using a Bootstrap Filter (BF), the models were then conditioned on field measurements of soil moisture, matric potential, leaf-area index, and evapotranspiration rates (from eddy-covariance measurements) during a vegetation period of winter wheat at a field site at the Swabian Alb in Southwestern Germany. Following our new method, we derived model weights when using all data or different subsets thereof. We discuss to which degree the posterior mean outperforms the prior mean and all individual posterior models, how informative the data types were for reducing prediction uncertainty of evapotranspiration and deep drainage, and how well the model structure can be identified based on the different data types and subsets. We further analyze the impact of measurement uncertainty und systematic model errors on the effective sample size of the BF and the resulting model weights.

Mineral-associated organic matter: are we now on the right path to accurately measuring and modelling it?

NASA Astrophysics Data System (ADS)

Cotrufo, M. F.

2017-12-01

Mineral-associated organic matter (MAOM) is the largest and most persistent pool of carbon in soil. Understanding and correctly modeling its dynamic is key to suggest management practices that can augment soil carbon storage for climate change mitigation, as well as increase soil organic matter (SOM) stocks to support soil health on the long-term. In the Microbial Efficiency Mineral Stabilization (MEMS) framework we proposed that, contrary to what originally thought, this form of persistent SOM is derived from the labile components of plant inputs, through their efficient microbial processing. I will present results from several experiments using dual isotope labeling of plant inputs that largely confirm this opinion, and point to the key role of dissolved organic matter in MAOM formation, and to the dynamic nature of the outer layer of MAOM. I will also show how we are incorporating this understanding in a new SOM model, which uses physically defined measurable pools rather than turnover-defined pools to forecast C cycling in soil.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Modelling Water Flow through Paddy Soils under Alternate Wetting and Drying Irrigation Practice

NASA Astrophysics Data System (ADS)

Shekhar, S.; Mailapalli, D. R.; Das, B. S.; Raghuwanshi, N. S.

2017-12-01

Alternate wetting and drying (AWD) irrigation practice in paddy cultivation requires an optimum soil moisture stress (OSMS) level at which irrigation water savings can be maximized without compromising the yield reduction. Determining OSMS experimentally is challenging and only possible with appropriate modeling tools. In this study, field experiments on paddy were conducted in thirty non-weighing type lysimeters during dry seasons of 2016 and 2017. Ten plots were irrigated using continuous flooding (CF) and the rest were irrigated with AWD practice at 40mb and 75mb soil moisture stress levels. Depth of ponding and soil suction at 10, 40 and 70 cm from the soil surface were measured daily from all lysimeter plots. The measured field data were used in calibration and validation of Hydrus-1D model and simulated the water flow for both AWD and CF plots. The Hydrus-1D is being used to estimate OSMS for AWD practice and compared the seasonal irrigation water input and deep percolation losses with CF practice.

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.

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A.D.

2013-01-01

Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Extension of laboratory-measured soil spectra to field conditions

NASA Technical Reports Server (NTRS)

Stoner, E. R.; Baumgardner, M. F.; Weismiller, R. A.; Biehl, L. L.; Robinson, B. F.

1982-01-01

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured in the laboratory under controlled moisture equilibria using an Exotech Model 20C spectroradiometer to obtain spectral data in the laboratory under artificial illumination. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory-measured spectra of moist soil are directly proportional to the spectral response of that same field-measured moist bare soil over the 0.52 micrometer to 1.75 micrometer wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6 micrometers to 0.8 micrometer transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

TDR water content inverse profiling in layered soils during infiltration and evaporation

NASA Astrophysics Data System (ADS)

Greco, R.; Guida, A.

2009-04-01

During the last three decades, time domain reflectometry (TDR) has become one of the most commonly used tools for soil water content measurements either in laboratory or in the field. Indeed, TDR provides easy and cheap water content estimations with relatively small disturbance to the investigated soil. TDR measurements of soil water content are based on the strong correlation between relative dielectric permittivity of wet soil and its volumetric water content. Several expressions of the relationship between relative dielectric permittivity and volumetric water content have been proposed, empirically stated (Topp et al., 1980) as well as based on semi-analytical approach to dielectric mixing models (Roth et al., 1990; Whalley, 1993). So far, TDR field applications suffered the limitation due to the capability of the technique of estimating only the mean water content in the volume investigated by the probe. Whereas the knowledge of non homogeneous vertical water content profiles was needed, it was necessary to install either several vertical probes of different length or several horizontal probes placed in the soil at different depths, in both cases strongly increasing soil disturbance as well as the complexity of the measurements. Several studies have been recently dedicated to the development of inversion methods aimed to extract more information from TDR waveforms, in order to estimate non homogeneous moisture profiles along the axis of the metallic probe used for TDR measurements. A common feature of all these methods is that electromagnetic transient through the wet soil along the probe is mathematically modelled, assuming that the unknown soil water content distribution corresponds to the best agreement between simulated and measured waveforms. In some cases the soil is modelled as a series of small layers with different dielectric properties, and the waveform is obtained as the result of the superposition of multiple reflections arising from impedance discontinuities between the layers (Nguyen et al., 1997; Todoroff et al., 1998; Heimovaara, 2001; Moret et al., 2006). Other methods consider the dielectric properties of the soil as smoothly variable along probe axis (Greco, 1999; Oswald et al., 2003; Greco, 2006). Aim of the study is testing the applicability to layered soils of the inverse method for the estimation of water content profiles along vertical TDR waveguides, originally applied in laboratory to homogeneous soil samples with monotonic moisture distributions (Greco, 2006), and recently extended to field measurements with more general water content profiles (Greco and Guida, 2008). Influence of soil electrical conductivity, uniqueness of solution, choices of parametrization, parameters identifiabilty, sensitivity of the method to chosen parameters variations are discussed. Finally, the results of the application of the inverse method to a series of infiltration and evaporation experiments carried out in a flume filled with three soil layers of different physical characteristics are presented. ACKNOWLEDGEMENTS The research was co-financed by the Italian Ministry of University, by means of the PRIN 2006 PRIN program, within the research project entitled ‘Definition of critical rainfall thresholds for destructive landslides for civil protection purposes'. REFERENCES Greco, R., 1999. Measurement of water content profiles by single TDR experiments. In: Feyen, J., Wiyo, K. (Eds.), Modelling of Transport Processes in Soils. Wageningen Pers, Wageningen, the Netherlands, pp. 276-283. Greco, R., 2006. Soil water content inverse profiling from single TDR waveforms. J. Hydrol. 317, 325-339. Greco R., Guida A., 2008. Field measurements of topsoil moisture profiles by vertical TDR probes. J. Hydrol. 348, 442- 451. Heimovaara, T.J., 2001. Frequency domain modelling of TDR waveforms in order to obtain frequency dependent dielectric properties of soil samples: a theoretical approach. In: TDR 2001 - Second International Symposium on Time Domain Reflectometry for Innovative Geotechnical Applications. Northwestern University, Evanston, Illinois, pp. 19-21. Moret, D., Arrue, J.L., Lopez, M.V., Gracia, R., 2006. A new TDR waveform analysis approach for soil moisture profiling using a single probe. J. Hydrol. 321, 163-172. Nguyen, B.L., Bruining, J., Slob, E.C., 1997. Saturation profiles from dielectric (frequency domain reflectometry) measurements in porous media. In: Proceedings of International Workshop on characterization and Measurements of the Hydraulic Properties of Unsaturated Porous Media, Riverside, California, pp. 363-375. Oswald, B., Benedickter, H.R., Ba¨chtold, W., Flu¨hler, H., 2003. Spatially resolved water content profiles from inverted time domain reflectometry signals. Water Resour. Res. 39 (12), 1357. Todoroff, P., Lorion, R., Lan Sun Luk, J.-D., 1998. L'utilisation des génétiques pour l'identification de profils hydriques de sol a` partir de courbes réflectométriques. CR Acad. Sci. Paris, Sciences de la terre et des plane`tes 327, 607-610. Topp, G.C., Davis, J.L., Annan, A.P., 1980. Electromagnetic determination of soil water content: measurement in coaxial transmission lines. Water Resour. Res. 16, 574-582. Roth, K., Schulin, R., Fluhler, H., Attinger, W., 1990. Calibration of time domain reflectometry for water content measurement using a composite dielectric approach. Water Resour. Res. 26, 2267-2273. Whalley, W.R., 1993. Considerations on the use of time domain reflectometry (TDR) for measuring soil water content. J. Soil Sci. 44, 1-9.

A novel in-situ method for real-time monitoring of gas transport in soil

NASA Astrophysics Data System (ADS)

Laemmel, Thomas; Maier, Martin; Schack-Kirchner, Helmer; Lang, Friederike

2017-04-01

Gas exchange between soil and atmosphere is important for the biogeochemistry of soils. Gas transport in soil is commonly assumed to be governed by molecular diffusion and is usually described by the soil gas diffusion coefficient DS characterizing the ability of the soil to "transport passively" gas through the soil. One way to determine DS is sampling soil cores in the field and measuring DS in the lab. Unfortunately this method is destructive and laborious. Moreover, a few previous field studies identified other gas transport processes in soil to significantly enhance the diffusive gas transport. However, until now, no method is available to measure gas transport in situ in the soil. We developed a novel method to monitor gas transport in soil in situ. The method includes a custom made gas sampling device, the continuous injection of an inert tracer gas and inverse gas transport modelling in the soil. The gas sampling device has several sampling depths and can be easily installed into a vertical hole drilled by an auger, which allows for fast installation of the system. Helium (He) as inert tracer gas was injected continuously at the lower end of the device. The resulting steady state distribution of He was used to deduce the depth profile of DS. Gas transport in the soil surrounding the gas-sampling-device/soil system was modeled using the Finite Element Modeling program COMSOL . We tested our new method both in the lab and during two short field studies and compared the results with a reference method using soil cores. DS profiles obtained by our in-situ method were consistent with DS profiles determined based on soil core analyses. During a longer monitoring field campaign, typical soil-moisture effects upon gas diffusivity such as an increase during a drying period or a decrease after rain could be observed consistently. Under windy conditions we additionally measured for the first time the direct enhancement of gas transport in soil due to wind-induced pressure-pumping which could increase the effective DS up to 30% in the topsoil. Our novel monitoring method can be quickly and easily installed and allows for monitoring continuously soil gas transport over a long time. It allows monitoring physical modifications of soil gas diffusivity due to rain events or evaporation but it also allows studying non-diffusive gas transport processes in the soil.

The BonaRes Centre - A virtual institute for soil research in the context of a sustainable bio-economy

NASA Astrophysics Data System (ADS)

Wollschläger, Ute; Helming, Katharina; Heinrich, Uwe; Bartke, Stephan; Kögel-Knabner, Ingrid; Russell, David; Eberhardt, Einar; Vogel, Hans-Jörg

2016-04-01

Fertile soils are central resources for the production of biomass and provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for both, food and bio-energy, which require preserving and improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained. To render soil management sustainable, we need to establish a scientific knowledge base about complex soil system processes that allows for the development of model tools to quantitatively predict the impact of a multitude of management measures on soil functions. This, finally, will allow for the provision of site-specific options for sustainable soil management. To face this challenge, the German Federal Ministry of Education and Research recently launched the funding program "Soil as a Natural Resource for the Bio-Economy - BonaRes". In a joint effort, ten collaborative projects and the coordinating BonaRes Centre are engaged to close existing knowledge gaps for a profound and systemic understanding of soil functions and their sensitivity to soil management. This presentation provides an overview of the concept of the BonaRes Centre which is responsible for i) setting up a comprehensive data base for soil-related information, ii) the development of model tools aiming to estimate the impact of different management measures on soil functions, and iii) establishing a web-based portal providing decision support tools for a sustainable soil management. A specific focus of the presentation will be laid on the so-called "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive meta-analysis on soil functions as a basis for future model developments.

Improving the soil moisture data record of the U.S. Climate Reference Network (USCRN) and Soil Climate Analysis Network (SCAN)

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are valuable for hydrologic modeling, drought prediction and management, climate change analysis, and agricultural decision support. However, in situ measurements of soil moisture have only become available within the past few decades with additional sensors being installed ...

Determination of field-effective soil properties in the tidewater region of North Carolina

Treesearch

J. McFero Grace; R.W. Skaggs

2013-01-01

Soils vary spatially in texture, structure, depth of horizons, and macropores, which can lead to a large variation in soil physical properties. In particular, saturated hydraulic conductivity (Ksat) and drainable porosity are critical properties required to model field hydrology in poorly drained lands. These soil-property values can be measured...

Numerical Investigations of Moisture Distribution in a Selected Anisotropic Soil Medium

NASA Astrophysics Data System (ADS)

Iwanek, M.

2018-01-01

The moisture of soil profile changes both in time and space and depends on many factors. Changes of the quantity of water in soil can be determined on the basis of in situ measurements, but numerical methods are increasingly used for this purpose. The quality of the results obtained using pertinent software packages depends on appropriate description and parameterization of soil medium. Thus, the issue of providing for the soil anisotropy phenomenon gains a big importance. Although anisotropy can be taken into account in many numerical models, isotopic soil is often assumed in the research process. However, this assumption can be a reason for incorrect results in the simulations of water changes in soil medium. In this article, results of numerical simulations of moisture distribution in the selected soil profile were presented. The calculations were conducted assuming isotropic and anisotropic conditions. Empirical verification of the results obtained in the numerical investigations indicated statistical essential discrepancies for the both analyzed conditions. However, better fitting measured and calculated moisture values was obtained for the case of providing for anisotropy in the simulation model.

Evidence from Amazonian forests is consistent with isohydric control of leaf water potential.

PubMed

Fisher, Rosie A; Williams, Mathew; Do Vale, Raquel Lobo; Da Costa, Antonio Lola; Meir, Patrick

2006-02-01

Climate modelling studies predict that the rain forests of the Eastern Amazon basin are likely to experience reductions in rainfall of up to 50% over the next 50-100 years. Efforts to predict the effects of changing climate, especially drought stress, on forest gas exchange are currently limited by uncertainty about the mechanism that controls stomatal closure in response to low soil moisture. At a through-fall exclusion experiment in Eastern Amazonia where water was experimentally excluded from the soil, we tested the hypothesis that plants are isohydric, that is, when water is scarce, the stomata act to prevent leaf water potential from dropping below a critical threshold level. We made diurnal measurements of leaf water potential (psi 1), stomatal conductance (g(s)), sap flow and stem water potential (psi stem) in the wet and dry seasons. We compared the data with the predictions of the soil-plant-atmosphere (SPA) model, which embeds the isohydric hypothesis within its stomatal conductance algorithm. The model inputs for meteorology, leaf area index (LAI), soil water potential and soil-to-leaf hydraulic resistance (R) were altered between seasons in accordance with measured values. No optimization parameters were used to adjust the model. This 'mechanistic' model of stomatal function was able to explain the individual tree-level seasonal changes in water relations (r2 = 0.85, 0.90 and 0.58 for psi 1, sap flow and g(s), respectively). The model indicated that the measured increase in R was the dominant cause of restricted water use during the dry season, resulting in a modelled restriction of sap flow four times greater than that caused by reduced soil water potential. Higher resistance during the dry season resulted from an increase in below-ground resistance (including root and soil-to-root resistance) to water flow.

A radiative transfer model for microwave emissions from bare agricultural soils

NASA Technical Reports Server (NTRS)

Burke, W. J.; Paris, J. F.

1975-01-01

A radiative transfer model for microwave emissions from bare, stratified agricultural soils was developed to assist in the analysis of data gathered in the joint soil moisture experiment. The predictions of the model were compared with preliminary X band (2.8 cm) microwave and ground based observations. Measured brightness temperatures at vertical and horizontal polarizations can be used to estimate the moisture content of the top centimeter of soil with + or - 1 percent accuracy. It is also shown that the Stokes parameters can be used to distinguish between moisture and surface roughness effects.

Infiltration and soil erosion modelling on Lausatian post mine sites

NASA Astrophysics Data System (ADS)

Kunth, Franziska; Schmidt, Jürgen

2013-04-01

Land management of reclaimed lignite mine sites requires long-term and safe structuring of recultivation areas. Erosion by water leads to explicit soil losses, especially on heavily endangered water repellent and non-vegetated soil surfaces. Beyond that, weathering of pyrite-containing lignite burden dumps causes sulfuric acid-formation, and hence the acidification of groundwater, seepage water and surface waters. Pyrite containing sediment is detached by precipitation and transported into worked-out open cuts by draining runoff. In addition to ground water influence, erosion processes are therefore involved in acidification of surface waters. A model-based approach for the conservation of man-made slopes of post mining sites is the objective of this ongoing study. The study shall be completed by modeling of the effectiveness of different mine site recultivation scenarios. Erosion risks on man-made slopes in recultivation areas should be determined by applying the physical, raster- and event based computer model EROSION 2D/3D (Schmidt, 1991, 1992; v. Werner, 1995). The widely used erosion model is able to predict runoff as well as detachment, transport and deposition of sediments. Lignite burden dumps contain hydrophobic substances that cover soil particles. Consequently, these soils show strong water repellency, which influences the processes of infiltration and soil erosion on non-vegetated, coal containing dump soils. The influence of water repellency had to be implemented into EROSION 2D/3D. Required input data for soil erosion modelling (e.g. physical soil parameters, infiltration rates, calibration factors, etc.) were gained by soil sampling and rainfall experiments on non-vegetated as well as recultivated reclaimed mine sites in the Lusatia lignite mining region (southeast of Berlin, Germany). The measured infiltration rates on the non-vegetated water repellent sites were extremely low. Therefore, a newly developed water repellency-factor was applied to depict infiltration and erosion processes on water repellent dump soils. For infiltration modelling with EROSION 2D calibration factors (e.g. water repellency factor, skin-factor, etc.) were determined in different steps by calibrating computer modelled infiltration, respectively volume rate of flow to the measured data.

Assessing dry density and gravimetric water content of soils in geotechnics with complex conductivity measurements : preliminary investigations

NASA Astrophysics Data System (ADS)

Kaouane, C.; Beck, Y.; Fauchard, C.; Chouteau, M.

2012-12-01

Quality controls of geotechnical works need gravimetric water content (w) and dry density (γd) measurements. Afterwards, results are compared to Proctor tests and referred to soil classification. Depending on the class of soils, different objectives must be achieved. Those measurements are usually carried out with neutron and gamma probes. Combined use of theses probes directly access (w, γd). Theses probes show great disadvantages as: nuclear hazard, heavy on-site, transporation and storage restrictions and low sampling volumes. Last decades showed a strong development of electrical and electromagnetic methods for mapping water content in soils. Still, their use in Geotechnics is limited due to interfacial effects neglected in common models but strong in compacted soils. We first showed that (w, γd) is equivalent to (φ, Sr) assuming density of particles γs=2.7 (g.cm-3). This assumption is true for common soils used in civil engineering. That first relationship allows us to work with meaningful parameters for geophysicists. Revil&Florsh recently adapted Vinegar&Waxman model for Spectal Induced Polarization (SIP) measurements at low frequencies (<50 kHz). This model relates quantitatively the electrical double layer polarization at the surface of grains. It takes into account saturation, porosity and granulometry. Standard granulometry and mineralogy are generally available in geotechnical campaigns. In-phase conductivity would be mostly related to saturation as quadrature conductivity would be related to porosity and surface conductivity. Although this model was developed for oil-bearing sands, we investigated its potential for compacted soils. Former DC-resistivity (ρ) measurements were carried out on a silty fined-grained soil (A1 in GTR classification or ML-CL in USCS) in a cylindrical cell (radius ~4 cm, heigth 7 cm). Median diameter of grain was 50 μm. For each measurement, samples were compacted at Proctor energy. We assessed (w, γd) by weighting and drying samples. We obtained γd = 1.6-1.9 (g.cm-3) and w=7-14% which lead to φ=0.3-0.4 and Sr=0.3-0.8. Tap water (ρw= 30 Ω.m) was used for the experiment. We first evaluated the saturation factor n=1.35 by fitting a power law ρ/ρw =a*Sr^n+b. a=0.223 agreed with φ^(-n)=F, F being the formation factor. This leads to a mean tortuosity α=1.47. b=0.5 might be related to surface conductivity. An empirical Rhoades-Corwin model also fit great to data. Revil&Florsh model allows us to predict a phase peak in case of complex conductivity measurements. We predicted a frequency peak at 2.4 Hz. This peak is well located in the frequency range of SIP (from 1 mHz to ~10 Hz). At the frequency peak, this model allows the direct evaluation of saturation and porosity. Hence, complex conductivity measurements might be a fine alternative to nuclear probes. Still, driving in electrodes in compacted soils remains difficult. Ongoing studies are looking further to extend this model to higher frequency range (5-200 kHz) where capacitively coupled resistivity arrays might be used allowing continuous measurements.

Strategies for using remotely sensed data in hydrologic models

NASA Technical Reports Server (NTRS)

Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

1981-01-01

Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

Usability of calcium carbide gas pressure method in hydrological sciences

NASA Astrophysics Data System (ADS)

Arsoy, S.; Ozgur, M.; Keskin, E.; Yilmaz, C.

2013-10-01

Soil moisture is a key engineering variable with major influence on ecological and hydrological processes as well as in climate, weather, agricultural, civil and geotechnical applications. Methods for quantification of the soil moisture are classified into three main groups: (i) measurement with remote sensing, (ii) estimation via (soil water balance) simulation models, and (iii) measurement in the field (ground based). Remote sensing and simulation modeling require rapid ground truthing with one of the ground based methods. Calcium carbide gas pressure (CCGP) method is a rapid measurement procedure for obtaining soil moisture and relies on the chemical reaction of the calcium carbide reagent with the water in soil pores. However, the method is overlooked in hydrological science applications. Therefore, the purpose of this study is to evaluate the usability of the CCGP method in comparison with standard oven-drying and dielectric methods in terms of accuracy, time efficiency, operational ease, cost effectiveness and safety for quantification of the soil moisture over a wide range of soil types. The research involved over 250 tests that were carried out on 15 different soil types. It was found that the accuracy of the method is mostly within ±1% of soil moisture deviation range in comparison to oven-drying, and that CCGP method has significant advantages over dielectric methods in terms of accuracy, cost, operational ease and time efficiency for the purpose of ground truthing.

Carbon and nitrogen accumulation and fluxes on Landscape Evolution Observatory (LEO) slopes

NASA Astrophysics Data System (ADS)

Dontsova, K.; Volk, M.; Webb, C.; Hunt, E.; Tfaily, M. M.; Van Haren, J. L. M.; Sengupta, A.; Chorover, J.; Troch, P.; Ruiz, J.

2017-12-01

Carbon accumulation on the landscapes in organic and inorganic forms is an important sink of CO2 from the atmosphere. Formation and preservation of organic compounds is accompanied by N fixation from the atmosphere and cycling in the soil. Model slopes of Landscape Evolution Observatory present unique opportunity to examine carbon and nitrogen buildup on the landscapes during soil formation processes, such as weathering of primary minerals and microbial activity, due to low original levels of C and N, tight control over environmental conditions, and high spatial and temporal density of measurements. This presents results of inorganic and organic C and N measurements in the cores collected in LEO slopes after several years of exposure to the rainfall, as well as soil solution measurements collected through 496 samplers on each of three model slopes and in seepage. We observed significant spatially distributed accumulation of both C (organic and inorganic) and N in soil profiles. We also observed differences in the composition of organic compounds in the solid and solution phases depending on location on the slope indicating formation of heterogeneity as soils develop. This works indicates potential of physical models to help understand accumulation and fluxes of C and N on natural landscapes.

Effects of soil water and heat relationship under various snow cover during freezing-thawing periods in Songnen Plain, China.

PubMed

Fu, Qiang; Hou, Renjie; Li, Tianxiao; Jiang, Ruiqi; Yan, Peiru; Ma, Ziao; Zhou, Zhaoqiang

2018-01-22

In this study, the spatial variations of soil water and heat under bare land (BL), natural snow (NS), compacted snow (CS) and thick snow (TS) treatments were analyzed. The relationship curve between soil temperature and water content conforms to the exponential filtering model, by means of the functional form of the model, it was defined as soil water and heat relation function model. On this basis, soil water and heat function models of 10, 20, 40, 60, 100, and 140 cm were established. Finally, a spatial variation law of the relationship effect was described based on analysising of the differences between the predicted and measured results. During freezing period, the effects of external factors on soil were hindered by snow cover. As the snow increased, the accuracy of the function model gradually improved. During melting period, infiltration by snowmelt affected the relationship between the soil temperature and moisture. With the increasing of snow, the accuracy of the function models gradually decreased. The relationship effects of soil water and heat increased with increasing depth within the frozen zone. In contrast, below the frozen layer, the relationship of soil water and heat was weaker, and the function models were less accurate.

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

DOE PAGES

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard; ...

2018-01-02

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

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

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

PubMed

Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

2018-08-01

Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John

2010-01-01

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Implications of complete watershed soil moisture measurements to hydrologic modeling

NASA Technical Reports Server (NTRS)

Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

1983-01-01

A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

On the importance of measurement error correlations in data assimilation for integrated hydrological models

NASA Astrophysics Data System (ADS)

Camporese, Matteo; Botto, Anna

2017-04-01

Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows us to integrate multisource observation data in modeling predictions and, in doing so, to reduce uncertainty. For this reason, data assimilation has been recently the focus of much attention also for physically-based integrated hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). One of the typical assumptions in these studies is that the measurement errors are uncorrelated, whereas in certain situations it is reasonable to believe that some degree of correlation occurs, due for example to the fact that a pair of sensors share the same soil type. The goal of this study is to show if and how the measurement error correlations between different observation data play a significant role on assimilation results in a real-world application of an integrated hydrological model. The model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope. The physical model, located in the Department of Civil, Environmental and Architectural Engineering of the University of Padova (Italy), consists of a reinforced concrete box containing a soil prism with maximum height of 3.5 m, length of 6 m, and width of 2 m. The hillslope is equipped with sensors to monitor the pressure head and soil moisture responses to a series of generated rainfall events applied onto a 60 cm thick sand layer overlying a sandy clay soil. The measurement network is completed by two tipping bucket flow gages to measure the two components (subsurface and surface) of the outflow. By collecting data at a temporal resolution of 0.5 Hz (relatively high, compared to the hydrological dynamics), we can perform a comprehensive statistical analysis of the observations, including the cross-correlations between data from different sensors. We report on the impact of taking these correlations into account in a series of assimilation scenarios, where the EnKF is used to assimilate pressure head and/or soil moisture and/or subsurface outflow.

Effect of a controlled burn on the thermophysical properties of a dry soil using a new model of soil heat flow and a new high temperature heat flux sensor

Treesearch

W. J. Massman; J. M. Frank

2004-01-01

Some fires can be beneficial to soils but, if a fire is sufficiently intense, soil can be irreversible altered. We measured soil temperatures and heat fluxes at several soil depths before, during, and after a controlled surface burn at Manitou Experimental Forest (southern Colorado, USA) to evaluate its effects on the soil's thermophysical properties (thermal...

Comparison of soil thickness in a zero-order basin in the Oregon Coast Range using a soil probe and electrical resistivity tomography

USGS Publications Warehouse

Morse, Michael S.; Lu, Ning; Godt, Jonathan W.; Revil, André; Coe, Jeffrey A.

2012-01-01

Accurate estimation of the soil thickness distribution in steepland drainage basins is essential for understanding ecosystem and subsurface response to infiltration. One important aspect of this characterization is assessing the heavy and antecedent rainfall conditions that lead to shallow landsliding. In this paper, we investigate the direct current (DC) resistivity method as a tool for quickly estimating soil thickness over a steep (33–40°) zero-order basin in the Oregon Coast Range, a landslide prone region. Point measurements throughout the basin showed bedrock depths between 0.55 and 3.2 m. Resistivity of soil and bedrock samples collected from the site was measured for degrees of saturation between 40 and 92%. Resistivity of the soil was typically higher than that of the bedrock for degrees of saturation lower than 70%. Results from the laboratory measurements and point-depth measurements were used in a numerical model to evaluate the resistivity contrast at the soil-bedrock interface. A decreasing-with-depth resistivity contrast was apparent at the interface in the modeling results. At the field site, three transects were surveyed where coincident ground truth measurements of bedrock depth were available, to test the accuracy of the method. The same decreasing-with-depth resistivity trend that was apparent in the model was also present in the survey data. The resistivity contour of between 1,000 and 2,000 Ωm that marked the top of the contrast was our interpreted bedrock depth in the survey data. Kriged depth-to-bedrock maps were created from both the field-measured ground truth obtained with a soil probe and interpreted depths from the resistivity tomography, and these were compared for accuracy graphically. Depths were interpolated as far as 16.5 m laterally from the resistivity survey lines with root mean squared error (RMSE) = 27 cm between the measured and interpreted depth at those locations. Using several transects and analysis of the subsurface material properties, the direct current (DC) resistivity method is shown to be able to delineate bedrock depth trends within the drainage basin.

Sediment and solute transport in a mountainous watershed in Valle del Cauca, Colombia

NASA Astrophysics Data System (ADS)

Guzman, Christian; Hoyos Villada, Fanny; Morales Vargas, Amalia; Rivera, Baudelino; Da Silva, Mayesse; Moreno Padilla, Pedro; Steenhuis, Tammo

2015-04-01

Sediment samples and solute concentrations were measured from the La Vega micro watershed in the southwestern region of the Colombian Andes. A main goal of this study was to improve prediction of soil surface and soil nutrient changes, based on field measurements, within small basin of the Aguaclara watershed network receiving different types of conservation measures. Two modeling approaches for stream discharge and sediment transport predictions were used with one of these based on infiltration-excess and the other on saturation-excess runoff. These streams are a part of a recent initiative from a water fund established by Asobolo, Asocaña, and Cenicaña in collaboration with the Natural Capital Project to improve conservation efforts and monitor their effects. On-site soil depth changes, groundwater depth measurements, and soil nutrient concentrations were also monitored to provide more information about changes within this mountainous watershed during one part of the yearly rainy season. This information is being coupled closely with the outlet sediment concentration and solute concentration patterns to discern correlations between scales. Lateral transects in the upper, middle, and lower part of the hillsides in the La Vega micro watershed showed differences in soil nutrient status and soil surface depth changes. The model based on saturation-excess, semi-distributed hydrology was able to reproduce discharge and sediment transport rates as well as the initially used infiltration excess model indicating available options for comparison of conservation changes in the future.

Microwave remote sensing of soil moisture content over bare and vegetated fields

NASA Technical Reports Server (NTRS)

Wang, J. R.; Shiue, J. C.; Mcmurtrey, J. E., III

1980-01-01

Remote measurements of soil moisture contents over bare fields and fields covered with orchard grass, corn, and soybean were made during October 1979 with 1.4 GHz and 5 GHz microwave radiometers mounted on a truck. Ground truth of soil moisture content, ambient air, and soil temperatures was acquired concurrently with the radiometric measurements. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperature data with appropriate values of dielectric constants for soil-water mixtures. Good agreement was found between the calculated and the measured results over 10-70 deg incident angles. The presence of vegetation was found to reduce the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from approximately 20% for 10-cm tall grassland to over 60% for the dense soybean field. At 5 GHz the corresponding reduction in sensitivity ranged from approximately 70 to approximately 90%.

Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

NASA Astrophysics Data System (ADS)

Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

2015-12-01

The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

Linking Annual N2O Emission in Organic Soils to Mineral Nitrogen Input as Estimated by Heterotrophic Respiration and Soil C/N Ratio

PubMed Central

Mu, Zhijian; Huang, Aiying; Ni, Jiupai; Xie, Deti

2014-01-01

Organic soils are an important source of N2O, but global estimates of these fluxes remain uncertain because measurements are sparse. We tested the hypothesis that N2O fluxes can be predicted from estimates of mineral nitrogen input, calculated from readily-available measurements of CO2 flux and soil C/N ratio. From studies of organic soils throughout the world, we compiled a data set of annual CO2 and N2O fluxes which were measured concurrently. The input of soil mineral nitrogen in these studies was estimated from applied fertilizer nitrogen and organic nitrogen mineralization. The latter was calculated by dividing the rate of soil heterotrophic respiration by soil C/N ratio. This index of mineral nitrogen input explained up to 69% of the overall variability of N2O fluxes, whereas CO2 flux or soil C/N ratio alone explained only 49% and 36% of the variability, respectively. Including water table level in the model, along with mineral nitrogen input, further improved the model with the explanatory proportion of variability in N2O flux increasing to 75%. Unlike grassland or cropland soils, forest soils were evidently nitrogen-limited, so water table level had no significant effect on N2O flux. Our proposed approach, which uses the product of soil-derived CO2 flux and the inverse of soil C/N ratio as a proxy for nitrogen mineralization, shows promise for estimating regional or global N2O fluxes from organic soils, although some further enhancements may be warranted. PMID:24798347

Multi-temporal Soil Erosion Modelling over the Mt Kenya Region with Multi-Sensor Earth Observation Data

NASA Astrophysics Data System (ADS)

Symeonakis, Elias; Higginbottom, Thomas

2015-04-01

Accelerated soil erosion is the principal cause of soil degradation across the world. In Africa, it is seen as a serious problem creating negative impacts on agricultural production, infrastructure and water quality. Regarding the Mt Kenya region, specifically, soil erosion is a serious threat mainly due to unplanned and unsustainable practices linked to tourism, agriculture and rapid population growth. The soil types roughly correspond with different altitudinal zones and are generally very fertile due to their volcanic origin. Some of them have been created by eroding glaciers while others are due to millions of years of fluvial erosion. The soils on the mountain are easily eroded once exposed: when vegetation is removed, the soil quickly erodes down to bedrock by either animals or humans, as tourists erode paths and local people clear large swaths of forested land for agriculture, mostly illegally. It is imperative, therefore, that a soil erosion monitoring system for the Mt Kenya region is in place in order to understand the magnitude of, and be able to respond to, the increasing number of demands on this renewable resource. In this paper, we employ a simple regional-scale soil erosion modelling framework based on the Thornes model and suggest an operational methodology for quantifying and monitoring water runoff and soil erosion using multi-sensor and multi-temporal remote sensing data in a GIS framework. We compare the estimates of this study with general data on the severity of soil erosion over Kenya and with measured rates of soil loss at different locations over the area of study. The results show that the measured and estimated rates of erosion are generally similar and within the same order of magnitude. They also show that, over the last years, erosion rates are increasing in large parts of the region at an alarming rate, and that mitigation measures are needed to reverse the negative effects of uncontrolled socio-economic practices.

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.

Modeling of Water Flow Processes in the Soil-Plant-Atmosphere System: The Soil-Tree-Atmosphere Continuum Model

NASA Astrophysics Data System (ADS)

Massoud, E. C.; Vrugt, J. A.

2015-12-01

Trees and forests play a key role in controlling the water and energy balance at the land-air surface. This study reports on the calibration of an integrated soil-tree-atmosphere continuum (STAC) model using Bayesian inference with the DREAM algorithm and temporal observations of soil moisture content, matric head, sap flux, and leaf water potential from the King's River Experimental Watershed (KREW) in the southern Sierra Nevada mountain range in California. Water flow through the coupled system is described using the Richards' equation with both the soil and tree modeled as a porous medium with nonlinear soil and tree water relationships. Most of the model parameters appear to be reasonably well defined by calibration against the observed data. The posterior mean simulation reproduces the observed soil and tree data quite accurately, but a systematic mismatch is observed between early afternoon measured and simulated sap fluxes. We will show how this points to a structural error in the STAC-model and suggest and test an alternative hypothesis for root water uptake that alleviates this problem.

[Convertibility of the data determined by ICP-AES and FAAS for soil available K and Na].

PubMed

Zhang, Jian-min; Wang, Meng; Ge, Xiao-ping; Wu, Jian-zhi; Ge, Ying; Li, Shi-peng; Chang, Jie

2009-05-01

In recent years, inductively coupled plasma atomic emission spectrometry (ICP-AES) have been commonly used to determine the soil available K and Na with the extraction solution of HCl-H2SO4, while previous data of soil available K and Na were measured by flame atomic absorption spectrometry (FAAS) with the extraction solution of NH4OAc. In order to utilize previous data, quest for the convertibility of the data determined by ICP-AES and FAAS, and compare the data determined by both methods, the authors chose four types of soil to determine soil available K and Na by ICP-AES and FAAS, respectively. Four types of soil represent grit soil, clay, silt from river and silt from sea, respectively. Soil samples included four types of soil and these samples represent different soil nutrition. The authors analyzed the correlations of two kinds of measured data. The paired samples t-test proves that there was significantly positively correlation between these two methods. The correlation coefficient of the data between these two methods for measuring soil available K is 0.98. The results of soil available K determined by the two methods can be conversed through the formula, y = l.14x + 6.53 (R2 = 0.91, n=24, p < 0.001). As for Na, although there is a significantly positively correlation between these two methods, the slopes of single model of clay and grit soil were different from that of general model. And so the results determined by the two methods can be conversed through different formula according to the types of soil, that is, for clay: y = l.23x + 10.03; for grit soil: y = 3.12x - 23.03; for silt: y = 0.60x. In conclusion, the authors' results showed that previous data of available K and Na measured by FAAS with the extraction solution of NH4OAc were available. And these data were comparable to the data measured by ICP-AES through definite formula The authors' results also suggested that ICP-AES was preferable when many elements were measured at the same time. Under this condition, ICP-AES was economical, efficient and reliable.

A dual-porous, biophysical void structure model of soil for the understanding of the conditions causing nitrous oxide emission

NASA Astrophysics Data System (ADS)

Matthews, G. Peter; Maurizio Laudone, G.; Whalle, W. Richard; Bird, Nigel; Gregory, Andrew; Cardenas, Laura; Misselbrook, Tom

2010-05-01

Nitrous oxide is the fourth most important greenhouse gas. It is 300 times more potent than carbon dioxide, and two-thirds of anthropogenic nitrous oxide is emitted by agricultural land. This presentation will begin with a brief overview of the laboratory measurements of nitrous oxide emission from carefully characterised soils, presented in more detail by Cardenas et al.. The measurements were made in a twelve-chamber, gas chromatographic apparatus at North Wyke Research (formerly IGER). The presentation will then continue with a description of a void network model of sufficient accuracy and authenticity that it can be used to explain and predict the nitrous oxide production, and the modelling of the biological, chemical and physical processes for the production of nitrous oxide within the constructed network. Finally, conclusions will be drawn from a comparison of the model results with experiment. The void network model Nitrous oxide is produced by microbial activity located in ‘hotspots' within the microstructure of soil, and nutrients and gases flow or diffuse to and from these hotspots through the water or gas-filled macro-porosity. It is clear, therefore, that a network model to describe and explain nitrous oxide production must encompass the full size range of pore space active within the process, which covers 6 orders of magnitude, and must make realistic suppositions about the positional relationship of the hotspots relative to the soil macro-porosity. Previous experimental (Tsakiroglou, C. D. et al, European J.Soil Sci., 2008) and theoretical approaches to the modelling of soil void structure cannot generally meet these two requirements. We have therefore built on the success of the previous uni-porous model of soil (Matthews, G. P. et al, Wat.Resour.Res, 2010), and the concept of a critical percolation path, to develop a dual porous model (Laudone, G. M. et al, European J.Soil Sci., 2010) with the following features: • A porous unit cell, with periodic boundary conditions, and with a critical percolation path with the correct percolation characteristics and void volume of the macro-porosity of the soil. • A solid phase between the pores of the large unit cell, with the correct volume of the fraction of larger soil aggregates (larger 1 mm). • All the remaining pores of the large unit cell, which are not part of the critical percolation path, filled with smaller unit cells, which account for the micro-porosity of the soil sample. We describe the construction of a model that closely matches the following characteristics of a specific example of typical arable soil, taken from the Warren field of the Rothamsted experimental farm at Woburn, although the model can be used for a wide range of soils: (i) macroporosity and microporosity as measured by the water retention curve, (ii) the shape of the water retention characteristic under a wide range of tensions, (iii) the soil texture, and (iv) the extent of irreducible water content. Process model We will describe the insertion of Michaelis-Menten kinetics and Crank-Nicholson diffusion equations into the precisely scaled model, building on previous diffusion modelling (Laudone, G. M. et al, Chem.Eng.Sci., 2008). Comparison with experiment A comparison with experimental results sheds light on (i) the positional relationships of aerobic and anaerobic bacteria relative to the critical percolation path, (ii) the relationship between the critical percolation path and the preferential / critical flow path (Figure 4), (iii) the extent of ignorance about the reaction kinetics of some of the fundamental processes occurring, (iv) the soil conditions that cause nitrous oxide emission, and (v) the effect of soil compaction on the emission. Acknowledgement This presentation is a summary of the some of the work of the BBSRC funded U.K. soil research consortium "Soil Programme for Quality and Resilience" (BB/E001793/1 and others), of which Matthews is principal investigator.

The dielectric properties of soil-water mixtures at microwave frequencies

NASA Technical Reports Server (NTRS)

Wang, J. R.

1979-01-01

Recent measurements on the dielectric constants of soil-water mixtures show the existence of two frequency regions in which the dielectric behavior of these mixtures was quite different. At the frequencies of 1.4 GHz to 5 GHz, there were strong evidences that the variations of the dielectric (epsilon) with water content (W) depended on soil type. While the real part of epsilon for sandy soils rose rapidly with the increase in W, epsilon for the high-clay content soils rose only slowly with W. As a consequence, epsilon was generally higher for the sandy soils than for the high-clay content soils at a given W. On the other hand, most of the measurements at frequencies 1 GHz indicated the increase of epsilon with W independent of soil types. At a given W, epsilon' (sandy soil) approximately equals epsilon (high-clay content soil) within the precision of the measurements. These observational features can be satisfactorily interpreted in terms of a simple dielectric relaxation model, with an appropriate choice of the mean relaxation frequency f(m) and the range of the activation energy (beta). It was found that smaller f(m) and larger beta were required for the high-clay content soils than the sandy soils in order to be consistent with the measured data.

High-resolution moisture profiles from full-waveform probabilistic inversion of TDR signals

NASA Astrophysics Data System (ADS)

Laloy, Eric; Huisman, Johan Alexander; Jacques, Diederik

2014-11-01

This study presents an novel Bayesian inversion scheme for high-dimensional undetermined TDR waveform inversion. The methodology quantifies uncertainty in the moisture content distribution, using a Gaussian Markov random field (GMRF) prior as regularization operator. A spatial resolution of 1 cm along a 70-cm long TDR probe is considered for the inferred moisture content. Numerical testing shows that the proposed inversion approach works very well in case of a perfect model and Gaussian measurement errors. Real-world application results are generally satisfying. For a series of TDR measurements made during imbibition and evaporation from a laboratory soil column, the average root-mean-square error (RMSE) between maximum a posteriori (MAP) moisture distribution and reference TDR measurements is 0.04 cm3 cm-3. This RMSE value reduces to less than 0.02 cm3 cm-3 for a field application in a podzol soil. The observed model-data discrepancies are primarily due to model inadequacy, such as our simplified modeling of the bulk soil electrical conductivity profile. Among the important issues that should be addressed in future work are the explicit inference of the soil electrical conductivity profile along with the other sampled variables, the modeling of the temperature-dependence of the coaxial cable properties and the definition of an appropriate statistical model of the residual errors.

Microstrip Ring Resonator for Soil Moisture Measurements

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Li, Eric S.

1993-01-01

Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant (epsilon(sub soil)) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of epsilon(sub soil). In this paper a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of epsilon(sub soil) are determined from the changes in the resonant frequency and the quality factor of the resonator respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasi-static formulation in conjunction with experimental data obtained from reference dielectric samples. Also a simple inversion algorithm for epsilon(sub soil) = epsilon'(sub r) + j(epsilon"(sub r)) based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

Infusion of SMAP Data into Offline and Coupled Models: Evaluation, Calibration, and Assimilation

NASA Astrophysics Data System (ADS)

Lawston, P.; Santanello, J. A., Jr.; Dennis, E. J.; Kumar, S.

2017-12-01

The impact of the land surface on the water and energy cycle is modulated by its coupling to the planetary boundary layer (PBL), and begins at the local scale. A core component of the local land-atmosphere coupling (LoCo) effort requires understanding the `links in the chain' between soil moisture and precipitation, most notably through surface heat fluxes and PBL evolution. To date, broader (i.e. global) application of LoCo diagnostics has been limited by observational data requirements of the coupled system (and in particular, soil moisture) that are typically only met during localized, short-term field campaigns. SMAP offers, for the first time, the ability to map high quality, near-surface soil moisture globally every few days at a spatial resolution comparable to current modeling efforts. As a result, there are numerous potential avenues for SMAP model-data fusion that can be explored in the context of improving understanding of L-A interaction and NWP. In this study, we assess multiple points of intersection of SMAP products with offline and coupled models and evaluate impacts using process-level diagnostics. Results will inform upon the importance of high-resolution soil moisture mapping for improved coupled prediction and model development, as well as reconciling differences in modeled, retrieved, and measured soil moisture. Specifically, NASA model (LIS, NU-WRF) and observation (SMAP, NLDAS-2) products are combined with in-situ standard and IOP measurements (soil moisture, flux, and radiosonde) over the ARM-SGP. An array of land surface model spinups (via LIS-Noah) are performed with varying atmospheric forcing, greenness fraction, and soil layering permutations. Calibration of LIS-Noah soil hydraulic parameters is then performed using an array of in-situ soil moisture and flux and SMAP products. In addition, SMAP assimilation is performed in LIS-Noah both at the scale of the observation (36 and 9km) and the model grid (1km). The focus is on the consistency in calibrated parameters, impact of soil drydown dynamics and soil layers, and terrestrial (soil moisture-flux) coupling. The impacts of these various spinup runs and initialization of NU-WRF coupled forecasts then follows with a focus on weather (ambient, PBL, and precipitation) using LoCo metrics.

Forest floor methane flux modelled by soil water content and ground vegetation - comparison to above canopy flux

NASA Astrophysics Data System (ADS)

Halmeenmäki, Elisa; Peltola, Olli; Haikarainen, Iikka; Ryhti, Kira; Rannik, Üllar; Pihlatie, Mari

2017-04-01

Methane (CH4) is an important and strong greenhouse gas of which atmospheric concentration is rising. While boreal forests are considered as an important sink of CH4 due to soil CH4 oxidation, the soils have also a capacity to emit CH4. Moreover, vegetation is shown to contribute to the ecosystem-atmosphere CH4 flux, and it has been estimated to be the least well known natural sources of CH4. In addition to well-known CH4 emissions from wetland plants, even boreal trees have been discovered to emit CH4. At the SMEAR (Station for Measuring Ecosystem-Atmosphere Relations) II station in Hyytiälä, southern Finland (61° 51' N, 24°17' E; 181 m asl), we have detected small CH4 emissions from above the canopy of a Scots pine (Pinus sylvestris) dominated forest. To assess the origin of the observed emissions, we conducted forest floor CH4 flux measurements with 54 soil chambers at the footprint area of the above canopy flux measurements during two growing seasons. In addition, we measured the soil volumetric water content (VWC) every time next to the forest floor chamber measurements, and estimated vegetation coverages inside the chambers. In order to model the forest floor CH4 flux at the whole footprint area, we combined lidar (light detection and ranging) data with the field measurements. To predict the soil water content and thus the potential CH4 flux, we used local elevation, slope, and ground return intensity (GRI), calculated from the lidar data (National Land Survey of Finland). We categorized the soil chambers into four classes based on the VWC so that the class with the highest VWC values includes all the soil chambers with a potential to emit CH4. Based on a statistically significant correlation between the VWC and the forest floor CH4 flux (r = 0.30, p < 0.001), we modelled the potential forest floor CH4 flux of the whole area. The results of the soil chamber measurements show a few areas of the forest floor with significant CH4 emissions. The modelled map of the potential CH4 flux is consistent with the measurements of the flux and the VWC, indicating that the wetter areas have potential for CH4 emissions, while the drier areas have potential for CH4 uptake. Preliminary results of the vegetation coverage show a positive correlation between the first year forest floor CH4 flux and the coverage of Sphagnum spp. mosses (r = 0.55, p < 0.001). Furthermore, we will include the vegetation coverage to the analysis, and compare the modelled forest floor CH4 flux with the measured above canopy flux. This ongoing research will give valuable information about the CH4 sources and dynamics in boreal forests.

Method to measure soil matrix infiltration in forest soil

NASA Astrophysics Data System (ADS)

Zhang, Jing; Lei, Tingwu; Qu, Liqin; Chen, Ping; Gao, Xiaofeng; Chen, Chao; Yuan, Lili; Zhang, Manliang; Su, Guangxu

2017-09-01

Infiltration of water into forest soil commonly involves infiltration through the matrix body and preferential passages. Determining the matrix infiltration process is important in partitioning water infiltrating into the soil through the soil body and macropores to evaluate the effects of soil and water conservation practices on hillslope hydrology and watershed sedimentation. A new method that employs a double-ring infiltrometer was applied in this study to determine the matrix infiltration process in forest soil. Field experiments were conducted in a forest field on the Loess Plateau at Tianshui Soil and Water Conservation Experimental Station. Nylon cloth was placed on the soil surface in the inner ring and between the inner and outer rings of infiltrometers. A thin layer of fine sands were placed onto the nylon cloth to shelter the macropores and ensure that water infiltrates the soil through the matrix only. Brilliant Blue tracers were applied to examine the exclusion of preferential flow occurrences in the measured soil body. The infiltration process was measured, computed, and recorded through procedures similar to those of conventional methods. Horizontal and vertical soil profiles were excavated to check the success of the experiment and ensure that preferential flow did not occur in the measured soil column and that infiltration was only through the soil matrix. The infiltration processes of the replicates of five plots were roughly the same, thereby indicating the feasibility of the methodology to measure soil matrix infiltration. The measured infiltration curves effectively explained the transient process of soil matrix infiltration. Philip and Kostiakov models fitted the measured data well, and all the coefficients of determination were greater than 0.9. The wetted soil bodies through excavations did not present evidence of preferential flow. Therefore, the proposed method can determine the infiltration process through the forest soil matrix. This method can also be applied to explore matrix infiltration in other land-use types.

Predicting the mineral composition of dust aerosols: Insights from elemental composition measured at the Izaña Observatory

NASA Astrophysics Data System (ADS)

Pérez García-Pando, Carlos; Miller, Ron L.; Perlwitz, Jan P.; Rodríguez, Sergio; Prospero, Joseph M.

2016-10-01

Regional variations of dust mineral composition are fundamental to climate impacts but generally neglected in climate models. A challenge for models is that atlases of soil composition are derived from measurements following wet sieving, which destroys the aggregates potentially emitted from the soil. Aggregates are crucial to simulating the observed size distribution of emitted soil particles. We use an extension of brittle fragmentation theory in a global dust model to account for these aggregates. Our method reproduces the size-resolved dust concentration along with the approximately size-invariant fractional abundance of elements like Fe and Al in the decade-long aerosol record from the Izaña Observatory, off the coast of West Africa. By distinguishing between Fe in structural and free forms, we can attribute improved model behavior to aggregation of Fe and Al-rich clay particles. We also demonstrate the importance of size-resolved measurements along with elemental composition analysis to constrain models.

Evaluation of different field methods for measuring soil water infiltration

NASA Astrophysics Data System (ADS)

Pla-Sentís, Ildefonso; Fonseca, Francisco

2010-05-01

Soil infiltrability, together with rainfall characteristics, is the most important hydrological parameter for the evaluation and diagnosis of the soil water balance and soil moisture regime. Those balances and regimes are the main regulating factors of the on site water supply to plants and other soil organisms and of other important processes like runoff, surface and mass erosion, drainage, etc, affecting sedimentation, flooding, soil and water pollution, water supply for different purposes (population, agriculture, industries, hydroelectricity), etc. Therefore the direct measurement of water infiltration rates or its indirect deduction from other soil characteristics or properties has become indispensable for the evaluation and modelling of the previously mentioned processes. Indirect deductions from other soil characteristics measured under laboratory conditions in the same soils, or in other soils, through the so called "pedo-transfer" functions, have demonstrated to be of limited value in most of the cases. Direct "in situ" field evaluations have to be preferred in any case. In this contribution we present the results of past experiences in the measurement of soil water infiltration rates in many different soils and land conditions, and their use for deducing soil water balances under variable climates. There are also presented and discussed recent results obtained in comparing different methods, using double and single ring infiltrometers, rainfall simulators, and disc permeameters, of different sizes, in soils with very contrasting surface and profile characteristics and conditions, including stony soils and very sloping lands. It is concluded that there are not methods universally applicable to any soil and land condition, and that in many cases the results are significantly influenced by the way we use a particular method or instrument, and by the alterations in the soil conditions by the land management, but also due to the manipulation of the surface soil before and during the measurement. Due to the commonly found high variability, natural or induced by land management, of the soil surface and subsurface hydrological properties, and to the limitations imposed by the requirements of water for the measurements, there is proposed a simple and handy method, which do not use high volumes of water, adaptable to very different soil and land conditions, and that allow many repeated measurements with acceptable accuracy for most of the purposes. References Pla, I., 1997. A soil water balance model for monitoring soil erosion processes and effects on steep lands in the tropics. Soil Technology. 11(1):17-30. Elsevier Pla, I., 2006. Hydrological approach for assessing desertification processes in the Mediterranean region. In W.G. Kepner et al. (Editors), Desertification in the Mediterranean Region. A Security Issue. 579-600 Springer. Heidelberg (Germany) Reynolds W.D., B.T. Bowman, R.R. Brunke, C.F. Drury and C.S. Tan. 2000. Comparison of Tension Infiltrometer, Pressure Infiltrometer, and Soil Core Estimates of Saturated Hydraulic Conductivity . Soil Science Society of America Journal 64:478-484 Segal, E., S.A.Bradford, P. Shouse; N. Lazarovich, and D. Corwin. 2008. Integration of Hard and Soft Data to Characterize Field-Scale Hydraulic Properties for Flow and Transport Studies. Vadose Zone J 7:878-889 Young, E. 1991. Infiltration measurements, a review. Hydrological processes 5: 309-320.

Integrated measurements and modeling of CO2, CH4, and N2O fluxes using soil microsite frequency distributions

NASA Astrophysics Data System (ADS)

Davidson, Eric; Sihi, Debjani; Savage, Kathleen

2017-04-01

Soil fluxes of greenhouse gases (GHGs) play a significant role as biotic feedbacks to climate change. Production and consumption of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) are affected by complex interactions of temperature, moisture, and substrate supply, which are further complicated by spatial heterogeneity of the soil matrix. Models of belowground processes of these GHGs should be internally consistent with respect to the biophysical processes of gaseous production, consumption, and transport within the soil, including the contrasting effects of oxygen (O2) as either substrate or inhibitor. We installed automated chambers to simultaneously measure soil fluxes of CO2 (using LiCor-IRGA), CH4, and N2O (using Aerodyne quantum cascade laser) along soil moisture gradients at the Howland Forest in Maine, USA. Measured fluxes of these GHGs were used to develop and validate a merged model. While originally intended for aerobic respiration, the core structure of the Dual Arrhenius and Michaelis-Menten (DAMM) model was modified by adding M-M and Arrhenius functions for each GHG production and consumption process, and then using the same diffusion functions for each GHG and for O2. The area under a soil chamber was partitioned according to a log-normal probability distribution function, where only a small fraction of microsites had high available-C. The probability distribution of soil C leads to a simulated distribution of heterotrophic respiration, which translates to a distribution of O2 consumption among microsites. Linking microsite consumption of O2 with a diffusion model generates microsite concentrations of O2, which then determine the distribution of microsite production and consumption of CH4 and N2O, and subsequently their microsite concentrations using the same diffusion function. At many moisture values, there are some microsites of production and some of consumption for each gas, and the resulting simulated microsite concentrations of CH4 and N2O range from below ambient to above ambient atmospheric values. As soil moisture or temperature increase, the skewness of the microsite distributions of heterotrophic respiration and CH4 concentrations shifts toward a larger fraction of high values, while the skewness of microsite distributions of O2 and N2O concentrations shifts toward a larger fraction of low values. This approach of probability distribution functions for each gas simulates the importance of microsite hotspots of methanogenesis and N2O reduction at high moisture (and temperature). In addition, the model demonstrates that net consumption of atmospheric CH4 and N2O can occur simultaneously within a chamber due to the distribution of soil microsite conditions, which is consistent with some episodes of measured fluxes. Because soil CO2, N2O and CH4 fluxes are linked through substrate supply and O2 effects, the multiple constraints of simultaneous measurements of all three GHGs proved to be effective when applied to our combined model. Simulating all three GHGs simultaneously in a parsimonious modeling framework provides confidence that the most important mechanisms are skillfully simulated using appropriate parameterization and good process representation.

Hydrologic controls on the development of equilibrium soil depths

NASA Astrophysics Data System (ADS)

Nicotina, L.; Tarboton, D. G.; Tesfa, T. K.; Rinaldo, A.

2010-12-01

The object of the present work was the study of the coevolution of runoff production and geomorphological processes and its effects on the formation of equilibrium soil depth by focusing on their mutual feedbacks. The primary goal of this work is to describe spatial patterns of soil depth resulting, under the hypothesis of dynamic equilibrium, from long-term interactions between hydrologic forcings and soil production, erosion and sediment transport processes. These processes dominate the formation of actual soil depth patterns that represent the boundary condition for water redistribution, thus this paper also proposes and attempt to set the premises for decoding their individual role and mutual interactions in shaping the hydrologic response of a catchment. The relevance of the study stems from the massive improvement in hydrologic predictions for ungauged basins that would be achieved by using directly soil depths derived from geomorphic features remotely measured and objectively manipulated. Moreover the setup of a coupled hydrologic-geomorphologic approach represents a first step into the study of such interactions and in particular of the effects of soil moisture in determining soil production functions. Hydrological processes are here described by explicitly accounting for local soil depths and detailed catchment topography from high resolution digital terrain models (DTM). Geomorphological processes are described by means of well-studied geomorphic transport laws. Soil depth is assumed, in the exponential soil production function, as a proxy for all the mechanisms that induce mechanical disruption of bedrock and it’s conversion into soil. This formulation, although empirical, has been widely used in the literature and is currently accepted. The modeling approach is applied to the semi-arid Dry Creek Experimental Watershed, located near Boise, Idaho, USA. Modeled soil depths are compared with field data obtained from an extensive survey of the catchment. Our results show the ability of the model to describe properly the mean soil depth and the broad features of the distribution of measured data. However, local comparisons show significant scatter whose origin is discussed.

Modelling soil erosion at European scale: towards harmonization and reproducibility

NASA Astrophysics Data System (ADS)

Bosco, C.; de Rigo, D.; Dewitte, O.; Poesen, J.; Panagos, P.

2015-02-01

Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water-holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale, because a systematic knowledge of local climatological and soil parameters is often unavailable. A new approach for modelling soil erosion at regional scale is here proposed. It is based on the joint use of low-data-demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available data sets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country-level statistics of pre-existing European soil erosion maps is also provided.

Soil respiration and photosynthetic uptake of carbon dioxide by ground-cover plants in four ages of jack pine forest

USGS Publications Warehouse

Striegl, Robert G.; Wickland, K.P.

2001-01-01

Soil carbon dioxide (CO2) emission (soil respiration), net CO2 exchange after photosynthetic uptake by ground-cover plants, and soil CO2 concentration versus depth below land surface were measured at four ages of jack pine (Pinus banksiana Lamb.) forest in central Saskatchewan. Soil respiration was smallest at a clear-cut site, largest in an 8-year-old stand, and decreased with stand age in 20-year-old and mature (60-75 years old) stands during May-September 1994 (12.1, 34.6, 31.5, and 24.9 mol C??m-2, respectively). Simulations of soil respiration at each stand based on continuously recorded soil temperature were within one standard deviation of measured flux for 48 of 52 measurement periods, but were 10%-30% less than linear interpolations of measured flux for the season. This was probably due to decreased soil respiration at night modeled by the temperature-flux relationships, but not documented by daytime chamber measurements. CO2 uptake by ground-cover plants ranged from 0 at the clear-cut site to 29, 25, and 9% of total growing season soil respiration at the 8-year, 20-year, and mature stands. CO2 concentrations were as great as 7150 ppmv in the upper 1 m of unsaturated zone and were proportional to measured soil respiration.

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A. D.

2013-07-01

surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Validating the use of 137Cs and 210Pbex measurements to estimate rates of soil loss from cultivated land in southern Italy.

PubMed

Porto, Paolo; Walling, Des E

2012-04-01

Soil erosion represents an important threat to the long-term sustainability of agriculture and forestry in many areas of the world, including southern Italy. Numerous models and prediction procedures have been developed to estimate rates of soil loss and soil redistribution, based on the local topography, hydrometeorology, soil type and land management. However, there remains an important need for empirical measurements to provide a basis for validating and calibrating such models and prediction procedures as well as to support specific investigations and experiments. In this context, erosion plots provide useful information on gross rates of soil loss, but are unable to document the efficiency of the onward transfer of the eroded sediment within a field and towards the stream system, and thus net rates of soil loss from larger areas. The use of environmental radionuclides, particularly caesium-137 ((137)Cs) and excess lead-210 ((210)Pb(ex)), as a means of estimating rates of soil erosion and deposition has attracted increasing attention in recent years and the approach has now been recognised as possessing several important advantages. In order to provide further confirmation of the validity of the estimates of longer-term erosion and soil redistribution rates provided by (137)Cs and (210)Pb(ex) measurements, there is a need for studies aimed explicitly at validating the results obtained. In this context, the authors directed attention to the potential offered by a set of small erosion plots located near Reggio Calabria in southern Italy, for validating estimates of soil loss provided by (137)Cs and (210)Pb(ex) measurements. A preliminary assessment suggested that, notwithstanding the limitations and constraints involved, a worthwhile investigation aimed at validating the use of (137)Cs and (210)Pb(ex) measurements to estimate rates of soil loss from cultivated land could be undertaken. The results demonstrate a close consistency between the measured rates of soil loss and the estimates provided by the (137)Cs and (210)Pb(ex) measurements and can therefore been seen as validating the use of these fallout radionuclides to document soil erosion rates in that environment. Further studies are clearly required to exploit other opportunities for validation in contrasting environments and under different land use conditions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology

NASA Astrophysics Data System (ADS)

Mohanty, B.; Kathuria, D.; Katzfuss, M.

2016-12-01

Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.

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.

Estimation of effective soil hydraulic properties at field scale via ground albedo neutron sensing

NASA Astrophysics Data System (ADS)

Rivera Villarreyes, C. A.; Baroni, G.; Oswald, S. E.

2012-04-01

Upscaling of soil hydraulic parameters is a big challenge in hydrological research, especially in model applications of water and solute transport processes. In this contest, numerous attempts have been made to optimize soil hydraulic properties using observations of state variables such as soil moisture. However, in most of the cases the observations are limited at the point-scale and then transferred to the model scale. In this way inherent small-scale soil heterogeneities and non-linearity of dominate processes introduce sources of error that can produce significant misinterpretation of hydrological scenarios and unrealistic predictions. On the other hand, remote-sensed soil moisture over large areas is also a new promising approach to derive effective soil hydraulic properties over its observation footprint, but it is still limited to the soil surface. In this study we present a new methodology to derive soil moisture at the intermediate scale between point-scale observations and estimations at the remote-sensed scale. The data are then used for the estimation of effective soil hydraulic parameters. In particular, ground albedo neutron sensing (GANS) was used to derive non-invasive soil water content in a footprint of ca. 600 m diameter and a depth of few decimeters. This approach is based on the crucial role of hydrogen compared to other landscape materials as neutron moderator. As natural neutron measured aboveground depends on soil water content, the vertical footprint of the GANS method, i.e. its penetration depth, does also. Firstly, this study was designed to evaluate the dynamics of GANS vertical footprint and derive a mathematical model for its prediction. To test GANS-soil moisture and its penetration depth, it was accompanied by other soil moisture measurements (FDR) located at 5, 20 and 40 cm depths over the GANS horizontal footprint in a sunflower field (Brandenburg, Germany). Secondly, a HYDRUS-1D model was set up with monitored values of crop height and meteorological variables as input during a four-month period. Parameter estimation (PEST) software was coupled to HYDRUS-1D in order to calibrate soil hydraulic properties based on soil water content data. Thirdly, effective soil hydraulic properties were derived from GANS-soil moisture. Our observations show the potential of GANS to compensate the lack of information at the intermediate scale, soil water content estimation and effective soil properties. Despite measurement volumes, GANS-derived soil water content compared quantitatively to FDRs at several depths. For one-hour estimations, root mean square error was estimated as 0.019, 0.029 and 0.036 m3/m3 for 5 cm, 20 cm and 40 cm depths, respectively. In the context of soil hydraulic properties, this first application of GANS method succeed and its estimations were comparable to those derived by other approaches.

Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

NASA Astrophysics Data System (ADS)

Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu

2017-09-01

Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.

A new optical method coupling light polarization and Vis-NIR spectroscopy to improve the measured absorbance signal's quality of soil samples.

NASA Astrophysics Data System (ADS)

Gobrecht, Alexia; Bendoula, Ryad; Roger, Jean-Michel; Bellon-Maurel, Véronique

2014-05-01

Visible - Near-infrared spectroscopy (Vis-NIRS) is now commonly used to measure different physical and chemical parameters of soils, including carbon content. However, prediction model accuracy is insufficient for Vis-NIRS to replace routine laboratory analysis. One of the biggest issues this technique is facing up to is light scattering due to soil particles. It causes departure in the assumed linear relationship between the Absorbance spectrum and the concentration of the chemicals of interest as stated by Beer-Lambert's Law, which underpins the calibration models. Therefore it becomes essential to improve the metrological quality of the measured signal in order to optimize calibration as light/matter interactions are at the basis of the resulting linear modeling. Optics can help to mitigate scattering effect on the signal. We put forward a new optical setup coupling linearly polarized light with a Vis-NIR spectrometer to free the measured spectra from multi-scattering effect. The corrected measured spectrum was then used to compute an Absorbance spectrum of the sample, using Dahm's Equation in the frame of the Representative Layer Theory. This method has been previously tested and validated on liquid (milk+ dye) and powdered (sand + dye) samples showing scattering (and absorbing) properties. The obtained Absorbance was a very good approximation of the Beer-Lambert's law absorbance. Here, we tested the method on a set of 54 soil samples to predict Soil Organic Carbon content. In order to assess the signal quality improvement by this method, we built and compared calibration models using Partial Least Square (PLS) algorithm. The prediction model built from new Absorbance spectrum outperformed the model built with the classical Absorbance traditionally obtained with Vis-NIR diffuse reflectance. This study is a good illustration of the high influence of signal quality on prediction model's performances.

Development of a model to simulate the impact of atmospheric stability on N2O-fluxes from soil

NASA Astrophysics Data System (ADS)

Thieme, Christoph; Klein, Christian; Biernath, Christian; Heinlein, Florian; Priesack, Eckart

2014-05-01

The trace gas N2O, mainly produced by microorganisms in agricultural soils, is a very stable and thus potent greenhouse gas and is the main contributor for the recent depletion of ozone in the stratosphere. Therefore N2O-emissions need to be mitigated and thus much effort has been made to reveal the causes of N2O-formation in soils. At present some crucial drivers for N2O-fluxes are known, but underlying processes of N2O-fluxes are not yet understood or described adequately. An important shortcoming is the description of the upper boundary layer at the soil-atmosphere interface. Therefore, the aim of this study is to develop a mechanistic simulation model, which considers both the formation of N2O in agricultural soils, and the impact of the atmospheric conditions on the transport of soil-born N2O into the atmosphere. The new model simulates N2O-flux as a function of meteorological values instead of a model that just releases the whole amount of N2O into the atmosphere. For this purpose the modular ecosystem model framework Expert-N, which allows to simulate the formation of N2O in the soils will be extended to a model with a more detailed description of the upper boundary condition at the soil-atmosphere interface. In detail, this is realized in the form of a resistance approach, where N2O-fluxes are constrained by a land-air resistance that depends on a Bulk-Exchange Coefficient, wind speed and a gradient of N2O concentrations in the lower atmosphere. Descriptions of atmospheric stability follow the Monin-Obhukov Similarity Theory. The newly developed model will be validated using Eddy Covariance measurements of N2O-fluxes. Measurement device for the N2O concentrations is a Quantum-Cascade-Dual-Laser produced by Aerodyne Research Inc. (Billerca, Mass., USA). The measurements were conducted on an intensively managed field at the TERENO research farm Scheyern (Germany), which is part of the TERENO Bavarian Alps / Pre-Alps observatory.

Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies

NASA Technical Reports Server (NTRS)

Norman, J. M.

1984-01-01

Efforts to develop a three dimensional model to predict canopy, bidirectional reflectance for heterogenous plant stands using incident radiation and canopy structural descriptions as inputs are described. Utility programs were developed to cope with the complex output from the 3 dimensional model. In addition an attempt was made to define leaf and soil properties, which are appropriate to the mode, by measuring leaf and soil bidirectional reflectance distribution functions; since almost no data exist on these distributions. In the process it was realized that most models probably are using the wrong leaf spectral properties, and that off-nadir reflectance measurements are difficult to make because of non-Lambertian properties of reference surfaces. Also, in the visible wavebands, rough soil may not be distinguishable from canopies when viewed from above.

Using 50 years of soil radiocarbon data to identify optimal approaches for estimating soil carbon residence times

NASA Astrophysics Data System (ADS)

Baisden, W. T.; Canessa, S.

2013-01-01

In 1959, Athol Rafter began a substantial programme of systematically monitoring the flow of 14C produced by atmospheric thermonuclear tests through organic matter in New Zealand soils under stable land use. A database of ∼500 soil radiocarbon measurements spanning 50 years has now been compiled, and is used here to identify optimal approaches for soil C-cycle studies. Our results confirm the potential of 14C to determine residence times, by estimating the amount of ‘bomb 14C’ incorporated. High-resolution time series confirm this approach is appropriate, and emphasise that residence times can be calculated routinely with two or more time points as little as 10 years apart. This approach is generally robust to the key assumptions that can create large errors when single time-point 14C measurements are modelled. The three most critical assumptions relate to: (1) the distribution of turnover times, and particularly the proportion of old C (‘passive fraction’), (2) the lag time between photosynthesis and C entering the modelled pool, (3) changes in the rates of C input. When carrying out approaches using robust assumptions on time-series samples, multiple soil layers can be aggregated using a mixing equation. Where good archived samples are available, AMS measurements can develop useful understanding for calibrating models of the soil C cycle at regional to continental scales with sample numbers on the order of hundreds rather than thousands. Sample preparation laboratories and AMS facilities can play an important role in coordinating the efficient delivery of robust calculated residence times for soil carbon.

Mercury emission and dispersion models from soils contaminated by cinnabar mining and metallurgy.

PubMed

Llanos, Willians; Kocman, David; Higueras, Pablo; Horvat, Milena

2011-12-01

The laboratory flux measurement system (LFMS) and dispersion models were used to investigate the kinetics of mercury emission flux (MEF) from contaminated soils. Representative soil samples with respect to total Hg concentration (26-9770 μg g(-1)) surrounding a decommissioned mercury-mining area (Las Cuevas Mine), and a former mercury smelter (Cerco Metalúrgico de Almadenejos), in the Almadén mercury mining district (South Central Spain), were collected. Altogether, 14 samples were analyzed to determine the variation in mercury emission flux (MEF) versus distance from the sources, regulating two major environmental parameters comprising soil temperature and solar radiation. In addition, the fraction of the water-soluble mercury in these samples was determined in order to assess how MEF from soil is related to the mercury in the aqueous soil phase. Measured MEFs ranged from less than 140 to over 10,000 ng m(-2) h(-1), with the highest emissions from contaminated soils adjacent to point sources. A significant decrease of MEF was then observed with increasing distance from these sites. Strong positive effects of both temperature and solar radiation on MEF was observed. Moreover, MEF was found to occur more easily in soils with higher proportions of soluble mercury compared to soils where cinnabar prevails. Based on the calculated Hg emission rates and with the support of geographical information system (GIS) tools and ISC AERMOD software, dispersion models for atmospheric mercury were implemented. In this way, the gaseous mercury plume generated by the soil-originated emissions at different seasons was modeled. Modeling efforts revealed that much higher emissions and larger mercury plumes are generated in dry and warm periods (summer), while the plume is smaller and associated with lower concentrations of atmospheric mercury during colder periods with higher wind activity (fall). Based on the calculated emissions and the model implementation, yearly emissions from the "Cerco Metalúrgico de Almadenejos" decommissioned metallurgical precinct were estimated at 16.4 kg Hg y(-1), with significant differences between seasons.

Fort A.P. Hill Soil Permittivity and Conductivity Measurements for the Wide Area Airborne Minefield Detection Program

DTIC Science & Technology

2003-09-01

4 3. Purpose 4 4. Description of Test Equipment 4 4.1 Damaskos Model 3000T Liquid/Powder Cell Permittivity...Permeability System ..........4 4.2 HP8510 Network Analyzer/ Damaskos System Overview..............................................5 5. Soil Sample Site...Permittivity and conductivity values were measured from 100 to 3000 MHz. The soil samples were packed as tight as possible into the Damaskos

The effect of measured and estimated soil hydraulic properties on simulated water regime in the analysis of grapevine adaptability to future climate

NASA Astrophysics Data System (ADS)

Bonfante, Antonello; Alfieri, Silvia Maria; Agrillo, Antonietta; Dragonetti, Giovanna; Mileti, Antonio; Monaco, Eugenia; De Lorenzi, Francesca

2013-04-01

In the last years many research works have been addressed to evaluate the impact of future climate on crop productivity and plant water use at different spatial scales (global, regional, field) by means of simulation models of agricultural crop systems. Most of these approaches use estimated soil hydraulic properties, through pedotransfer functions (PTF). This choice is related to soil data availability: soil data bases lack measured soil hydraulic properties, but generally they contain information that allow the application of PTF . Although the reliability of the predicted future climate scenarios cannot be immediately validated, we address to evaluate the effects of a simplification of the soil system by using PTF. Thus we compare simulations performed with measured soil hydraulic properties versus simulations carried out with estimated properties. The water regimes resulting from the two procedures are evaluated with respect to crop adaptability to future climate. In particular we will examine if the two procedures bring about different seasonal and spatial variations in the soil water regime patterns, and if these patterns influence adaptation options. The present case study uses the agro-hydrological model SWAP (soil-water-atmosphere and plant) and studies future adaptability of grapevine. The study area is a viticultural area of Southern Italy (Valle Telesina, BN) devoted to the production of high quality wines (DOC and DOCG), and characterized by a complex geomorphology and pedology. The future climate scenario (2021-2050) was constructed applying statistical downscaling techniques to GCMs scenarios. The moisture regime for 25 soils of the selected study area was calculated by means of SWAP model, using both measured and estimated soil hydraulic properties. In the simulation, the upper boundary conditions were derived from the regional climate scenarios. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were estimated on the basis of scientific literature and assumed to be generically representative of the species. From the output of the simulation runs, the relative evapotranspiration deficit (or Crop Water Stress Index - CWSI) of the soil units was calculated. Since CWSI is considered an important indicator of the qualitative grapevine responses, its pattern in both simulation procedures has been evaluated. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)

Weathering profiles in soils and rocks on Earth and Mars

NASA Astrophysics Data System (ADS)

Hausrath, E.; Adcock, C. T.; Bamisile, T.; Baumeister, J. L.; Gainey, S.; Ralston, S. J.; Steiner, M.; Tu, V.

2017-12-01

Interactions of liquid water with rock, soil, or sediments can result in significant chemical and mineralogical changes with depth. These changes can include transformation from one phase to another as well as translocation, addition, and loss of material. The resulting chemical and mineralogical depth profiles can record characteristics of the interacting liquid water such as pH, temperature, duration, and abundance. We use a combined field, laboratory, and modeling approach to interpret the environmental conditions preserved in soils and rocks. We study depth profiles in terrestrial field environments; perform dissolution experiments of primary and secondary phases important in soil environments; and perform numerical modeling to quantitatively interpret weathering environments. In our field studies we have measured time-integrated basaltic mineral dissolution rates, and interpreted the impact of pH and temperature on weathering in basaltic and serpentine-containing rocks and soils. These results help us interpret fundamental processes occurring in soils on Earth and on Mars, and can also be used to inform numerical modeling and laboratory experiments. Our laboratory experiments provide fundamental kinetic data to interpret processes occurring in soils. We have measured dissolution rates of Mars-relevant phosphate minerals, clay minerals, and amorphous phases, as well as dissolution rates under specific Mars-relevant conditions such as in concentrated brines. Finally, reactive transport modeling allows a quantitative interpretation of the kinetic, thermodynamic, and transport processes occurring in soil environments. Such modeling allows the testing of conditions under longer time frames and under different conditions than might be possible under either terrestrial field or laboratory conditions. We have used modeling to examine the weathering of basalt, olivine, carbonate, phosphate, and clay minerals, and placed constraints on the duration, pH, and solution chemistry of past aqueous alteration occurring on Mars.

Why the predictions for monsoon rainfall fail?

NASA Astrophysics Data System (ADS)

Lee, J.

2016-12-01

To be in line with the Global Land/Atmosphere System Study (GLASS) of the Global Energy and Water Cycle Experiment (GEWEX) international research scheme, this study discusses classical arguments about the feedback mechanisms between land surface and precipitation to improve the predictions of African monsoon rainfall. In order to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, several data sets will be presented. First, in-situ soil moisture field measurements acquired by the AMMA field campaign will be shown together with rain gauge data. This data set will validate various model and satellite data sets such as NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models, SMOS soil moisture. To relate soil moisture with precipitation, two approaches are employed: one approach makes a direct comparison between the spatial distributions of soil moisture as an absolute value and rainfall, while the other measures a temporal evolution of the consecutive dry days (i.e. a relative change within the same soil moisture data set over time) and rainfall occurrences. Consecutive dry days shows consistent results of a negative feedback between soil moisture and rainfall across various data sets, contrary to the direct comparison of soil moisture state. This negative mechanism needs attention, as most climate models usually focus on a positive feedback only. The approach of consecutive dry days takes into account the systematic errors in satellite observations, reminding us that it may cause the misinterpretation to directly compare model with satellite data, due to their difference in data retrievals. This finding is significant, as the climate indices employed by the Intergovernmental Panel on Climate Change (IPCC) modelling archive are based on the atmospheric variable rathr than land.

Spatio-temporal interpolation of soil moisture in 3D+T using automated sensor network data

NASA Astrophysics Data System (ADS)

Gasch, C.; Hengl, T.; Magney, T. S.; Brown, D. J.; Gräler, B.

2014-12-01

Soil sensor networks provide frequent in situ measurements of dynamic soil properties at fixed locations, producing data in 2- or 3-dimensions and through time (2D+T and 3D+T). Spatio-temporal interpolation of 3D+T point data produces continuous estimates that can then be used for prediction at unsampled times and locations, as input for process models, and can simply aid in visualization of properties through space and time. Regression-kriging with 3D and 2D+T data has successfully been implemented, but currently the field of geostatistics lacks an analytical framework for modeling 3D+T data. Our objective is to develop robust 3D+T models for mapping dynamic soil data that has been collected with high spatial and temporal resolution. For this analysis, we use data collected from a sensor network installed on the R.J. Cook Agronomy Farm (CAF), a 37-ha Long-Term Agro-Ecosystem Research (LTAR) site in Pullman, WA. For five years, the sensors have collected hourly measurements of soil volumetric water content at 42 locations and five depths. The CAF dataset also includes a digital elevation model and derivatives, a soil unit description map, crop rotations, electromagnetic induction surveys, daily meteorological data, and seasonal satellite imagery. The soil-water sensor data, combined with the spatial and temporal covariates, provide an ideal dataset for developing 3D+T models. The presentation will include preliminary results and address main implementation strategies.

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.

Plant identity and shallow soil moisture are primary drivers of stomatal conductance in the savannas of Kruger National Park.

PubMed

Tobin, Rebecca L; Kulmatiski, Andrew

2018-01-01

Our goal was to describe stomatal conductance (gs) and the site-scale environmental parameters that best predict gs in Kruger National Park (KNP), South Africa. Dominant grass and woody species were measured over two growing seasons in each of four study sites that represented the natural factorial combination of mean annual precipitation [wet (750 mm) or dry (450 mm)] and soil type (clay or sand) found in KNP. A machine-learning (random forest) model was used to describe gs as a function of plant type (species or functional group) and site-level environmental parameters (CO2, season, shortwave radiation, soil type, soil moisture, time of day, vapor pressure deficit and wind speed). The model explained 58% of the variance among 6,850 gs measurements. Species, or plant functional group, and shallow (0-20 cm) soil moisture had the greatest effect on gs. Atmospheric drivers and soil type were less important. When parameterized with three years of observed environmental data, the model estimated mean daytime growing season gs as 68 and 157 mmol m-2 sec-1 for grasses and woody plants, respectively. The model produced here could, for example, be used to estimate gs and evapotranspiration in KNP under varying climate conditions. Results from this field-based study highlight the role of species identity and shallow soil moisture as primary drivers of gs in savanna ecosystems of KNP.

3D soil water nowcasting using electromagnetic conductivity imaging and the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Huang, Jingyi; McBratney, Alex; Minasny, Budiman; Triantafilis, John

2017-04-01

Mapping and immediate forecasting of soil water content (θ) and its movement can be challenging. Although apparent electrical conductivity (ECa) measured by electromagnetic induction has been used, it is difficult to apply it along a transect or across a field. Across a 3.95-ha field with varying soil texture, an ensemble Kalman filter (EnFK) was used to monitor and nowcast θ dynamics in 2-d and 3-d over 16 days. The EnKF combined a physical model fitted with θ measured by soil moisture sensors and an Artificial Neural Network model comprising estimate of true electrical conductivity (σ) generated by inversions of DUALEM-421S ECa data. Results showed that the spatio-temporal variation in θ can be successfully modelled using the EnKF (Lin's concordance = 0.89). Soil water dried fast at the beginning of the irrigation and decreased with time and soil depth, which were consistent with the classical soil drying theory and experiments. It was also found that the soil dried fast in the loamy and duplex soils across the field, which was attributable to deep drainage and preferential flows. It was concluded that the EnKF approach can be used to better the irrigation practice so that variation in irrigation is minimised and irrigation efficiency is improved by applying variable rates of irrigation across the field. In addition, soil water status can be nowcasted using this method with weather forecast information, which will provide guidance to farmers for real-time irrigation management.

Environmental forcing does not induce diel or synoptic variation in the carbon isotope content of forest soil respiration

DOE PAGES

Bowling, D. R.; Egan, J. E.; Hall, S. J.; ...

2015-08-31

Recent studies have examined temporal fluctuations in the amount and carbon isotope content (δ 13C) of CO 2 produced by the respiration of roots and soil organisms. These changes have been correlated with diel cycles of environmental forcing (e.g., sunlight and soil temperature) and with synoptic-scale atmospheric motion (e.g., rain events and pressure-induced ventilation). We used an extensive suite of measurements to examine soil respiration over 2 months in a subalpine forest in Colorado, USA (the Niwot Ridge AmeriFlux forest). Observations included automated measurements of CO 2 and δ 13C of CO 2 in the soil efflux, the soil gasmore » profile, and forest air. There was strong diel variability in soil efflux but no diel change in the δ 13C of the soil efflux (δ R) or the CO 2 produced by biological activity in the soil (δ J). Following rain, soil efflux increased significantly, but δ R and δ J did not change. Temporal variation in the δ 13C of the soil efflux was unrelated to measured environmental variables, and we failed to find an explanation for this unexpected result. Measurements of the δ 13C of the soil efflux with chambers agreed closely with independent observations of the isotopic composition of soil CO 2 production derived from soil gas well measurements. Deeper in the soil profile and at the soil surface, results confirmed established theory regarding diffusive soil gas transport and isotopic fractionation. Deviation from best-fit diffusion model results at the shallower depths illuminated a pump-induced ventilation artifact that should be anticipated and avoided in future studies. There was no evidence of natural pressure-induced ventilation of the deep soil. However, higher variability in δ 13C of the soil efflux relative to δ 13C of production derived from soil profile measurements was likely caused by transient pressure-induced transport with small horizontal length scales.« less

Field measures show methanotroph sensitivity to soil moisture follows precipitation regime of the grassland sites across the US Great Plains

NASA Astrophysics Data System (ADS)

Koyama, A.; Webb, C. T.; Johnson, N. G.; Brewer, P. E.; von Fischer, J. C.

2015-12-01

Methane uptake rates are known to have temporal variation in response to changing soil moisture levels. However, the relative importance of soil diffusivity vs. methanotroph physiology has not been disentangled to date. Testing methanotroph physiology in the laboratory can lead to misleading results due to changes in the fine-scale habitat where methanotrophs reside. To assay the soil moisture sensitivity of methanotrophs under field conditions, we studied 22 field plots scattered across eight Great Plains grassland sites that differed in precipitation regime and soil moisture, making ca. bi-weekly measures during the growing seasons over three years. Quantification of methanotroph activity was achieved from chamber-based measures of methane uptake coincident with SF6-derived soil diffusivity, and interpretation in a reaction-diffusion model. At each plot, we also measured soil water content (SWC), soil temperature and inorganic nitrogen (N) contents. We also assessed methanotroph community composition via 454 sequencing of the pmoA gene. Statistical analyses showed that methanotroph activity had a parabolic response with SWC (concave down), and significant differences in the shape of this response among sites. Moreover, we found that the SWC at peak methanotroph activity was strongly correlated with mean annual precipitation (MAP) of the site. The sequence data revealed distinct composition patterns, with structure that was associated with variation in MAP and soil texture. These results suggest that local precipitation regime shapes methanotroph community composition, which in turn lead to unique sensitivity of methane uptake rates with soil moisture. Our findings suggest that methanotroph activity may be more accurately modeled when the biological and environmental responses are explicitly described.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Predicting available water of soil from particle-size distribution and bulk density in an oasis-desert transect in northwestern China

NASA Astrophysics Data System (ADS)

Li, Danfeng; Gao, Guangyao; Shao, Ming'an; Fu, Bojie

2016-07-01

A detailed understanding of soil hydraulic properties, particularly the available water content of soil, (AW, cm3 cm-3), is required for optimal water management. Direct measurement of soil hydraulic properties is impractical for large scale application, but routinely available soil particle-size distribution (PSD) and bulk density can be used as proxies to develop various prediction functions. In this study, we compared the performance of the Arya and Paris (AP) model, Mohammadi and Vanclooster (MV) model, Arya and Heitman (AH) model, and Rosetta program in predicting the soil water characteristic curve (SWCC) at 34 points with experimental SWCC data in an oasis-desert transect (20 × 5 km) in the middle reaches of the Heihe River basin, northwestern China. The idea of the three models emerges from the similarity of the shapes of the PSD and SWCC. The AP model, MV model, and Rosetta program performed better in predicting the SWCC than the AH model. The AW determined from the SWCCs predicted by the MV model agreed better with the experimental values than those derived from the AP model and Rosetta program. The fine-textured soils were characterized by higher AW values, while the sandy soils had lower AW values. The MV model has the advantages of having robust physical basis, being independent of database-related parameters, and involving subclasses of texture data. These features make it promising in predicting soil water retention at regional scales, serving for the application of hydrological models and the optimization of soil water management.

Emission of pesticides into the air

USGS Publications Warehouse

Van Den, Berg; Kubiak, R.; Benjey, W.G.; Majewski, M.S.; Yates, S.R.; Reeves, G.L.; Smelt, J.H.; Van Der Linden, A. M. A.

1999-01-01

During and after the application of a pesticide in agriculture, a substantial fraction of the dosage may enter the atmosphere and be transported over varying distances downwind of the target. The rate and extent of the emission during application, predominantly as spray particle drift, depends primarily on the application method (equipment and technique), the formulation and environmental conditions, whereas the emission after application depends primarily on the properties of the pesticide, soils, crops and environmental conditions. The fraction of the dosage that misses the target area may be high in some cases and more experimental data on this loss term are needed for various application types and weather conditions. Such data are necessary to test spray drift models, and for further model development and verification as well. Following application, the emission of soil fumigants and soil incorporated pesticides into the air can be measured and computed with reasonable accuracy, but further model development is needed to improve the reliability of the model predictions. For soil surface applied pesticides reliable measurement methods are available, but there is not yet a reliable model. Further model development is required which must be verified by field experiments. Few data are available on pesticide volatilization from plants and more field experiments are also needed to study the fate processes on the plants. Once this information is available, a model needs to be developed to predict the volatilization of pesticides from plants, which, again, should be verified with field measurements. For regional emission estimates, a link between data on the temporal and spatial pesticide use and a geographical information system for crops and soils with their characteristics is needed.

On quantifying active soil carbon using mid-infrared ...

EPA Pesticide Factsheets

Soil organic matter (SOM) is derived from plant or animal residues deposited to soil and is in various stages of decomposition and mineralization. Total SOM is a common measure of soil quality, although due to its heterogeneous composition SOM can vary dramatically in terms of its biochemical properties and residence times, which ultimately affect soil heath and function. One operationally defined SOM fraction is “active soil carbon” (ASC) which is thought to consist of readily oxidizable SOM that is responsive to management practices and may provide one measure of “soil health” closely associated with soil biological activity. ASC can be a useful indicator to assist farmers and land managers in their selection of soil management practices to maintain ASC or to build total SOM. ASC has generally been measured using permanganate oxidation, a costly and time-intensive procedure. Chemometric modeling using mid-infrared spectroscopy (MIR) has been successfully used to estimate a range of soil properties, including total organic carbon (TOC) and particulate organic carbon (POC). Consequently, we hypothesized that we could use MIR to estimate ASC. Here we report on a method that uses MIR and chemometric signal processing to quantify TOC and ASC on a variety of soils collected serially and seasonally from a maximum of 76 locations across the United States. TOC was measured using high temperature oxidation and ASC was measured as permanganate-oxidizabl

Effective soil hydraulic properties in space and time: some field data analysis and modeling concepts

USDA-ARS?s Scientific Manuscript database

Soil hydraulic properties, which control surface fluxes and storage of water and chemicals in the soil profile, vary in space and time. Spatial variability above the measurement scale (e.g., soil area of 0.07 m2 or support volume of 14 L) must be upscaled appropriately to determine “effective” hydr...

Effects on soils from hot storage tanks

NASA Astrophysics Data System (ADS)

Ko, K. C.

1982-02-01

Behavioral characteristics of foundation soils for hot storage tanks were investigated on two soil models representative of the soils in the Continental U.S. The changes in the engineering properties of the foundation soils due to heating and the effects of four storage media liquids; hydrocarbon oil, silicon oil, molten nitrate salt and liquid sodium into the foundation were investigated. The remedial measures such as soil preconditioning to alleviate the detrimental effects of the heat on soils are presented and the areas for further research are delineated.

A new method to measure effective soil solution concentration predicts copper availability to plants.

PubMed

Zhang, H; Zhao, F J; Sun, B; Davison, W; McGrath, S P

2001-06-15

Risk assessments of metal contaminated soils need to address metal bioavailability. To predict the bioavailability of metals to plants, it is necessary to understand both solution and solid phase supply processes in soils. In striving to find surrogate chemical measurements, scientists have focused either on soil solution chemistry, including free ion activities, or operationally defined fractions of metals. Here we introduce the new concept of effective concentration, CE, which includes both the soil solution concentration and an additional term, expressed as a concentration, that represents metal supplied from the solid phase. CE was measured using the technique of diffusive gradients in thin films (DGT) which, like a plant, locally lowers soil solution concentrations, inducing metal supply from the solid phase, as shown by a dynamic model of the DGT-soil system. Measurements of Cu as CE, soil solution concentration, by EDTA extraction and as free Cu2+ activity in soil solution were made on 29 different soils covering a large range of copper concentrations. Theywere compared to Cu concentrations in the plant material of Lepidium heterophyllum grown on the same soils. Plant concentrations were linearly related and highly correlated with CE but were more scattered and nonlinear with respect to free Cu2+ activity, EDTA extraction, or soil solution concentrations. These results demonstrate that the dominant supply processes in these soils are diffusion and labile metal release, which the DGT-soil system mimics. The quantity CE is shown to have promise as a quantitative measure of the bioavailable metal in soils.

Modelling nitrous oxide emissions from mown-grass and grain-cropping systems: Testing and sensitivity analysis of DailyDayCent using high frequency measurements.

PubMed

Senapati, Nimai; Chabbi, Abad; Giostri, André Faé; Yeluripati, Jagadeesh B; Smith, Pete

2016-12-01

The DailyDayCent biogeochemical model was used to simulate nitrous oxide (N 2 O) emissions from two contrasting agro-ecosystems viz. a mown-grassland and a grain-cropping system in France. Model performance was tested using high frequency measurements over three years; additionally a local sensitivity analysis was performed. Annual N 2 O emissions of 1.97 and 1.24kgNha -1 year -1 were simulated from mown-grassland and grain-cropland, respectively. Measured and simulated water filled pore space (r=0.86, ME=-2.5%) and soil temperature (r=0.96, ME=-0.63°C) at 10cm soil depth matched well in mown-grassland. The model predicted cumulative hay and crop production effectively. The model simulated soil mineral nitrogen (N) concentrations, particularly ammonium (NH 4 + ), reasonably, but the model significantly underestimated soil nitrate (NO 3 - ) concentration under both systems. In general, the model effectively simulated the dynamics and the magnitude of daily N 2 O flux over the whole experimental period in grain-cropland (r=0.16, ME=-0.81gNha -1 day -1 ), with reasonable agreement between measured and modelled N 2 O fluxes for the mown-grassland (r=0.63, ME=-0.65gNha -1 day -1 ). Our results indicate that DailyDayCent has potential for use as a tool for predicting overall N 2 O emissions in the study region. However, in-depth analysis shows some systematic discrepancies between measured and simulated N 2 O fluxes on a daily basis. The current exercise suggests that the DailyDayCent may need improvement, particularly the sub-module responsible for N transformations, for better simulating soil mineral N, especially soil NO 3 - concentration, and N 2 O flux on a daily basis. The sensitivity analysis shows that many factors such as climate change, N-fertilizer use, input uncertainty and parameter value could influence the simulation of N 2 O emissions. Sensitivity estimation also helped to identify critical parameters, which need careful estimation or site-specific calibration for successful modelling of N 2 O emissions in the study region. Copyright © 2016 Elsevier B.V. All rights reserved.

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2016-02-01

The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

Monitoring of In-Situ Remediation By Time Lapse 3D Geo-Electric Measurements

NASA Astrophysics Data System (ADS)

Kanli, A. I.; Tildy, P.; Neducza, B.; Nagy, P.; Hegymegi, C.

2017-12-01

Injection of chemical oxidant solution to degrade the subsurface contaminants can be used for hydrocarbon contamination remediation. In this study, we developed a non-destructive measurement strategy to monitor oxidative in-situ remediation processes. The difficulties of the presented study originate from the small volume of conductive solution that can be used due to environmental considerations. Due to the effect of conductive groundwater and the high clay content of the targeted layer and the small volume of conductive solution that can be used due to environmental considerations, a site specific synthetic modelling is necessary for measurement design involving the results of preliminary 2D ERT measurements, electrical conductivity measurements of different active agents and expected resistivity changes calculated by soil resistivity modelling. Because of chemical biodegradation, the results of soil resistivity modelling have suggested that the reagent have complex effects on contaminated soils. As a result the plume of resistivity changes caused by the injected agent was determined showing strong fracturing effect because of the high pressure of injection. 3D time-lapse geo-electric measurements were proven to provide a usable monitoring tool for in-situ remediation as a result of our sophisticated tests and synthetic modelling.

Enzyme activity in terrestrial soil in relation to exploration of the Martian surface

NASA Technical Reports Server (NTRS)

Ardakani, M. S.; Mclaren, A. D.; Pukite, A. H.

1972-01-01

An exploration was made of enzyme activities in soil, including abundance, persistence and localization of these activities. An attempt was made to develop procedures for the detection and assaying of enzymes in soils suitable for presumptive tests for life in planetary soils. A suitable extraction procedure for soil enzymes was developed and measurements were made of activities in extracts in order to study how urease is complexed in soil organic matter. Mathematical models were developed, based on enzyme action and microbial growth in soil, for rates of oxidation of nitrogen as nitrogen compounds are moved downward in soil by water flow. These biogeochemical models should be applicable to any percolating system, with suitable modification for special features, such as oxygen concetrations, and types of hydrodynamic flow.

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.

Integrating auxiliary data and geophysical techniques for the estimation of soil clay content using CHAID algorithm

NASA Astrophysics Data System (ADS)

Abbaszadeh Afshar, Farideh; Ayoubi, Shamsollah; Besalatpour, Ali Asghar; Khademi, Hossein; Castrignano, Annamaria

2016-03-01

This study was conducted to estimate soil clay content in two depths using geophysical techniques (Ground Penetration Radar-GPR and Electromagnetic Induction-EMI) and ancillary variables (remote sensing and topographic data) in an arid region of the southeastern Iran. GPR measurements were performed throughout ten transects of 100 m length with the line spacing of 10 m, and the EMI measurements were done every 10 m on the same transect in six sites. Ten soil cores were sampled randomly in each site and soil samples were taken from the depth of 0-20 and 20-40 cm, and then the clay fraction of each of sixty soil samples was measured in the laboratory. Clay content was predicted using three different sets of properties including geophysical data, ancillary data, and a combination of both as inputs to multiple linear regressions (MLR) and decision tree-based algorithm of Chi-Squared Automatic Interaction Detection (CHAID) models. The results of the CHAID and MLR models with all combined data showed that geophysical data were the most important variables for the prediction of clay content in two depths in the study area. The proposed MLR model, using the combined data, could explain only 0.44 and 0.31% of the total variability of clay content in 0-20 and 20-40 cm depths, respectively. Also, the coefficient of determination (R2) values for the clay content prediction, using the constructed CHAID model with the combined data, was 0.82 and 0.76 in 0-20 and 20-40 cm depths, respectively. CHAID models, therefore, showed a greater potential in predicting soil clay content from geophysical and ancillary data, while traditional regression methods (i.e. the MLR models) did not perform as well. Overall, the results may encourage researchers in using georeferenced GPR and EMI data as ancillary variables and CHAID algorithm to improve the estimation of soil clay content.

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

Accessibility, searchability, transparency and engagement of soil carbon data: The International Soil Carbon Network

NASA Astrophysics Data System (ADS)

Harden, Jennifer W.; Hugelius, Gustaf; Koven, Charlie; Sulman, Ben; O'Donnell, Jon; He, Yujie

2016-04-01

Soils are capacitors for carbon and water entering and exiting through land-atmosphere exchange. Capturing the spatiotemporal variations in soil C exchange through monitoring and modeling is difficult in part because data are reported unevenly across spatial, temporal, and management scales and in part because the unit of measure generally involves destructive harvest or non-recurrent measurements. In order to improve our fundamental basis for understanding soil C exchange, a multi-user, open source, searchable database and network of scientists has been formed. The International Soil Carbon Network (ISCN) is a self-chartered, member-based and member-owned network of scientists dedicated to soil carbon science. Attributes of the ISCN include 1) Targeted ISCN Action Groups which represent teams of motivated researchers that propose and pursue specific soil C research questions with the aim of synthesizing seminal articles regarding soil C fate. 2) Datasets to date contributed by institutions and individuals to a comprehensive, searchable open-access database that currently includes over 70,000 geolocated profiles for which soil C and other soil properties. 3) Derivative products resulting from the database, including depth attenuation attributes for C concentration and storage; C storage maps; and model-based assessments of emission/sequestration for future climate scenarios. Several examples illustrate the power of such a database and its engagement with the science community. First, a simplified, data-constrained global ecosystem model estimated a global sensitivity of permafrost soil carbon to climate change (g sensitivity) of -14 to -19 Pg C °C-1 of warming on a 100 years time scale. Second, using mathematical characterizations of depth profiles for organic carbon storage, C at the soil surface reflects Net Primary Production (NPP) and its allotment as moss or litter, while e-folding depths are correlated to rooting depth. Third, storage of deep C is highly correlated with bulk density and porosity of the rock/sediment matrix. Thus C storage is most stable at depth, yet is susceptible to changes in tillage, rooting depths, and erosion/sedimentation. Fourth, current ESMs likely overestimate the turnover time of soil organic carbon and subsequently overestimate soil carbon sequestration, thus datasets combined with other soil properties will help constrain the ESM predictions. Last, analysis of soil horizon and carbon data showed that soils with a history of tillage had significantly lower carbon concentrations in both near-surface and deep layers, and that the effect persisted even in reforested areas. In addition to the opportunities for empirical science using a large database, the database has great promise for evaluation of biogeochemical and earth system models. The preservation of individual soil core measurements avoids issues with spatial averaging while facilitating evaluation of advanced model processes such as depth distributions of soil carbon, land use impacts, and spatial heterogeneity.

Ecological controls on N2O emission in surface litter and near-surface soil of a managed grassland: modelling and measurements

NASA Astrophysics Data System (ADS)

Grant, Robert F.; Neftel, Albrecht; Calanca, Pierluigi

2016-06-01

Large variability in N2O emissions from managed grasslands may occur because most emissions originate in surface litter or near-surface soil where variability in soil water content (θ) and temperature (Ts) is greatest. To determine whether temporal variability in θ and Ts of surface litter and near-surface soil could explain this in N2O emissions, a simulation experiment was conducted with ecosys, a comprehensive mathematical model of terrestrial ecosystems in which processes governing N2O emissions were represented at high temporal and spatial resolution. Model performance was verified by comparing N2O emissions, CO2 and energy exchange, and θ and Ts modelled by ecosys with those measured by automated chambers, eddy covariance (EC) and soil sensors on an hourly timescale during several emission events from 2004 to 2009 in an intensively managed pasture at Oensingen, Switzerland. Both modelled and measured events were induced by precipitation following harvesting and subsequent fertilizing or manuring. These events were brief (2-5 days) with maximum N2O effluxes that varied from < 1 mgNm-2h-1 in early spring and autumn to > 3 mgNm-2h-1 in summer. Only very small emissions were modelled or measured outside these events. In the model, emissions were generated almost entirely in surface litter or near-surface (0-2 cm) soil, at rates driven by N availability with fertilization vs. N uptake with grassland regrowth and by O2 supply controlled by litter and soil wetting relative to O2 demand from microbial respiration. In the model, NOx availability relative to O2 limitation governed both the reduction of more oxidized electron acceptors to N2O and the reduction of N2O to N2, so that the magnitude of N2O emissions was not simply related to surface and near-surface θ and Ts. Modelled N2O emissions were found to be sensitive to defoliation intensity and timing which controlled plant N uptake and soil θ and Ts prior to and during emission events. Reducing leaf area index (LAI) remaining after defoliation to half that under current practice and delaying harvesting by 5 days raised modelled N2O emissions by as much as 80 % during subsequent events and by an average of 43 % annually. Modelled N2O emissions were also found to be sensitive to surface soil properties. Increasing near-surface bulk density by 10 % raised N2O emissions by as much as 100 % during emission events and by an average of 23 % annually. Relatively small spatial variation in management practices and soil surface properties could therefore cause the large spatial variation in N2O emissions commonly found in field studies. The global warming potential from annual N2O emissions in this intensively managed grassland largely offset those from net C uptake in both modelled and field experiments. However, model results indicated that this offset could be adversely affected by suboptimal land management and soil properties.

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.

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

NASA Astrophysics Data System (ADS)

Wu, S. H.; Jansson, P.-E.

2012-05-01

Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Application of spatial time domain reflectometry measurements in heterogeneous, rocky substrates

NASA Astrophysics Data System (ADS)

Gonzales, C.; Scheuermann, A.; Arnold, S.; Baumgartl, T.

2016-10-01

Measurement of soil moisture across depths using sensors is currently limited to point measurements or remote sensing technologies. Point measurements have limitations on spatial resolution, while the latter, although covering large areas may not represent real-time hydrologic processes, especially near the surface. The objective of the study was to determine the efficacy of elongated soil moisture probes—spatial time domain reflectometry (STDR)—and to describe transient soil moisture dynamics of unconsolidated mine waste rock materials. The probes were calibrated under controlled conditions in the glasshouse. Transient soil moisture content was measured using the gravimetric method and STDR. Volumetric soil moisture content derived from weighing was compared with values generated from a numerical model simulating the drying process. A calibration function was generated and applied to STDR field data sets. The use of elongated probes effectively assists in the real-time determination of the spatial distribution of soil moisture. It also allows hydrologic processes to be uncovered in the unsaturated zone, especially for water balance calculations that are commonly based on point measurements. The elongated soil moisture probes can potentially describe transient substrate processes and delineate heterogeneity in terms of the pore size distribution in a seasonally wet but otherwise arid environment.

Measuring and modeling of soil N2O emissions - How well are we doing?

NASA Astrophysics Data System (ADS)

Butterbach-Bahl, K.; Ralf, K.; Werner, C.; Wolf, B.

2017-12-01

Microbial processes in soils are the primarily source of atmospheric N2O. Fertilizer use to boost food and feed production of agricultural systems as well as nitrogen deposition to natural and semi-natural ecosystems due to emissions of NOx and NH3 from agriculture and energy production and re-deposition to terrestrial ecosystems has likely nearly doubled the pre-industrial source strength of soils for atmospheric N2O. Quantifying soil emissions and identifying mitigation options is becoming a major focus in the climate debate as N2O emissions from agricultural soils are a major contributor to the greenhouse gas footprint of agricultural systems, with agriculture incl. land use change contributing up to 30% to total anthropogenic GHG emissions. The increasing number of annual datasets show that soil emissions a) are largely depended on soil N availability and thus e.g. fertilizer application, b) vary with management (e.g. timing of fertilization, residue management, tillage), c) depend on soil properties such as organic matter content and pH, e) are affected by plant N uptake, and e) are controlled by environmental factors such as moisture and temperature regimes. It is remarkable that the magnitude of annual emissions is largely controlled by short-term N2O pulses occurring due to fertilization, wetting and drying or freezing and thawing of soils. All of this contributes to a notorious variability of soil N2O emissions in space and time. Overcoming this variability for quantification of source strengths and identifying tangible mitigation options requires targeted measuring approaches as well as the translation of our knowledge on mechanisms underlying emissions into process oriented models, which finally might be used for upscaling and scenario studies. This paper aims at reviewing current knowledge on measurements, modelling and upscaling of soil N2O emissions, thereby identifying short comes and uncertainties of the various approaches and fields for future research.

Soil Biogeochemistry in the Ent DGVM

NASA Astrophysics Data System (ADS)

Kharecha, P. A.; Kiang, N. Y.; Aleinov, I.; Moorcroft, P.; Koster, R.

2007-12-01

As the global climate continues to warm in the 21st century, it will be vital to assess the degree of carbon cycle feedbacks from the terrestrial biosphere, particularly the soil. Global soil carbon stocks, which amount to approximately double the carbon stored in vegetation, could provide either positive or negative climate feedbacks, depending on a given ecosystem's response to warming. To predict changes in net terrestrial CO2 fluxes and belowground organic carbon storage, we have developed and evaluated a soil biogeochemistry submodel for the Ent dynamic global vegetation model currently being tested within the GISS GCM. It is a modified version of the soil submodel in the CASA biosphere model (Potter et al., Glob. Biogeoch. Cyc. 7, 1993). We have enhanced it to allow for explicit depth structure (2 soil layers, 0-30 cm and 30-100 cm), first-order inter-layer (vertical) soil organic carbon transport, and a variable-Q10 temperature dependence for soil microbial respiration. We have tested the soil model in numerous offline runs. To spin up the simulated carbon pools offline, we conducted multi-century runs using meteorological and ecological data from various FLUXNET field sites that represent 7 of the 8 GISS GCM plant functional types: tundra, grassland, shrubland, savanna, deciduous forest, evergreen needleleaf forest, and tropical rainforest (the eighth, cropland, will be dealt with in a separate study). We then compare the magnitudes of the simulated spun-up soil pools to soil carbon stock data from these field sites as well as the biome-aggregated data from Post et al. (Nature 317, 1985). Net ecosystem CO2 fluxes and soil respiration are also compared to site-specific measurements where available. Preliminary results suggest that simulated fluxes are reasonably close to measured values, but simulated carbon storage tends to be lower than the measurements. In addition to site-specific comparisons, we discuss the broader implications of our results, e.g., the effects of including explicit depth structure and inter-layer soil carbon transport on simulated soil respiration, carbon storage, and estimation of the global carbon budget.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

Determination of the saturated film conductivity to improve the EMFX model in describing the soil hydraulic properties over the entire moisture range

NASA Astrophysics Data System (ADS)

Wang, Yunquan; Ma, Jinzhu; Guan, Huade; Zhu, Gaofeng

2017-06-01

Difficulty in measuring hydraulic conductivity, particularly under dry conditions, calls for methods of predicting the conductivity from easily obtained soil properties. As a complement to the recently published EMFX model, a method based on two specific suction conditions is proposed to estimate saturated film conductivity from the soil water retention curve. This method reduces one fitting parameter in the previous EMFX model, making it possible to predict the hydraulic conductivity from the soil water retention curve over the complete moisture range. Model performance is evaluated with published data of soils in a broad texture range from sand to clay. The testing results indicate that 1) the modified EMFX model (namely the EMFX-K model), incorporating both capillary and adsorption forces, provides good agreement with the conductivity data over the entire moisture range; 2) a value of 0.5 for the tortuosity factor in the EMFX-K model as that in the Mualem's model gives comparable estimation of the relative conductivity associated with the capillary force; and 3) a value of -1.0 × 10-20 J for the Hamaker constant, rather than the commonly used value of -6.0 × 10-20 J, appears to be more appropriate to represent solely the effect of the van der Waals forces and to predict the film conductivity. In comparison with the commonly used van Genuchten-Mualem model, the EMFX-K model significantly improves the prediction of hydraulic conductivity under dry conditions. The sensitivity analysis result suggests that the uncertainty in the film thickness estimation is important in explaining the model underestimation of hydraulic conductivity for the soils with fine texture, in addition to the uncertainties from the measurements and the model structure. High quality data that cover the complete moisture range for a variety of soil textures are required to further test the method.

Ground penetrating radar for underground sensing in agriculture: a review

NASA Astrophysics Data System (ADS)

Liu, Xiuwei; Dong, Xuejun; Leskovar, Daniel I.

2016-10-01

Belowground properties strongly affect agricultural productivity. Traditional methods for quantifying belowground properties are destructive, labor-intensive and pointbased. Ground penetrating radar can provide non-invasive, areal, and repeatable underground measurements. This article reviews the application of ground penetrating radar for soil and root measurements and discusses potential approaches to overcome challenges facing ground penetrating radar-based sensing in agriculture, especially for soil physical characteristics and crop root measurements. Though advanced data-analysis has been developed for ground penetrating radar-based sensing of soil moisture and soil clay content in civil engineering and geosciences, it has not been used widely in agricultural research. Also, past studies using ground penetrating radar in root research have been focused mainly on coarse root measurement. Currently, it is difficult to measure individual crop roots directly using ground penetrating radar, but it is possible to sense root cohorts within a soil volume grid as a functional constituent modifying bulk soil dielectric permittivity. Alternatively, ground penetrating radarbased sensing of soil water content, soil nutrition and texture can be utilized to inversely estimate root development by coupling soil water flow modeling with the seasonality of plant root growth patterns. Further benefits of ground penetrating radar applications in agriculture rely on the knowledge, discovery, and integration among differing disciplines adapted to research in agricultural management.

Validation and Sensitivity Analysis of a New Atmosphere-Soil-Vegetation Model.

NASA Astrophysics Data System (ADS)

Nagai, Haruyasu

2002-02-01

This paper describes details, validation, and sensitivity analysis of a new atmosphere-soil-vegetation model. The model consists of one-dimensional multilayer submodels for atmosphere, soil, and vegetation and radiation schemes for the transmission of solar and longwave radiations in canopy. The atmosphere submodel solves prognostic equations for horizontal wind components, potential temperature, specific humidity, fog water, and turbulence statistics by using a second-order closure model. The soil submodel calculates the transport of heat, liquid water, and water vapor. The vegetation submodel evaluates the heat and water budget on leaf surface and the downward liquid water flux. The model performance was tested by using measured data of the Cooperative Atmosphere-Surface Exchange Study (CASES). Calculated ground surface fluxes were mainly compared with observations at a winter wheat field, concerning the diurnal variation and change in 32 days of the first CASES field program in 1997, CASES-97. The measured surface fluxes did not satisfy the energy balance, so sensible and latent heat fluxes obtained by the eddy correlation method were corrected. By using options of the solar radiation scheme, which addresses the effect of the direct solar radiation component, calculated albedo agreed well with the observations. Some sensitivity analyses were also done for model settings. Model calculations of surface fluxes and surface temperature were in good agreement with measurements as a whole.

Modeling the dynamics of DDT in a remote tropical floodplain: indications of post-ban use?

PubMed

Mendez, Annelle; Ng, Carla A; Torres, João Paulo Machado; Bastos, Wanderley; Bogdal, Christian; Dos Reis, George Alexandre; Hungerbuehler, Konrad

2016-06-01

Significant knowledge gaps exist regarding the fate and transport of persistent organic pollutants like dichlorodiphenyltrichloroethane (DDT) in tropical environments. In Brazil, indoor residual spraying with DDT to combat malaria and leishmaniasis began in the 1950s and was banned in 1998. Nonetheless, high concentrations of DDT and its metabolites were recently detected in human breast milk in the community of Lake Puruzinho in the Brazilian Amazon. In this work, we couple analysis of soils and sediments from 2005 to 2014 at Puruzinho with a novel dynamic floodplain model to investigate the movement and distribution of DDT and its transformation products (dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD)) and implications for human exposure. The model results are in good agreement with the accumulation pattern observed in the measurements, in which DDT, DDE, and DDD (collectively, DDX) accumulate primarily in upland soils and sediments. However, a significant increase was observed in DDX concentrations in soil samples from 2005 to 2014, coupled with a decrease of DDT/DDE ratios, which do not agree with model results assuming a post-ban regime. These observations strongly suggest recent use. We used the model to investigate possible re-emissions after the ban through two scenarios: one assuming DDT use for IRS and the other assuming use against termites and leishmaniasis. Median DDX concentrations and p,p'-DDT/p,p'-DDE ratios from both of these scenarios agreed with measurements in soils, suggesting that the soil parameterization in our model was appropriate. Measured DDX concentrations in sediments were between the two re-emission scenarios. Therefore, both soil and sediment comparisons suggest re-emissions indeed occurred between 2005 and 2014, but additional measurements would be needed to better understand the actual re-emission patterns. Monte Carlo analysis revealed model predictions for sediments were very sensitive to highly uncertain parameters associated with DDT degradation and partitioning. With this model as a tool for understanding inter-media cycling, additional research to refine these parameters would improve our understanding of DDX fate and transport in tropical sediments.

Prediction of local concentration statistics in variably saturated soils: Influence of observation scale and comparison with field data

NASA Astrophysics Data System (ADS)

Graham, Wendy; Destouni, Georgia; Demmy, George; Foussereau, Xavier

1998-07-01

The methodology developed in Destouni and Graham [Destouni, G., Graham, W.D., 1997. The influence of observation method on local concentration statistics in the subsurface. Water Resour. Res. 33 (4) 663-676.] for predicting locally measured concentration statistics for solute transport in heterogeneous porous media under saturated flow conditions is applied to the prediction of conservative nonreactive solute transport in the vadose zone where observations are obtained by soil coring. Exact analytical solutions are developed for both the mean and variance of solute concentrations measured in discrete soil cores using a simplified physical model for vadose-zone flow and solute transport. Theoretical results show that while the ensemble mean concentration is relatively insensitive to the length-scale of the measurement, predictions of the concentration variance are significantly impacted by the sampling interval. Results also show that accounting for vertical heterogeneity in the soil profile results in significantly less spreading in the mean and variance of the measured solute breakthrough curves, indicating that it is important to account for vertical heterogeneity even for relatively small travel distances. Model predictions for both the mean and variance of locally measured solute concentration, based on independently estimated model parameters, agree well with data from a field tracer test conducted in Manatee County, Florida.

Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status

NASA Astrophysics Data System (ADS)

Ťupek, Boris; Ortiz, Carina A.; Hashimoto, Shoji; Stendahl, Johan; Dahlgren, Jonas; Karltun, Erik; Lehtonen, Aleksi

2016-08-01

Inaccurate estimate of the largest terrestrial carbon pool, soil organic carbon (SOC) stock, is the major source of uncertainty in simulating feedback of climate warming on ecosystem-atmosphere carbon dioxide exchange by process-based ecosystem and soil carbon models. Although the models need to simplify complex environmental processes of soil carbon sequestration, in a large mosaic of environments a missing key driver could lead to a modeling bias in predictions of SOC stock change.We aimed to evaluate SOC stock estimates of process-based models (Yasso07, Q, and CENTURY soil sub-model v4) against a massive Swedish forest soil inventory data set (3230 samples) organized by a recursive partitioning method into distinct soil groups with underlying SOC stock development linked to physicochemical conditions.For two-thirds of measurements all models predicted accurate SOC stock levels regardless of the detail of input data, e.g., whether they ignored or included soil properties. However, in fertile sites with high N deposition, high cation exchange capacity, or moderately increased soil water content, Yasso07 and Q models underestimated SOC stocks. In comparison to Yasso07 and Q, accounting for the site-specific soil characteristics (e. g. clay content and topsoil mineral N) by CENTURY improved SOC stock estimates for sites with high clay content, but not for sites with high N deposition.Our analysis suggested that the soils with poorly predicted SOC stocks, as characterized by the high nutrient status and well-sorted parent material, indeed have had other predominant drivers of SOC stabilization lacking in the models, presumably the mycorrhizal organic uptake and organo-mineral stabilization processes. Our results imply that the role of soil nutrient status as regulator of organic matter mineralization has to be re-evaluated, since correct SOC stocks are decisive for predicting future SOC change and soil CO2 efflux.

Seasonal and inter-annual dynamics in the stable oxygen isotope compositions of water pools in a temperate humid grassland ecosystem: results from MIBA sampling and MuSICA modelling

NASA Astrophysics Data System (ADS)

Hirl, Regina; Schnyder, Hans; Auerswald, Karl; Vetter, Sylvia; Ostler, Ulrike; Schleip, Inga; Wingate, Lisa; Ogée, Jérôme

2015-04-01

The oxygen isotope composition (δ18O) of water in terrestrial ecosystems usually shows strong and dynamic variations within and between the various compartments. These variations originate from changes in the δ18O of water inputs (e.g. rain or water vapour) and from 18O fractionation phenomena in the soil-plant-atmosphere continuum. Investigations of δ18O in ecosystem water pools and of their main drivers can help us understand water relations at plant, canopy or ecosystem scale and interpret δ18O signals in plant and animal tissues as paleo-climate proxies. During the vegetation periods of 2006 to 2012, soil, leaf and stem water as well as atmospheric humidity, rain water and groundwater were sampled at bi-weekly intervals in a temperate humid pasture of the Grünschwaige Grassland Research Station near Munich (Germany). The sampling was performed following standardised MIBA (Moisture Isotopes in the Biosphere and Atmosphere) protocols. Leaf water samples were prepared from a mixture of co-dominant species in the plant community in order to obtain a canopy-scale leaf water δ18O signal. All samples were then analysed for their δ18O compositions. The measured δ18O of leaf, stem and soil water were then compared with the δ18O signatures simulated by the process-based isotope-enabled ecosystem model MuSICA (Multi-layer Simulator of the Interactions between a vegetation Canopy and the Atmosphere). MuSICA integrates current mechanistic understanding of processes in the soil-plant-atmosphere continuum. Hence, the comparison of modelled and measured data allows the identification of gaps in current knowledge and of questions to be tackled in the future. Soil and plant characteristics for model parameterisation were derived from investigations at the experimental site and supplemented by values from the literature. Eddy-covariance measurements of ecosystem CO2 (GPP, NEE) and energy (H, LE) fluxes and soil temperature data were used for model evaluation. The comparison of measured and predicted ecosystem fluxes showed that the model captured the main features of the diurnal cycles of GPP, NEE, LE and H, as well as the soil temperature dynamics. In this presentation I will present the main results of this model-data comparison, as well as results from a model sensitivity analysis performed over a range of soil, plant and meteorological parameters to evaluate the relative importance of each parameter on the δ18O signatures of the various water pools.

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models.

PubMed

Bilgili, Mehmet; Sahin, Besir; Sangun, Levent

2013-01-01

The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy.

Evaluating the Classical Versus an Emerging Conceptual Model of Peatland Methane Dynamics

NASA Astrophysics Data System (ADS)

Yang, Wendy H.; McNicol, Gavin; Teh, Yit Arn; Estera-Molina, Katerina; Wood, Tana E.; Silver, Whendee L.

2017-09-01

Methane (CH4) is a potent greenhouse gas that is both produced and consumed in soils by microbially mediated processes sensitive to soil redox. We evaluated the classical conceptual model of peatland CH4 dynamics—in which the water table position determines the vertical distribution of methanogenesis and methanotrophy—versus an emerging model in which methanogenesis and methanotrophy can both occur throughout the soil profile due to spatially heterogeneous redox and anaerobic CH4 oxidation. We simultaneously measured gross CH4 production and oxidation in situ across a microtopographical gradient in a drained temperate peatland and ex situ along the soil profile, giving us novel insight into the component fluxes of landscape-level net CH4 fluxes. Net CH4 fluxes varied among landforms (p < 0.001), ranging from 180.3 ± 81.2 mg C m-2 d-1 in drainage ditches to -0.7 ± 1.2 mg C m-2 d-1 in the highest landform. Contrary to prediction by the classical conceptual model, variability in methanogenesis alone drove the landscape-level net CH4 flux patterns. Consistent with the emerging model, freshly collected soils from above the water table produced CH4 within anaerobic microsites. Even in soil from beneath the water table, gross CH4 production was best predicted by the methanogenic fraction of carbon mineralization, an index of highly reducing microsites. We measured low rates of anaerobic CH4 oxidation, which may have been limited by relatively low in situ CH4 concentrations in the hummock/hollow soil profile. Our study revealed complex CH4 dynamics better represented by the emerging heterogeneous conceptual model than the classical model based on redox strata.

Improving soil moisture simulation to support Agricultural Water Resource Management using Satellite-based water cycle observations

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2016-04-01

Efficient and sustainable irrigation systems require optimization of operational parameters such as irrigation amount which are dependent on the soil hydraulic parameters that affect the model's accuracy in simulating soil water content. However, it is a scientific challenge to provide reliable estimates of soil hydraulic parameters and irrigation estimates, given the absence of continuously operating soil moisture and rain gauge network. For agricultural water resource management, the in-situ measurements of soil moisture are currently limited to discrete measurements at specific locations, and such point-based measurements do not represent the spatial distribution at a larger scale accurately, as soil moisture is highly variable both spatially and temporally (Wang and Qu 2009). In the current study, flood irrigation scheme within the land surface model is triggered when the root-zone soil moisture deficit reaches below a threshold of 25%, 50% and 75% with respect to the maximum available water capacity (difference between field capacity and wilting point) and applied until the top layer is saturated. An additional important criterion needed to activate the irrigation scheme is to ensure that it is irrigation season by assuming that the greenness vegetation fraction (GVF) of the pixel exceed 0.40 of the climatological annual range of GVF (Ozdogan et al. 2010). The main hypothesis used in this study is that near-surface remote sensing soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately inverted, it would provide field capacity and wilting point soil moisture, which may be representative of that basin. Thus, genetic algorithm inverse method is employed to derive the effective parameters and derive the soil moisture deficit for the root zone by coupling of AMSR-E soil moisture with the physically based hydrological model. Model performance is evaluated using MODIS-evapotranspiration (ET) and MODIS land surface temperature (LST) products. The soil moisture estimates for the root zone are also validated with the in-situ field data, for three sites (2- irrigated and 1- rainfed) located at the University of Nebraska Agricultural Research and Development Center near Mead, NE and monitored by three AmeriFlux installations (Verma et al., 2005) by evaluating the root mean square error (RMSE) and Mean Bias error (MBE).

Graphical determination of metal bioavailability to soil invertebrates utilizing the Langmuir sorption model

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

Donkin, S.G.

1997-09-01

A new method of performing soil toxicity tests with free-living nematodes exposed to several metals and soil types has been adapted to the Langmuir sorption model in an attempt at bridging the gap between physico-chemical and biological data gathered in the complex soil matrix. Pseudo-Langmuir sorption isotherms have been developed using nematode toxic responses (lethality, in this case) in place of measured solvated metal, in order to more accurately model bioavailability. This method allows the graphical determination of Langmuir coefficients describing maximum sorption capacities and sorption affinities of various metal-soil combinations in the context of real biological responses of indigenousmore » organisms. Results from nematode mortality tests with zinc, cadmium, copper, and lead in four soil types and water were used for isotherm construction. The level of agreement between these results and available literature data on metal sorption behavior in soils suggests that biologically relevant data may be successfully fitted to sorption models such as the Langmuir. This would allow for accurate prediction of soil contaminant concentrations which have minimal effect on indigenous invertebrates.« less

Application of atomic force microscopy to the study of natural and model soil particles.

PubMed

Cheng, S; Bryant, R; Doerr, S H; Rhodri Williams, P; Wright, C J

2008-09-01

The structure and surface chemistry of soil particles has extensive impact on many bulk scale properties and processes of soil systems and consequently the environments that they support. There are a number of physiochemical mechanisms that operate at the nanoscale which affect the soil's capability to maintain native vegetation and crops; this includes soil hydrophobicity and the soil's capacity to hold water and nutrients. The present study used atomic force microscopy in a novel approach to provide unique insight into the nanoscale properties of natural soil particles that control the physiochemical interaction of material within the soil column. There have been few atomic force microscopy studies of soil, perhaps a reflection of the heterogeneous nature of the system. The present study adopted an imaging and force measurement research strategy that accounted for the heterogeneity and used model systems to aid interpretation. The surface roughness of natural soil particles increased with depth in the soil column a consequence of the attachment of organic material within the crevices of the soil particles. The roughness root mean square calculated from ten 25 microm(2) images for five different soil particles from a Netherlands soil was 53.0 nm, 68.0 nm, 92.2 nm and 106.4 nm for the respective soil depths of 0-10 cm, 10-20 cm, 20-30 cm and 30-40 cm. A novel analysis method of atomic force microscopy phase images based on phase angle distribution across a surface was used to interpret the nanoscale distribution of organic material attached to natural and model soil particles. Phase angle distributions obtained from phase images of model surfaces were found to be bimodal, indicating multiple layers of material, which changed with the concentration of adsorbed humic acid. Phase angle distributions obtained from phase images of natural soil particles indicated a trend of decreasing surface coverage with increasing depth in the soil column. This was consistent with previous macroscopic determination of the proportions of organic material chemically extracted from bulk samples of the soils from which specimen particles were drawn. Interaction forces were measured between atomic force microscopy cantilever tips (Si(3)N(4)) and natural soil and model surfaces. Adhesion forces at humic acid free specimen surfaces (Av. 20.0 nN), which are primarily hydrophilic and whose interactions are subject to a significant contribution from the capillary forces, were found to be larger than those of specimen surfaces with adsorbed humic acid (Av. 6.5 nN). This suggests that adsorbed humic acid increased surface hydrophobicity. The magnitude and distribution of adhesion forces between atomic force microscopy tips and the natural particle surfaces was affected by both local surface roughness and the presence of adsorbed organic material. The present study has correlated nanoscale measurements with established macroscale methods of soil study. Thus, the research demonstrates that atomic force microscopy is an important addition to soil science that permits a multiscale analysis of the multifactorial phenomena of soil hydrophobicity and wetting.

Passive Microwave Soil Moisture Retrieval through Combined Radar/Radiometer Ground Based Simulator with Special Reference to Dielectric Schemes

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K., ,, Dr.; O'Neill, Peggy, ,, Dr.

2014-05-01

Soil moisture is an important element for weather and climate prediction, hydrological sciences, and applications. Hence, measurements of this hydrologic variable are required to improve our understanding of hydrological processes, ecosystem functions, and the linkages between the Earth's water, energy, and carbon cycles (Srivastava et al. 2013). The retrieval of soil moisture depends not only on parameterizations in the retrieval algorithm but also on the soil dielectric mixing models used (Behari 2005). Although a number of soil dielectric mixing models have been developed, testing these models for soil moisture retrieval has still not been fully explored, especially with SMAP-like simulators. The main objective of this work focuses on testing different dielectric models for soil moisture retrieval using the Combined Radar/Radiometer (ComRAD) ground-based L-band simulator developed jointly by NASA/GSFC and George Washington University (O'Neill et al., 2006). The ComRAD system was deployed during a field experiment in 2012 in order to provide long active/passive measurements of two crops under controlled conditions during an entire growing season. L-band passive data were acquired at a look angle of 40 degree from nadir at both horizontal & vertical polarization. Currently, there are many dielectric models available for soil moisture retrieval; however, four dielectric models (Mironov, Dobson, Wang & Schmugge and Hallikainen) were tested here and found to be promising for soil moisture retrieval (some with higher performances). All the above-mentioned dielectric models were integrated with Single Channel Algorithms using H (SCA-H) and V (SCA-V) polarizations for the soil moisture retrievals. All the ground-based observations were collected from test site-United States Department of Agriculture (USDA) OPE3, located a few miles away from NASA GSFC. Ground truth data were collected using a theta probe and in situ sensors which were then used for validation. Analysis indicated a higher performance in terms of soil moisture retrieval accuracy for the Mironov dielectric model (RMSE of 0.035 m3/m3), followed by Dobson, Wang & Schmugge, and Hallikainen. This analysis indicates that Mironov dielectric model is promising for passive-only microwave soil moisture retrieval and could be a useful choice for SMAP satellite soil moisture retrieval. Keywords: Dielectric models; Single Channel Algorithm, Combined Radar/Radiometer, Soil moisture; L band References: Behari, J. (2005). Dielectric Behavior of Soil (pp. 22-40). Springer Netherlands O'Neill, P. E., Lang, R. H., Kurum, M., Utku, C., & Carver, K. R. (2006), Multi-Sensor Microwave Soil Moisture Remote Sensing: NASA's Combined Radar/Radiometer (ComRAD) System. In IEEE MicroRad, 2006 (pp. 50-54). IEEE. Srivastava, P. K., Han, D., Rico Ramirez, M. A., & Islam, T. (2013), Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology, 498, 292-304. USDA OPE3 web site at http://www.ars.usda.gov/Research/.

Modeled and monitored variation in space and time of PCB-153 concentrations in air, sediment, soil and aquatic biota on a European scale.

PubMed

Hauck, Mara; Huijbregts, Mark A J; Hollander, Anne; Hendriks, A Jan; van de Meent, Dik

2010-08-15

We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well. Copyright 2009 Elsevier B.V. All rights reserved.

Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season

NASA Astrophysics Data System (ADS)

Robock, Alan; Luo, Lifeng; Wood, Eric F.; Wen, Fenghua; Mitchell, Kenneth E.; Houser, Paul R.; Schaake, John C.; Lohmann, Dag; Cosgrove, Brian; Sheffield, Justin; Duan, Qingyun; Higgins, R. Wayne; Pinker, Rachel T.; Tarpley, J. Dan; Basara, Jeffery B.; Crawford, Kenneth C.

2003-11-01

North American Land Data Assimilation System (NLDAS) land surface models have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation to calculate land hydrology. We evaluated these simulations using in situ observations over the southern Great Plains for the periods of May-September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model-specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow-free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Modelling uncertainties in the diffusion-advection equation for radon transport in soil using interval arithmetic.

PubMed

Chakraverty, S; Sahoo, B K; Rao, T D; Karunakar, P; Sapra, B K

2018-02-01

Modelling radon transport in the earth crust is a useful tool to investigate the changes in the geo-physical processes prior to earthquake event. Radon transport is modeled generally through the deterministic advection-diffusion equation. However, in order to determine the magnitudes of parameters governing these processes from experimental measurements, it is necessary to investigate the role of uncertainties in these parameters. Present paper investigates this aspect by combining the concept of interval uncertainties in transport parameters such as soil diffusivity, advection velocity etc, occurring in the radon transport equation as applied to soil matrix. The predictions made with interval arithmetic have been compared and discussed with the results of classical deterministic model. The practical applicability of the model is demonstrated through a case study involving radon flux measurements at the soil surface with an accumulator deployed in steady-state mode. It is possible to detect the presence of very low levels of advection processes by applying uncertainty bounds on the variations in the observed concentration data in the accumulator. The results are further discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Advances in wind erosion modelling in Europe

NASA Astrophysics Data System (ADS)

Borrelli, Pasquale; Lugato, Emanuele; Alewell, Christine; Montanarella, Luca; Panagos, Panos

2017-04-01

Soil erosion by wind is a serious environmental problem often resulting in severe forms of soil degradation. Wind erosion is also a phenomenon relevant for Europe, although this land degradation process has been overlooked until very recently. The state-of-the-art literature presents wind erosion as a process that locally affects the semi-arid areas of the Mediterranean region as well as the temperate climate areas of the northern European countries. Actual observations, field measurements and modelling assessments, however, are all extremely limited and highly unequally distributed across Europe. As a result, we currently lack comprehensive understanding about where and when wind erosion occurs in Europe, and the intensity of erosion that poses a threat to agricultural productivity. Today's challenge is to integrate the insights of local experiments and field-scale models into a new generation of large-scale wind erosion models. While naturally being less accurate than field-scale models, these large-scale modelling approaches still provide essential knowledge about where and when wind erosion occurs and can disclose the level of risk for agricultural productivity in specific areas. Here, we present a geographic information system (GIS) version of the RWEQ (named GIS-RWEQ) to quantitatively assess soil loss by wind over large study areas (Land Degradation & Development, DOI: 10.1002/ldr.2588). The model designed to predict the daily soil loss potential at a ca. 1 km2 spatial resolution shows high consistency with local measurements reported in literature. The average soil loss predicted by GIS-RWEQ for the European arable land totals 62 million Mg yr-1, with an average area-specific soil loss of 0.53 Mg yr-1. The JRC model RUSLE2015, for the same area estimates 295 million Mg yr-1 of soil loss due to water erosion. Notably, soil loss by wind erosion in the European arable land could be as high as 20% of water erosion, even though the areas affected are mainly concentrated in hotspots.

The Raam regional soil moisture monitoring network in the Netherlands

NASA Astrophysics Data System (ADS)

Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier

2018-01-01

We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.

Portable gamma spectrometry: measuring soil erosion in-situ at four Critical Zone Observatories in P. R. China

NASA Astrophysics Data System (ADS)

Sanderson, N. K.; Green, S. M.; Chen, Z.; Wang, J.; Wang, Y.; Wang, R.; Yu, K.; Tu, C.; Jia, X.; Li, G.; Peng, X.; Quine, T. A.

2017-12-01

Detecting patterns of soil erosion, redistribution, and/soil nutrient loss is important for long-term soil conservation and agricultural sustainability. Caesium-137 (137Cs) and other fallout radionuclide inventories have been used over the the last 50 years to track soil erosion, transport and deposition on a catchment scale, and have been shown to be useful for informing models of temporal/spatial soil redistribution. Traditional sampling methods usually involves coring, grinding, sieving, sub-sampling and laboratory analysis using HPGe detectors, all of which can be costly and time consuming. In-situ measurements can provide a mechanism for assessment of 137Cs over larger areas that integrate the spatial variability, and expand turnover of analyses. Here, we assess the applicability of an in-situ approach based on radionuclide principles, and provide a comparison of the two approaches: laboratory vs. in-situ. The UK-China Critical Zone Observatory (CZO) programme provides an ideal research platform to assess the in-situ approach to measuring soil erosion: using a portable gamma spectrometer to determine 137Cs inventories. Four extensive field slope surveys were conducted in the CZO's, which covers four ecosystem types in China: karst, red soil, peri-urban, and loess plateau. In each CZO, 3-6 plots were measured along 2 slope transects, with 3 replicated 1 hour counts of 137Cs in each plot. In addition, 137Cs soil depth and bulk density profiles were also sampled for each plot, and lab-derived inventories calculated using traditional methods for comparison. Accurately and rapidly measuring 137Cs inventories using a portable field detector allows for a greater coverage of sampling locations and the potential for small-scale spatial integration, as well as the ability to re-visit sites over time and continually adapt and improve soil erosion/redistribution models, thus more effectively targeting areas of interest with reduced cost and time constraints.

Quantitative comparisons of three modeling approaches for characterizing drought response of a highly variable, widely grown crop species

NASA Astrophysics Data System (ADS)

Pleban, J. R.; Mackay, D. S.; Aston, T.; Ewers, B. E.; Wienig, C.

2013-12-01

Quantifying the drought tolerance of crop species and genotypes is essential in order to predict how water stress may impact agricultural productivity. As climate models predict an increase in both frequency and severity of drought corresponding plant hydraulic and biochemical models are needed to accurately predict crop drought tolerance. Drought can result in cavitation of xylem conduits and related loss of plant hydraulic conductivity. This study tested the hypothesis that a model incorporating a plants vulnerability to cavitation would best assess drought tolerance in Brassica rapa. Four Brassica genotypes were subjected to drought conditions at a field site in Laramie, WY. Concurrent leaf gas exchange, volumetric soil moisture content and xylem pressure measurements were made during the drought period. Three models were used to access genotype specific drought tolerance. All 3 models rely on the Farquhar biochemical/biophysical model of leaf level photosynthesis, which is integrated into the Terrestrial Regional Ecosystem Exchange Simulator (TREES). The models differ in how TREES applies the environmental driving data and plant physiological mechanisms; specifically how water availability at the site of photosynthesis is derived. Model 1 established leaf water availability from a modeled soil moisture content; Model 2 input soil moisture measurements directly to establish leaf water availability; Model 3 incorporated the Sperry soil-plant transport model, which calculates flows and pressure along the soil-plant water transport pathway to establish leaf water availability. This third model incorporated measured xylem pressures thus constraining leaf water availability via genotype specific vulnerability curves. A multi-model intercomparison was made using a Bayesian approach, which assessed the interaction between uncertainty in model results and data. The three models were further evaluated by assessing model accuracy and complexity via deviance information criteria (DIC). Results suggest that model 1 was unable to model soil moisture accurately and thus did not effectively characterize drought tolerance. Models 2 and 3 were both effective at characterizing drought tolerance; model 3 preformed best in genotypes with the highest vulnerability to cavitation. By identifying through both Bayesian and DIC analyses models that best characterize drought tolerance future investigations into the interaction between crop productivity and water use can be informed by hypothesis testing using models prior to experimentation.

Quantification Of Erosion Rates Of Agriculturally Used Soils By Artificial

NASA Astrophysics Data System (ADS)

Jha, Abhinand

2010-05-01

0.0.1 1. Introduction to soil erosion measurement by radionuclides Soil erosion by water, wind and tillage affects both agriculture and the natural environment. Studying this phenomenon would be one of the advancements in science. Soil erosion occurs worldwide and since the last two decades it has been a main topic of discussion all over the world. The use of environmental radionuclides such as 90Sr, 137Cs to study medium term soil erosion (40 yrs) started in the early 1990's. Using these new techniques better knowledge about erosion can be gained and this knowledge can be implemented for erosion risk management. The erosion and sedimentation study by using man-made and natural radioisotopes is a key technique, which has developed over the past 30 years. Fallout 137Cs and Cosmogenic 7Be are radionuclides that have been used to provide independent measurements of soil-erosion and sediment-deposition rates and patterns [1] [2] [3] [4]. Erosion measurements using radionuclides 137Cs, 7Be Caesium-137 from atmospheric nuclear-weapons tests in the 1950s and 1960s (Fig.1) is a unique tracer of erosion and sedimentation, since there are no natural sources of 137Cs. Unique events such as the Chernobyl accident in April 1986 caused regional dispersal of 137Cs that affects the total global deposition budget. This yearly pattern of fallout can be used to develop a chronology of deposition horizons in lakes, reservoirs, and floodplains. 137Cs can be easily measured by gamma spectroscopy. Using 137Cs is a fast and cheap method to study erosion-deposition processes compared to the traditional methods like silt bags. PIC Figure 1: Global 137Cs fallout (Modified from SAAS Bulletin 353, Part E, DDR, 1986) When 137Cs, 7Be reach the soil surface by wet and dry deposition, they are quickly and strongly adsorbed by ion exchange and are essentially non exchangeable in most environments. Each radionuclide is distributed differently in the soil because of differences in half-lives (30 yrs for 137Cs and 53 days for 7Be), delivery rates, delivery histories, and land use (Fig. 2). An Physical processes, such as water and wind, are the dominant factors moving 137Cs, 7Be tagged soil particles within and between landscape compartments. PIC Figure 2: Generalized sketch illustrating the distributions of 137Cs and 7Be in tilled and undisturbed soils 2 Erosion study at Young Moraine regions of Germany Recently, a study had been performed to evaluate erosion rates in a typical pattern of landscapes in the Young Moraine regions of North-East Germany [5]. The 137Cs concentrations were measured at selected sampling points of various study sites. Among the areas selected for sampling was Basedow, which is a cultivated area, situated north of Berlin. During a master thesis study at university of Bremen in the academic year 2008-2009 [6] a second sampling campaign was performed at the same study site and 137Cs and 7Be concentrations were measured. Two mathematical models (a proportional model and a mass balance model) were applied to estimate erosion or deposition rates giving a distinction between uncultivated or essentially undisturbed soils and cultivated or soils under permanent pasture (Fig.3A). An improved depositional model was developed during this study. The simulation results from this model are presented in Fig.4. Due to the half-life (53.2 days) of 7Be, a mass balance model was developed and used to calculate erosion rates from 7Be (Fig.3B). PIC Figure 3: A: Erosion rates for 137Cs calculated by mass balance model. B: Erosion rates calculated with mass balance model using the 7Be data at Basedow (2008). The results verify that there is long term erosion as a result of wind, water and agricultural practices. The annual erosion rates at Basedow calculated using a mass balance and a proportional model were in the range between 30-50 t ha-1yr-1. These values were comparable to the erosion rates calculated in the previous study [5] by the models mentioned above. PIC Figure 4: Profiles of sediment calculated for different erosion rates by Cs-137 within the ploughed soil 3 Conclusions and outlook Erosion rates for agricultural soils at Young Moraine regions of North-East Germany were determined by using two radionuclides, 137Cs and 7Be. In combination, the two radionuclides provide a valuable means of investigating soil erosion and assessing erosion risk in the study area. Potentials and limitations of the erosion measurement techniques using radiotracers are discussed in this study. The models used to quantify erosion rates using 137Cs and 7Be were studied. Erosion rates calculated by theses models are difficult to measure over a period of 50 years. A validation of these erosion rates for the time period (50 years) used in the 137Cs-based models will give a new perspective to the use of soil erosion modeling. Most of the regions in India are suffering from high erosion rates [7]. By using the new techniques in erosion quantification the land management practices can be improved and the erosion risk can be reduced in India.

High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system - combining experimental and modeling approaches

NASA Astrophysics Data System (ADS)

Cardinael, Rémi; Guenet, Bertrand; Chevallier, Tiphaine; Dupraz, Christian; Cozzi, Thomas; Chenu, Claire

2018-01-01

Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC) stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC) inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia × nigra) and durum wheat (Triticum turgidum L. subsp. durum) and an adjacent agricultural control plot to quantify all OC inputs to the soil - leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation - and measured SOC stocks down to 2 m of depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. The model was calibrated to the control plot only. Measured OC inputs to soil were increased by about 40 % (+ 1.11 t C ha-1 yr-1) down to 2 m of depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha-1 down to 1 m of depth. However, most of the SOC storage occurred in the first 30 cm of soil and in the tree rows. The model was strongly validated, properly describing the measured SOC stocks and distribution with depth in agroforestry tree rows and alleys. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, only a priming effect variant of the model was able to capture the depth distribution of SOC stocks, suggesting the priming effect as a possible mechanism driving deep SOC dynamics. This result questions the potential of soils to store large amounts of carbon, especially at depth. Deep-rooted trees modify OC inputs to soil, a process that deserves further study given its potential effects on SOC dynamics.

Challenges in Interpreting and Validating Satellite Soil Moisture Information

USDA-ARS?s Scientific Manuscript database

Global soil moisture products are now being generated routinely using microwave-based satellite observing systems. These include the NASA Soil Moisture Active Passive (SMAP) mission. In order to fully exploit these observations they must be integrated with both in situ measurements and model-based e...

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

Using measures of information content and complexity of time series as hydrologic metrics

USDA-ARS?s Scientific Manuscript database

The information theory has been previously used to develop metrics that allowed to characterize temporal patterns in soil moisture dynamics, and to evaluate and to compare performance of soil water flow models. The objective of this study was to apply information and complexity measures to characte...

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.

Using Mid Infrared Spectroscopy to Predict the Decomposability of Soil Organic Matter Stored in Arctic Tundra Soils

NASA Astrophysics Data System (ADS)

Matamala, R.; Fan, Z.; Jastrow, J. D.; Liang, C.; Calderon, F.; Michaelson, G.; Ping, C. L.; Mishra, U.; Hofmann, S. M.

2016-12-01

The large amounts of organic matter stored in permafrost-region soils are preserved in a relatively undecomposed state by the cold and wet environmental conditions limiting decomposer activity. With pending climate changes and the potential for warming of Arctic soils, there is a need to better understand the amount and potential susceptibility to mineralization of the carbon stored in the soils of this region. Studies have suggested that soil C:N ratio or other indicators based on the molecular composition of soil organic matter could be good predictors of potential decomposability. In this study, we investigated the capability of Fourier-transform mid infrared spectroscopy (MidIR) spectroscopy to predict the evolution of carbon dioxide (CO2) produced by Arctic tundra soils during a 60-day laboratory incubation. Soils collected from four tundra sites on the Coastal Plain, and Arctic Foothills of the North Slope of Alaska were separated into active-layer organic, active-layer mineral, and upper permafrost and incubated at 1, 4, 8 and 16 °C. Carbon dioxide production was measured throughout the incubations. Total soil organic carbon (SOC) and total nitrogen (TN) concentrations, salt (0.5 M K2SO4) extractable organic matter (SEOM), and MidIR spectra of the soils were measured before and after incubation. Multivariate partial least squares (PLS) modeling was used to predict cumulative CO2 production, decay rates, and the other measurements. MidIR reliably estimated SOC and TN and SEOM concentrations. The MidIR prediction models of CO2 production were very good for active-layer mineral and upper permafrost soils and good for the active-layer organic soils. SEOM was also a very good predictor of CO2 produced during the incubations. Analysis of the standardized beta coefficients from the PLS models of CO2 production for the three soil layers indicated a small number (9) of influential spectral bands. Of these, bands associated with O-H and N-H stretch, carbonates, and ester C-O appeared to be most important for predicting CO2 production for both active-layer mineral and upper permafrost soils. Further analysis of these influential bands and their relationships to SEOM in soil will be explored. Our results show that the MidIR spectra contains valuable information that can be related to decomposability of soils.

Soil erosion risk assessment using interviews, empirical soil erosion modeling (RUSLE) and fallout radionuclides in a volcanic crater lake watershed subjected to land use change, western Uganda

NASA Astrophysics Data System (ADS)

De Crop, Wannes; Ryken, Nick; Tomma Okuonzia, Judith; Van Ranst, Eric; Baert, Geert; Boeckx, Pascal; Verschuren, Dirk; Verdoodt, Ann

2017-04-01

Population pressure results in conversion of natural vegetation to cropland within the western Ugandan crater lake watersheds. These watersheds however are particularly prone to soil degradation and erosion because of the high rainfall intensity and steep topography. Increased soil erosion losses expose the aquatic ecosystems to excessive nutrient loading. In this study, the Katinda crater lake watershed, which is already heavily impacted by agricultural land use, was selected for an explorative study on its (top)soil characteristics - given the general lack of data on soils within these watersheds - as well as an assessment of soil erosion risks. Using group discussions and structured interviews, the local land users' perceptions on land use, soil quality, soil erosion and lake ecology were compiled. Datasets on rainfall, topsoil characteristics, slope gradient and length, and land use were collected. Subsequently a RUSLE erosion model was run. Results from this empirical erosion modeling approach were validated against soil erosion estimates based on 137Cs measurements.

Modeling soil moisture processes and recharge under a melting snowpack

USGS Publications Warehouse

Flint, A.L.; Flint, L.E.; Dettinger, M.D.

2008-01-01

Recharge into granitic bedrock under a melting snowpack is being investigated as part of a study designed to understand hydrologic processes involving snow at Yosemite National Park in the Sierra Nevada Mountains of California. Snowpack measurements, accompanied by water content and matric potential measurements of the soil under the snowpack, allowed for estimates of infiltration into the soil during snowmelt and percolation into the bedrock. During portions of the snowmelt period, infiltration rates into the soil exceeded the permeability of the bedrock and caused ponding to be sustained at the soil-bedrock interface. During a 5-d period with little measured snowmelt, drainage of the ponded water into the underlying fractured granitic bedrock was estimated to be 1.6 cm d?1, which is used as an estimate of bedrock permeability. The numerical simulator TOUGH2 was used to reproduce the field data and evaluate the potential for vertical flow into the fractured bedrock or lateral flow at the bedrock-soil interface. During most of the snowmelt season, the snowmelt rates were near or below the bedrock permeability. The field data and model results support the notion that snowmelt on the shallow soil overlying low permeability bedrock becomes direct infiltration unless the snowmelt rate greatly exceeds the bedrock permeability. Late in the season, melt rates are double that of the bedrock permeability (although only for a few days) and may tend to move laterally at the soil-bedrock interface downgradient and contribute directly to streamflow. ?? Soil Science Society of America.

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

NASA Technical Reports Server (NTRS)

Labgaa, Rachid R.; Gautier, Catherine

1992-01-01

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

Numerical analysis of field-scale transport of bromacil

NASA Astrophysics Data System (ADS)

Russo, David; Tauber-Yasur, Inbar; Laufer, Asher; Yaron, Bruno

Field-scale transport of bromacil (5-bromo-3- sec-butyl-6-methyluracil) was analyzed using two different model processes for local description of the transport. The first was the classical, one-region convection dispersion equation (CDE) model while the second was the two-region, mobile-immobile (MIM) model. The analyses were performed by means of detailed three-dimensional, numerical simulations of the flow and the transport [Russo, D., Zaidel, J. and Laufer, A., Numerical analysis of flow and transport in a three-dimensional partially saturated heterogeneous soil. Water Resour. Res., 1998, in press], employing local soil hydraulic properties parameters from field measurements and local adsorption/desorption coefficients and the first-order degradation rate coefficient from laboratory measurements. Results of the analyses suggest that for a given flow regime, mass exchange between the mobile and the immobile regions retards the bromacil degradation, considerably affects the distribution of the bromacil resident concentration, c, at relatively large travel times, slightly affects the spatial moments of the distribution of c, and increases the skewing of the bromacil breakthrough and the uncertainty in its prediction, compared with the case in which the soil contained only a single (mobile) region. Mean and standard deviation of the simulated concentration profiles at various elapsed times were compared with measurements from a field-scale transport experiment [Tauber-Yasur, I., Hadas, A., Russo, D. and Yaron, B., Leaching of terbuthylazine and bromacil through field soils. Water, Air Soil Poln., 1998, in press] conducted at the Bet Dagan site. Given the limitations of the present study (e.g. the lack of detailed field data on the spatial variability of the soil chemical properties) the main conclusion of the present study is that the field-scale transport of bromacil at the Bet Dagan site is better quantified with the MIM model than the CDE model.

Proceedings of the International Symposium on Frozen Soil Impacts on Agricultural, Range, and Forest Lands Held at Spokane, Washington on March 21-22, 1990

DTIC Science & Technology

1990-03-01

Antecedent soil water conditions were measured during the preceding fall using a neutron probe at three locations within each plot to a depth of 1.0 m. A...interrelated heat, water , and solute transfer through snow, residue and soil for a wide range of conditions . Because the model uses fundamental equations... water content profiles at the other sites were measured weekly. Frost depth was measured using cylindrical gypsum moisture blocks read every three hours

Geologic and climatic controls on the radon emanation coefficient

USGS Publications Warehouse

Schumann, R.R.; Gundersen, L.C.S.; ,

1997-01-01

Geologic, pedologic, and climatic factors, including radium content, grain size, siting of radon parents within soil grains or on grain coatings, and soil moisture conditions, determine a soil's emanating power and radon transport characteristics. Data from field studies indicate that soils derived from similar parent rocks in different regions have significantly different emanation coefficients due to the effects of climate on these soil characteristics. An important tool for measuring radon source strength (i.e., radium content) is ground-based and aerial gamma radioactivity measurements. Regional correlations between soil radium content, determined by gamma spectrometry, and soil-gas or indoor radon concentrations can be traced to the influence of climatic and geologic factors on intrinsic permeability and radon emanation coefficients. Data on soil radium content, permeability, and moisture content, when combined with data on emanation coefficients, can form a framework for development of quantitative predictive models for radon generation in rocks and soils.

Simulating maize yield and bomass with spatial variability of soil field capacity

USGS Publications Warehouse

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Evaluation of a surface/vegetation parameterization using satellite measurements of surface temperature

NASA Technical Reports Server (NTRS)

Taconet, O.; Carlson, T.; Bernard, R.; Vidal-Madjar, D.

1986-01-01

Ground measurements of surface-sensible heat flux and soil moisture for a wheat-growing area of Beauce in France were compared with the values derived by inverting two boundary layer models with a surface/vegetation formulation using surface temperature measurements made from NOAA-AVHRR. The results indicated that the trends in the surface heat fluxes and soil moisture observed during the 5 days of the field experiment were effectively captured by the inversion method using the remotely measured radiative temperatures and either of the two boundary layer methods, both of which contain nearly identical vegetation parameterizations described by Taconet et al. (1986). The sensitivity of the results to errors in the initial sounding values or measured surface temperature was tested by varying the initial sounding temperature, dewpoint, and wind speed and the measured surface temperature by amounts corresponding to typical measurement error. In general, the vegetation component was more sensitive to error than the bare soil model.

Estimation of CO2 diffusion coefficient at 0-10 cm depth in undisturbed and tilled soils

USDA-ARS?s Scientific Manuscript database

Diffusion coefficients (D) of CO2 at 0 – 10 cm layers in undisturbed and tilled soil conditions were estimated using Penman, Millington-Quirk, Ridgwell et al. (1999), Troeh et al., and Moldrup et al. models. Soil bulk density and volumetric soil water content ('v) at 0 – 10 cm were measured on April...

Time Series Analysis of Photovoltaic Soiling Station Data: Version 1.0, August 2017

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

Micheli, Leonardo; Muller, Matthew T.; Deceglie, Michael G.

The time series data from PV soiling stations, operating in the USA, at different time periods are analyzed and presented. The current version of the paper includes twenty stations operating between 2013 and 2016, but the paper is intended to be periodically updated as more stations and more data become available. The challenges in working with soiling stations data are discussed, including measurement methodology, quality controls, and measurement uncertainty. The soiling profiles of the soiling stations are made available so that the PV community can make use of this data to guide operations and maintence decisions, estimate soiling derate inmore » performance models, and more generally come to a better understanding of the challenges associated with the variability of PV soiling.« less

Modelling of agricultural diffuse pollution and mitigation measures effectiveness in Wallonia (Belgium)

NASA Astrophysics Data System (ADS)

Sohier, C.; Deraedt, D.; Degré, A.

2012-04-01

Implementation of European directives in the environmental field and, specially, in the water management field, generates a request from policy-makers for news tools able to evaluate impact of management measures aiming at reducing pressures on ecosystems. In Wallonia (Southern Region of Belgium), the Nitrate Directive (EEC/676/91) was transposed into the "Walloon action plan for nitrogen sustainable management in agriculture" (PGDA1) in 2002. In 2007, a second plan was launched to reinforce some topics (PGDA2). Furthermore, the goal of "good quality" of surface waters and groundwater imposed by the Water Framework Directive poses new challenges in water management. In this context, a "soil and vadose" hydrological model is used in order to evaluate diffuse pollutions and efficiency of mitigation measures. This model, called EPICgrid, has been developed at catchment scale with an original modular concept on the basis of the field scale "water-soil-plant" EPIC model (Williams J.R., Jones C.A., Dyke P.T. (1984). A modelling approach to determining the relationship between erosion and soil productivity. Transactions of the ASAE. 27, 129-144). The model estimates, for each HRU identified into a 1km2 grid, water and nutrients flows into the plant-soil-vadose zone system (Sohier C., Degré A., Dautrebande S. (2009). From root zone modelling to regional forecasting of nitrate concentration in recharge flows - The case of the Walloon Region (Belgium). Journal of Hydrology, Volume 369, Issues 3-4, 15 May 2009, Pages 350-359). The model is used to make prospective simulations in order to evaluate the impact of measures currently performed to reduce the effect of diffuse pollution on water surface quality and groundwater quality, at regional scale. Response of the soil-vadose zone to agricultural practices modification is analyzed for the deadlines of the Water Framework Directive: 2015, 2021 and 2027, taking into account two climatic scenarios. Simulations results showed that actual measures are not sufficient in some areas and that new actions are necessary. The EPICgrid model was also used to evaluate effectiveness of further measures that could be implemented in order to reduce agricultural diffuse pollution. The increasing of catch crops in vulnerable zones has shown a limited impact in the Walloon context. The modifications of agricultural practices such as crop rotations or mineral fertilizing amounts have shown a more significant impact on water quality. Furthermore, the farmers' practices are evaluated each year by a measuring campaign of the soil nitrogen residue after harvest. These data allow us to improve the representativeness of the EPICgrid model in areas in which agricultural practices largely differs from regional statistics.

Pesticide uptake in potatoes: model and field experiments.

PubMed

Juraske, Ronnie; Vivas, Carmen S Mosquera; Velásquez, Alexander Erazo; Santos, Glenda García; Moreno, Mónica B Berdugo; Gomez, Jaime Diaz; Binder, Claudia R; Hellweg, Stefanie; Dallos, Jairo A Guerrero

2011-01-15

A dynamic model for uptake of pesticides in potatoes is presented and evaluated with measurements performed within a field trial in the region of Boyacá, Colombia. The model takes into account the time between pesticide applications and harvest, the time between harvest and consumption, the amount of spray deposition on soil surface, mobility and degradation of pesticide in soil, diffusive uptake and persistence due to crop growth and metabolism in plant material, and loss due to food processing. Food processing steps included were cleaning, washing, storing, and cooking. Pesticide concentrations were measured periodically in soil and potato samples from the beginning of tuber formation until harvest. The model was able to predict the magnitude and temporal profile of the experimentally derived pesticide concentrations well, with all measurements falling within the 90% confidence interval. The fraction of chlorpyrifos applied on the field during plant cultivation that eventually is ingested by the consumer is on average 10(-4)-10(-7), depending on the time between pesticide application and ingestion and the processing step considered.

Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model

NASA Astrophysics Data System (ADS)

Thomsen, L. M.; Baartman, J. E. M.; Barneveld, R. J.; Starkloff, T.; Stolte, J.

2015-04-01

Quantification of soil roughness, i.e. the irregularities of the soil surface due to soil texture, aggregates, rock fragments and land management, is important as it affects surface storage, infiltration, overland flow, and ultimately sediment detachment and erosion. Roughness has been measured in the field using both contact methods (such as roller chain and pinboard) and sensor methods (such as stereophotogrammetry and terrestrial laser scanning (TLS)). A novel depth-sensing technique, originating in the gaming industry, has recently become available for earth sciences: the Xtion Pro method. Roughness data obtained using various methods are assumed to be similar; this assumption is tested in this study by comparing five different methods to measure roughness in the field on 1 m2 agricultural plots with different management (ploughing, harrowing, forest and direct seeding on stubble) in southern Norway. Subsequently, the values were used as input for the LISEM soil erosion model to test their effect on the simulated hydrograph at catchment scale. Results show that statistically significant differences between the methods were obtained only for the fields with direct seeding on stubble; for the other land management types the methods were in agreement. The spatial resolution of the contact methods was much lower than for the sensor methods (10 000 versus at least 57 000 points per square metre). In terms of costs and ease of use in the field, the Xtion Pro method is promising. Results from the LISEM model indicate that especially the roller chain overestimated the random roughness (RR) values and the model subsequently calculated less surface runoff than measured. In conclusion, the choice of measurement method for roughness data matters and depends on the required accuracy, resolution, mobility in the field and available budget. It is recommended to use only one method within one study.

Soil surface roughness: comparing old and new measuring methods and application in a soil erosion model

NASA Astrophysics Data System (ADS)

Thomsen, L. M.; Baartman, J. E. M.; Barneveld, R. J.; Starkloff, T.; Stolte, J.

2014-11-01

Quantification of soil roughness, i.e. the irregularities of the soil surface due to soil texture, aggregates, rock fragments and land management, is important as it affects surface storage, infiltration, overland flow and ultimately sediment detachment and erosion. Roughness has been measured in the field using both contact methods, such as roller chain and pinboard, and sensor methods, such as stereophotogrammetry and terrestrial laser scanning (TLS). A novel depth sensing technique, originating in the gaming industry, has recently become available for earth sciences; the Xtion Pro method. Roughness data obtained using various methods are assumed to be similar; this assumption is tested in this study by comparing five different methods to measure roughness in the field on 1 m2 agricultural plots with different management (ploughing, harrowing, forest and direct seeding on stubble) in southern Norway. Subsequently, the values were used as input for the LISEM soil erosion model to test their effect on the simulated hydrograph on catchment scale. Results show that statistically significant differences between the methods were obtained only for the fields with direct drilling on stubble; for the other land management types the methods were in agreement. The spatial resolution of the contact methods was much lower than for the sensor methods (10 000 versus at least 57 000 points per m2 respectively). In terms of costs and ease of handling in the field, the Xtion Pro method is promising. Results from the LISEM model indicate that especially the roller chain underestimated the RR values and the model thereby calculated less surface runoff than measured. In conclusion: the choice of measurement method for roughness data matters and depends on the required accuracy, resolution, mobility in the field and available budget. It is recommended to use only one method within one study.

Research of the diurnal soil respiration dynamic in two typical vegetation communities in Tianjin estuarine wetland

NASA Astrophysics Data System (ADS)

Zhang, Q.; Meng, W. Q.; Li, H. Y.

2016-08-01

Understanding the differences and diurnal variations of soil respiration in different vegetation communities in coastal wetland is to provide basic reliable scientific evidence for the carbon "source" function of wetland ecosystems in Tianjin.Measured soil respiration rate which changed during a day between two typical vegetation communities (Phragmites australis, Suaeda salsa) in coastal wetland in October, 2015. Soil temperature and moisture were measured at the same time. Each of the diurnal curves of soil temperature in two communities had a single peak value, and the diurnal variations of soil moisture showed a "two peak-one valley" trend. The diurnal dynamic of soil respiration under the two communities had obvious volatility which showed a single peak form with its maximum between 12:00-14:00 and minimum during 18:00. The diurnal average of soil respiration rate in Phragmites australis communities was 3.37 times of that in Suaeda salsa communities. Significant relationships were found by regression analysis among soil temperature, soil moisture and soil respiration rate in Suaeda salsa communities. There could be well described by exponential models which was y = -0.245e0.105t between soil respiration rate and soil temperature, by quadratic models which was y = -0.276×2 + 15.277× - 209.566 between soil respiration rate and soil moisture. But the results of this study showed that there were no significant correlations between soil respiration and soil temperature and soil moisture in Phragmites australis communities (P > 0.05). Therefore, under the specific wetland environment conditions in Tianjin, soil temperature and moisture were not main factors influencing the diurnal variations of soil respiration rate in Phragmites australis communities.

Comparing soil functions for a wide range of agriculture soils focusing on production for bioenergy using a combined isotope-based observation and modelling approach

NASA Astrophysics Data System (ADS)

Leistert, Hannes; Herbstritt, Barbara; Weiler, Markus

2017-04-01

Increase crop production for bioenergy will result in changes in land use and the resulting soil functions and may generate new chances and risks. However, detailed data and information are still missing how soil function may be altered under changing crop productions for bioenergy, in particular for a wide range of agricultural soils since most data are currently derived from individual experimental sites studying different bioenergy crops at one location. We developed a new, rapid measurement approach to investigate the influence of bioenergy plants on the water cycle and different soil functions (filter and buffer of water and N-cycling). For this approach, we drilled 89 soil cores (1-3 m deep) in spring and fall at 11 sites with different soil properties and climatic conditions comparing different crops (grass, corn, willow, poplar, and other less common bioenergy crops) and analyzing 1150 soil samples for water content, nitrate concentration and stable water isotopes. We benchmarked a soil hydrological model (1-D numerical Richards equation, ADE, water isotope fractionation including liquid and vapor composition of isotopes) using longer-term climate variables and water isotopes in precipitation to derive crop specific parameterization and to specifically validate the differences in water transport and water partitioning into evaporation, transpiration and groundwater recharge among the sites and crops using the water isotopes in particular. The model simulation were in good agreement with the observed isotope profiles and allowed us to differentiate among the different crops. We defined different indicators for the soil functions considered in this study. These indicators included the proportion of groundwater recharge, transit time of water (different percentiles) though the upper 2m and nutrient leaching potential (e.g. nitrate) during the dormant season from the rooting zone. The parameterized model was first used to calculate the indicators for the sampled locations and to derive the changes in soil functions by altering the land cover among the different bioenergy crops in comparison to the grassland as a reference. We could show that percolation is strongly influenced by the crops and climate, the transit time is influenced by a combination of soil type, climate and land use, but the effect of soil type is very strong and the nitrate leaching is strongly influenced by soil type. The high variability of transit times and nitrate leaching are due to high variability of the temporal distribution of precipitation. Finally, the model was used to regionalized the indicators to a wide range of soils in the state of Baden-Württemberg and to assess if there are locations where bioenergy crops may improve the considered soil function. Our idea behind this was to propose location where specific bioenergy crops may be highly suitable to improve the current soil function to increase for example the protection of groundwater for drinking water, reduce erosion risk or increase water availability. The proposed method allows to assess the influence of different bioenergy crops on soil functions without costly multi-year measurement systems for assessing the soil functions using soil water content measurements or/and soil water suction devices.

Soil-Bacterium Compatibility Model as a Decision-Making Tool for Soil Bioremediation.

PubMed

Horemans, Benjamin; Breugelmans, Philip; Saeys, Wouter; Springael, Dirk

2017-02-07

Bioremediation of organic pollutant contaminated soil involving bioaugmentation with dedicated bacteria specialized in degrading the pollutant is suggested as a green and economically sound alternative to physico-chemical treatment. However, intrinsic soil characteristics impact the success of bioaugmentation. The feasibility of using partial least-squares regression (PLSR) to predict the success of bioaugmentation in contaminated soil based on the intrinsic physico-chemical soil characteristics and, hence, to improve the success of bioaugmentation, was examined. As a proof of principle, PLSR was used to build soil-bacterium compatibility models to predict the bioaugmentation success of the phenanthrene-degrading Novosphingobium sp. LH128. The survival and biodegradation activity of strain LH128 were measured in 20 soils and correlated with the soil characteristics. PLSR was able to predict the strain's survival using 12 variables or less while the PAH-degrading activity of strain LH128 in soils that show survival was predicted using 9 variables. A three-step approach using the developed soil-bacterium compatibility models is proposed as a decision making tool and first estimation to select compatible soils and organisms and increase the chance of success of bioaugmentation.

A (137)Cs erosion model with moving boundary.

PubMed

Yin, Chuan; Ji, Hongbing

2015-12-01

A novel quantitative model of the relationship between diffused concentration changes and erosion rates using assessment of soil losses was developed. It derived from the analysis of surface soil (137)Cs flux variation under persistent erosion effect and based on the principle of geochemistry kinetics moving boundary. The new moving boundary model improves the basic simplified transport model (Zhang et al., 2008), and mainly applies to uniform rainfall areas which show a long-time soil erosion. The simulation results for this kind of erosion show under a long-time soil erosion, the influence of (137)Cs concentration will decrease exponentially with increasing depth. Using the new model fit to the measured (137)Cs depth distribution data in Zunyi site, Guizhou Province, China which has typical uniform rainfall provided a good fit with R(2) = 0.92. To compare the soil erosion rates calculated by the simple transport model and the new model, we take the Kaixian reference profile as example. The soil losses estimated by the previous simplified transport model are greater than those estimated by the new moving boundary model, which is consistent with our expectations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combining in situ and laboratory measurements of soil-atmosphere carbonyl sulfide fluxes from four different biomes across Europe

NASA Astrophysics Data System (ADS)

Kitz, Florian; Gomez-Brandon, Maria; Hammerle, Albin; Spielmann, Felix M.; Insam, Heribert; Ibrom, Andreas; Migliavacca, Mirco; Moreno, Gerardo; Noe, Steffen M.; Wohlfahrt, Georg

2017-04-01

Flux partitioning, the quantification of photosynthesis and respiration, is a major uncertainty in modelling the carbon cycle and in times when robust models are needed to assess future global changes a persistent problem. A promising new approach is to derive gross primary production (GPP) from measurements of the carbonyl sulfide (COS) flux, the most abundant sulfur-containing trace gas in the atmosphere, with a mean concentration of about 500 pptv in the troposphere. This is possible because COS and CO2 enter the leaf via a similar pathway and are processed by the same enzyme (carbonic anhydrase). A prerequisite for using COS as a proxy for photosynthesis is a robust estimation of all non-leaf sources and sinks in an ecosystem. Past studies described soils either as a sink or source, depending on their properties like soil temperature and soil water content. In 2016 we conducted field campaigns in Austria (managed temperate mountain grassland), Spain (savannah), Denmark (temperate beech forest) and Estonia (hemiboreal forest) to estimate the soil-atmosphere COS fluxes under ambient conditions in different biomes. We used self-built fused silica soil chambers to avoid COS emissions from built-in materials and to assess the impact of radiation. At the grassland sites (Austria, Spain) vegetation was removed below the chambers, therefor more radiation reached the soil surface compared to natural conditions. The grassland sites were characterized by highly positive COS fluxes during daytime and COS fluxes around zero during nighttime. In contrast, the soils at the forest sites (Denmark, Estonia), characterized by less radiation on the soil surface, acted as a sink for COS. The impact of other abiotic factors, like soil water content and soil temperature, varied between the ecosystems. In addition to the field measurements soil and litter samples were taken at the study sites and used to measure COS fluxes under controlled conditions in the lab. Results from the temperate mountain grassland in Austria suggest high initial but rapidly decreasing COS emission from soil mixed with litter, but uptake by soil alone. Those lab measurements were followed up by genetical analyses to link the fluxes to the soil microbial communities present in the samples.

Enhanced migration of polychlorodibenzo-p-dioxins and furans in the presence of pentachlorophenol-treated oil in soil around utility poles: screening model validation.

PubMed

Bulle, Cécile; Samson, Réjean; Deschênes, Louise

2010-03-01

Field samples were collected around six pentachlorophenol (PCP)-treated wooden poles (in clay, organic soil, and sand) to evaluate the vertical migration of polychlorodibenzo-p-dioxins and furans (PCDD/Fs). Soils were characterized, PCDD/Fs, C(10)-C(50), and PCP were analyzed for seven composite samples located at a depth from 0 to 100 cm and at a distance from 0 to 50 cm from each pole. Concentrations of PCDD/Fs measured in organic soils were the highest (maximum 1.2E + 05 pg toxic equivalent TEQ/g soil), followed by clay (maximum 3.8E + 04 pg TEQ/g soil) and sand (maximum 1.8E + 04 pg TEQ/g soil). Model predictions, including the influence of wood treatment oil, were validated using measured concentration values in soils around poles. The model predicts a migration of PCDD/Fs due to the migration of oil, which differs depending on the type of soil: in clay, 90% of PCDD/Fs are predicted to remain in the first 29 cm, whereas in sand, 80 to 90% of the emitted PCDD/Fs are predicted to migrate deeper than 185 cm. For the organic soil, the predicted migration depth varies from 90 to 155 cm. This screening model allows evaluating the danger of microcontaminated sites around PCP-treated wooden poles: from a risk assessment perspective, in the case of organic soil and clay, no PCDD/F contamination is to be expected below the pole, but high levels of PCDD/Fs can be found in the first 2 m below the surface. For sand, however, significantly lower levels of PCDD/Fs were predicted in the surface soil, while the migration depth remains elevated, posing an inherent danger of aquifer contamination under the pole.

A multi-frequency radiometric measurement of soil moisture content over bare and vegetated fields

NASA Technical Reports Server (NTRS)

Wang, J. R.; Schmugge, T. J.; Gould, W. I.; Glazar, W. S.; Fuchs, J. E.; Mcmurtrey, J. E., III

1982-01-01

An experiment on soil moisture remote sensing was conducted during July to September 1981 on bare, grass, and alfalfa fields at frequencies of 0.6, 1.4, 5.0, and 10.6 GHz with radiometers mounted on mobile towers. The results confirm the frequency dependence of sensitivity reduction due to the presence of vegetation cover. For the type of vegetated fields reported here, the vegetation effect is appreciable even at 0.6 GHz. Measurements over bare soil show that when the soil is wet, the measured brightness temperature is lowest at 5.0 GHz and highest at 0.6 GHz, a result contrary to the expectation based on the estimated dielectric permittivity of soil-water mixtures and the current radiative transfer model in that frequency range.

Infiltration Processes and Flow Velocities Across the Landscape: When and Where is Macropore Flow Relevant?

NASA Astrophysics Data System (ADS)

Demand, D.; Blume, T.; Weiler, M.

2017-12-01

Preferential flow in macropores significantly affects the distributions of water and solutes in soil and many studies showed its relevance worldwide. Although some models include this process as a second pore domain, little is known about the spatial patterns and temporal dynamics. For example, while flow in the matrix is usually modeled and parameterized based on soil texture, an influence of texture on non-capillary flow for a given land-use class is poorly understood. To investigate the temporal and spatial dynamics on preferential flow we used a four-year soil moisture dataset from the mesoscale Attert catchment (288 km²) in Luxembourg. This dataset contains time series from 126 soil profiles in different textures and two land-use classes (forest, grassland). The soil moisture probes were installed in 10, 30 and 50 cm depth and measured in a 5-minute temporal resolution. Events were defined by a soil moisture increase higher than the instrument noise after a precipitation sum of more than 1 mm. Precipitation was measured next to the profiles so that each location could be associated to its unique precipitation characteristics. For every event and profile the soil moisture reaction was classified in sequential (ordered by depth) and non-sequential response. A non-sequential soil moisture reaction was used as an indicator of preferential flow. For sequential flow, the velocity was determined by the first reaction between two vertically adjacent sensors. The sensor reaction and wetting front velocity was analyzed in the context of precipitation characteristics and initial soil water content. Grassland sites showed a lower proportion of non-sequential flow than forest sites. For forest, non-sequential response is dependent on texture, rainfall intensity and initial water content. This is less distinct for the grassland sites. Furthermore, sequential reactions show higher flow velocities at sites, which also have high percentage of non-sequential response. In contrast, grassland sites show a more homogenous wetting front independent of soil texture. Compared against common modelling approaches of soil water flow, measured velocities show clear evidence of preferential flow, especially for forest soils. The analysis also shows that vegetation can alter the soil properties above the textural properties alone.

Accuracy of sample dimension-dependent pedotransfer functions in estimation of soil saturated hydraulic conductivity

USDA-ARS?s Scientific Manuscript database

Saturated hydraulic conductivity Ksat is a fundamental characteristic in modeling flow and contaminant transport in soils and sediments. Therefore, many models have been developed to estimate Ksat from easily measureable parameters, such as textural properties, bulk density, etc. However, Ksat is no...

Variability and scaling of hydraulic properties for 200 Area soils, Hanford Site

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

Khaleel, R.; Freeman, E.J.

Over the years, data have been obtained on soil hydraulic properties at the Hanford Site. Much of these data have been obtained as part of recent site characterization activities for the Environmental Restoration Program. The existing data on vadose zone soil properties are, however, fragmented and documented in reports that have not been formally reviewed and released. This study helps to identify, compile, and interpret all available data for the principal soil types in the 200 Areas plateau. Information on particle-size distribution, moisture retention, and saturated hydraulic conductivity (K{sub s}) is available for 183 samples from 12 sites in themore » 200 Areas. Data on moisture retention and K{sub s} are corrected for gravel content. After the data are corrected and cataloged, hydraulic parameters are determined by fitting the van Genuchten soil-moisture retention model to the data. A nonlinear parameter estimation code, RETC, is used. The unsaturated hydraulic conductivity relationship can subsequently be predicted using the van Genuchten parameters, Mualem`s model, and laboratory-measured saturated hydraulic conductivity estimates. Alternatively, provided unsaturated conductivity measurements are available, the moisture retention curve-fitting parameters, Mualem`s model, and a single unsaturated conductivity measurement can be used to predict unsaturated conductivities for the desired range of field moisture regime.« less

Simulating carbon dioxide exchange rates of deciduous tree species: evidence for a general pattern in biochemical changes and water stress response.

PubMed

Reynolds, Robert F; Bauerle, William L; Wang, Ying

2009-09-01

Deciduous trees have a seasonal carbon dioxide exchange pattern that is attributed to changes in leaf biochemical properties. However, it is not known if the pattern in leaf biochemical properties - maximum Rubisco carboxylation (V(cmax)) and electron transport (J(max)) - differ between species. This study explored whether a general pattern of changes in V(cmax), J(max), and a standardized soil moisture response accounted for carbon dioxide exchange of deciduous trees throughout the growing season. The model MAESTRA was used to examine V(cmax) and J(max) of leaves of five deciduous trees, Acer rubrum 'Summer Red', Betula nigra, Quercus nuttallii, Quercus phellos and Paulownia elongata, and their response to soil moisture. MAESTRA was parameterized using data from in situ measurements on organs. Linking the changes in biochemical properties of leaves to the whole tree, MAESTRA integrated the general pattern in V(cmax) and J(max) from gas exchange parameters of leaves with a standardized soil moisture response to describe carbon dioxide exchange throughout the growing season. The model estimates were tested against measurements made on the five species under both irrigated and water-stressed conditions. Measurements and modelling demonstrate that the seasonal pattern of biochemical activity in leaves and soil moisture response can be parameterized with straightforward general relationships. Over the course of the season, differences in carbon exchange between measured and modelled values were within 6-12 % under well-watered conditions and 2-25 % under water stress conditions. Hence, a generalized seasonal pattern in the leaf-level physiological change of V(cmax) and J(max), and a standardized response to soil moisture was sufficient to parameterize carbon dioxide exchange for large-scale evaluations. Simplification in parameterization of the seasonal pattern of leaf biochemical activity and soil moisture response of deciduous forest species is demonstrated. This allows reliable modelling of carbon exchange for deciduous trees, thus circumventing the need for extensive gas exchange experiments on different species.

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

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.

Benchmark Data Set for Wheat Growth Models: Field Experiments and AgMIP Multi-Model Simulations.

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Martre, P.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.J.; Rotter, R. P.

2015-01-01

The data set includes a current representative management treatment from detailed, quality-tested sentinel field experiments with wheat from four contrasting environments including Australia, The Netherlands, India and Argentina. Measurements include local daily climate data (solar radiation, maximum and minimum temperature, precipitation, surface wind, dew point temperature, relative humidity, and vapor pressure), soil characteristics, frequent growth, nitrogen in crop and soil, crop and soil water and yield components. Simulations include results from 27 wheat models and a sensitivity analysis with 26 models and 30 years (1981-2010) for each location, for elevated atmospheric CO2 and temperature changes, a heat stress sensitivity analysis at anthesis, and a sensitivity analysis with soil and crop management variations and a Global Climate Model end-century scenario.

Applying Monte-Carlo simulations to optimize an inelastic neutron scattering system for soil carbon analysis

USDA-ARS?s Scientific Manuscript database

Computer Monte-Carlo (MC) simulations (Geant4) of neutron propagation and acquisition of gamma response from soil samples was applied to evaluate INS system performance characteristic [sensitivity, minimal detectable level (MDL)] for soil carbon measurement. The INS system model with best performanc...

A Simple Close Range Photogrammetry Technique to Assess Soil Erosion in the Field

USDA-ARS?s Scientific Manuscript database

Evaluating the performance of a soil erosion prediction model depends on the ability to accurately measure the gain or loss of sediment in an area. Recent development in acquiring detailed surface elevation data (DEM) makes it feasible to assess soil erosion and deposition spatially. Digital photogr...

Modelling the Impact of Soil Management on Soil Functions

NASA Astrophysics Data System (ADS)

Vogel, H. J.; Weller, U.; Rabot, E.; Stößel, B.; Lang, B.; Wiesmeier, M.; Urbanski, L.; Wollschläger, U.

2017-12-01

Due to an increasing soil loss and an increasing demand for food and energy there is an enormous pressure on soils as the central resource for agricultural production. Besides the importance of soils for biomass production there are other essential soil functions, i.e. filter and buffer for water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these functions have a direct feed back to biogeochemical cycles and climate. To render agricultural production efficient and sustainable we need to develop model tools that are capable to predict quantitatively the impact of a multitude of management measures on these soil functions. These functions are considered as emergent properties produced by soils as complex systems. The major challenge is to handle the multitude of physical, chemical and biological processes interacting in a non-linear manner. A large number of validated models for specific soil processes are available. However, it is not possible to simulate soil functions by coupling all the relevant processes at the detailed (i.e. molecular) level where they are well understood. A new systems perspective is required to evaluate the ensemble of soil functions and their sensitivity to external forcing. Another challenge is that soils are spatially heterogeneous systems by nature. Soil processes are highly dependent on the local soil properties and, hence, any model to predict soil functions needs to account for the site-specific conditions. For upscaling towards regional scales the spatial distribution of functional soil types need to be taken into account. We propose a new systemic model approach based on a thorough analysis of the interactions between physical, chemical and biological processes considering their site-specific characteristics. It is demonstrated for the example of soil compaction and the recovery of soil structure, water capacity and carbon stocks as a result of plant growth and biological activity. Coupling of the observed nonlinear interactions allows for modeling the stability and resilience of soil systems in terms of their essential functions.

An inversion method for retrieving soil moisture information from satellite altimetry observations

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Forootan, Ehsan; Kusche, Jürgen; Braakmann-Folgmann, Anne

2016-04-01

Soil moisture represents an important component of the terrestrial water cycle that controls., evapotranspiration and vegetation growth. Consequently, knowledge on soil moisture variability is essential to understand the interactions between land and atmosphere. Yet, terrestrial measurements are sparse and their information content is limited due to the large spatial variability of soil moisture. Therefore, over the last two decades, several active and passive radar and satellite missions such as ERS/SCAT, AMSR, SMOS or SMAP have been providing backscatter information that can be used to estimate surface conditions including soil moisture which is proportional to the dielectric constant of the upper (few cm) soil layers . Another source of soil moisture information are satellite radar altimeters, originally designed to measure sea surface height over the oceans. Measurements of Jason-1/2 (Ku- and C-Band) or Envisat (Ku- and S-Band) nadir radar backscatter provide high-resolution along-track information (~ 300m along-track resolution) on backscatter every ~10 days (Jason-1/2) or ~35 days (Envisat). Recent studies found good correlation between backscatter and soil moisture in upper layers, especially in arid and semi-arid regions, indicating the potential of satellite altimetry both to reconstruct and to monitor soil moisture variability. However, measuring soil moisture using altimetry has some drawbacks that include: (1) the noisy behavior of the altimetry-derived backscatter (due to e.g., existence of surface water in the radar foot-print), (2) the strong assumptions for converting altimetry backscatters to the soil moisture storage changes, and (3) the need for interpolating between the tracks. In this study, we suggest a new inversion framework that allows to retrieve soil moisture information from along-track Jason-2 and Envisat satellite altimetry data, and we test this scheme over the Australian arid and semi-arid regions. Our method consists of: (i) deriving time-invariant spatial patterns (base-functions) by applying principal component analysis (PCA) to simulated soil moisture from a large-scale land surface model. (ii) Estimating time-variable soil moisture evolution by fitting these base functions of (i) to the along-track retracked backscatter coefficients in a least squares sense. (iii) Combining the estimated time-variable amplitudes and the pre-computed base-functions, which results in reconstructed (spatio-temporal) soil moisture information. We will show preliminary results that are compared to available high-resolution soil moisture model data over the region (the Australian Water Resource Assessment, AWRA model). We discuss the possibility of using altimetry-derived soil moisture estimations to improve the simulation skill of soil moisture in the Global Land Data Assimilation System (GLDAS) over Australia.

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

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.

Effects of Inter- and Intra-aggregate Pore Space on the Soil-Gas Diffusivity Behavior in Unsaturated, Undisturbed Volcanic Ash Soils

NASA Astrophysics Data System (ADS)

Resurreccion, A. C.; Kawamoto, K.; Komatsu, T.; Moldrup, P.

2006-12-01

Volcanic ash soils (Andisols) have a unique dual porosity structure that results in good drainage and high soil- water retention. Despite of the complicated and highly developed soil structure, recent studies have reported a simple, highly linear relation between the soil-gas diffusion coefficient, Dp, and the soil-air content, ɛ, for several Japanese Andisols. In this study, we explain the linear Dp(ɛ) behavior from the effects of the inter- and intra-aggregate pore-size distributions. We couple the bimodal van Genuchten soil-water retention model with a general Dp(ɛ) model, ɛ^{X}, allowing the tortuosity- connectivity factor X to vary with pF (= log(-ψ; the soil-water matric potential in cm H2O)). Measured data suggest that the tortuosity-connectivity parameter X is at the minimum at pF 3 (where X ~ 2, following Buckingham, 1904), equal to the water retention point where a separation of inter- and intra-aggregate effects on Dp is observed. At pF < 3, the X values increased as pF decreased because of inactive/remote air-filled pore space entrapped by the inter-connected water films between inter-aggregate pore spaces. At pF > 3, X increased to a high value at very dry conditions due to remote air-filled space inside the intra-aggregate pores. By combining the complex dual porosity soil-water retention model with the power- law gas diffusivity model using a parabolic X(pF) function, the surprisingly simple linear behavior of Dp with ɛ was captured while the variation of Dp with pF followed a dual s-shaped curve similar to the water retention curve. A simple linear model to predict Dp(ɛ) is suggested, with slope C and threshold soil-air content, ɛth, calculated from the power-law model ɛ^{X} at pF 2 (near field capacity) and at pF 4.1 (near wilting point) using the same X value (= 2.3) at both pF in agreement with measured data. This linear Dp(ɛ) model performed better, especially at dry conditions, compared to the traditionally-used predictive models when tested against several independent Andisol datasets from literature.

Remote monitoring of soil moisture using airborne microwave radiometers

NASA Technical Reports Server (NTRS)

Kroll, C. L.

1973-01-01

The current status of microwave radiometry is provided. The fundamentals of the microwave radiometer are reviewed with particular reference to airborne operations, and the interpretative procedures normally used for the modeling of the apparent temperature are presented. Airborne microwave radiometer measurements were made over selected flight lines in Chickasha, Oklahoma and Weslaco, Texas. Extensive ground measurements of soil moisture were made in support of the aircraft mission over the two locations. In addition, laboratory determination of the complex permittivities of soil samples taken from the flight lines were made with varying moisture contents. The data were analyzed to determine the degree of correlation between measured apparent temperatures and soil moisture content.

Prediction of relative and absolute permeabilities for gas and water from soil water retention curves using a pore-scale network model

NASA Astrophysics Data System (ADS)

Fischer, Ulrich; Celia, Michael A.

1999-04-01

Functional relationships for unsaturated flow in soils, including those between capillary pressure, saturation, and relative permeabilities, are often described using analytical models based on the bundle-of-tubes concept. These models are often limited by, for example, inherent difficulties in prediction of absolute permeabilities, and in incorporation of a discontinuous nonwetting phase. To overcome these difficulties, an alternative approach may be formulated using pore-scale network models. In this approach, the pore space of the network model is adjusted to match retention data, and absolute and relative permeabilities are then calculated. A new approach that allows more general assignments of pore sizes within the network model provides for greater flexibility to match measured data. This additional flexibility is especially important for simultaneous modeling of main imbibition and drainage branches. Through comparisons between the network model results, analytical model results, and measured data for a variety of both undisturbed and repacked soils, the network model is seen to match capillary pressure-saturation data nearly as well as the analytical model, to predict water phase relative permeabilities equally well, and to predict gas phase relative permeabilities significantly better than the analytical model. The network model also provides very good estimates for intrinsic permeability and thus for absolute permeabilities. Both the network model and the analytical model lost accuracy in predicting relative water permeabilities for soils characterized by a van Genuchten exponent n≲3. Overall, the computational results indicate that reliable predictions of both relative and absolute permeabilities are obtained with the network model when the model matches the capillary pressure-saturation data well. The results also indicate that measured imbibition data are crucial to good predictions of the complete hysteresis loop.

Short- and Long-Term Feedbacks on Vegetation Water Use: Unifying Evidence from Observations and Modeling

NASA Astrophysics Data System (ADS)

Mackay, D. S.

2001-05-01

Recent efforts to measure and model the interacting influences of climate, soil, and vegetation on soil water and nutrient dynamics have identified numerous important feedbacks that produce nonlinear responses. In particular, plant physiological factors that control rates of transpiration respond to soil water deficits and vapor pressure deficits (VPD) in the short-term, and to climate, nutrient cycling and disturbance in the long-term. The starting point of this presentation is the observation that in many systems, in particular forest ecosystems, conservative water use emerges as a result of short-term closure of stomata in response to high evaporative demand, and long-term vegetative canopy development under nutrient limiting conditions. Evidence for important short-term controls is presented from sap flux measurements of stand transpiration, remote sensing, and modeling of transpiration through a combination of physically-based modeling and Monte Carlo analysis. A common result is a strong association between stomatal conductance (gs) and the negative evaporative gain (∂ gs/∂ VPD) associated with the sensitivity of stomatal closure to rates of water loss. The importance of this association from the standpoint of modeling transpiration depends on the degree of canopy-atmosphere coupling. This suggests possible simplifications to future canopy component models for use in watershed and larger-scale hydrologic models for short-term processes. However, further results are presented from theoretical modeling, which suggest that feedbacks between hydrology and vegetation in current long-term (inter-annual to century) models may be too simple, as they do not capture the spatially variable nature of slow nutrient cycling in response to soil water dynamics and site history. Memory effects in the soil nutrient pools can leave lasting effects on more rapid processes associated with soil, vegetation, atmosphere coupling.

Water retention of repellent and subcritical repellent soils: New insights from model and experimental investigations

NASA Astrophysics Data System (ADS)

Czachor, H.; Doerr, S. H.; Lichner, L.

2010-01-01

SummarySoil organic matter can modify the surface properties of the soil mineral phase by changing the surface tension of the mineral surfaces. This modifies the soil's solid-water contact angle, which in turn would be expected to affect its water retention curve (SWRC). Here we model the impact of differences in the soil pore-water contact angle on capillarity in non-cylindrical pores by accounting for their complex pore geometry. Key outcomes from the model include that (i) available methods for measuring the Young's wetting angle on soil samples are insufficient in representing the wetting angle in the soil pore space, (ii) the wetting branch of water retention curves is strongly affected by the soil pore-water contact angle, as manifest in the wetting behavior of water repellent soils, (iii) effects for the drying branch are minimal, indicating that both wettable and water repellent soils should behave similarly, and (vi) water retention is a feature not of only wettable soils, but also soils that are in a water repellent state. These results are tested experimentally by determining drying and wetting branches for (a) 'model soil' (quartz sands with four hydrophobization levels) and (b) five field soil samples with contrasting wettability, which were used with and without the removal of the soil organic matter. The experimental results support the theoretical predictions and indicate that small changes in wetting angle can cause switches between wettable and water repellent soil behavior. This may explain the common observation that relatively small changes in soil water content can cause substantial changes in soil wettability.

Hyperspectral Imaging Analysis for the Classification of Soil Types and the Determination of Soil Total Nitrogen

PubMed Central

Jia, Shengyao; Li, Hongyang; Wang, Yanjie; Tong, Renyuan; Li, Qing

2017-01-01

Soil is an important environment for crop growth. Quick and accurately access to soil nutrient content information is a prerequisite for scientific fertilization. In this work, hyperspectral imaging (HSI) technology was applied for the classification of soil types and the measurement of soil total nitrogen (TN) content. A total of 183 soil samples collected from Shangyu City (People’s Republic of China), were scanned by a near-infrared hyperspectral imaging system with a wavelength range of 874–1734 nm. The soil samples belonged to three major soil types typical of this area, including paddy soil, red soil and seashore saline soil. The successive projections algorithm (SPA) method was utilized to select effective wavelengths from the full spectrum. Pattern texture features (energy, contrast, homogeneity and entropy) were extracted from the gray-scale images at the effective wavelengths. The support vector machines (SVM) and partial least squares regression (PLSR) methods were used to establish classification and prediction models, respectively. The results showed that by using the combined data sets of effective wavelengths and texture features for modelling an optimal correct classification rate of 91.8%. could be achieved. The soil samples were first classified, then the local models were established for soil TN according to soil types, which achieved better prediction results than the general models. The overall results indicated that hyperspectral imaging technology could be used for soil type classification and soil TN determination, and data fusion combining spectral and image texture information showed advantages for the classification of soil types. PMID:28974005

Effects of prolonged soil drought on CH4 oxidation in a temperate spruce forest

NASA Astrophysics Data System (ADS)

Borken, W.; Brumme, R.; Xu, Y.-J.

2000-03-01

Our objective was to determine potential impacts of changes in rainfall amount and distribution on soil CH4 oxidation in a temperate forest ecosystem. We constructed a roof below the canopy of a 65-year-old Norway spruce forest (Picea abies (L.) Karst.) and simulated two climate change scenarios: (1) an extensively prolonged summer drought of 172 days followed by a rewetting period of 19 days in 1993 and (2) a less intensive summer drought of 108 days followed by a rewetting period of 33 days in 1994. CH4 oxidation, soil matric potential, and soil temperature were measured hourly to daily over a 2-year period. The results showed that annual CH4 oxidation in the drought experiment increased by 102% for the climate change scenario 1 and by 41% for the climate change scenario 2, compared to those of the ambient plot (1.33 kg CH4 ha-1 in 1993 and 1.65 kg CH4 ha-1 in 1994). We tested the relationships between CH4 oxidation rates, water-filled pore space (WFPS), soil matric potential, gas diffusivity, and soil temperature. Temporal variability in the CH4 oxidation rates corresponded most closely to soil matric potential. Employing soil matric potential and soil temperature, we developed a nonlinear model for estimating CH4 oxidation rates. Modeled results were in strong agreement with the measured CH4 oxidation for the ambient (r2 = 0.80) and drought plots (r2 = 0.89) over two experimental years, suggesting that soil matric potential is a highly reliable parameter for modeling CH4 oxidation rate.

Intra-aggregate CO2 enrichment: a modelling approach for aerobic soils

NASA Astrophysics Data System (ADS)

Schlotter, D.; Schack-Kirchner, H.

2013-02-01

CO2 concentration gradients inside soil aggregates, caused by the respiration of soil microorganisms and fungal hyphae, might lead to variations in the soil solution chemistry on a mm-scale, and to an underestimation of the CO2 storage. But, up to now, there seems to be no feasible method for measuring CO2 inside natural aggregates with sufficient spatial resolution. We combined a one-dimensional model for gas diffusion in the inter-aggregate pore space with a cylinder diffusion model, simulating the consumption/production and diffusion of O2 and CO2 inside soil aggregates with air- and water-filled pores. Our model predicts that for aerobic respiration (respiratory quotient = 1) the intra-aggregate increase in the CO2 partial pressure can never be higher than 0.9 kPa for siliceous, and 0.1 kPa for calcaric aggregates, independent of the level of water-saturation. This suggests that only for siliceous aggregates CO2 produced by aerobic respiration might cause a high small-scale spatial variability in the soil solution chemistry. In calcaric aggregates, however, the contribution of carbonate species to the CO2 transport should lead to secondary carbonates on the aggregate surfaces. As regards the total CO2 storage in aerobic soils, both siliceous and calcaric, the effect of intra-aggregate CO2 gradients seems to be negligible. To assess the effect of anaerobic respiration on the intra-aggregate CO2 gradients, the development of a device for measuring CO2 on a mm-scale in soils is indispensable.

Density-driven transport of gas phase chemicals in unsaturated soils

NASA Astrophysics Data System (ADS)

Fen, Chiu-Shia; Sun, Yong-tai; Cheng, Yuen; Chen, Yuanchin; Yang, Whaiwan; Pan, Changtai

2018-01-01

Variations of gas phase density are responsible for advective and diffusive transports of organic vapors in unsaturated soils. Laboratory experiments were conducted to explore dense gas transport (sulfur hexafluoride, SF6) from different source densities through a nitrogen gas-dry soil column. Gas pressures and SF6 densities at transient state were measured along the soil column for three transport configurations (horizontal, vertically upward and vertically downward transport). These measurements and others reported in the literature were compared with simulation results obtained from two models based on different diffusion approaches: the dusty gas model (DGM) equations and a Fickian-type molar fraction-based diffusion expression. The results show that the DGM and Fickian-based models predicted similar dense gas density profiles which matched the measured data well for horizontal transport of dense gas at low to high source densities, despite the pressure variations predicted in the soil column were opposite to the measurements. The pressure evolutions predicted by both models were in trend similar to the measured ones for vertical transport of dense gas. However, differences between the dense gas densities predicted by the DGM and Fickian-based models were discernible for vertically upward transport of dense gas even at low source densities, as the DGM-based predictions matched the measured data better than the Fickian results did. For vertically downward transport, the dense gas densities predicted by both models were not greatly different from our experimental measurements, but substantially greater than the observations obtained from the literature, especially at high source densities. Further research will be necessary for exploring factors affecting downward transport of dense gas in soil columns. Use of the measured data to compute flux components of SF6 showed that the magnitudes of diffusive flux component based on the Fickian-type diffusion expressions in terms of molar concentration, molar fraction and mass density fraction gradient were almost the same. However, they were greater than the result computed with the mass fraction gradient for > 24% and the DGM-based result for more than one time. As a consequence, the DGM-based total flux of SF6 was in magnitude greatly less than the Fickian result not only for horizontal transport (diffusion-dominating) but also for vertical transport (advection and diffusion) of dense gas. Particularly, the Fickian-based total flux was more than two times in magnitude as much as the DGM result for vertically upward transport of dense gas.

Lessons from simultaneous measurements of soil respiration and net ecosystem exchange of CO2 in temperate forests

NASA Astrophysics Data System (ADS)

Renchon, A.; Pendall, E.

2017-12-01

Land-surface exchanges of CO2 play a key role in ameliorating or exacerbating climate change. The eddy-covariance method allows direct measurement of net ecosystem-atmosphere exchange of CO2 (NEE), but partitioning daytime NEE into its components - gross primary productivity (GPP) and ecosystem respiration (RE) - remains challenging. Continuous measurements of soil respiration (RS), along with flux towers, have the potential to better constrain data and models of RE and GPP. We use simultaneous half-hourly NEE and RS data to: (1) compare the short-term (fortnightly) apparent temperature sensitivity (Q10) of nighttime RS and RE; (2) assess whether daytime RS can be estimated using nighttime response functions; and (3) compare the long-term (annual) responses of nighttime RS and nighttime RE to interacting soil moisture and soil temperature. We found that nighttime RS has a lower short-term Q10 than nighttime RE. This suggests that the Q10 of nighttime RE is strongly influenced by the Q10 of nighttime above-ground respiration, or possibly by a bias in RE measurements. The short-term Q10 of RS and RE decreased with increasing temperature. In general, daytime RS could be estimated using nighttime RS temperature and soil moisture (r2 = 0.9). However, this results from little to no diurnal variation in RS, and estimating daytime RS as the average of nighttime RS gave similar results (r2 = 0.9). Furthermore, we observed a day-night hysteresis of RS response to temperature, especially when using air temperature and sometimes when using soil temperature at 5cm depth. In fact, during some months, soil respiration observations were lower during daytime compared to nighttime, despite higher temperature in daytime. Therefore, daytime RS modelled from nighttime RS temperature response was overestimated during these periods. RS and RE responses to the combination of soil moisture and soil temperature were similar, and consistent with the DAMM model of soil-C decomposition. These findings underscore the value of continuous measurements of RS in flux tower footprints. Findings are also relevant to recent research on light inhibition of leaf respiration and contribute to improved understanding of ecosystem carbon cycle - climate feedback processes.

Biodiversity effects on the water balance of an experimental grassland

NASA Astrophysics Data System (ADS)

Leimer, Sophia; Kreutziger, Yvonne; Rosenkranz, Stephan; Beßler, Holger; Engels, Christof; Oelmann, Yvonne; Weisser, Wolfgang W.; Wirth, Christian; Wilcke, Wolfgang

2013-04-01

Plant species richness increases aboveground biomass production in biodiversity experiments. Biomass production depends on and feeds back to the water balance, but it remains unclear how plant species richness influences soil water contents and water fluxes (actual evapotranspiration (ETa), downward flux (DF), and upward flux (UF)). Our objective was to determine the effects of plant species and functional richness and functional identity on soil water contents and water fluxes for two soil depths (0-0.3 and 0.3.-0.7 m). To achieve this, we used a water balance model in connection with Bayesian hierarchical modeling. We monitored soil water contents on 86 plots of a grassland plant diversity experiment in Jena, Germany between July 2002 and January 2006. In the field experiment, plant species richness (0, 1, 2, 4, 8, 16, 60) and functional group composition (0-4 functional groups: legumes, grasses, non-leguminous tall herbs, non-leguminous small herbs) were manipulated in a factorial design. Climate data (air temperature, precipitation, wind velocity, relative humidity, global radiation, soil moisture) was measured at a central climate station between July 2002 and December 2007. Root biomass data from July 2006 was available per plot. Missing water contents per plot and depth were estimated in weekly resolution for the years 2003-2007 with a Bayesian hierarchical model using measured water contents per plot and centrally measured soil moisture. To obtain ETa, DF, and UF of the two different soil depths, we modified a soil water balance model which had been developed for our study site. The model is based on changes in soil water content between subsequent observation dates and modeled potential evapotranspiration which was partitioned between soil layers according to percentage of root biomass. The presence of specific functional groups significantly changed water contents and fluxes with partly opposing effects in the two soil depths. Presence of grasses decreased water contents in both depths, DF in topsoil, and ETa in subsoil, but increased ETa in topsoil. As grasses produce less shade than other plant functional groups because of their leaf morphology, higher ETa in topsoil could be explained by higher soil evaporation. Moreover, grasses have an extensive, shallow rooting system which facilitates exhaustive water use from the upper soil layer and therefore probably decreases water contents and DF. Species richness did not significantly affect water contents and fluxes in both soil layers except that the relation between species richness and water contents in subsoil changed over time. This can be explained by two equivalent but opposite effects. Transpiration increases with biomass which is positively correlated with species richness. By contrast, soil evaporation decreases with species richness because the greater vegetation cover in species-rich communities produces more shade. We conclude that the contrasting effects of plant species richness on transpiration and evaporation counterbalance each other and that functional traits of specific plant functional groups mediate the biologically-induced changes in the water balance.

Ecosystem CO2 and CH4 exchange in a mixed tundra and a fen within a hydrologically diverse Arctic landscape: 1. Modeling versus measurements

NASA Astrophysics Data System (ADS)

Grant, R. F.; Humphreys, E. R.; Lafleur, P. M.

2015-07-01

CO2 and CH4 exchange are strongly affected by hydrology in landscapes underlain by permafrost. Hypotheses for these effects in the model ecosys were tested by comparing modeled CO2 and CH4 exchange with CO2 fluxes measured by eddy covariance from 2006 to 2009, and with CH4 fluxes measured with surface chambers in 2008, along a topographic gradient at Daring Lake, NWT. In an upland tundra, rises in net CO2 uptake in warmer years were constrained by declines in CO2 influxes when vapor pressure deficits (D) exceeded 1.5 kPa and by rises in CO2 effluxes with greater active layer depth. Consequently, net CO2 uptake rose little with warming. In a lowland fen, CO2 influxes declined less with D and CO2 effluxes rose less with warming, so that rises in net CO2 uptake were greater than those in the tundra. Greater declines in CO2 influxes with warming in the tundra were modeled from greater soil-plant-atmosphere water potential gradients that developed under higher D in drained upland soil, and smaller rises in CO2 effluxes with warming in the fen were modeled from O2 constraints to heterotrophic and belowground autotrophic respiration from a shallow water table in poorly drained lowland soil. CH4 exchange modeled during July and August indicated very small influxes in the tundra and larger effluxes characterized by afternoon emission events caused by degassing of warming soil in the fen. Emissions of CH4 modeled from degassing during soil freezing in October-November contributed about one third of the annual total.

Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions

NASA Astrophysics Data System (ADS)

Song, Lisheng; Kustas, William P.; Liu, Shaomin; Colaizzi, Paul D.; Nieto, Hector; Xu, Ziwei; Ma, Yanfei; Li, Mingsong; Xu, Tongren; Agam, Nurit; Tolk, Judy A.; Evett, Steven R.

2016-09-01

In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measured ET measurements were less than 10% and 20% on a daytime basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics of E, T and ET over a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.

A predictive wheel-soil interaction model for planetary rovers validated in testbeds and against MER Mars rover performance data

NASA Astrophysics Data System (ADS)

Richter, L.; Ellery, A.; Gao, Y.; Michaud, S.; Schmitz, N.; Weiss, S.

Successful designs of vehicles intended for operations on planetary objects outside the Earth demand, just as for terrestrial off-the-road vehicles, a careful assessment of the terrain relevant for the vehicle mission and predictions of the mobility performance to allow rational trade-off's to be made for the choice of the locomotion concept and sizing. Principal issues driving the chassis design for rovers are the stress-strain properties of the planetary surface soil, the distribution of rocks in the terrain representing potential obstacles to movement, and the gravity level on the celestial object in question. Thus far, planetary rovers have been successfully designed and operated for missions to the Earth's moon and to the planet Mars, including NASA's Mars Exploration Rovers (MER's) `Spirit' and `Opportunity' being in operation on Mars since their landings in January 2004. Here we report on the development of a wheel-soil interaction model with application to wheel sizes and wheel loads relevant to current and near-term robotic planetary rovers, i.e. wheel diameters being between about 200 and 500 mm and vertical quasistatic wheel loads in operation of roughly 100 to 200 N. Such a model clearly is indispensable for sizings of future rovers to analyse the aspect of rover mobility concerned with motion across soils. This work is presently funded by the European Space Agency (ESA) as part of the `Rover Chassis Evaluation Tools' (RCET) effort which has developed a set of S/W-implemented models for predictive mobility analysis of rovers in terms of movement on soils and across obstacles, coupled with dedicated testbeds to validate the wheel-soil models. In this paper, we outline the details of the wheel-soil modelling performed within the RCET work and present comparisons of predictions of wheel performance (motion resistance, torque vs. slip and drawbar pull vs. slip) for specific test cases with the corresponding measurements performed in the RCET single wheel testbed and in the RCET system-level testbed, the latter permitting drawbar pull vs. slip measurements for complete rover development vehicles under controlled and homogeneous soil conditions. Required modifications of the wheel-soil model, in particular related to modelling the effect of wheel slip, are discussed. To strengthen the model validation base, we have run single wheel measurements using a spare MER Mars rover wheel and have performed comparisons with MER actual mobility performance data, available through one of us (LR) who is a member of the MER Athena science team. Corresponding results will be presented. Keywords: rovers, wheel, soil, mobility, vehicle performance, RCET (Rover Chassis Evaluation Tools), MER (Mars Exploration Rover mission) 2

Plant identity and shallow soil moisture are primary drivers of stomatal conductance in the savannas of Kruger National Park

PubMed Central

Tobin, Rebecca L.

2018-01-01

Our goal was to describe stomatal conductance (gs) and the site-scale environmental parameters that best predict gs in Kruger National Park (KNP), South Africa. Dominant grass and woody species were measured over two growing seasons in each of four study sites that represented the natural factorial combination of mean annual precipitation [wet (750 mm) or dry (450 mm)] and soil type (clay or sand) found in KNP. A machine-learning (random forest) model was used to describe gs as a function of plant type (species or functional group) and site-level environmental parameters (CO2, season, shortwave radiation, soil type, soil moisture, time of day, vapor pressure deficit and wind speed). The model explained 58% of the variance among 6,850 gs measurements. Species, or plant functional group, and shallow (0–20 cm) soil moisture had the greatest effect on gs. Atmospheric drivers and soil type were less important. When parameterized with three years of observed environmental data, the model estimated mean daytime growing season gs as 68 and 157 mmol m-2 sec-1 for grasses and woody plants, respectively. The model produced here could, for example, be used to estimate gs and evapotranspiration in KNP under varying climate conditions. Results from this field-based study highlight the role of species identity and shallow soil moisture as primary drivers of gs in savanna ecosystems of KNP. PMID:29373605

Analysing the mechanisms of soil water and vapour transport in the desert vadose zone of the extremely arid region of northern China

NASA Astrophysics Data System (ADS)

Du, Chaoyang; Yu, Jingjie; Wang, Ping; Zhang, Yichi

2018-03-01

The transport of water and vapour in the desert vadose zone plays a critical role in the overall water and energy balances of near-surface environments in arid regions. However, field measurements in extremely dry environments face many difficulties and challenges, so few studies have examined water and vapour transport processes in the desert vadose zone. The main objective of this study is to analyse the mechanisms of soil water and vapour transport in the desert vadose zone (depth of ∼350 cm) by using measured and modelled data in an extremely arid environment. The field experiments are implemented in an area of the Gobi desert in northwestern China to measure the soil properties, daily soil moisture and temperature, daily water-table depth and temperature, and daily meteorological records from DOYs (Days of Year) 114-212 in 2014 (growing season). The Hydrus-1D model, which simulates the coupled transport of water, vapour and heat in the vadose zone, is employed to simulate the layered soil moisture and temperature regimes and analyse the transport processes of soil water and vapour. The measured results show that the soil water and temperatures near the land surface have visible daily fluctuations across the entire soil profile. Thermal vapour movement is the most important component of the total water flux and the soil temperature gradient is the major driving factor that affects vapour transport in the desert vadose zone. The most active water and heat exchange occurs in the upper soil layer (depths of 0-25 cm). The matric potential change from the precipitation mainly re-draws the spatio-temporal distribution of the isothermal liquid water in the soil near the land surface. The matric potential has little effect on the isothermal vapour and thermal liquid water flux. These findings offer new insights into the liquid water and vapour movement processes in the extremely arid environment.

A structural equation model of soil metal bioavailability to earthworms: confronting causal theory and observations using a laboratory exposure to field-contaminated soils.

PubMed

Beaumelle, Léa; Vile, Denis; Lamy, Isabelle; Vandenbulcke, Franck; Gimbert, Frédéric; Hedde, Mickaël

2016-11-01

Structural equation models (SEM) are increasingly used in ecology as multivariate analysis that can represent theoretical variables and address complex sets of hypotheses. Here we demonstrate the interest of SEM in ecotoxicology, more precisely to test the three-step concept of metal bioavailability to earthworms. The SEM modeled the three-step causal chain between environmental availability, environmental bioavailability and toxicological bioavailability. In the model, each step is an unmeasured (latent) variable reflected by several observed variables. In an exposure experiment designed specifically to test this SEM for Cd, Pb and Zn, Aporrectodea caliginosa was exposed to 31 agricultural field-contaminated soils. Chemical and biological measurements used included CaC12-extractable metal concentrations in soils, free ion concentration in soil solution as predicted by a geochemical model, dissolved metal concentration as predicted by a semi-mechanistic model, internal metal concentrations in total earthworms and in subcellular fractions, and several biomarkers. The observations verified the causal definition of Cd and Pb bioavailability in the SEM, but not for Zn. Several indicators consistently reflected the hypothetical causal definition and could thus be pertinent measurements of Cd and Pb bioavailability to earthworm in field-contaminated soils. SEM highlights that the metals present in the soil solution and easily extractable are not the main source of available metals for earthworms. This study further highlights SEM as a powerful tool that can handle natural ecosystem complexity, thus participating to the paradigm change in ecotoxicology from a bottom-up to a top-down approach. Copyright © 2016 Elsevier B.V. All rights reserved.

The effect of organic contaminants on the spectral induced polarization response of porous media - mechanistic approach

NASA Astrophysics Data System (ADS)

Schwartz, N.; Huisman, J. A.; Furman, A.

2012-12-01

In recent years, there is a growing interest in using geophysical methods in general and spectral induced polarization (SIP) in particular as a tool to detect and monitor organic contaminants within the subsurface. The general idea of the SIP method is to inject alternating current through a soil volume and to measure the resultant potential in order to obtain the relevant soil electrical properties (e.g. complex impedance, complex conductivity/resistivity). Currently, a complete mechanistic understanding of the effect of organic contaminants on the SIP response of soil is still absent. In this work, we combine laboratory experiments with modeling to reveal the main processes affecting the SIP signature of soil contaminated with organic pollutant. In a first set of experiments, we investigate the effect of non-aqueous phase liquids (NAPL) on the complex conductivity of unsaturated porous media. Our results show that addition of NAPL to the porous media increases the real component of the soil electrical conductivity and decreases the polarization of the soil (imaginary component of the complex conductivity). Furthermore, addition of NAPL to the soil resulted in an increase of the electrical conductivity of the soil solution. Based on these results, we suggest that adsorption of NAPL to the soil surface, and exchange process between polar organic compounds in the NAPL and inorganic ions in the soil are the main processes affecting the SIP signature of the contaminated soil. To further support our hypothesis, the temporal change of the SIP signature of a soil as function of a single organic cation concentration was measured. In addition to the measurements of the soil electrical properties, we also measured the effect of the organic cation on the chemical composition of both the bulk and the surface of the soil. The results of those experiments again showed that the electrical conductivity of the soil increased with increasing contaminant concentration. In addition, direct evidence showed that the organic cation was adsorbed on the soil surface and exchanged with inorganic ions that usually exist in soil. This experiment confirmed that adsorption to the soil surface and the associated release of inorganic ions is the main mechanism affecting the complex conductivity of the contaminated porous media. Furthermore, our results show that adsorption of organic ions to the soil surface resulted in a decrease of the soil polarization. Using a chemical complexation model of the soil surface and a model for the polarization of the Stern layer, we were able to show that the decrease in the polarization of the soil can be related to the decrease in the surface site density of inorganic ions, and that the contribution of the soil-organic complexes to the polarization of the soil is negligible. We attribute this to the strong interaction between polar organic compounds and soil which results in a significant decrease in the mobility of the organic compounds in the Stern layer. The results of this work are essential to better interpret SIP signatures of soil contaminated with organic contaminants.

[Study on a new prevention and control model on soil-borne parasitic diseases in rural areas of China].

PubMed

Li, Xue-Ming; Chen, Ying-Dan; Xu, Long-Qi; Zhou, Chang-Hai; Ou-Yang, Yi; Lin, Rui; Yang, Fang-Fang; Zhang, Xiao-Juan; Wang, Ge; Liu, Teng; Wang, Jing

2011-12-01

To explore a new prevention and control model on soil-borne parasitic diseases in rural areas of China. Eight provinces and autonomous regions were selected in China as demonstration areas implementing integrated control on soil-borne parasitic diseases. The integrated control measures included authority organization and harmonization, health education, deworming, and environment modification. After three years, the infection rates of soil-borne parasitic diseases were significantly decreased in these areas. There were three safe guard and organization modes, three health education modes, four mass worming medication modes, and two modes of water, toilet and environment changes. The work in the various demonstration areas was summarized which pointed out a new model with efficiency and local characteristics on soil-borne parasitic disease prevention and control.

Evaluation of Electromagnetic Induction to Characterize and Map Sodium-Affected Soils in the Northern Great Plains of the United States

NASA Astrophysics Data System (ADS)

Brevik, E. C.; Heilig, J.; Kempenich, J.; Doolittle, J.; Ulmer, M.

2012-04-01

Sodium-affected soils (SAS) cover over 4 million hectares in the Northern Great Plains of the United States. Improving the classification, interpretation, and mapping of SAS is a major goal of the United States Department of Agriculture-Natural Resource Conservation Service (USDA-NRCS) as Northern Great Plains soil surveys are updated. Apparent electrical conductivity (ECa) as measured with ground conductivity meters has shown promise for mapping SAS, however, this use of this geophysical tool needs additional evaluation. This study used an EM-38 MK2-2 meter (Geonics Limited, Mississauga, Ontario), a Trimble AgGPS 114 L-band DGPS (Trimble, Sunnyvale, CA) and the RTmap38MK2 program (Geomar Software, Inc., Mississauga, Ontario) on an Allegro CX field computer (Juniper Systems, North Logan, UT) to collect, observe, and interpret ECa data in the field. The ECa map generated on-site was then used to guide collection of soil samples for soil characterization and to evaluate the influence of soil properties in SAS on ECa as measured with the EM-38MK2-2. Stochastic models contained in the ESAP software package were used to estimate the SAR and salinity levels from the measured ECa data in 30 cm depth intervals to a depth of 90 cm and for the bulk soil (0 to 90 cm). This technique showed promise, with meaningful spatial patterns apparent in the ECa data. However, many of the stochastic models used for salinity and SAR for individual depth intervals and for the bulk soil had low R-squared values. At both sites, significant variability in soil clay and water contents along with a small number of soil samples taken to calibrate the ECa values to soil properties likely contributed to these low R-squared values.

Representing Microbial Dormancy in Soil Decomposition Models Improves Model Performance and Reveals Key Ecosystem Controls on Microbial Activity

NASA Astrophysics Data System (ADS)

He, Y.; Yang, J.; Zhuang, Q.; Wang, G.; Liu, Y.

2014-12-01

Climate feedbacks from soils can result from environmental change and subsequent responses of plant and microbial communities and nutrient cycling. Explicit consideration of microbial life history traits and strategy may be necessary to predict climate feedbacks due to microbial physiology and community changes and their associated effect on carbon cycling. In this study, we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of dormancy at six temperate forest sites with observed soil efflux ranged from 4 to 10 years across different forest types. We then extrapolated the model to all temperate forests in the Northern Hemisphere (25-50°N) to investigate spatial controls on microbial and soil C dynamics. Both models captured the observed soil heterotrophic respiration (RH), yet no-dormancy model consistently exhibited large seasonal amplitude and overestimation in microbial biomass. Spatially, the total RH from temperate forests based on dormancy model amounts to 6.88PgC/yr, and 7.99PgC/yr based on no-dormancy model. However, no-dormancy model notably overestimated the ratio of microbial biomass to SOC. Spatial correlation analysis revealed key controls of soil C:N ratio on the active proportion of microbial biomass, whereas local dormancy is primarily controlled by soil moisture and temperature, indicating scale-dependent environmental and biotic controls on microbial and SOC dynamics. These developments should provide essential support to modeling future soil carbon dynamics and enhance the avenue for collaboration between empirical soil experiment and modeling in the sense that more microbial physiological measurements are needed to better constrain and evaluate the models.

Soil Structure - A Neglected Component of Land-Surface Models

NASA Astrophysics Data System (ADS)

Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

2017-12-01

Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity are less significant but they can reach up to 10% in specific locations. Significance for land-surface and hydrological modeling and implications for distributed domains are discussed.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Global spatiotemporal distribution of soil respiration modeled using a global database

NASA Astrophysics Data System (ADS)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to the atmosphere in response to climate change. Further approaches should additionally focus on climate controls in soil respiration in combination with changes in vegetation dynamics and soil carbon stocks, along with their effects on the long temporal dynamics of soil respiration. We expect that these spatiotemporal estimates will provide a benchmark for future studies and also help to constrain process-oriented models.

Linking hydraulic properties of fire-affected soils to infiltration and water repellency

USGS Publications Warehouse

Moody, John A.; David Kinner,; Xavier Úbeda,

2009-01-01

Heat from wildfires can produce a two-layer system composed of extremely dry soil covered by a layer of ash, which when subjected to rainfall, may produce extreme floods. To understand the soil physics controlling runoff for these initial conditions, we used a small, portable disk infiltrometer to measure two hydraulic properties: (1) near-saturated hydraulic conductivity, Kf and (2) sorptivity, S(θi), as a function of initial soil moisture content, θi, ranging from extremely dry conditions (θi < 0.02 cm3 cm−3) to near saturation. In the field and in the laboratory replicate measurements were made of ash, reference soils, soils unaffected by fire, and fire-affected soils. Each has a different degrees of water repellency that influences Kf and S(θi).Values of Kf ranged from 4.5 × 10−3 to 53 × 10−3 cm s−1 for ash; from 0.93 × 10−3 to 130 × 10−3 cm s−1 for reference soils; and from 0.86 × 10−3 to 3.0 × 10−3 cm s−1, for soil unaffected by fire, which had the lowest values of Kf. Measurements indicated that S(θi) could be represented by an empirical non-linear function of θi with a sorptivity maximum of 0.18–0.20 cm s−0.5, between 0.03 and 0.08 cm3 cm−3. This functional form differs from the monotonically decreasing non-linear functions often used to represent S(θi) for rainfall–runoff modeling. The sorptivity maximum may represent the combined effects of gravity, capillarity, and adsorption in a transitional domain corresponding to extremely dry soil, and moreover, it may explain the observed non-linear behavior, and the critical soil-moisture threshold of water repellent soils. Laboratory measurements of Kf and S(θi) are the first for ash and fire-affected soil, but additional measurements are needed of these hydraulic properties for in situ fire-affected soils. They provide insight into water repellency behavior and infiltration under extremely dry conditions. Most importantly, they indicate how existing rainfall–runoff models can be modified to accommodate a possible two-layer system in extremely dry conditions. These modified models can be used to predict floods from burned watersheds under these initial conditions.

Microwave remote sensing of soil moisture content over bare and vegetated fields

NASA Technical Reports Server (NTRS)

Wang, J. R.; Shiue, J. C.; Mcmurtrey, J. E., III (Principal Investigator)

1980-01-01

The author has identified the following significant results. Ground truth of soil moisture content, and ambient air and soil temperatures were acquired concurrently with measurements of soil moisture in bare fields and fields covered with grass, corn, and soybeans obtained with 1.4 GHz and 5 GHz radiometers mounted on a truck. The biomass of the vegetation was sampled about once a week. The measured brightness temperatures over the bare fields were compared with those of radiative transfer model calculations using as inputs the acquired soil moisture and temperatures data with appropriate values of dielectric constants for soil-water mixtures. A good agreement was found between the calculated and measured results over 10 deg to 70 deg incident angles. The presence of vegetation reduced the sensitivity of soil moisture sensing. At 1.4 GHz the sensitivity reduction ranged from about 20% for 10 cm tall grassland cover to over 50 to 60% for the dense soybean field. At 5 GHz corresponding reduction in sensitivity ranged from approximately 70% to approximately 90%.